WorldWideScience

Sample records for resolution ikonos satellite

  1. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  2. High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

    Science.gov (United States)

    Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

    2003-01-01

    Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

  3. IKONOS: future and present

    Science.gov (United States)

    Schaap, Niek

    2003-04-01

    The IKONOS satellite has been operational since January 2000 and was the first commercial satellite collecting imagery with 1 meter resolution. The current life expectancy of the satellite is 10 years. Since the launch, Space Imaging Inc. (the owner of the satellite) supplied IKONOS imagery to users in many vertical markets, such as: agriculture, defense, oil & gas and telecommunications. This oral presentation will give comprehensive information about IKONOS and the future: * Block II, the successor of IKONOS. Space Imaging expects to launch in 2004 a new high-resolution satellite, ensuring both continuity and (for some years) a tandem operation with IKONOS, greatly improving the availability of imagery. * Space Imaging affiliates. IKONOS imagery collected, processed and sold by regional affiliates. These regional affiliates are strategically located around the world, like Japan Space Imaging (Tokyo), Space Imaging Middle East (Dubai) and Space Imaging Eurasia (Ankara, Turkey). * Technical briefing IKONOS. IKONOS (compared to other commercial high-resolution satellites) has superior collection capabilities. Due to, the higher orbit altitude, local reception of the imagery, bi-directional scanning and the high agility of the satellite, is the IKONOS satellite capable to collect the imagery relative quickly.

  4. Detailed Maps Depicting the Shallow-Water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Detailed, shallow-water coral reef ecosystem maps were generated by rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations...

  5. Detailed Maps Depicting the Shallow-Water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Detailed, shallow-water coral reef ecosystem maps were generated by rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations...

  6. High resolution satellite imagery : from spies to pipeline management

    Energy Technology Data Exchange (ETDEWEB)

    Adam, S. [Canadian Geomatic Solutions Ltd., Calgary, AB (Canada); Farrell, M. [TransCanada Transmission, Calgary, AB (Canada)

    2000-07-01

    The launch of Space Imaging's IKONOS satellite in September 1999 has opened the door for corridor applications. The technology has been successfully implemented by TransCanada PipeLines in mapping over 1500 km of their mainline. IKONOS is the world's first commercial high resolution satellite which collects data at 1-meter black/white and 4-meter multi-spectral. Its use is regulated by the U.S. government. It is the best source of high resolution satellite image data. Other sources include the Indian Space Agency's IRS-1 C/D satellite and the Russian SPIN-2 which provides less reliable coverage. In addition, two more high resolution satellites may be launched this year to provide imagery every day of the year. IKONOS scenes as narrow as 5 km can be purchased. TransCanada conducted a pilot study to determine if high resolution satellite imagery is as effective as ortho-photos for identifying population structures within a buffer of TransCanada's east line right-of-way. The study examined three unique segments where residential, commercial, industrial and public features were compared. It was determined that IKONOS imagery is as good as digital ortho-photos for updating structures from low to very high density areas. The satellite imagery was also logistically easier than ortho-photos to acquire. This will be even more evident when the IKONOS image archives begins to grow. 4 tabs., 3 figs.

  7. Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

    Science.gov (United States)

    Michael Palace; Michael Keller; Gregory P. Asner; Stephen Hagen; Bobby . Braswell

    2008-01-01

    We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75◦ S, 48.37◦ W) in the eastern Amazon, and then compared with forest...

  8. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  9. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  10. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  11. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  12. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  13. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  14. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  15. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  16. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  17. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  18. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  19. Analysis of the 2006 block-and-ash flow deposits of Merapi Volcano, Java, Indonesia, using high-spatial resolution IKONOS images and complementary ground based observations

    Science.gov (United States)

    Thouret, Jean-Claude; Gupta, Avijit; Liew, Soo Chin; Lube, Gert; Cronin, Shane J.; Surono, Dr

    2010-05-01

    On 16 June 2006 an overpass of IKONOS coincided with the emplacement of an active block-and-ash flow fed by a lava dome collapse event at Merapi Volcano (Java, Indonesia). This was the first satellite image recorded for a moving pyroclastic flow. The very high-spatial resolution data displayed the extent and impact of the pyroclastic deposits emplaced during and prior to, the day of image acquisition. This allowed a number of features associated with high-hazard block-and-ash flows emplaced in narrow, deep gorges to be mapped, interpreted and understood. The block-and-ash flow and surge deposits recognized in the Ikonos images include: (1) several channel-confined flow lobes and tongues in the box-shaped valley; (2) thin ash-cloud surge deposit and knocked-down trees in constricted areas on both slopes of the gorge; (3) fan-like over bank deposits on the Gendol-Tlogo interfluves from which flows were re-routed in the Tlogo secondary valley; (4) massive over bank lobes on the right bank from which flows devastated the village of Kaliadem 0.5 km from the main channel, a small part of this flow being re-channeled in the Opak secondary valley. The high-resolution IKONOS images also helped us to identify geomorphic obstacles that enabled flows to ramp and spill out from the sinuous channel, a process called flow avulsion. Importantly, the avulsion redirected flows to unexpected areas away from the main channel. In the case of Merapi we see that the presence of valley fill by previous deposits, bends and man-made dams influence the otherwise valley-guided course of the flows. Sadly, Sabo dams (built to ameliorate the effect of high sediment load streams) can actually cause block-and-ash flows to jump out of their containing channel and advance into sensitive areas. Very-high-spatial resolution satellite images are very useful for mapping and interpreting the distribution of freshly erupted volcanic deposits. IKONOS-type images with 1-m resolution provide opportunities to

  20. Empirical Estimation of Total Nitrogen and Total Phosphorus Concentration of Urban Water Bodies in China Using High Resolution IKONOS Multispectral Imagery

    Directory of Open Access Journals (Sweden)

    Jiaming Liu

    2015-11-01

    Full Text Available Measuring total nitrogen (TN and total phosphorus (TP is important in managing heavy polluted urban waters in China. This study uses high spatial resolution IKONOS imagery with four multispectral bands, which roughly correspond to Landsat/TM bands 1–4, to determine TN and TP in small urban rivers and lakes in China. By using Lake Cihu and the lower reaches of Wen-Rui Tang (WRT River as examples, this paper develops both multiple linear regressions (MLR and artificial neural network (ANN models to estimate TN and TP concentrations from high spatial resolution remote sensing imagery and in situ water samples collected concurrently with overpassing satellite. The measured and estimated values of both MLR and ANN models are in good agreement (R2 > 0.85 and RMSE < 2.50. The empirical equations selected by MLR are more straightforward, whereas the estimated accuracy using ANN model is better (R2 > 0.86 and RMSE < 0.89. Results validate the potential of using high resolution IKONOS multispectral imagery to study the chemical states of small-sized urban water bodies. The spatial distribution maps of TN and TP concentrations generated by the ANN model can inform the decision makers of variations in water quality in Lake Cihu and lower reaches of WRT River. The approaches and equations developed in this study could be applied to other urban water bodies for water quality monitoring.

  1. Vectorized Shoreline of Guam, Derived from IKONOS Satellite Imagery, 2000 through 2003

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  2. [Characteristic study on village landscape patterns in Sichuan Basin hilly region based on high resolution IKONOS remote sensing].

    Science.gov (United States)

    Li, Shoucheng; Liu, Wenquan; Cheng, Xu; Ellis, Erle C

    2005-10-01

    To realize the landscape programming of agro-ecosystem management, landscape-stratification can provide us the best understanding of landscape ecosystem at very detailed scales. For this purpose, the village landscapes in densely populated Jintang and Jianyang Counties of Sichuan Basin hilly region were mapped from high resolution (1 m) IKONOS satellite imagery by using a standardized 4 level ecological landscape classification and mapping system in a regionally-representative sample of five 500 x 500 m2 landscape quadrats (sample plots). Based on these maps, the spatial patterns were analyzed by landscape indicators, which demonstrated a large variety of landscape types or ecotopes across the village landscape of this region, with diversity indexes ranging from 1.08 to 2.26 at different levels of the landscape classification system. The richness indices ranged from 42.2% to 58.6 %, except that for the landcover at 85 %. About 12.5 % of the ecotopes were distributed in the same way in each landscape sample, and the remaining 87.5% were distributed differently. The landscape fragmentation indices varied from 2.93 to 4.27 across sample plots, and from 2.86 to 5.63 across classification levels. The population density and the road and hamlet areas had strong linear correlations with some landscape indicators, and especially, the correlation coefficients of hamlet areas with fractal indexes and fragmental dimensions were 0.957* and 0.991**, respectively. The differences in most landscape pattern indices across sample plots and landscape classes were statistically significant, indicating that cross-scale mapping and classification of village landscapes could provide more detailed information on landscape patterns than those from a single level of classification.

  3. Strengthening IAEA safeguards using high-resolution commercial satellite imagery

    International Nuclear Information System (INIS)

    Zhang Hui

    2001-01-01

    Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the

  4. Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

    Science.gov (United States)

    Spruce, Joseph; McKellip, Rodney

    2006-01-01

    Hurricane Katrina hit southeastern Louisiana and the Mississippi Gulf Coast as a Category 3 hurricane with storm surges as high as 9 m. Katrina devastated several coastal towns by destroying or severely damaging hundreds of homes. Several Federal agencies are assessing storm impacts and assisting recovery using high-spatial-resolution remotely sensed data from satellite and airborne platforms. High-quality IKONOS satellite imagery was collected on September 2, 2005, over southwestern Mississippi. Pan-sharpened IKONOS multispectral data and ERDAS IMAGINE software were used to classify post-storm land cover for coastal Hancock and Harrison Counties. This classification included a storm debris category of interest to FEMA for disaster mitigation. The classification resulted from combining traditional unsupervised and supervised classification techniques. Higher spatial resolution aerial and handheld photography were used as reference data. Results suggest that traditional classification techniques and IKONOS data can map wood-dominated storm debris in open areas if relevant training areas are used to develop the unsupervised classification signatures. IKONOS data also enabled other hurricane damage assessment, such as flood-deposited mud on lawns and vegetation foliage loss from the storm. IKONOS data has also aided regional Katrina vegetation damage surveys from multidate Land Remote Sensing Satellite and Moderate Resolution Imaging Spectroradiometer data.

  5. FFT-enhanced IHS transform method for fusing high-resolution satellite images

    Science.gov (United States)

    Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

    2007-01-01

    Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

  6. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    Keywords. High resolution image; texture analysis; segmentation; IKONOS; Hölder exponent; cluster. ... are that. • it can be used as a tool to measure the roughness ... uses reinforcement learning to learn the reward values of ..... The numerical.

  7. TRANSFER OF TECHNOLOGY FOR CADASTRAL MAPPING IN TAJIKISTAN USING HIGH RESOLUTION SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    R. Kaczynski

    2012-07-01

    Full Text Available European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m

  8. Mapping turbidity in the Charles River, Boston using a high-resolution satellite.

    Science.gov (United States)

    Hellweger, Ferdi L; Miller, Will; Oshodi, Kehinde Sarat

    2007-09-01

    The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).

  9. High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

    Science.gov (United States)

    Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

  10. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  11. Object-oriented classification of land use in urban areas applying very high resolution satellite data

    International Nuclear Information System (INIS)

    Bauer, T.B.

    2001-08-01

    The availability of the new very high resolution satellite imagery will offer a wide range of new applications in the field of remote sensing. Information about actual land use is an important task for the management and planning in urban areas. High resolution satellite data will be an alternative to aerial photographs for updating and maintaining cartographic and geographic databases at reduced costs. The aim of the research is to formalize the visual interpretation procedure in order to automate the whole process. The assumption underlying this approach is that the land use functions can be distinguished on the basis of the differences in spatial distribution and pattern of land cover forms. Therefore a two-stage classification procedure is applied. In a first stage a land cover map is produced. In a second stage the morphological properties and spatial patterns of the land cover objects are analyzed with the structural analyzing and mapping system leading to a characterization and description of distinct urban land use categories. This information is then used for building a rule system that is implemented in a new commercial software tool called eCognition. An object-oriented classifier applies the rules to the land cover objects resulting in the required land use map. The potential of this method is demonstrated in a case study using IKONOS data covering a part of the metropolitan area of Vienna. (author)

  12. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    Science.gov (United States)

    Husak, G. J.; Marshall, M. T.; Michaelsen, J.; Pedreros, D.; Funk, C.; Galu, G.

    2008-07-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

  13. Ambiguity resolution for satellite Doppler positioning systems

    Science.gov (United States)

    Argentiero, P.; Marini, J.

    1979-01-01

    The implementation of satellite-based Doppler positioning systems frequently requires the recovery of transmitter position from a single pass of Doppler data. The least-squares approach to the problem yields conjugate solutions on either side of the satellite subtrack. It is important to develop a procedure for choosing the proper solution which is correct in a high percentage of cases. A test for ambiguity resolution which is the most powerful in the sense that it maximizes the probability of a correct decision is derived. When systematic error sources are properly included in the least-squares reduction process to yield an optimal solution the test reduces to choosing the solution which provides the smaller valuation of the least-squares loss function. When systematic error sources are ignored in the least-squares reduction, the most powerful test is a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudoinverse of a reduced-rank square matrix. A formula for computing the power of the most powerful test is provided. Numerical examples are included in which the power of the test is computed for situations that are relevant to the design of a satellite-aided search and rescue system.

  14. Habitat Mapping and Change Assessment of Coastal Environments: An Examination of WorldView-2, QuickBird, and IKONOS Satellite Imagery and Airborne LiDAR for Mapping Barrier Island Habitats

    Directory of Open Access Journals (Sweden)

    Matthew J. McCarthy

    2014-03-01

    Full Text Available Habitat mapping can be accomplished using many techniques and types of data. There are pros and cons for each technique and dataset, therefore, the goal of this project was to investigate the capabilities of new satellite sensor technology and to assess map accuracy for a variety of image classification techniques based on hundreds of field-work sites. The study area was Masonboro Island, an undeveloped area in coastal North Carolina, USA. Using the best map results, a habitat change assessment was conducted between 2002 and 2010. WorldView-2, QuickBird, and IKONOS satellite sensors were tested using unsupervised and supervised methods using a variety of spectral band combinations. Light Detection and Ranging (LiDAR elevation and texture data pan-sharpening, and spatial filtering were also tested. In total, 200 maps were generated and results indicated that WorldView-2 was consistently more accurate than QuickBird and IKONOS. Supervised maps were more accurate than unsupervised in 80% of the maps. Pan-sharpening the images did not consistently improve map accuracy but using a majority filter generally increased map accuracy. During the relatively short eight-year period, 20% of the coastal study area changed with intertidal marsh experiencing the most change. Smaller habitat classes changed substantially as well. For example, 84% of upland scrub-shrub experienced change. These results document the dynamic nature of coastal habitats, validate the use of the relatively new Worldview-2 sensor, and may be used to guide future coastal habitat mapping.

  15. GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    Catherine Mering

    2011-05-01

    Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

  16. Rigorous Line-Based Transformation Model Using the Generalized Point Strategy for the Rectification of High Resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Kun Hu

    2016-09-01

    Full Text Available High precision geometric rectification of High Resolution Satellite Imagery (HRSI is the basis of digital mapping and Three-Dimensional (3D modeling. Taking advantage of line features as basic geometric control conditions instead of control points, the Line-Based Transformation Model (LBTM provides a practical and efficient way of image rectification. It is competent to build the mathematical relationship between image space and the corresponding object space accurately, while it reduces the workloads of ground control and feature recognition dramatically. Based on generalization and the analysis of existing LBTMs, a novel rigorous LBTM is proposed in this paper, which can further eliminate the geometric deformation caused by sensor inclination and terrain variation. This improved nonlinear LBTM is constructed based on a generalized point strategy and resolved by least squares overall adjustment. Geo-positioning accuracy experiments with IKONOS, GeoEye-1 and ZiYuan-3 satellite imagery are performed to compare rigorous LBTM with other relevant line-based and point-based transformation models. Both theoretic analysis and experimental results demonstrate that the rigorous LBTM is more accurate and reliable without adding extra ground control. The geo-positioning accuracy of satellite imagery rectified by rigorous LBTM can reach about one pixel with eight control lines and can be further improved by optimizing the horizontal and vertical distribution of control lines.

  17. Use of IKONOS Data for Mapping Cultural Resources of Stennis Space Center, Mississippi

    Science.gov (United States)

    Spruce, Joseph P.; Giardino, Marco

    2002-01-01

    Cultural resource surveys are important for compliance with Federal and State law. Stennis Space Center (SSC) in Mississippi is researching, developing, and validating remote sensing and Geographical Information System (GIS) methods for aiding cultural resource assessments on the center's own land. The suitability of IKONOS satellite imagery for georeferencing scanned historic maps is examined in this viewgraph presentation. IKONOS data can be used to map historic buildings and farmland in Gainsville, MS, and plan archaeological surveys.

  18. Hurricane Satellite (HURSAT) from Advanced Very High Resolution Radiometer (AVHRR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Huricane Satellite (HURSAT)-Advanced Very High Resolution Radiometer (AVHRR) is used to extend the HURSAT data set such that appling the Objective Dvorak technique...

  19. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  20. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  1. Spectroscopic Characterization of GEO Satellites with Gunma LOW Resolution Spectrograph

    Science.gov (United States)

    Endo, T.; Ono, H.; Hosokawa, M.; Ando, T.; Takanezawa, T.; Hashimoto, O.

    The spectroscopic observation is potentially a powerful tool for understanding the Geostationary Earth Orbit (GEO) objects. We present here the results of an investigation of energy spectra of GEO satellites obtained from a groundbased optical telescope. The spectroscopic observations were made from April to June 2016 with the Gunma LOW resolution Spectrograph and imager (GLOWS) at the Gunma Astronomical Observatory (GAO) in JAPAN. The observation targets consist of eleven different satellites: two weather satellites, four communications satellites, and five broadcasting satellites. All the spectra of those GEO satellites are inferred to be solar-like. A number of well-known absorption features such as H-alpha, H-beta, Na-D,water vapor and oxygen molecules are clearly seen in thewavelength range of 4,000 - 8,000 Å. For comparison, we calculated the intensity ratio of the spectra of GEO satellites to that of the Moon which is the natural satellite of the earth. As a result, the following characteristics were obtained. 1) Some variations are seen in the strength of absorption features of water vapor and oxygen originated by the telluric atmosphere, but any other characteristic absorption features were not found. 2) For all observed satellites, the intensity ratio of the spectrum of GEO satellites decrease as a function of wavelength or to be flat. It means that the spectral reflectance of satellite materials is bluer than that of the Moon. 3) A characteristic dip at around 4,800 Å is found in all observed spectra of a weather satellite. Based on these observations, it is indicated that the characteristics of the spectrum are mainly derived from the solar panels because the apparent area of the solar cell is probably larger than that of the satellite body.

  2. Assessment of visual landscape quality using IKONOS imagery.

    Science.gov (United States)

    Ozkan, Ulas Yunus

    2014-07-01

    The assessment of visual landscape quality is of importance to the management of urban woodlands. Satellite remote sensing may be used for this purpose as a substitute for traditional survey techniques that are both labour-intensive and time-consuming. This study examines the association between the quality of the perceived visual landscape in urban woodlands and texture measures extracted from IKONOS satellite data, which features 4-m spatial resolution and four spectral bands. The study was conducted in the woodlands of Istanbul (the most important element of urban mosaic) lying along both shores of the Bosporus Strait. The visual quality assessment applied in this study is based on the perceptual approach and was performed via a survey of expressed preferences. For this purpose, representative photographs of real scenery were used to elicit observers' preferences. A slide show comprising 33 images was presented to a group of 153 volunteers (all undergraduate students), and they were asked to rate the visual quality of each on a 10-point scale (1 for very low visual quality, 10 for very high). Average visual quality scores were calculated for landscape. Texture measures were acquired using the two methods: pixel-based and object-based. Pixel-based texture measures were extracted from the first principle component (PC1) image. Object-based texture measures were extracted by using the original four bands. The association between image texture measures and perceived visual landscape quality was tested via Pearson's correlation coefficient. The analysis found a strong linear association between image texture measures and visual quality. The highest correlation coefficient was calculated between standard deviation of gray levels (SDGL) (one of the pixel-based texture measures) and visual quality (r = 0.82, P landscapes can be estimated by using texture measures extracted from satellite data in combination with appropriate modelling techniques.

  3. A method for generating high resolution satellite image time series

    Science.gov (United States)

    Guo, Tao

    2014-10-01

    There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation

  4. Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

    Science.gov (United States)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

    In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

  5. Global High Resolution Sea Surface Flux Parameters From Multiple Satellites

    Science.gov (United States)

    Zhang, H.; Reynolds, R. W.; Shi, L.; Bates, J. J.

    2007-05-01

    Advances in understanding the coupled air-sea system and modeling of the ocean and atmosphere demand increasingly higher resolution data, such as air-sea fluxes of up to 3 hourly and every 50 km. These observational requirements can only be met by utilizing multiple satellite observations. Generation of such high resolution products from multiple-satellite and in-situ observations on an operational basis has been started at the U.S. National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center. Here we describe a few products that are directly related to the computation of turbulent air-sea fluxes. Sea surface wind speed has been observed from in-situ instruments and multiple satellites, with long-term observations ranging from one satellite in the mid 1987 to six or more satellites since mid 2002. A blended product with a global 0.25° grid and four snapshots per day has been produced for July 1987 to present, using a near Gaussian 3-D (x, y, t) interpolation to minimize aliases. Wind direction has been observed from fewer satellites, thus for the blended high resolution vector winds and wind stresses, the directions are taken from the NCEP Re-analysis 2 (operationally run near real time) for climate consistency. The widely used Reynolds Optimum Interpolation SST analysis has been improved with higher resolutions (daily and 0.25°). The improvements use both infrared and microwave satellite data that are bias-corrected by in- situ observations for the period 1985 to present. The new versions provide very significant improvements in terms of resolving ocean features such as the meandering of the Gulf Stream, the Aghulas Current, the equatorial jets and other fronts. The Ta and Qa retrievals are based on measurements from the AMSU sounder onboard the NOAA satellites. Ta retrieval uses AMSU-A data, while Qa retrieval uses both AMSU-A and AMSU-B observations. The retrieval algorithms are developed using the neural network approach. Training

  6. Linear mixing model applied to coarse resolution satellite data

    Science.gov (United States)

    Holben, Brent N.; Shimabukuro, Yosio E.

    1992-01-01

    A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

  7. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    Science.gov (United States)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  8. APLICAÇÃO DE IMAGENS IKONOS II E TM/LANDSAT-5 NA ELABORAÇÃO DE UMA BASE CARTOGRÁFICA PARA A RESERVA DE DESENVOLVIMENTO SUSTENTÁVEL MAMIRAUÁ – AMAZONAS / APPLICATION OF IKONOS II AND TM/LANDSAT-5 SATELLITES DATA FOR DIGITAL BASE MAPPING THE SUSTAINABLE DEVELOPMENT RESERVE MAMIRAUÁ, AMAZON, BRAZIL

    Directory of Open Access Journals (Sweden)

    Josimara Martins Dias

    2009-12-01

    Full Text Available This paper has as purpose present the methodology developed to produce an updated digital map base support for participatory management Mamirauá Reserve of Sustainable Development in the state of Amazonas, Braszil. Because this protected área is situated within an area of flooded forest, both the physical landscape and social organization often change, and the dynamic demand the systematic update of cartographic databases. This work has images of orbital sensors IKONOS II and LANDSAT 5 TM, interviews with users and collecting spatial data in the Mamirauá Reserve. This work obtained a cartographic base at 1:100.000 scale and a geodatabase compatible with the local references, with which is possible to generate thematic maps updated to support dialogue in the sustainable management programs of the Mamirauá Reserve and minimize conflicts with communities.

  9. Landslide detection using very high-resolution satellite imageries

    Science.gov (United States)

    Suga, Yuzo; Konishi, Tomohisa

    2012-10-01

    The heavy rain induced by the 12th typhoon caused landslide disaster at Kii Peninsula in the middle part of Japan. We propose a quick response method for landslide disaster mapping using very high resolution (VHR) satellite imageries. Especially, Synthetic Aperture Radar (SAR) is effective because it has the capability of all weather and day/night observation. In this study, multi-temporal COSMO-SkyMed imageries were used to detect the landslide areas. It was difficult to detect the landslide areas using only backscatter change pattern derived from pre- and post-disaster COSMOSkyMed imageries. Thus, the authors adopted a correlation analysis which the moving window was selected for the correlation coefficient calculation. Low value of the correlation coefficient reflects land cover change between pre- and post-disaster imageries. This analysis is effective for the detection of landslides using SAR data. The detected landslide areas were compared with the area detected by EROS-B high resolution optical image. In addition, we have developed 3D viewing system for geospatial visualizing of the damaged area using these satellite image data with digital elevation model. The 3D viewing system has the performance of geographic measurement with respect to elevation height, area and volume calculation, and cross section drawing including landscape viewing and image layer construction using a mobile personal computer with interactive operation. As the result, it was verified that a quick response for the detection of landslide disaster at the initial stage could be effectively performed using optical and SAR very high resolution satellite data by means of 3D viewing system.

  10. COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

    Directory of Open Access Journals (Sweden)

    P. Agrafiotis

    2015-03-01

    Full Text Available This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO provided by NCMA S.A (Hellenic Cadastre from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  11. LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. Tom

    2018-05-01

    Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  12. Lake Ice Detection in Low-Resolution Optical Satellite Images

    Science.gov (United States)

    Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

    2018-05-01

    Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  13. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  14. Shoreline change after 12 years of tsunami in Banda Aceh, Indonesia: a multi-resolution, multi-temporal satellite data and GIS approach

    Science.gov (United States)

    Sugianto, S.; Heriansyah; Darusman; Rusdi, M.; Karim, A.

    2018-04-01

    The Indian Ocean Tsunami event on the 26 December 2004 has caused severe damage of some shorelines in Banda Aceh City, Indonesia. Tracing back the impact can be seen using remote sensing data combined with GIS. The approach is incorporated with image processing to analyze the extent of shoreline changes with multi-temporal data after 12 years of tsunami. This study demonstrates multi-resolution and multi-temporal satellite images of QuickBird and IKONOS to demarcate the shoreline of Banda Aceh shoreline from before and after tsunami. The research has demonstrated a significant change to the shoreline in the form of abrasion between 2004 and 2005 from few meters to hundred meters’ change. The change between 2004 and 2011 has not returned to the previous stage of shoreline before the tsunami, considered post tsunami impact. The abrasion occurs between 18.3 to 194.93 meters. Further, the change in 2009-2011 shows slowly change of shoreline of Banda Aceh, considered without impact of tsunami e.g. abrasion caused by ocean waves that erode the coast and on specific areas accretion occurs caused by sediment carried by the river flow into the sea near the shoreline of the study area.

  15. Integration of Ground and Multi-Resolution Satellite Data for Predicting the Water Balance of a Mediterranean Two-Layer Agro-Ecosystem

    Directory of Open Access Journals (Sweden)

    Piero Battista

    2016-09-01

    Full Text Available The estimation of site water budget is important in Mediterranean areas, where it represents a crucial factor affecting the quantity and quality of traditional crop production. This is particularly the case for spatially fragmented, multi-layer agricultural ecosystems such as olive groves, which are traditional cultivations of the Mediterranean basin. The current paper aims at demonstrating the effectiveness of spatialized meteorological data and remote sensing techniques to estimate the actual evapotranspiration (ETA and the soil water content (SWC of an olive orchard in Central Italy. The relatively small size of this orchard (about 0.1 ha and its two-layer structure (i.e., olive trees and grasses require the integration of remotely sensed data with different spatial and temporal resolutions (Terra-MODIS, Landsat 8-OLI and Ikonos. These data are used to drive a recently proposed water balance method (NDVI-Cws and predict ETA and then site SWC, which are assessed through comparison with sap flow and soil wetness measurements taken in 2013. The results obtained indicate the importance of integrating satellite imageries having different spatio-temporal properties in order to properly characterize the examined olive orchard. More generally, the experimental evidences support the possibility of using widely available remotely sensed and ancillary datasets for the operational estimation of ETA and SWC in olive tree cultivation systems.

  16. Analysis of smear in high-resolution remote sensing satellites

    Science.gov (United States)

    Wahballah, Walid A.; Bazan, Taher M.; El-Tohamy, Fawzy; Fathy, Mahmoud

    2016-10-01

    High-resolution remote sensing satellites (HRRSS) that use time delay and integration (TDI) CCDs have the potential to introduce large amounts of image smear. Clocking and velocity mismatch smear are two of the key factors in inducing image smear. Clocking smear is caused by the discrete manner in which the charge is clocked in the TDI-CCDs. The relative motion between the HRRSS and the observed object obliges that the image motion velocity must be strictly synchronized with the velocity of the charge packet transfer (line rate) throughout the integration time. During imaging an object off-nadir, the image motion velocity changes resulting in asynchronization between the image velocity and the CCD's line rate. A Model for estimating the image motion velocity in HRRSS is derived. The influence of this velocity mismatch combined with clocking smear on the modulation transfer function (MTF) is investigated by using Matlab simulation. The analysis is performed for cross-track and along-track imaging with different satellite attitude angles and TDI steps. The results reveal that the velocity mismatch ratio and the number of TDI steps have a serious impact on the smear MTF; a velocity mismatch ratio of 2% degrades the MTFsmear by 32% at Nyquist frequency when the TDI steps change from 32 to 96. In addition, the results show that to achieve the requirement of MTFsmear >= 0.95 , for TDI steps of 16 and 64, the allowable roll angles are 13.7° and 6.85° and the permissible pitch angles are no more than 9.6° and 4.8°, respectively.

  17. Super-resolution post-processing for satellites with yaw-steering capability

    CSIR Research Space (South Africa)

    Van den Dool, R

    2012-10-01

    Full Text Available We describe a method for improving Earth observation satellite image resolution, for specific areas of interest where the sensor design resolution is insufficient. Our method may be used for satellites with yaw-steering capability, such as Nigeria...

  18. Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

    Science.gov (United States)

    Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

  19. Fuel type characterization based on coarse resolution MODIS satellite data

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    Lanorte A

    2007-01-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  20. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

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    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  1. Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

    Science.gov (United States)

    Wallace, C.S.A.; Marsh, S.E.

    2005-01-01

    Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

  2. TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    G. Agugiaro

    2012-07-01

    Full Text Available Today the use of spaceborne Very High Spatial Resolution (VHSR optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM Unit of the Bruno Kessler Foundation (FBK in Trento (Italy has collected stereo VHSR satellite imagery, as well as aerial and terrestrial data over Trento, with the aim to create a complete data collection with state-of-the-art datasets for investigations on image analysis, automatic digital surface model (DSM generation, 2D/3D feature extraction, city modelling and data fusion. The testfield region covers the city of Trento, characterised by very dense urban (historical centre, residential and industrial areas, and the surrounding hills and steep mountains (approximate height range 200-2100 m with cultivations, forests and bare soil. This paper reports the analysis conducted in FBK on the VHSR spaceborne imagery of Trento testfield for 3D information extraction. The data include two stereo-pairs acquired by WorldView-2 in August 2010 and by GeoEye-1 in September 2011 in panchromatic and multispectral mode, together with their original Rational Polynomial Coefficients (RPC, and the position and description of well distributed ground points. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project and the dataset characteristics. The results achieved by 3DOM on DSM extraction from WorldView-2 and GeoEye-1 stereo-pairs are shown and commented.

  3. Roads Data Conflation Using Update High Resolution Satellite Images

    Science.gov (United States)

    Abdollahi, A.; Riyahi Bakhtiari, H. R.

    2017-11-01

    Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.

  4. Shallow-water Benthic Habitats of the Northwestern Hawaiian Islands from Aggregated Habitat Cover Maps Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Shallow-water, aggregated cover maps were produced by combining as many as four or more detailed habitat types into general cover categories. The original detailed...

  5. Aggregated Habitat Cover Maps Depicting the Shallow-water Benthic Habitats of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Shallow-water, aggregated cover maps were produced by combining as many as four or more detailed habitat types into general cover categories. The original detailed...

  6. ENVIRONMENTAL CHANGES ANALYSIS IN BUCHAREST CITY USING CORONA, SPOT HRV AND IKONOS IMAGES

    Directory of Open Access Journals (Sweden)

    I. Noaje

    2012-08-01

    Full Text Available Bucharest, capital of Romania, deals with serious difficulties as a result of urban politics: influx of people due to industrialization and development of dormitory areas, lack of a modern infrastructure, absence of coherent and long term urban development politics, continuous depletion of environment. This paper presents a multisensor study relying on multiple data sets, both analogical and digital: satellite images (Corona – 1964 panchromatic, SPOT HRV – 1994 multispctral and panchromatic, IKONOS – 2007 multispectral, aerial photographs – 1994, complementary products (topographic and thematic maps. Georeferenced basis needs to be generated to highlight changes detection. The digital elevation model is generated from aerial photography 1:5,000 scaled, acquired in 1994. First a height correction is required followed by an affine transformation to the ground control points identified both in aerial photographs and IKONOS image. SPOT-HRV pansharpened satellite image has been rectified on georeferenced IKONOS image, by an affine transformation method. The Corona panoramic negative film was scanned and rubber sheeting method is used for rectification. The first 25 years of the study period (1964–1989 are characterized by growth of industrial areas, high density apartment buildings residential areas and leisure green areas by demolition of cultural heritage areas (hundred years old churches and architectural monuments. Changes between the imagery were determined partially through visual interpretation, using elements such as location, size, shape, shadow, tone, texture, and pattern (Corona image, partially using unsupervised classification (SPOT HRV and IKONOS. The second period of 18 years (1989–2007 highlighted considerable growth of residential areas in the city neighborhood, simultaneously with the diminish of green areas and massive deforestation in confiscated areas before and returned to the original owners.

  7. Geology, tectonics, and the 2002-2003 eruption of the Semeru volcano, Indonesia: Interpreted from high-spatial resolution satellite imagery

    Science.gov (United States)

    Solikhin, Akhmad; Thouret, Jean-Claude; Gupta, Avijit; Harris, Andy J. L.; Liew, Soo Chin

    2012-02-01

    The paper illustrates the application of high-spatial resolution satellite images in interpreting volcanic structures and eruption impacts in the Tengger-Semeru massif in east Java, Indonesia. We use high-spatial resolution images (IKONOS and SPOT 5) and aerial photos in order to analyze the structures of Semeru volcano and map the deposits. Geological and tectonic mapping is based on two DEMs and on the interpretation of aerial photos and four SPOT and IKONOS optical satellite images acquired between 1996 and 2002. We also compared two thermal Surface Kinetic Temperature ASTER images before and after the 2002-2003 eruption in order to delineate and evaluate the impacts of the pyroclastic density currents. Semeru's principal structural features are probably due to the tectonic setting of the volcano. A structural map of the Tengger-Semeru massif shows four groups of faults orientated N40, N160, N75, and N105 to N140. Conspicuous structures, such as the SE-trending horseshoe-shaped scar on Semeru's summit cone, coincide with the N160-trending faults. The direction of minor scars on the east flank parallels the first and second groups of faults. The Semeru composite cone hosts the currently active Jonggring-Seloko vent. This is located on, and buttressed against, the Mahameru edifice at the head of a large scar that may reflect a failure plane at shallow depth. Dipping 35° towards the SE, this failure plane may correspond to a weak basal layer of weathered volcaniclastic rocks of Tertiary age. We suggest that the deformation pattern of Semeru and its large scar may be induced by flank spreading over the weak basal layer of the volcano. It is therefore necessary to consider the potential for flank and summit collapse in the future. The last major eruption took place in December 2002-January 2003, and involved emplacement of block-and-ash flows. We have used the 2003 ASTER Surface Kinetic Temperature image to map the 2002-2003 pyroclastic density current deposits. We

  8. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

  9. Effects of satellite image spatial aggregation and resolution on estimates of forest land area

    Science.gov (United States)

    M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

    2009-01-01

    Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

  10. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.

  11. Spatial scales of pollution from variable resolution satellite imaging.

    Science.gov (United States)

    Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. High resolution radar satellite imagery analysis for safeguards applications

    Energy Technology Data Exchange (ETDEWEB)

    Minet, Christian; Eineder, Michael [German Aerospace Center, Remote Sensing Technology Institute, Department of SAR Signal Processing, Wessling, (Germany); Rezniczek, Arnold [UBA GmbH, Herzogenrath, (Germany); Niemeyer, Irmgard [Forschungszentrum Juelich, Institue of Energy and Climate Research, IEK-6: Nuclear Waste Management and Reactor Safety, Juelich, (Germany)

    2011-12-15

    For monitoring nuclear sites, the use of Synthetic Aperture Radar (SAR) imagery shows essential promises. Unlike optical remote sensing instruments, radar sensors operate under almost all weather conditions and independently of the sunlight, i.e. time of the day. Such technical specifications are required both for continuous and for ad-hoc, timed surveillance tasks. With Cosmo-Skymed, TerraSARX and Radarsat-2, high-resolution SAR imagery with a spatial resolution up to 1m has recently become available. Our work therefore aims to investigate the potential of high-resolution TerraSAR data for nuclear monitoring. This paper focuses on exploiting amplitude of a single acquisition, assessing amplitude changes and phase differences between two acquisitions, and PS-InSAR processing of an image stack.

  13. The fusion of satellite and UAV data: simulation of high spatial resolution band

    Science.gov (United States)

    Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

    2017-10-01

    Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

  14. Design of the high resolution optical instrument for the Pleiades HR Earth observation satellites

    Science.gov (United States)

    Lamard, Jean-Luc; Gaudin-Delrieu, Catherine; Valentini, David; Renard, Christophe; Tournier, Thierry; Laherrere, Jean-Marc

    2017-11-01

    As part of its contribution to Earth observation from space, ALCATEL SPACE designed, built and tested the High Resolution cameras for the European intelligence satellites HELIOS I and II. Through these programmes, ALCATEL SPACE enjoys an international reputation. Its capability and experience in High Resolution instrumentation is recognised by the most customers. Coming after the SPOT program, it was decided to go ahead with the PLEIADES HR program. PLEIADES HR is the optical high resolution component of a larger optical and radar multi-sensors system : ORFEO, which is developed in cooperation between France and Italy for dual Civilian and Defense use. ALCATEL SPACE has been entrusted by CNES with the development of the high resolution camera of the Earth observation satellites PLEIADES HR. The first optical satellite of the PLEIADES HR constellation will be launched in mid-2008, the second will follow in 2009. To minimize the development costs, a mini satellite approach has been selected, leading to a compact concept for the camera design. The paper describes the design and performance budgets of this novel high resolution and large field of view optical instrument with emphasis on the technological features. This new generation of camera represents a breakthrough in comparison with the previous SPOT cameras owing to a significant step in on-ground resolution, which approaches the capabilities of aerial photography. Recent advances in detector technology, optical fabrication and electronics make it possible for the PLEIADES HR camera to achieve their image quality performance goals while staying within weight and size restrictions normally considered suitable only for much lower performance systems. This camera design delivers superior performance using an innovative low power, low mass, scalable architecture, which provides a versatile approach for a variety of imaging requirements and allows for a wide number of possibilities of accommodation with a mini-satellite

  15. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  16. Satellite image collection optimization

    Science.gov (United States)

    Martin, William

    2002-09-01

    Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

  17. Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

    Science.gov (United States)

    Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

    2017-11-01

    The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

  18. Improved wetland classification using eight-band high-resolution satellite imagery and a hybrid approach

    Science.gov (United States)

    Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of derived wetland maps were limited or often unsatisfactory largely due to the relatively coarse spatial resolution of conventional satellite imagery. This re...

  19. Analysis of high resolution satellite digital data for land use studies ...

    African Journals Online (AJOL)

    High-resolution satellite data can give vital information about land cover, which can lead to better interpretation and classification of land resources. This study examined the relationship between Systeme Probatoire d'Observation de la Terre (SPOT) digital data and land use types in the derived savanna ecosystem of ...

  20. Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

    Directory of Open Access Journals (Sweden)

    Aoran Xiao

    2018-04-01

    Full Text Available Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

  1. Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

    Science.gov (United States)

    Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

    2018-04-13

    Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

  2. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  3. Role of light satellites in the high-resolution Earth observation domain

    Science.gov (United States)

    Fishman, Moshe

    1999-12-01

    Current 'classic' applications using and exploring space based earth imagery are exclusive, narrow niche tailored, expensive and hardly accessible. On the other side new, inexpensive and widely used 'consumable' applications will be only developed concurrently to the availability of appropriate imagery allowing that process. A part of these applications can be imagined today, like WWW based 'virtual tourism' or news media, but the history of technological, cultural and entertainment evolution teaches us that most of future applications are unpredictable -- they emerge together with the platforms enabling their appearance. The only thing, which can be ultimately stated, is that the definitive condition for such applications is the availability of the proper imagery platform providing low cost, high resolution, large area, quick response, simple accessibility and quick dissemination of the raw picture. This platform is a constellation of Earth Observation satellites. Up to 1995 the Space Based High Resolution Earth Observation Domain was dominated by heavy, super-expensive and very inflexible birds. The launch of Israeli OFEQ-3 Satellite by MBT Division of Israel Aircraft Industries (IAI) marked the entrance to new era of light, smart and cheap Low Earth Orbited Imaging satellites. The Earth Resource Observation System (EROS) initiated by West Indian Space, is based on OFEQ class Satellites design and it is capable to gather visual data of Earth Surface both at high resolution and large image capacity. The main attributes, derived from its compact design, low weight and sophisticated logic and which convert the EROS Satellite to valuable and productive system, are discussed. The major advantages of Light Satellites in High Resolution Earth Observation Domain are presented and WIS guidelines featuring the next generation of LEO Imaging Systems are included.

  4. High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

    Science.gov (United States)

    Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

    2017-12-01

    We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

  5. Vectorized Shoreline of Anatahan CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  6. Vectorized Shoreline of Pagan CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  7. Vectorized Shoreline of Agrihan CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  8. Vectorized Shoreline of Guguan CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  9. Vectorized Shoreline of Alamagan CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  10. RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    K. Gong

    2017-05-01

    Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

  11. Framework of Jitter Detection and Compensation for High Resolution Satellites

    Directory of Open Access Journals (Sweden)

    Xiaohua Tong

    2014-05-01

    Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

  12. Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery

    Science.gov (United States)

    Eugenio, F.; Martin, J.; Marcello, J.; Fraile-Nuez, E.

    2014-06-01

    El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (Kd) and chlorophyll-a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.

  13. Automatic Classification of High Resolution Satellite Imagery - a Case Study for Urban Areas in the Kingdom of Saudi Arabia

    Science.gov (United States)

    Maas, A.; Alrajhi, M.; Alobeid, A.; Heipke, C.

    2017-05-01

    Updating topographic geospatial databases is often performed based on current remotely sensed images. To automatically extract the object information (labels) from the images, supervised classifiers are being employed. Decisions to be taken in this process concern the definition of the classes which should be recognised, the features to describe each class and the training data necessary in the learning part of classification. With a view to large scale topographic databases for fast developing urban areas in the Kingdom of Saudi Arabia we conducted a case study, which investigated the following two questions: (a) which set of features is best suitable for the classification?; (b) what is the added value of height information, e.g. derived from stereo imagery? Using stereoscopic GeoEye and Ikonos satellite data we investigate these two questions based on our research on label tolerant classification using logistic regression and partly incorrect training data. We show that in between five and ten features can be recommended to obtain a stable solution, that height information consistently yields an improved overall classification accuracy of about 5%, and that label noise can be successfully modelled and thus only marginally influences the classification results.

  14. Automatic urban debris zone extraction from post-hurricane very high-resolution satellite and aerial imagery

    Directory of Open Access Journals (Sweden)

    Shasha Jiang

    2016-05-01

    Full Text Available Automated remote sensing methods have not gained widespread usage for damage assessment after hurricane events, especially for low-rise buildings, such as individual houses and small businesses. Hurricane wind, storm surge with waves, and inland flooding have unique damage signatures, further complicating the development of robust automated assessment methodologies. As a step toward realizing automated damage assessment for multi-hazard hurricane events, this paper presents a mono-temporal image classification methodology that quickly and accurately differentiates urban debris from non-debris areas using post-event images. Three classification approaches are presented: spectral, textural, and combined spectral–textural. The methodology is demonstrated for Gulfport, Mississippi, using IKONOS panchromatic satellite and NOAA aerial colour imagery collected after 2005 Hurricane Katrina. The results show that multivariate texture information significantly improves debris class detection performance by decreasing the confusion between debris and other land cover types, and the extracted debris zone accurately captures debris distribution. Additionally, the extracted debris boundary is approximately equivalent regardless of imagery type, demonstrating the flexibility and robustness of the debris mapping methodology. While the test case presents results for hurricane hazards, the proposed methodology is generally developed and expected to be effective in delineating debris zones for other natural hazards, including tsunamis, tornadoes, and earthquakes.

  15. High Resolution Satellite Remote Sensing of the 2013-2014 Eruption of Sinabung Volcano, Sumatra, Indonesia

    Science.gov (United States)

    Wessels, R. L.; Griswold, J. P.

    2014-12-01

    Satellite remote sensing provided timely observations of the volcanic unrest and several months-long eruption at Sinabung Volcano, Indonesia. Visible to thermal optical and synthetic aperture radar (SAR) systems provided frequent observations of Sinabung. High resolution image data with spatial resolutions from 0.5 to 1.5m offered detailed measurements of early summit deformation and subsequent lava dome and lava flow extrusion. The high resolution data were captured by commercial satellites such as WorldView-1 and -2 visible to near-infrared (VNIR) sensors and by CosmoSkyMed, Radarsat-2, and TerraSar-X SAR systems. Less frequent 90 to 100m spatial resolution night time thermal infrared (TIR) observations were provided by ASTER and Landsat-8. The combination of data from multiple sensors allowed us to construct a more complete timeline of volcanic activity than was available via only ground-based observations. This satellite observation timeline documents estimates of lava volume and effusion rates and major explosive and lava collapse events. Frequent, repeat volume estimates suggest at least three high effusion rate pulses of up to 20 m3/s occurred during the first three months of lava effusion with an average effusion rate of 6m3/s from January 2014 to August 2014. Many of these rates and events show some correlation to variations in the Real-time Seismic-Amplitude Measurement (RSAM) documented by the Indonesian Center for Volcanology and Geologic Hazard Mitigation (CVGHM).

  16. Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

    Science.gov (United States)

    Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

    2016-06-01

    Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

  17. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  18. MODELING AND SIMULATION OF HIGH RESOLUTION OPTICAL REMOTE SENSING SATELLITE GEOMETRIC CHAIN

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2018-04-01

    Full Text Available The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.

  19. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Oscar Rojas

    2013-04-01

    Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

  20. Essential Technology and Application of Jitter Detection and Compensation for High Resolution Satellites

    Directory of Open Access Journals (Sweden)

    TONG Xiaohua

    2017-10-01

    Full Text Available Satellite jitter is a common and complex phenomenon for the on-orbit high resolution satellites, which may affect the mapping accuracy and quality of imagery. A framework of jitter detection and compensation integrating data processing of multiple sensors is proposed in this paper. Jitter detection is performed based on multispectral imagery, three-line-array imagery, dense ground control and attitude measurement data, and jitter compensation is conducted both on image and on attitude with the sensor model. The platform jitter of ZY-3 satellite is processed and analyzed using the proposed technology, and the results demonstrate the feasibility and reliability of jitter detection and compensation. The variation law analysis of jitter indicates that the frequencies of jitter of ZY-3 satellite hold in the range between 0.6 and 0.7 Hz, while the amplitudes of jitter of ZY-3 satellite drop from 1 pixel in the early stage to below 0.4 pixels and tend to remain stable in the following stage.

  1. Temporal resolution requirements of satellite constellations for 30 m global burned area mapping

    Science.gov (United States)

    Melchiorre, A.; Boschetti, L.

    2017-12-01

    Global burned area maps have been generated systematically with daily, coarse resolution satellite data (Giglio et al. 2013). The production of moderate resolution (10 - 30 m) global burned area products would meet the needs of several user communities: improved carbon emission estimations due to heterogeneous landscapes and for local scale air quality and fire management applications (Mouillot et al. 2014; van der Werf et al. 2010). While the increased spatial resolution reduces the influence of mixed burnt/unburnt pixels and it would increase the spectral separation of burned areas, moderate resolution satellites have reduced temporal resolution (10 - 16 days). Fire causes a land-cover change spectrally visible for a period ranging from a few weeks in savannas to over a year in forested ecosystems (Roy et al. 2010); because clouds, smoke, and other optically thick aerosols limit the number of available observations (Roy et al. 2008; Smith and Wooster 2005), burned areas might disappear before they are observed by moderate resolution sensors. Data fusion from a constellation of different sensors has been proposed to overcome these limits (Boschetti et al. 2015; Roy 2015). In this study, we estimated the probability of moderate resolution satellites and virtual constellations (including Landsat-8/9, Sentinel-2A/B) to provide sufficient observations for burned area mapping globally, and by ecosystem. First, we estimated the duration of the persistence of the signal associated with burned areas by combining the MODIS Global Burned Area and the Nadir BRDF-Adjusted Reflectance Product by characterizing the post-fire trends in reflectance to determine the length of the period in which the burn class is spectrally distinct from the unburned and, therefore, detectable. The MODIS-Terra daily cloud data were then used to estimate the probability of cloud cover. The cloud probability was used at each location to estimate the minimum revisit time needed to obtain at least one

  2. The high resolution optical instruments for the Pleiades HR Earth observation satellites

    Science.gov (United States)

    Gaudin-Delrieu, Catherine; Lamard, Jean-Luc; Cheroutre, Philippe; Bailly, Bruno; Dhuicq, Pierre; Puig, Olivier

    2017-11-01

    Coming after the SPOT satellites series, PLEIADESHR is a CNES optical high resolution satellite dedicated to Earth observation, part of a larger optical and radar multi-sensors system, ORFEO, which is developed in cooperation between France and Italy for dual Civilian and Defense use. The development of the two PLEIADES-HR cameras was entrusted by CNES to Thales Alenia Space. This new generation of instrument represents a breakthrough in comparison with the previous SPOT instruments owing to a significant step in on-ground resolution, which approaches the capabilities of aerial photography. The PLEIADES-HR instrument program benefits from Thales Alenia Space long and successful heritage in Earth observation from space. The proposed solution benefits from an extensive use of existing products, Cannes Space Optics Centre facilities, unique in Europe, dedicated to High Resolution instruments. The optical camera provides wide field panchromatic images supplemented by 4 multispectral channels with narrow spectral bands. The optical concept is based on a four mirrors Korsch telescope. Crucial improvements in detector technology, optical fabrication and electronics make it possible for the PLEIADES-HR instrument to achieve the image quality requirements while respecting the drastic limitations of mass and volume imposed by the satellite agility needs and small launchers compatibility. The two flight telescopes were integrated, aligned and tested. After the integration phase, the alignment, mainly based on interferometric measurements in vacuum chamber, was successfully achieved within high accuracy requirements. The wave front measurements show outstanding performances, confirmed, after the integration of the PFM Detection Unit, by MTF measurements on the Proto-Flight Model Instrument. Delivery of the proto flight model occurred mi-2008. The FM2 Instrument delivery is planned Q2-2009. The first optical satellite launch of the PLEIADES-HR constellation is foreseen

  3. Green leaf phenology at Landsat resolution: scaling from the plot to satellite

    Science.gov (United States)

    Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

    2005-12-01

    Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

  4. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the Sentinel-1 satellites

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of high resolution sea surface winds data produced from Synthetic Aperture Radar (SAR) on board Sentinel-1A and Sentinel-1B satellites. This...

  5. Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

    Science.gov (United States)

    Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

    2015-12-01

    Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

  6. A high-resolution and observationally constrained OMI NO2 satellite retrieval

    International Nuclear Information System (INIS)

    Goldberg, Daniel L.; Lamsal, Lok N.; Loughner, Christopher P.

    2017-01-01

    Here, this work presents a new high-resolution NO 2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO 2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO 2 vertical profile shape factors from a 1.25° × 1° (~110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO 2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO 2 vertical columns during summertime in the eastern US. In this new product, OMI NO 2 tropospheric columns increase by up to 160% in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO 2 and Airborne Compact Atmospheric Mapper (ACAM) NO 2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO 2 monitors in urban areas has improved dramatically: r 2 = 0.60 in the new product vs. r 2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NO x emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO 2 satellite retrievals.

  7. Monitoring Termite-Mediated Ecosystem Processes Using Moderate and High Resolution Satellite Imagery

    Science.gov (United States)

    Lind, B. M.; Hanan, N. P.

    2016-12-01

    Termites are considered dominant decomposers and prominent ecosystem engineers in the global tropics and they build some of the largest and architecturally most complex non-human-made structures in the world. Termite mounds significantly alter soil texture, structure, and nutrients, and have major implications for local hydrological dynamics, vegetation characteristics, and biological diversity. An understanding of how these processes change across large scales has been limited by our ability to detect termite mounds at high spatial resolutions. Our research develops methods to detect large termite mounds in savannas across extensive geographic areas using moderate and high resolution satellite imagery. We also investigate the effect of termite mounds on vegetation productivity using Landsat-8 maximum composite NDVI data as a proxy for production. Large termite mounds in arid and semi-arid Senegal generate highly reflective `mound scars' with diameters ranging from 10 m at minimum to greater than 30 m. As Sentinel-2 has several bands with 10 m resolution and Landsat-8 has improved calibration, higher radiometric resolution, 15 m spatial resolution (pansharpened), and improved contrast between vegetated and bare surfaces compared to previous Landsat missions, we found that the largest and most influential mounds in the landscape can be detected. Because mounds as small as 4 m in diameter are easily detected in high resolution imagery we used these data to validate detection results and quantify omission errors for smaller mounds.

  8. Mapping Robinia Pseudoacacia Forest Health Conditions by Using Combined Spectral, Spatial, and Textural Information Extracted from IKONOS Imagery and Random Forest Classifier

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2015-07-01

    Full Text Available The textural and spatial information extracted from very high resolution (VHR remote sensing imagery provides complementary information for applications in which the spectral information is not sufficient for identification of spectrally similar landscape features. In this study grey-level co-occurrence matrix (GLCM textures and a local statistical analysis Getis statistic (Gi, computed from IKONOS multispectral (MS imagery acquired from the Yellow River Delta in China, along with a random forest (RF classifier, were used to discriminate Robina pseudoacacia tree health levels. Specifically, eight GLCM texture features (mean, variance, homogeneity, dissimilarity, contrast, entropy, angular second moment, and correlation were first calculated from IKONOS NIR band (Band 4 to determine an optimal window size (13 × 13 and an optimal direction (45°. Then, the optimal window size and direction were applied to the three other IKONOS MS bands (blue, green, and red for calculating the eight GLCM textures. Next, an optimal distance value (5 and an optimal neighborhood rule (Queen’s case were determined for calculating the four Gi features from the four IKONOS MS bands. Finally, different RF classification results of the three forest health conditions were created: (1 an overall accuracy (OA of 79.5% produced using the four MS band reflectances only; (2 an OA of 97.1% created with the eight GLCM features calculated from IKONOS Band 4 with the optimal window size of 13 × 13 and direction 45°; (3 an OA of 93.3% created with the all 32 GLCM features calculated from the four IKONOS MS bands with a window size of 13 × 13 and direction of 45°; (4 an OA of 94.0% created using the four Gi features calculated from the four IKONOS MS bands with the optimal distance value of 5 and Queen’s neighborhood rule; and (5 an OA of 96.9% created with the combined 16 spectral (four, spatial (four, and textural (eight features. The most important feature ranked by RF

  9. Monitoring of oil pollution in the Arabian Gulf based on medium resolution satellite imagery

    Science.gov (United States)

    Zhao, J.; Ghedira, H.

    2013-12-01

    A large number of inland and offshore oil fields are located in the Arabian Gulf where about 25% of the world's oil is produced by the countries surrounding the Arabian Gulf region. Almost all of this oil production is shipped by sea worldwide through the Strait of Hormuz making the region vulnerable to environmental and ecological threats that might arise from accidental or intentional oil spills. Remote sensing technologies have the unique capability to detect and monitor oil pollutions over large temporal and spatial scales. Synoptic satellite imaging can date back to 1972 when Landsat-1 was launched. Landsat satellite missions provide long time series of imagery with a spatial resolution of 30 m. MODIS sensors onboard NASA's Terra and Aqua satellites provide a wide and frequent coverage at medium spatial resolution, i.e. 250 m and 500, twice a day. In this study, the capability of medium resolution MODIS and Landsat data in detecting and monitoring oil pollutions in the Arabian Gulf was tested. Oil spills and slicks show negative or positive contrasts in satellite derived RGB images compared with surrounding clean waters depending on the solar/viewing geometry, oil thickness and evolution, etc. Oil-contaminated areas show different spectral characteristics compared with surrounding waters. Rayleigh-corrected reflectance at the seven medium resolution bands of MODIS is lower in oil affected areas. This is caused by high light absorption of oil slicks. 30-m Landsat image indicated the occurrence of oil spill on May 26 2000 in the Arabian Gulf. The oil spill showed positive contrast and lower temperature than surrounding areas. Floating algae index (FAI) images are also used to detect oil pollution. Oil-contaminated areas were found to have lower FAI values. To track the movement of oil slicks found on October 21 2007, ocean circulations from a HYCOM model were examined and demonstrated that the oil slicks were advected toward the coastal areas of United Arab

  10. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

    Science.gov (United States)

    Benzouai, Siham; Smara, Youcef

    2010-12-01

    The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

  11. Comparison of different "along the track" high resolution satellite stereo-pair for DSM extraction

    Science.gov (United States)

    Nikolakopoulos, Konstantinos G.

    2013-10-01

    The possibility to create DEM from stereo pairs is based on the Pythagoras theorem and on the principles of photogrammetry that are applied to aerial photographs stereo pairs for the last seventy years. The application of these principles to digital satellite stereo data was inherent in the first satellite missions. During the last decades the satellite stereo-pairs were acquired across the track in different days (SPOT, ERS etc.). More recently the same-date along the track stereo-data acquisition seems to prevail (Terra ASTER, SPOT5 HRS, Cartosat, ALOS Prism) as it reduces the radiometric image variations (refractive effects, sun illumination, temporal changes) and thus increases the correlation success rate in any image matching.Two of the newest satellite sensors with stereo collection capability is Cartosat and ALOS Prism. Both of them acquire stereopairs along the track with a 2,5m spatial resolution covering areas of 30X30km. In this study we compare two different satellite stereo-pair collected along the track for DSM creation. The first one is created from a Cartosat stereopair and the second one from an ALOS PRISM triplet. The area of study is situated in Chalkidiki Peninsula, Greece. Both DEMs were created using the same ground control points collected with a Differential GPS. After a first control for random or systematic errors a statistical analysis was done. Points of certified elevation have been used to estimate the accuracy of these two DSMs. The elevation difference between the different DEMs was calculated. 2D RMSE, correlation and the percentile value were also computed and the results are presented.

  12. The High Visible Resolution (HVR) instrument of the spot ground observation satellite

    Science.gov (United States)

    Otrio, G.

    1980-01-01

    Two identical high resolution cameras, capable of attaining a track width of 116 km in an almost vertical line of sight from the two 60 km images of each instrument, will be carried on the initial mission of the space observation of Earth satellite (SPOT). Specifications for the instrument, including the telescope and CCD devices are summarized. The present status of development is described including the optical characteristics, structure and thermal control, detector assembly, electronic equipment, and calibration. SPOT mission objectives include the developments relating to soil use, the exploration of EART Earth resources, the discrimination of plant species, and cartography.

  13. A fast and automatic mosaic method for high-resolution satellite images

    Science.gov (United States)

    Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

    2015-12-01

    We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

  14. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    Science.gov (United States)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  15. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    KAUST Repository

    McCabe, Matthew

    2016-10-25

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-Agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  16. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  17. A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

    Science.gov (United States)

    Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

    2009-01-01

    Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

  18. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  19. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  20. Scene Classification Using High Spatial Resolution Multispectral Data

    National Research Council Canada - National Science Library

    Garner, Jamada

    2002-01-01

    ...), High-spatial resolution (8-meter), 4-color MSI data from IKONOS provide a new tool for scene classification, The utility of these data are studied for the purpose of classifying the Elkhorn Slough and surrounding wetlands in central...

  1. Image-based reflectance conversion of ASTER and IKONOS ...

    African Journals Online (AJOL)

    Spectral signatures derived from different image-based models for ASTER and IKONOS were inspected visually as first departure. This was followed by comparison of the total accuracy and Kappa index computed from supervised classification of images that were derived from different image-based atmospheric correction ...

  2. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

    Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

  3. Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

    Science.gov (United States)

    Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

    2016-10-01

    Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

  4. Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

    Science.gov (United States)

    Arellano-Baeza, Alonso A.

    Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.

  5. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

    Directory of Open Access Journals (Sweden)

    Yu Liu

    Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  6. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    Science.gov (United States)

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  7. VAST PLANES OF SATELLITES IN A HIGH-RESOLUTION SIMULATION OF THE LOCAL GROUP: COMPARISON TO ANDROMEDA

    International Nuclear Information System (INIS)

    Gillet, N.; Ocvirk, P.; Aubert, D.; Knebe, A.; Yepes, G.; Libeskind, N.; Gottlöber, S.; Hoffman, Y.

    2015-01-01

    We search for vast planes of satellites (VPoS) in a high-resolution simulation of the Local Group performed by the CLUES project, which improves significantly the resolution of previous similar studies. We use a simple method for detecting planar configurations of satellites, and validate it on the known plane of M31. We implement a range of prescriptions for modeling the satellite populations, roughly reproducing the variety of recipes used in the literature, and investigate the occurrence and properties of planar structures in these populations. The structure of the simulated satellite systems is strongly non-random and contains planes of satellites, predominantly co-rotating, with, in some cases, sizes comparable to the plane observed in M31 by Ibata et al. However, the latter is slightly richer in satellites, slightly thinner, and has stronger co-rotation, which makes it stand out as overall more exceptional than the simulated planes, when compared to a random population. Although the simulated planes we find are generally dominated by one real structure forming its backbone, they are also partly fortuitous and are thus not kinematically coherent structures as a whole. Provided that the simulated and observed planes of satellites are indeed of the same nature, our results suggest that the VPoS of M31 is not a coherent disk and that one-third to one-half of its satellites must have large proper motions perpendicular to the plane

  8. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

    Science.gov (United States)

    Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

    2015-12-01

    Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

  9. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

    OpenAIRE

    Xueke Li; Taixia Wu; Kai Liu; Yao Li; Lifu Zhang

    2016-01-01

    The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1) opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, ...

  10. Monitoring Powdery Mildew of Winter Wheat by Using Moderate Resolution Multi-Temporal Satellite Imagery

    Science.gov (United States)

    Zhang, Jingcheng; Pu, Ruiliang; Yuan, Lin; Wang, Jihua; Huang, Wenjiang; Yang, Guijun

    2014-01-01

    Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale. PMID:24691435

  11. Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

    Directory of Open Access Journals (Sweden)

    Shimelis B. Gebere

    2015-09-01

    Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

  12. Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

    Science.gov (United States)

    Kamangir, H.; Momeni, M.; Satari, M.

    2017-09-01

    This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

  13. Approaching bathymetry estimation from high resolution multispectral satellite images using a neuro-fuzzy technique

    Science.gov (United States)

    Corucci, Linda; Masini, Andrea; Cococcioni, Marco

    2011-01-01

    This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.

  14. Detection of a weak meddy-like anomaly from high-resolution satellite SST maps

    Directory of Open Access Journals (Sweden)

    Mikhail Emelianov

    2012-09-01

    Full Text Available Despite the considerable impact of meddies on climate through the long-distance transport of properties, a consistent observation of meddy generation and propagation in the ocean is rather elusive. Meddies propagate at about 1000 m below the ocean surface, so satellite sensors are not able to detect them directly and finding them in the open ocean is more fortuitous than intentional. However, a consistent census of meddies and their paths is required in order to gain knowledge about their role in transporting properties such as heat and salt. In this paper we propose a new methodology for processing high-resolution sea surface temperature maps in order to detect meddy-like anomalies in the open ocean on a near-real-time basis. We present an example of detection, involving an atypical meddy-like anomaly that was confirmed as such by in situ measurements.

  15. High resolution satellite image indexing and retrieval using SURF features and bag of visual words

    Science.gov (United States)

    Bouteldja, Samia; Kourgli, Assia

    2017-03-01

    In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

  16. Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

    Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

  17. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  18. Automatic Blocked Roads Assessment after Earthquake Using High Resolution Satellite Imagery

    Science.gov (United States)

    Rastiveis, H.; Hosseini-Zirdoo, E.; Eslamizade, F.

    2015-12-01

    In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to "debris" class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the "debris" class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

  19. Extraction of prospecting information of uranium deposit based on high spatial resolution satellite data. Taking bashibulake region as an example

    International Nuclear Information System (INIS)

    Yang Xu; Liu Dechang; Zhang Jielin

    2008-01-01

    In this study, the signification and content of prospecting information of uranium deposit are expounded. Quickbird high spatial resolution satellite data are used to extract the prospecting information of uranium deposit in Bashibulake area in the north of Tarim Basin. By using the pertinent methods of image processing, the information of ore-bearing bed, ore-control structure and mineralized alteration have been extracted. The results show a high consistency with the field survey. The aim of this study is to explore practicability of high spatial resolution satellite data for prospecting minerals, and to broaden the thinking of prospectation at similar area. (authors)

  20. Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

    Science.gov (United States)

    Spruce, Joseph P.; Ross, Kenton W.; Graham, William D.

    2007-01-01

    Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 9:45 a.m. CDT as a category 3 storm with surges up to approx. 9 m and sustained winds of approx. 120 mph. The hurricane's wind, rain, and flooding devastated several coastal towns, from New Orleans through Mobile. The storm also caused significant damage to infrastructure and vegetation of NASA's SSC (Stennis Space Center). Storm recovery at SSC involved not only repairs of critical infrastructure but also forest damage mitigation (via timber harvests and control burns to reduce fire risk). This presentation discusses an effort to use commercially available high spatial resolution multispectral IKONOS data for vegetation damage assessment, based on data collected over SSC on September 2, 2005.

  1. Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

    Science.gov (United States)

    Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

    The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the

  2. Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index

    Science.gov (United States)

    Yang, Dedi; Chen, Jin; Zhou, Yuan; Chen, Xiang; Chen, Xuehong; Cao, Xin

    2017-06-01

    Plastic greenhouses (PGs) are an important agriculture development technique to protect and control the growing environment for food crops. The extensive use of PGs can change the agriculture landscape and affects the local environment. Accurately mapping and estimating the coverage of PGs is a necessity to the strategic planning of modern agriculture. Unfortunately, PG mapping over large areas is methodologically challenging, as the medium spatial resolution satellite imagery (such as Landsat data) used for analysis lacks spatial details and spectral variations. To fill the gap, the paper proposes a new plastic greenhouse index (PGI) based on the spectral, sensitivity, and separability analysis of PGs using medium spatial resolution images. In the context of the Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, the paper examines the effectiveness and capability of the proposed PGI. The results indicate that PGs in Landsat ETM+ image can be successfully detected by the PGI if the PG fraction is greater than 12% in a mixed pixel. A kappa coefficient of 0.83 and overall accuracy of 91.2% were achieved when applying the proposed PGI in the case of Weifang District, Shandong, China. These results show that the proposed index can be applied to identifying transparent PGs in atmospheric corrected Landsat image and has the potential for the digital mapping of plastic greenhouse coverage over a large area.

  3. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    OpenAIRE

    Chandi Witharana; Heather J. Lynch

    2016-01-01

    The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA) methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR) satellite imagery and closely examined the transferability of knowle...

  4. Spatiotemporal estimation of air temperature patterns at the street level using high resolution satellite imagery.

    Science.gov (United States)

    Pelta, Ran; Chudnovsky, Alexandra A

    2017-02-01

    Although meteorological monitoring stations provide accurate measurements of Air Temperature (AT), their spatial coverage within a given region is limited and thus is often insufficient for exposure and epidemiological studies. In many applications, satellite imagery measures energy flux, which is spatially continuous, and calculates Brightness Temperature (BT) that used as an input parameter. Although both quantities (AT-BT) are physically related, the correlation between them is not straightforward, and varies daily due to parameters such as meteorological conditions, surface moisture, land use, satellite-surface geometry and others. In this paper we first investigate the relationship between AT and BT as measured by 39 meteorological stations in Israel during 1984-2015. Thereafter, we apply mixed regression models with daily random slopes to calibrate Landsat BT data with monitored AT measurements for the period 1984-2015. Results show that AT can be predicted with high accuracy by using BT with high spatial resolution. The model shows relatively high accuracy estimation of AT (R 2 =0.92, RMSE=1.58°C, slope=0.90). Incorporating meteorological parameters into the model generates better accuracy (R 2 =0.935) than the AT-BT model (R 2 =0.92). Furthermore, based on the relatively high model accuracy, we investigated the spatial patterns of AT within the study domain. In the latter we focused on July-August, as these two months are characterized by relativity stable synoptic conditions in the study area. In addition, a temporal change in AT during the last 30years was estimated and verified using available meteorological stations and two additional remote sensing platforms. Finally, the impact of different land coverage on AT were estimated, as an example of future application of the presented approach. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

    Science.gov (United States)

    Parida, P. K.; Sanabada, M. K.; Tripathi, S.

    2014-11-01

    Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.

  6. Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    CAO Yungang

    2016-10-01

    Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

  7. Space volcano observatory (SVO): a metric resolution system on-board a micro/mini-satellite

    Science.gov (United States)

    Briole, P.; Cerutti-Maori, G.; Kasser, M.

    2017-11-01

    1500 volcanoes on the Earth are potentially active, one third of them have been active during this century and about 70 are presently erupting. At the beginning of the third millenium, 10% of the world population will be living in areas directly threatened by volcanoes, without considering the effects of eruptions on climate or air-trafic for example. The understanding of volcanic eruptions, a major challenge in geoscience, demands continuous monitoring of active volcanoes. The only way to provide global, continuous, real time and all-weather information on volcanoes is to set up a Space Volcano Observatory closely connected to the ground observatories. Spaceborne observations are mandatory and implement the ground ones as well as airborne ones that can be implemented on a limited set of volcanoes. SVO goal is to monitor both the deformations and the changes in thermal radiance at optical wavelengths from high temperature surfaces of the active volcanic zones. For that, we propose to map at high resolution (1 to 1,5 m pixel size) the topography (stereoscopic observation) and the thermal anomalies (pixel-integrated temperatures above 450°C) of active volcanic areas in a size of 6 x 6 km to 12 x 12 km, large enough for monitoring most of the target features. A return time of 1 to 3 days will allow to get a monitoring useful for hazard mitigation. The paper will present the concept of the optical payload, compatible with a micro/mini satellite (mass in the range 100 - 400 kg), budget for the use of Proteus platform in the case of minisatellite approach will be given and also in the case of CNES microsat platform family. This kind of design could be used for other applications like high resolution imagery on a limited zone for military purpose, GIS, evolution cadaster…

  8. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  9. Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations

    Science.gov (United States)

    Durán Moro, Marina; Brankart, Jean-Michel; Brasseur, Pierre; Verron, Jacques

    2017-07-01

    Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below

  10. A global high resolution mean sea surface from multi mission satellite altimetry

    DEFF Research Database (Denmark)

    Knudsen, Per

    1999-01-01

    Satellite altimetry from the GEOSAT and the ERS-1 geodetic missions provide altimeter data with a very dense coverage. Hence, the heights of the sea surface may be recovered very detailed. Satellite altimetry from the 35 days repeat cycle mission of the ERS satellites and, especially, from the 10...

  11. Satellite monitoring at high spatial resolution of water bodies used for irrigation purposes

    Science.gov (United States)

    Baup, F.; Flanquart, S.; Marais-Sicre, C.; Fieuzal, R.

    2012-04-01

    In a changing climate context, with an increase of the need for food, it becomes increasingly important to improve our knowledge for monitoring agricultural surfaces by satellite for a better food management and to reduce the waste of natural resources (water storages and shortages, irrigation management, increase of soil and water salinity, soil erosion, threats on biodiversity). The main objective of this study is to evaluate the potentialities of multi-spectral and multi-resolution satellites for monitoring the temporal evolution of water bodies surfaces (mainly used for irrigation purposes). This analysis is based on the use of a series of images acquired between the years 2003 and 2011. The year 2010 is considered as a reference, with 110 acquisitions performed during the MCM'10 campaign (Multispectral Crop Monitoring 2010, http://www.cesbio.ups-tlse.fr/us/mcm.html). Those images are provided by 8 satellites (optical, thermal and RADAR) such as ALOS, TERRASAR-X, RADARSAT-2, FORMOSAT-2, SPOT-2, SPOT-4, SPOT-5, LANDSAT-5. The studied area is situated in the South-West of Toulouse in France; in a region governed by a temperate climate. The irrigated cultures represent almost 12% of the cultivated surface in 2009. The method consists in estimating the water bodies surfaces by using a generic approach suitable for all images, whatever the wavelength (optical, infrared, RADAR). The supervised parallelepiped classification allows discriminating four types of surfaces coverage: forests, water expanses, crops and bare soils. All RADAR images are filtered (Gamma) to reduce speckle effects and false detections of water bodies. In the context if the "South-West" project of the CESBIO laboratory, two spatial coverages are analyzed: SPOT 4 (4800km2) and FORMOSAT 2 (576km2). At these scales, 154 and 38 water bodies are identify. They respectively represent 4.85 km2 (0.10% of the image cover) and 2.06 km2 (0.36% of the image cover). Statistical analyses show that 8% of lakes

  12. FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Wohlfeil

    2012-07-01

    Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

  13. A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

    Directory of Open Access Journals (Sweden)

    Huai Yu

    2016-03-01

    Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

  14. Use of high-resolution satellite images for detection of geothermal reservoirs

    Science.gov (United States)

    Arellano-Baeza, A. A.

    2012-12-01

    Chile has an enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile and Puchuldiza geothermal field located in the Region of Tarapaca. It was done by applying the lineament extraction technique developed by author. These structures have been compared with the distribution of main geological structures obtained in the fields. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

  15. A Multi-stage Method to Extract Road from High Resolution Satellite Image

    International Nuclear Information System (INIS)

    Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang

    2014-01-01

    Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed

  16. Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

    Science.gov (United States)

    Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

    2017-09-01

    The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

  17. Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

    Directory of Open Access Journals (Sweden)

    Christopher S. R. Neigh

    2014-02-01

    Full Text Available Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs and height data derived from Goddard’s airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT with three types of IKONOS stereo derived digital surface models (DSMs that estimate CHMs by subtracting National Elevation Data (NED digital terrain models (DTMs. We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1 G-LiHT DTMs were highly correlated with NED DTMs with R2 > 0.98 and root mean square errors (RMSEs < 2.96 m; (2 when using one visually identifiable ground control point (GCP from NED, G-LiHT DSMs and IKONOS DSMs had R2 > 0.84 and RMSEs of 2.7 to 4.1 m; and (3 one GCP CHMs for two study sites had R2 > 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

  18. Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

    Science.gov (United States)

    Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

    2018-04-01

    The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

  19. The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation

    Science.gov (United States)

    Williams, Jason E.; Folkert Boersma, K.; Le Sager, Phillipe; Verstraeten, Willem W.

    2017-02-01

    We provide a comprehensive description of the high-resolution version of the TM5-MP global chemistry transport model, which is to be employed for deriving highly resolved vertical profiles of nitrogen dioxide (NO2), formaldehyde (CH2O), and sulfur dioxide (SO2) for use in satellite retrievals from platforms such as the Ozone Monitoring Instrument (OMI) and the Sentinel-5 Precursor, and the TROPOspheric Monitoring Instrument (tropOMI). Comparing simulations conducted at horizontal resolutions of 3° × 2° and 1° × 1° reveals differences of ±20 % exist in the global seasonal distribution of 222Rn, being larger near specific coastal locations and tropical oceans. For tropospheric ozone (O3), analysis of the chemical budget terms shows that the impact on globally integrated photolysis rates is rather low, in spite of the higher spatial variability of meteorological data fields from ERA-Interim at 1° × 1°. Surface concentrations of O3 in high-NOx regions decrease between 5 and 10 % at 1° × 1° due to a reduction in NOx recycling terms and an increase in the associated titration term of O3 by NO. At 1° × 1°, the net global stratosphere-troposphere exchange of O3 decreases by ˜ 7 %, with an associated shift in the hemispheric gradient. By comparing NO, NO2, HNO3 and peroxy-acetyl-nitrate (PAN) profiles against measurement composites, we show that TM5-MP captures the vertical distribution of NOx and long-lived NOx reservoirs at background locations, again with modest changes at 1° × 1°. Comparing monthly mean distributions in lightning NOx and applying ERA-Interim convective mass fluxes, we show that the vertical re-distribution of lightning NOx changes with enhanced release of NOx in the upper troposphere. We show that surface mixing ratios in both NO and NO2 are generally underestimated in both low- and high-NOx scenarios. For Europe, a negative bias exists for [NO] at the surface across the whole domain, with lower biases at 1° × 1° at only ˜ 20

  20. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

    Directory of Open Access Journals (Sweden)

    Xueke Li

    2016-05-01

    Full Text Available The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1 opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m to EO-1 Hyperion (with a spatial resolution of 30 m. The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC, pixel-based support vector machine (PSVM, hybrid maximum likelihood classifier (HMLC, and hybrid support vector machine (HSVM were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the

  1. SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-01-01

    To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

  2. [Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

    Science.gov (United States)

    Zhang, Pei-feng; Hu, Yuan-man; He, Hong-shi

    2010-05-01

    The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

  3. DEM GENERATION FROM HIGH RESOLUTION SATELLITE IMAGES THROUGH A NEW 3D LEAST SQUARES MATCHING ALGORITHM

    Directory of Open Access Journals (Sweden)

    T. Kim

    2012-09-01

    Full Text Available Automated generation of digital elevation models (DEMs from high resolution satellite images (HRSIs has been an active research topic for many years. However, stereo matching of HRSIs, in particular based on image-space search, is still difficult due to occlusions and building facades within them. Object-space matching schemes, proposed to overcome these problem, often are very time consuming and critical to the dimensions of voxels. In this paper, we tried a new least square matching (LSM algorithm that works in a 3D object space. The algorithm starts with an initial height value on one location of the object space. From this 3D point, the left and right image points are projected. The true height is calculated by iterative least squares estimation based on the grey level differences between the left and right patches centred on the projected left and right points. We tested the 3D LSM to the Worldview images over 'Terrassa Sud' provided by the ISPRS WG I/4. We also compared the performance of the 3D LSM with the correlation matching based on 2D image space and the correlation matching based on 3D object space. The accuracy of the DEM from each method was analysed against the ground truth. Test results showed that 3D LSM offers more accurate DEMs over the conventional matching algorithms. Results also showed that 3D LSM is sensitive to the accuracy of initial height value to start the estimation. We combined the 3D COM and 3D LSM for accurate and robust DEM generation from HRSIs. The major contribution of this paper is that we proposed and validated that LSM can be applied to object space and that the combination of 3D correlation and 3D LSM can be a good solution for automated DEM generation from HRSIs.

  4. Smoke Dispersion Modeling Over Complex Terrain Using High-Resolution Meteorological Data and Satellite Observations: The FireHub Platform

    Science.gov (United States)

    Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.

    2015-01-01

    A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002e2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.

  5. Evaluation of satellite technology for pipeline route surveillance and the prevention of third party interference damage

    Energy Technology Data Exchange (ETDEWEB)

    Palmer-Jones, Roland; Hopkins, Phil [Penspen Integrity, Newcastle upon Tyne (United Kingdom)]. E-mail: r.palmer-jones@penspen.com; p.hopkins@penspen.com; Fraser, Andy [Integrated Statistical Solutions (United States)]. E-mail: andy@issquared.co.uk; Dezobry, Jerome [Gas de France, Paris (France)]. E-mail: jerome.dezobry@gazdefrance.com; Merrienboer, Hugo Van [Gasunie, Groningen (Netherlands)]. E-mail: H.A.M.van.Merrienboer@gasunie.nl

    2003-07-01

    The damage caused by Third Party Interference (TPI) is one of the major causes of pipeline failures. Consequently, new technologies for identifying activities that may cause damage to our pipelines are constantly being developed. A recently completed project sponsored by a number of pipeline operators has investigated the use of high-resolution satellites for the integrity management of onshore transmission pipelines. The sponsors were BG Technology (on behalf of Transco), Dansk Olie NatureGas, Gasunie, BP, Gaz de France, Distrigas, and the Health and Safety Executive. The project started with a general review of the satellite technologies available and their potential. The study was then focussed on the identification of activities that might result in damage to the pipeline and the potential of high-resolution optical satellites in identifying hazardous activities. A key element of the study was a comparison with existing surveillance systems, which generally involve regular aerial patrols of the pipeline route. To achieve this a survey was carried out to try and evaluate the costs and benefits of existing systems. In addition a simple model for analysing the cost benefit of pipeline surveillance was constructed, and a functional specification for a surveillance system drafted. Finally the performance of the IKONOS 2 high-resolution satellite system was tested in a controlled experiment using targets placed along a pipeline route. The results of this test were compared with a similar test of helicopter-based surveillance carried out by one of the sponsors. (author)

  6. Satellite microwave remote sensing of North Eurasian inundation dynamics: development of coarse-resolution products and comparison with high-resolution synthetic aperture radar data

    International Nuclear Information System (INIS)

    Schroeder, R; Rawlins, M A; McDonald, K C; Podest, E; Zimmermann, R; Kueppers, M

    2010-01-01

    Wetlands are not only primary producers of atmospheric greenhouse gases but also possess unique features that are favourable for application of satellite microwave remote sensing to monitoring their status and trend. In this study we apply combined passive and active microwave remote sensing data sets from the NASA sensors AMSR-E and QuikSCAT to map surface water dynamics over Northern Eurasia. We demonstrate our method on the evolution of large wetland complexes for two consecutive years from January 2006 to December 2007. We apply river discharge measurements from the Ob River along with land surface runoff simulations derived from the Pan-Arctic Water Balance Model during and after snowmelt in 2006 and 2007 to interpret the abundance of widespread flooding along the River Ob in early summer of 2007 observed in the remote sensing products. The coarse-resolution, 25 km, surface water product is compared to a high-resolution, 30 m, inundation map derived from ALOS PALSAR (Advanced Land Observation Satellite phased array L-band synthetic aperture radar) imagery acquired for 11 July 2006, and extending along a transect in the central Western Siberian Plain. We found that the surface water fraction derived from the combined AMSR-E/QuikSCAT data sets closely tracks the inundation mapped using higher-resolution ALOS PALSAR data.

  7. Coastal and Inland Water Applications of High Resolution Optical Satellite Data from Landsat-8 and Sentinel-2

    Science.gov (United States)

    Vanhellemont, Q.

    2016-02-01

    Since the launch of Landsat-8 (L8) in 2013, a joint NASA/USGS programme, new applications of high resolution imagery for coastal and inland waters have become apparent. The optical imaging instrument on L8, the Operational Land Imager (OLI), is much improved compared to its predecessors on L5 and L7, especially with regards to SNR and digitization, and is therefore well suited for retrieving water reflectances and derived parameters such as turbidity and suspended sediment concentration. In June 2015, the European Space Agency (ESA) successfully launched a similar instrument, the MultiSpectral Imager (MSI), on board of Sentinel-2A (S2A). Imagery from both L8 and S2A are free of charge and publicly available (S2A starting at the end of 2015). Atmospheric correction schemes and processing software is under development in the EC-FP7 HIGHROC project. The spatial resolution of these instruments (10-60 m) is a great improvement over typical moderate resolution ocean colour sensors such as MODIS and MERIS (0.25 - 1 km). At higher resolution, many more lakes, rivers, ports and estuaries are spatially resolved, and can thus now be studied using satellite data, unlocking potential for mandatory monitoring e.g. under European Directives such as the Marine Strategy Framework Directive and the Water Framework Directive. We present new applications of these high resolution data, such as monitoring of offshore constructions, wind farms, sediment transport, dredging and dumping, shipping and fishing activities. The spatial variability at sub moderate resolution (0.25 - 1 km) scales can be assessed, as well as the impact of sub grid scale variability (including ships and platforms used for validation) on the moderate pixel retrieval. While the daily revisit time of the moderate resolution sensors is vastly superior to those of the high resolution satellites, at the equator respectively 16 and 10 days for L8 and S2A, the low revisit times can be partially mitigated by combining data

  8. Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

    Science.gov (United States)

    Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

    2008-06-01

    Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

  9. The absolute calibration of KOMPSAT-3 and 3A high spatial resolution satellites using radiometric tarps and MFRSR measurments

    Science.gov (United States)

    Yeom, J. M.

    2017-12-01

    Recently developed Korea Multi-Purpose Satellite-3A (KOMPSAT-3A), which is a continuation of the KOMPSAT-1, 2 and 3 earth observation satellite (EOS) programs from the Korea Aerospace Research Institute (KARI) was launched on March, 25 2015 on a Dnepr-1 launch vehicle from the Jasny Dombarovsky site in Russia. After launched, KARI performed in-orbit-test (IOT) including radiometric calibration for 6 months from 14 Apr. to 4 Sep. 2015. KOMPSAT-3A is equipped with two distinctive sensors; one is a high resolution multispectral optical sensor, namely the Advances Earth Image Sensor System-A (AEISS-A) and the other is the Scanner Infrared Imaging System (SIIS). In this study, we focused on the radiometric calibration of AEISS-A. The multispectral wavelengths of AEISS-A are covering three visible regions: blue (450 - 520 nm), green (520 - 600 nm), red (630 - 690 nm), one near infrared (760 - 900 nm) with a 2.0 m spatial resolution at nadir, whereas the panchromatic imagery (450 - 900 nm) has a 0.5 m resolution. Those are the same spectral response functions were same with KOMPSAT-3 multispectral and panchromatic bands but the spatial resolutions are improved. The main mission of KOMPSAT-3A is to develop for Geographical Information System (GIS) applications in environmental, agriculture, and oceanographic sciences, as well as natural hazard monitoring.

  10. Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

    Science.gov (United States)

    Hester, David Barry

    The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

  11. Semi-automatic building extraction in informal settlements from high-resolution satellite imagery

    Science.gov (United States)

    Mayunga, Selassie David

    The extraction of man-made features from digital remotely sensed images is considered as an important step underpinning management of human settlements in any country. Man-made features and buildings in particular are required for varieties of applications such as urban planning, creation of geographical information systems (GIS) databases and Urban City models. The traditional man-made feature extraction methods are very expensive in terms of equipment, labour intensive, need well-trained personnel and cannot cope with changing environments, particularly in dense urban settlement areas. This research presents an approach for extracting buildings in dense informal settlement areas using high-resolution satellite imagery. The proposed system uses a novel strategy of extracting building by measuring a single point at the approximate centre of the building. The fine measurement of the building outlines is then effected using a modified snake model. The original snake model on which this framework is based, incorporates an external constraint energy term which is tailored to preserving the convergence properties of the snake model; its use to unstructured objects will negatively affect their actual shapes. The external constrained energy term was removed from the original snake model formulation, thereby, giving ability to cope with high variability of building shapes in informal settlement areas. The proposed building extraction system was tested on two areas, which have different situations. The first area was Tungi in Dar Es Salaam, Tanzania where three sites were tested. This area is characterized by informal settlements, which are illegally formulated within the city boundaries. The second area was Oromocto in New Brunswick, Canada where two sites were tested. Oromocto area is mostly flat and the buildings are constructed using similar materials. Qualitative and quantitative measures were employed to evaluate the accuracy of the results as well as the performance

  12. Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method

    Science.gov (United States)

    Brovelli, Maria Antonia; Crespi, Mattia; Fratarcangeli, Francesca; Giannone, Francesca; Realini, Eugenio

    Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic. In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment. The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation-orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available. To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV

  13. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

  14. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 1999 on board the Terra satellite platform (a...

  15. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 2002 on board the Aqua satellite platform (a...

  16. Validation of ERS-1 and high-resolution satellite gravity with in-situ shipborne gravity over the Indian offshore regions: Accuracies and implications to subsurface modeling

    Digital Repository Service at National Institute of Oceanography (India)

    Chatterjee, S.; Bhattacharyya, R.; Michael, L.; Krishna, K.S.; Majumdar, T.J.

    Geoid and gravity anomalies derived from satellite altimetry are gradually gaining importance in marine geoscientific investigations. Keeping this in mind, we have validated ERS-1 (168 day repeat) altimeter data and very high-resolution free...

  17. Feature extraction from high resolution satellite imagery as an input to the development and rapid update of a METRANS geographic information system (GIS).

    Science.gov (United States)

    2011-06-01

    This report describes an accuracy assessment of extracted features derived from three : subsets of Quickbird pan-sharpened high resolution satellite image for the area of the : Port of Los Angeles, CA. Visual Learning Systems Feature Analyst and D...

  18. Vectorized Shoreline of Rota, Commonwealth of the Northern Mariana Islands, Derived from IKONOS Imagery, 2002

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  19. Vectorized Shoreline of Farallon de Medinilla CNMI, 2001 Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  20. Vectorized Shoreline of Saipan, Commonwealth of the Northern Mariana Islands, Derived from IKONOS Imagery, 2002

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  1. Vectorized Shoreline of Tinian, Commonwealth of the Northern Mariana Islands, Derived from IKONOS Imagery, 2001

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  2. Vectorized Shoreline of Manua Islands, American Samoa 2001, Derived from IKONOS Imagery,

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  3. Vectorized Shoreline of Saipan, Commonwealth of the Northern Mariana Islands, Derived from IKONOS Imagery, 2001

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  4. Vectorized Shoreline of Rose Atoll, American Samoa, 2001 Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  5. Vectorized Shoreline of Farallon de Pajaros CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  6. Vectorized Shoreline of Tutuila, American Samoa, 2001 Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  7. Vectorized Shoreline of Maug Islands CNMI 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  8. Vectorized Shoreline of Sarigan, Commonwealth of the Northern Mariana Islands 2001, Derived from IKONOS Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  9. Quantifying the resolution level where the GRACE satellites can separate Greenland's glacial mass balance from surface mass balance

    Science.gov (United States)

    Bonin, J. A.; Chambers, D. P.

    2015-09-01

    Mass change over Greenland can be caused by either changes in the glacial dynamic mass balance (DMB) or the surface mass balance (SMB). The GRACE satellite gravity mission cannot directly separate the two physical causes because it measures the sum of the entire mass column with limited spatial resolution. We demonstrate one theoretical way to indirectly separate cumulative SMB from DMB with GRACE, using a least squares inversion technique with knowledge of the location of the glaciers. However, we find that the limited 60 × 60 spherical harmonic representation of current GRACE data does not provide sufficient resolution to adequately accomplish the task. We determine that at a maximum degree/order of 90 × 90 or above, a noise-free gravity measurement could theoretically separate the SMB from DMB signals. However, current GRACE satellite errors are too large at present to separate the signals. A noise reduction of a factor of 10 at a resolution of 90 × 90 would provide the accuracy needed for the interannual cumulative SMB and DMB to be accurately separated.

  10. Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

    Science.gov (United States)

    Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

    2013-01-01

    Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

  11. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    Science.gov (United States)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    , including skyscrapers and bridges, which were confounded and extracted as buildings. This can be attributed to low point density at building edges and on flat roofs or occlusions due to which LiDAR cannot give as much precise planimetric accuracy as photogrammetric techniques (in segmentation) and lack of optimum use of textural information as well as contextual information (especially at walls which are away from roof) in automatic extraction algorithm. In addition, there were no separate classes for bridges or the features lying inside the water and multiple water height levels were also not considered. Based on these inferences, we conclude that the LiDAR-based 3D feature extraction supplemented by high resolution satellite data is a potential application which can be used for understanding and characterization of urban setup.

  12. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

    Directory of Open Access Journals (Sweden)

    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  13. Using high-resolution satellite imagery and double sampling as a ...

    African Journals Online (AJOL)

    QuickBird satellite images were used to extract auxiliary variables (image data), such as photogrammetric crown diameter and number of stems, using visual interpretation and measuring tools offered by Erdas 8.7 geographic imaging software. Field inventory data (terrestric data) collected in 2002 were used to obtain the ...

  14. Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

    Science.gov (United States)

    Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

    2012-12-01

    Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

  15. Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

    Science.gov (United States)

    Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

    2017-12-01

    To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

  16. Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

    Science.gov (United States)

    Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-07-21

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

  17. Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Elizabeth J. Botha

    2016-05-01

    Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

  18. Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES

    Directory of Open Access Journals (Sweden)

    M. Kopacz

    2010-02-01

    Full Text Available We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005 global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD, and aircraft (MOZAIC are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

  19. An Object-Oriented Classification Method on High Resolution Satellite Data

    National Research Council Canada - National Science Library

    Xiaoxia, Sun; Jixian, Zhang; Zhengjun, Liu

    2004-01-01

    .... Thereby only the spectral information is used for the classification. High spatial resolution sensors involves a general increase of spatial information and the accuracy of results may decrease on a per-pixel basis...

  20. A new Ellipsoidal Gravimetric-Satellite Altimetry Boundary Value Problem; Case study: High Resolution Geoid of Iran

    Science.gov (United States)

    Ardalan, A.; Safari, A.; Grafarend, E.

    2003-04-01

    A new ellipsoidal gravimetric-satellite altimetry boundary value problem has been developed and successfully tested. This boundary value problem has been constructed for gravity observables of the type (i) gravity potential (ii) gravity intensity (iii) deflection of vertical and (iv) satellite altimetry data. The developed boundary value problem is enjoying the ellipsoidal nature and as such can take advantage of high precision GPS observations in the set-up of the problem. The highlights of the solution are as follows: begin{itemize} Application of ellipsoidal harmonic expansion up to degree/order and ellipsoidal centrifugal field for the reduction of global gravity and isostasy effects from the gravity observable at the surface of the Earth. Application of ellipsoidal Newton integral on the equal area map projection surface for the reduction of residual mass effects within a radius of 55 km around the computational point. Ellipsoidal harmonic downward continuation of the residual observables from the surface of the earth down to the surface of reference ellipsoid using the ellipsoidal height of the observation points derived from GPS. Restore of the removed effects at the application points on the surface of reference ellipsoid. Conversion of the satellite altimetry derived heights of the water bodies into potential. Combination of the downward continued gravity information with the potential equivalent of the satellite altimetry derived heights of the water bodies. Application of ellipsoidal Bruns formula for converting the potential values on the surface of the reference ellipsoid into the geoidal heights (i.e. ellipsoidal heights of the geoid) with respect to the reference ellipsoid. Computation of the high-resolution geoid of Iran has successfully tested this new methodology!

  1. Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

    Directory of Open Access Journals (Sweden)

    Shan-hu Jiang

    2010-12-01

    Full Text Available Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center's (CPC morphing technique precipitation product (CMORPH, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation: 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 (with 10%, 50%, and −5% biases for 3B42V6, 3B42RT, and CMORPH, respectively. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

  2. Fine Resolution Air Quality Monitoring from a Small Satellite: CHRIS/PROBA

    Directory of Open Access Journals (Sweden)

    Man Sing Wong

    2008-11-01

    Full Text Available Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has the potential to address this problem, with customised platform-sensor combinations dedicated to monitoring single complex regions or mega-cities. This paper demonstrates the ability of the European Space Agency’s small satellite sensor CHRIS/PROBA to provide reliable AOT estimates at a spatially detailed level over Hong Kong, using a modified version of the dense dark vegetation (DDV algorithm devised for MODIS. Since CHRIS has no middle-IR band such as the MODIS 2,100 nm band which is transparent to fine aerosols, the longest waveband of CHRIS, the 1,019 nm band was used to approximate surface reflectance, by the subtraction of an offset derived from synchronous field reflectance spectra. Aerosol reflectance in the blue and red bands was then obtained from the strong empirical relationship observed between the CHRIS 1,019 nm, and the blue and red bands respectively. AOT retrievals for three different dates were shown to be reliable, when compared with AERONET and Microtops II sunphotometers, and a Lidar, as well as air quality data at ground stations. The AOT images exhibited considerable spatial variability over the 11 x 11km image area and were able to indicate both local and long distance sources.

  3. Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

    Science.gov (United States)

    Holben, Brent N.; Shimabukuro, Yosio E.

    1993-01-01

    A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

  4. Study of high-resolution satellite geoid and gravity anomaly data over the Bay of Bengal

    Digital Repository Service at National Institute of Oceanography (India)

    Majumdar, T. J.; Krishna, K.S.; Chatterjee, S.; Bhattacharya, R.; Michael, L.

    research vessels. Solid line shows location of the profile along which interpreted seismic results and var i- ous products of satellite gravity data are shown in Fi gure 4. RESEARCH COMMUNICATIONS CURRENT SCIENCE, VOL. 90, NO. 2 , 25 JANUARY 2006... depth le v els. Location o f the profile is shown with solid line in Figure 3. of the Bay of Bengal can be reasonably co n sidered in mapping the structural features of the region. Thereby the results can be used to study the tectonics...

  5. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

    Science.gov (United States)

    Champion, Nicolas

    2016-06-01

    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  6. AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

    Directory of Open Access Journals (Sweden)

    N. Champion

    2016-06-01

    Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

  7. Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

    Science.gov (United States)

    Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

    2015-04-01

    Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

  8. High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

    Science.gov (United States)

    Jaumann, R.; Stephan, K.; Brown, R.H.; Buratti, B.J.; Clark, R.N.; McCord, T.B.; Coradini, A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K.H.; Bellucci, G.; Bibring, J.-P.; Combes, M.; Cruikshank, D.P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.L.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Soderbloom, L.A.; Griffith, C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C.C.

    2006-01-01

    The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

  9. Combining high-resolution satellite images and altimetry to estimate the volume of small lakes

    Science.gov (United States)

    Baup, F.; Frappart, F.; Maubant, J.

    2014-05-01

    This study presents an approach to determining the volume of water in small lakes (manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.

  10. 3D high resolution tracking of ice flow using mutli-temporal stereo satellite imagery, Franz Josef Glacier, New Zealand

    Science.gov (United States)

    Leprince, S.; Lin, J.; Ayoub, F.; Herman, F.; Avouac, J.

    2013-12-01

    We present the latest capabilities added to the Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) software, which aim at analyzing time-series of stereoscopic imagery to document 3D variations of the ground surface. We review the processing chain and present the new and improved modules for satellite pushbroom imagery, in particular the N-image bundle block adjustment to jointly optimize the viewing geometry of multiple acquisitions, the improved multi-scale image matching based on Semi-Global Matching (SGM) to extract high resolution topography, and the triangulation of multi-temporal disparity maps to derive 3D ground motion. In particular, processes are optimized to run on a cluster computing environment. This new suite of algorithms is applied to the study of Worldview stereo imagery above the Franz Josef, Fox, and Tasman Glaciers, New Zealand, acquired on 01/30/2013, 02/09/2013, and 02/28/2013. We derive high resolution (1m post-spacing) maps of ice flow in three dimensions, where ice velocities of up to 4 m/day are recorded. Images were collected in early summer during a dry and sunny period, which followed two weeks of unsettled weather with several heavy rainfall events across the Southern Alps. The 3D tracking of ice flow highlights the surface response of the glaciers to changes in effective pressure at the ice-bedrock interface due to heavy rainfall, at an unprecedented spatial resolution.

  11. A flexible spatiotemporal method for fusing satellite images with different resolutions

    Science.gov (United States)

    Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

    2016-01-01

    Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

  12. Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

    Science.gov (United States)

    Brown, I.; Wennbom, M.

    2013-12-01

    Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors

  13. Identifying and Allocating Geodetic Systems to historical oil gas wells by using high-resolution satellite imagery

    Science.gov (United States)

    Alvarez, Gabriel O.

    2018-05-01

    Hydrocarbon exploration in Argentina started long before the IGM created a single, high-precision geodetic reference network for the whole country. Several geodetic surveys were conducted in every producing basin, which have ever since then supported well placement. Currently, every basin has a huge amount of information referenced to the so-called "local" geodetic systems, such as Chos Malal - Quiñi Huao in the Neuquén Basin, and Pampa del Castillo in the San Jorge Basin, which differ to a greater or lesser extent from the national Campo Inchauspe datum established by the IGM in 1969 as the official geodetic network. However, technology development over the last few years and the expansion of satellite positioning systems such as GPS resulted in a new world geodetic order. Argentina rapidly joined this new geodetic order through the implementation of a new national geodetic system by the IGM: POSGAR network, which replaced the old national Campo Inchauspe system. However, this only helped to worsen the data georeferencing issue for oil companies, as a third reference system was added to each basin. Now every basin has a local system, the national system until 1997 (Campo Inchauspe), and finally the newly created POSGAR network national satellite system, which is geocentric unlike the former two planimetric datums. The purpose of this paper is to identify and allocate geodetic systems of coordinates to historical wells, whose geodetic system is missing or has been erroneously allocated, by using currently available technological resources such as geographic information systems and high-resolution satellite imagery.

  14. Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

    Science.gov (United States)

    Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

    2014-12-01

    Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

  15. Millisecond resolution electron fluxes from the Cluster satellites: Calibrated EDI ambient electron data

    Science.gov (United States)

    Förster, Matthias; Rashev, Mikhail; Haaland, Stein

    2017-04-01

    The Electron Drift Instrument (EDI) onboard Cluster can measure 500 eV and 1 keV electron fluxes with high time resolution during passive operation phases in its Ambient Electron (AE) mode. Data from this mode is available in the Cluster Science Archive since October 2004 with a cadence of 16 Hz in the normal mode or 128 Hz for burst mode telemetry intervals. The fluxes are recorded at pitch angles of 0, 90, and 180 degrees. This paper describes the calibration and validation of these measurements. The high resolution AE data allow precise temporal and spatial diagnostics of magnetospheric boundaries and will be used for case studies and statistical studies of low energy electron fluxes in the near-Earth space. We show examples of applications.

  16. Mesoscale spiral vortex embedded within a Lake Michigan snow squall band - High resolution satellite observations and numerical model simulations

    Science.gov (United States)

    Lyons, Walter A.; Keen, Cecil S.; Hjelmfelt, Mark; Pease, Steven R.

    1988-01-01

    It is known that Great Lakes snow squall convection occurs in a variety of different modes depending on various factors such as air-water temperature contrast, boundary-layer wind shear, and geostrophic wind direction. An exceptional and often neglected source of data for mesoscale cloud studies is the ultrahigh resolution multispectral data produced by Landsat satellites. On October 19, 1972, a clearly defined spiral vortex was noted in a Landsat-1 image near the southern end of Lake Michigan during an exceptionally early cold air outbreak over a still very warm lake. In a numerical simulation using a three-dimensional Eulerian hydrostatic primitive equation mesoscale model with an initially uniform wind field, a definite analog to the observed vortex was generated. This suggests that intense surface heating can be a principal cause in the development of a low-level mesoscale vortex.

  17. Use of high-resolution satellite images for detection of geological structures related to Calerias geothermal field, Chile

    Science.gov (United States)

    Arellano-Baeza, A. A.; Urzua, L.

    2011-12-01

    Chile has enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique developed by authors. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

  18. Use of the high-resolution satellite images for detection of fractures related to the ore deposits

    Science.gov (United States)

    Cruz-Mondaca, M.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

    2012-12-01

    The Aster and GeoEye satellite high-resolution images were used to detect the structures related to the fracturing of the upper crust in the North of Chile. In particular, lineament analysis has been applied to detect the presence of epithermal fluids of low sulfurization associated with the Paleozoic ore deposits. These results have been compared with the location of the minerals altered by the presence of geothermal fluids detected using the spectral libraries. Later, the presence of fractures has been corroborated during recognition of fractures in situ and the geochemical analysis of samples of minerals altered by the presence of fluids. It was shown that the results obtained are relevant for the gold vein detection.

  19. Global Navigation Satellite System (GNSS) Final Clock Product (5 minute resolution, daily files, generated weekly) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This derived product set consists of Global Navigation Satellite System Final Satellite and Receiver Clock Product (5-minute granularity, daily files, generated...

  20. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  1. Typhoon Doksuri Flooding in 2017 - High-Resolution Inundation Mapping and Monitoring from Sentinel Satellite SAR Data

    Science.gov (United States)

    Nghiem, S. V.; Nguyen, D. T.

    2017-12-01

    In 2017, typhoons and hurricanes have inflicted catastrophic flooding across extensive regions in many countries on several continents, including Asia and North America. The U.S. Federal Emergency Management Agency (FEMA) requested urgent support for flood mapping and monitoring in an emergency response to the devastating flood situation. An innovative satellite remote sensing method, called the Depolarization Reduction Algorithm for Global Observations of inundatioN (DRAGON), has been developed and implemented for use with Sentinel synthetic aperture radar (SAR) satellite data at a resolution of 10 meters to identify, map, and monitor inundation including pre-existing water bodies and newly flooded areas. Because Sentinel SAR operates at C-band microwave frequency, it can be used for flood mapping regardless of could cover conditions typically associated with storms, and thus can provide immediate results without the need to wait for the clouds to clear out. In Southeast Asia, Typhoon Doksuri caused significant flooding across extensive regions in Vietnam and other countries in September 2017. Figure 1 presents the flood mapping result over a region around Hà Tĩnh (north central coast of Vietnam) showing flood inundated areas (in yellow) on 16 September 2017 together with pre-existing surface water (in blue) on 4 September 2017. This is just one example selected from a larger flood map covering an extensive region of about 250 km x 680 km all along the central coast of Vietnam.

  2. Shadow Analysis Technique for Extraction of Building Height using High Resolution Satellite Single Image and Accuracy Assessment

    Science.gov (United States)

    Raju, P. L. N.; Chaudhary, H.; Jha, A. K.

    2014-11-01

    These High resolution satellite data with metadata information is used to extract the height of the building using shadow. Proposed approach divides into two phases 1) rooftop and shadow extraction and 2) height estimation. Firstly the rooftop and shadow region were extracted by manual/ automatic methods using Example - Based and Rule - Based approaches. After feature extraction next step is estimating height of the building by taking rooftop in association with shadow using Ratio Method and by using the relation between sun-satellite geometry. The performance analysis shows the total mean error of height is 0.67 m from ratio method, 1.51 m from Example - Based Approach and 0.96 m from Rule - Based Approach. Analysis concluded that Ratio Method i.e. manual method is best for height estimation but it is time consuming so the automatic Rule Based approach is best for height estimation in comparison to Example Based Approach because it require more knowledge and selection of more training samples as well as slows the processing rate of the method.

  3. Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

    Directory of Open Access Journals (Sweden)

    Mailys Lopes

    2017-07-01

    Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

  4. AN ACTIVE-PASSIVE COMBINED ALGORITHM FOR HIGH SPATIAL RESOLUTION RETRIEVAL OF SOIL MOISTURE FROM SATELLITE SENSORS (Invited)

    Science.gov (United States)

    Lakshmi, V.; Mladenova, I. E.; Narayan, U.

    2009-12-01

    Soil moisture is known to be an essential factor in controlling the partitioning of rainfall into surface runoff and infiltration and solar energy into latent and sensible heat fluxes. Remote sensing has long proven its capability to obtain soil moisture in near real-time. However, at the present time we have the Advanced Scanning Microwave Radiometer (AMSR-E) on board NASA’s AQUA platform is the only satellite sensor that supplies a soil moisture product. AMSR-E coarse spatial resolution (~ 50 km at 6.9 GHz) strongly limits its applicability for small scale studies. A very promising technique for spatial disaggregation by combining radar and radiometer observations has been demonstrated by the authors using a methodology is based on the assumption that any change in measured brightness temperature and backscatter from one to the next time step is due primarily to change in soil wetness. The approach uses radiometric estimates of soil moisture at a lower resolution to compute the sensitivity of radar to soil moisture at the lower resolution. This estimate of sensitivity is then disaggregated using vegetation water content, vegetation type and soil texture information, which are the variables on which determine the radar sensitivity to soil moisture and are generally available at a scale of radar observation. This change detection algorithm is applied to several locations. We have used aircraft observed active and passive data over Walnut Creek watershed in Central Iowa in 2002; the Little Washita Watershed in Oklahoma in 2003 and the Murrumbidgee Catchment in southeastern Australia for 2006. All of these locations have different soils and land cover conditions which leads to a rigorous test of the disaggregation algorithm. Furthermore, we compare the derived high spatial resolution soil moisture to in-situ sampling and ground observation networks

  5. Using Instrument Simulators and a Satellite Database to Evaluate Microphysical Assumptions in High-Resolution Simulations of Hurricane Rita

    Science.gov (United States)

    Hristova-Veleva, S. M.; Chao, Y.; Chau, A. H.; Haddad, Z. S.; Knosp, B.; Lambrigtsen, B.; Li, P.; Martin, J. M.; Poulsen, W. L.; Rodriguez, E.; Stiles, B. W.; Turk, J.; Vu, Q.

    2009-12-01

    Improving forecasting of hurricane intensity remains a significant challenge for the research and operational communities. Many factors determine a tropical cyclone’s intensity. Ultimately, though, intensity is dependent on the magnitude and distribution of the latent heating that accompanies the hydrometeor production during the convective process. Hence, the microphysical processes and their representation in hurricane models are of crucial importance for accurately simulating hurricane intensity and evolution. The accurate modeling of the microphysical processes becomes increasingly important when running high-resolution models that should properly reflect the convective processes in the hurricane eyewall. There are many microphysical parameterizations available today. However, evaluating their performance and selecting the most representative ones remains a challenge. Several field campaigns were focused on collecting in situ microphysical observations to help distinguish between different modeling approaches and improve on the most promising ones. However, these point measurements cannot adequately reflect the space and time correlations characteristic of the convective processes. An alternative approach to evaluating microphysical assumptions is to use multi-parameter remote sensing observations of the 3D storm structure and evolution. In doing so, we could compare modeled to retrieved geophysical parameters. The satellite retrievals, however, carry their own uncertainty. To increase the fidelity of the microphysical evaluation results, we can use instrument simulators to produce satellite observables from the model fields and compare to the observed. This presentation will illustrate how instrument simulators can be used to discriminate between different microphysical assumptions. We will compare and contrast the members of high-resolution ensemble WRF model simulations of Hurricane Rita (2005), each member reflecting different microphysical assumptions

  6. Exploring New Challenges of High-Resolution SWOT Satellite Altimetry with a Regional Model of the Solomon Sea

    Science.gov (United States)

    Brasseur, P.; Verron, J. A.; Djath, B.; Duran, M.; Gaultier, L.; Gourdeau, L.; Melet, A.; Molines, J. M.; Ubelmann, C.

    2014-12-01

    The upcoming high-resolution SWOT altimetry satellite will provide an unprecedented description of the ocean dynamic topography for studying sub- and meso-scale processes in the ocean. But there is still much uncertainty on the signal that will be observed. There are many scientific questions that are unresolved about the observability of altimetry at vhigh resolution and on the dynamical role of the ocean meso- and submesoscales. In addition, SWOT data will raise specific problems due to the size of the data flows. These issues will probably impact the data assimilation approaches for future scientific or operational oceanography applications. In this work, we propose to use a high-resolution numerical model of the Western Pacific Solomon Sea as a regional laboratory to explore such observability and dynamical issues, as well as new data assimilation challenges raised by SWOT. The Solomon Sea connects subtropical water masses to the equatorial ones through the low latitude western boundary currents and could potentially modulate the tropical Pacific climate. In the South Western Pacific, the Solomon Sea exhibits very intense eddy kinetic energy levels, while relatively little is known about the mesoscale and submesoscale activities in this region. The complex bathymetry of the region, complicated by the presence of narrow straits and numerous islands, raises specific challenges. So far, a Solomon sea model configuration has been set up at 1/36° resolution. Numerical simulations have been performed to explore the meso- and submesoscales dynamics. The numerical solutions which have been validated against available in situ data, show the development of small scale features, eddies, fronts and filaments. Spectral analysis reveals a behavior that is consistent with the SQG theory. There is a clear evidence of energy cascade from the small scales including the submesoscales, although those submesoscales are only partially resolved by the model. In parallel

  7. High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

    Science.gov (United States)

    Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment

  8. A model of regional primary production for use with coarse resolution satellite data

    Science.gov (United States)

    Prince, S. D.

    1991-01-01

    A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

  9. Estimation and quantification of mangrove forest extent by using different spatial resolution satellite data for the sandspit area of Karachi coast

    International Nuclear Information System (INIS)

    Saeed, U.; Daud, A.; Ashraf, S.; Mahmood, A.

    2006-01-01

    Mangrove forest is an integral part of inter-tidal zone of the coastal environment extending throughout the tropics and subtropics of the world. In Pakistan, for the last thirty years, remote-sensing data has significantly been used for area estimation of mangrove forests. In the previous studies medium resolution satellite data have been used for the area estimation of mangrove forests that revealed some of the discrepancies in terms of recognition of the subtle variations of landcover features in the satellite imagery. Current study aims at the classification techniques employed for the area estimation using high and medium resolution satellite imageries. To study the effects of spatial resolution on classification results, three different satellite data were used, including Quickbird, TERRA and Landsat satellites. Thematic map derived from Quickbird data was comprised of maximum number of land cover classes with a definite zone of mangroves that extends from regeneration to mature canopies. Total estimated mangroves extent was 370 ha with 57.45, 125.9, 180.89, and 5.35 ha of tall, medium, small, and new recruitment mangrove plants respectively. While mangrove area estimations from thematic maps derived using TERRA and Landsat satellite data, showed a gradual increase in the mangrove extent from 390.95 ha to 417.92 ha. This increase in area is an indicative of the fact that some of the landcover classes may have been miss-classified and hence added to the area under mangrove forests. This study also showed that high-resolution satellite data could be used for identifying different height zones of mangrove forests, along with an accurate delineation of classes like salt bushes and algae, which could not be classified otherwise. (author)

  10. A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

    Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  11. a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

    Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  12. Feature extraction and classification of clouds in high resolution panchromatic satellite imagery

    Science.gov (United States)

    Sharghi, Elan

    The development of sophisticated remote sensing sensors is rapidly increasing, and the vast amount of satellite imagery collected is too much to be analyzed manually by a human image analyst. It has become necessary for a tool to be developed to automate the job of an image analyst. This tool would need to intelligently detect and classify objects of interest through computer vision algorithms. Existing software called the Rapid Image Exploitation Resource (RAPIER®) was designed by engineers at Space and Naval Warfare Systems Center Pacific (SSC PAC) to perform exactly this function. This software automatically searches for anomalies in the ocean and reports the detections as a possible ship object. However, if the image contains a high percentage of cloud coverage, a high number of false positives are triggered by the clouds. The focus of this thesis is to explore various feature extraction and classification methods to accurately distinguish clouds from ship objects. An examination of a texture analysis method, line detection using the Hough transform, and edge detection using wavelets are explored as possible feature extraction methods. The features are then supplied to a K-Nearest Neighbors (KNN) or Support Vector Machine (SVM) classifier. Parameter options for these classifiers are explored and the optimal parameters are determined.

  13. Mapping tropical dry forest habitats integrating Landsat NDVI, Ikonos imagery, and topographic information in the Caribbean Island of Mona

    Directory of Open Access Journals (Sweden)

    Sebastián Martinuzzi

    2008-06-01

    Full Text Available Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference vegetation Index (NDvI from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDvI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5 500 ha area, with a kappa coefficient of accuracy equal to 79 %. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island. Rev. Biol. Trop. 56 (2: 625-639. Epub 2008 June 30.El estudio y evaluación de los bosques tropicales secos mediante herramientas de teledetección es una de las prioridades de investigación en los ambientes neotropicales. Desarrollamos una metodología simple para mapear la vegetación de la isla de Mona, Puerto Rico, mediante el uso del índice de vegetación normalizado (NDVI por sus siglas en inglés de Landsat, información topográfica, e imágenes auxiliares de alta resolución Ikonos. La metodología fue útil para identificar las clases de vegetación en un área de gran variedad de comunidades vegetales y relieve complejo, y puede ser adaptada a otras regiones de bosque seco de las islas del Caribe. El NDVI permitió identificar la distribución de

  14. New optical sensor systems for high-resolution satellite, airborne and terrestrial imaging systems

    Science.gov (United States)

    Eckardt, Andreas; Börner, Anko; Lehmann, Frank

    2007-10-01

    The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

  15. Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

    Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

  16. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Chandi Witharana

    2016-04-01

    Full Text Available The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.

  17. Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

    Science.gov (United States)

    Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

    2013-01-01

    Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

  18. Satellite imagery and the Department of Safeguards

    International Nuclear Information System (INIS)

    Chitumbo, K.; Bunney, J.; Leve, G.; Robb, S.

    2001-01-01

    Full text: The presentation examines some of the challenges the Satellite Imagery and Analysis Laboratory (SIAL) is facing in supporting Strengthened Safeguards. It focuses on the analytical process, starting with specifying initial tasking and continuing through to end products that are a direct result of in-house analysis. In addition it also evaluates the advantages and disadvantages of SIAL's mission and introduces external forces that the agency must consider, but cannot itself, predict or control. Although SIAL's contribution to tasks relating to Article 2a(iii) of the Additional Protocol are known and are presently of great benefit to operations areas, this is only one aspect of its work. SIAL's ability to identify and analyze historical satellite imagery data has the advantage of permitting operations to take a more in depth view of a particular area of interest's (AOI) development, and thus may permit operations to confirm or refute specific assertions relating to the AOI's function or abilities. These assertions may originate in-house or may be open source reports the agency feels it is obligated to explore. SIAL's mission is unique in the world of imagery analysis. Its aim is to support all operations areas equally and in doing so it must maintain global focus. The task is tremendous, but the resultant coverage and concentration of unique expertise will allow SIAL to develop and provide operations with datasets that can be exploited in standalone mode or be incorporated into new cutting edge tools to be developed in SGIT. At present SIAL relies on two remote sensors, IKONOS-2 and EROS-AI, for present high- resolution imagery data and is using numerous sources for historical, pre 1999, data. A multiplicity of sources for high-resolution data is very important to SIAL, but is something that it cannot influence. It is hoped that the planned launch of two new sensors by Summer 2002 will be successful and will offer greater flexibility for image collection

  19. MULTI-ELEMENT ABUNDANCE MEASUREMENTS FROM MEDIUM-RESOLUTION SPECTRA. II. CATALOG OF STARS IN MILKY WAY DWARF SATELLITE GALAXIES

    International Nuclear Information System (INIS)

    Kirby, Evan N.; Cohen, Judith G.; Guhathakurta, Puragra; Rockosi, Constance M.; Simon, Joshua D.; Geha, Marla C.; Sneden, Christopher; Sohn, Sangmo Tony; Majewski, Steven R.; Siegel, Michael

    2010-01-01

    We present a catalog of Fe, Mg, Si, Ca, and Ti abundances for 2961 stars in eight dwarf satellite galaxies of the Milky Way (MW): Sculptor, Fornax, Leo I, Sextans, Leo II, Canes Venatici I, Ursa Minor, and Draco. For the purposes of validating our measurements, we also observed 445 red giants in MW globular clusters and 21 field red giants in the MW halo. The measurements are based on Keck/DEIMOS medium-resolution spectroscopy (MRS) combined with spectral synthesis. We estimate uncertainties in [Fe/H] by quantifying the dispersion of [Fe/H] measurements in a sample of stars in monometallic globular clusters (GCs). We estimate uncertainties in Mg, Si, Ca, and Ti abundances by comparing to high-resolution spectroscopic abundances of the same stars. For this purpose, a sample of 132 stars with published high-resolution spectroscopy in GCs, the MW halo field, and dwarf galaxies has been observed with MRS. The standard deviations of the differences in [Fe/H] and ([α/Fe]) (the average of [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe]) between the two samples is 0.15 and 0.16, respectively. This catalog represents the largest sample of multi-element abundances in dwarf galaxies to date. The next papers in this series draw conclusions on the chemical evolution, gas dynamics, and star formation histories from the catalog presented here. The wide range of dwarf galaxy luminosity reveals the dependence of dwarf galaxy chemical evolution on galaxy stellar mass.

  20. Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

    Science.gov (United States)

    Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

    2015-12-01

    Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately, the resulting fine resolution UTC map will be compared with previously created UTC maps of the same area but for earlier dates, producing a canopy change map corresponding to the Worcester area tree removal and replanting effort.

  1. The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

    Science.gov (United States)

    Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

    2017-12-01

    The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

  2. Tree survey and allometric models for tiger bush in northern Senegal and comparison with tree parameters derived from high resolution satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Goettsche, Frank-M.; Diop, Doudou

    2011-01-01

    A tree survey and an analysis of high resolution satellite data were performed to characterise the woody vegetation within a 10 x 10 km(2) area around a site located close to the town of Dahra in the semiarid northern part of Senegal. The surveyed parameters were tree species, height, tree crown...

  3. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  4. 3-Dimentional Mapping Coastal Zone using High Resolution Satellite Stereo Imageries

    International Nuclear Information System (INIS)

    Hong, Zhonghua; Liu, Fengling; Zhang, Yun

    2014-01-01

    The metropolitan coastal zone mapping is critical for coastal resource management, coastal environmental protection, and coastal sustainable development and planning. The results of geometric processing of a Shanghai coastal zone from 0.7-m-resolution QuickBird Geo stereo images are presented firstly. The geo-positioning accuracy of ground point determination with vendor-provided rigorous physical model (RPM) parameters is evaluated and systematic errors are found when compared with ground control points surveyed by GPS real-time kinematic (GPS-RTK) with 5cm accuracy. A bias-compensation process in image space that applies a RPM bundle adjustment to the RPM-calculated 3D ground points to correct the systematic errors is used to improve the geo-positioning accuracy. And then, a area-based matching (ABM) method is used to generated the densely corresponding points of left and right QuickBird images. With the densely matching points, the 3-dimentinal coordinates of ground points can be calculated by using the refined geometric relationship between image and ground points. At last step, digital surface model (DSM) can be achieved automatically using interpolation method. Accuracies of the DSM as assessed from independent checkpoints (ICPs) are approximately 1.2 m in height

  5. High Resolution Topography of Polar Regions from Commercial Satellite Imagery, Petascale Computing and Open Source Software

    Science.gov (United States)

    Morin, Paul; Porter, Claire; Cloutier, Michael; Howat, Ian; Noh, Myoung-Jong; Willis, Michael; Kramer, WIlliam; Bauer, Greg; Bates, Brian; Williamson, Cathleen

    2017-04-01

    Surface topography is among the most fundamental data sets for geosciences, essential for disciplines ranging from glaciology to geodynamics. Two new projects are using sub-meter, commercial imagery licensed by the National Geospatial-Intelligence Agency and open source photogrammetry software to produce a time-tagged 2m posting elevation model of the Arctic and an 8m posting reference elevation model for the Antarctic. When complete, this publically available data will be at higher resolution than any elevation models that cover the entirety of the Western United States. These two polar projects are made possible due to three equally important factors: 1) open-source photogrammetry software, 2) petascale computing, and 3) sub-meter imagery licensed to the United States Government. Our talk will detail the technical challenges of using automated photogrammetry software; the rapid workflow evolution to allow DEM production; the task of deploying the workflow on one of the world's largest supercomputers; the trials of moving massive amounts of data, and the management strategies the team needed to solve in order to meet deadlines. Finally, we will discuss the implications of this type of collaboration for future multi-team use of leadership-class systems such as Blue Waters, and for further elevation mapping.

  6. Advances In very high resolution satellite imagery analysis for Monitoring human settlements

    Energy Technology Data Exchange (ETDEWEB)

    Vatsavai, Raju [ORNL; Cheriyadat, Anil M [ORNL; Bhaduri, Budhendra L [ORNL

    2014-01-01

    The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

  7. Development of a technique for long-term detection of precursors of strong earthquakes using high-resolution satellite images

    Science.gov (United States)

    Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.

    2012-12-01

    Among a variety of processes involved in seismic activity, the principal process is the accumulation and relaxation of stress in the crust, which takes place at the depth of tens of kilometers. While the Earth's surface bears at most the indirect sings of the accumulation and relaxation of the crust stress, it has long been understood that there is a strong correspondence between the structure of the underlying crust and the landscape. We assume the structure of the lineaments reflects an internal structure of the Earth's crust, and the variation of the lineament number and arrangement reflects the changes in the stress patterns related to the seismic activity. Contrary to the existing assumptions that lineament structure changes only at the geological timescale, we have found that the much faster seismic activity strongly affects the system of lineaments extracted from the high-resolution multispectral satellite images. Previous studies have shown that accumulation of the stress in the crust previous to a strong earthquake is directly related to the number increment and preferential orientation of lineament configuration present in the satellite images of epicenter zones. This effect increases with the earthquake magnitude and can be observed approximately since one month before. To study in details this effect we have developed a software based on a series of algorithms for automatic detection of lineaments. It was found that the Hough transform implemented after the application of discontinuity detection mechanisms like Canny edge detector or directional filters is the most robust technique for detection and characterization of changes in the lineament patterns related to strong earthquakes, which can be used as a robust long-term precursor of earthquakes indicating regions of strong stress accumulation.

  8. High-resolution satellite remote sensing of provincial PM2.5 trends in China from 2001 to 2015

    Science.gov (United States)

    Lin, C. Q.; Liu, G.; Lau, A. K. H.; Li, Y.; Li, C. C.; Fung, J. C. H.; Lao, X. Q.

    2018-05-01

    Given the vast territory of China, the long-term PM2.5 trends may substantially differ among the provinces. In this study, we aim to assess the provincial PM2.5 trends in China during the past few Five-Year Plan (FYP) periods. The lack of long-term PM2.5 measurements, however, makes such assessment difficult. Satellite remote sensing of PM2.5 concentration is an important step toward filling this data gap. In this study, a PM2.5 data set was built over China at a resolution of 1 km from 2001 to 2015 using satellite remote sensing. Analyses show that the national average of PM2.5 concentration increased by 0.04 μg·m-3·yr-1 during the 10th FYP period (2001-2005) and started to decline by -0.65 μg·m-3·yr-1 and -2.33 μg·m-3·yr-1 during the 11th (2006-2010) and the 12th (2011-2015) FYP period, respectively. In addition, substantial differences in the PM2.5 trends were observed among the provinces. Provinces in the Beijing-Tianjin-Hebei (BTH) region had the largest reduction of PM2.5 concentrations during the 10th and 12th FYP period. The greatest reduction rate of PM2.5 concentration during the 10th and 12th FYP period was observed in Beijing (-3.68 μg·m-3·yr-1) and Tianjin (-6.62 μg·m-3·yr-1), respectively. In contrast, PM2.5 concentrations remained steady for provinces in eastern and southeastern China (e.g., Shanghai) during the 12th FYP period. In overall, great efforts are still required to effectively reduce the PM2.5 concentrations in future.

  9. Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

    Science.gov (United States)

    De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

    2014-12-01

    The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

  10. Winter Crop Mapping for Improving Crop Production Estimates in Argentina Using Moderation Resolution Satellite Imagery

    Science.gov (United States)

    Humber, M. L.; Copati, E.; Sanchez, A.; Sahajpal, R.; Puricelli, E.; Becker-Reshef, I.

    2017-12-01

    Accurate crop production data is fundamental for reducing uncertainly and volatility in the domestic and international agricultural markets. The Agricultural Estimates Department of the Buenos Aires Grain Exchange has worked since 2000 on the estimation of different crop production data. With this information, the Grain Exchange helps different actors of the agricultural chain, such as producers, traders, seed companies, market analyst, policy makers, into their day to day decision making. Since 2015/16 season, the Grain Exchange has worked on the development of a new earth observations-based method to identify winter crop planted area at a regional scale with the aim of improving crop production estimates. The objective of this new methodology is to create a reliable winter crop mask at moderate spatial resolution using Landsat-8 imagery by exploiting bi-temporal differences in the phenological stages of winter crops as compared to other landcover types. In collaboration with the University of Maryland, the map has been validated by photointerpretation of a stratified statistically random sample of independent ground truth data in the four largest producing provinces of Argentina: Buenos Aires, Cordoba, La Pampa, and Santa Fe. In situ measurements were also used to further investigate conditions in the Buenos Aires province. Preliminary results indicate that while there are some avenues for improvement, overall the classification accuracy of the cropland and non-cropland classes are sufficient to improve downstream production estimates. Continuing research will focus on improving the methodology for winter crop mapping exercises on a yearly basis as well as improving the sampling methodology to optimize collection of validation data in the future.

  11. Urban area and green space: volume estimation using medium resolution satellite imagery

    Science.gov (United States)

    Handayani, H. H.

    2017-12-01

    The latest revision of the UN World Urbanization Prospects predicts the world's urban population to increase by 1.4 billion between 2010 and 2030, 60% of the population will live in cities. Consequently, this expansion affects the existence of ecosystem services in the context of sustainability environment. Green space is a focal point of the ecological system and is affected by the urbanization process. The green space has essential functions in cleaning the water, adjusting the microclimate, eliminating noise, and beautifying the surrounding makes the green quantity as well as quality very vital to its existence. The urban expansion leads the growth into vertical development. Therefore, the third dimension using urban volume as an indicator of vertical development is introduced. Therefore, this study estimates the urban and green volume by using medium resolution remote sensing. Surabaya is used as a case study since the city has grown up significantly in both of population and capital investment in this decade. Here, urban and green volume is investigated by ALOS datasets with urban referring built-up. Also, we examine the area with low and high green volume by performing hot and cold spots analysis. The average of built-up volume reaches 173.05 m3/pixel presented by the building for a residential single house with the height less than 7m. The average of green volume is 14.74m3/pixel performed by the vegetation with the height generally 0.6 to 1m which is frequently planted in the backyard of house. However, the ratio of green volume to the built-up volume shows a small portion which is around 8.52%. Therefore, we identify the hot and cold spots, we evaluate 5 areas having cold spot regarding lack of green volume. The two locations of cold spot are located in the northern part and another is in the southern part. Those areas have high number of built-up volume which is in particularly as sub-CBD area. We emphasize that the improvement of green quantity is needed

  12. Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

    Science.gov (United States)

    Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

    2018-08-01

    The regulatory monitoring data of particulate matter with an aerodynamic diameter images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

    KAUST Repository

    Houborg, Rasmus

    2016-09-19

    Planet Labs ("Planet") operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3-5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet\\'s RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 (~9%). The MAD increased to 0.021 (~14%) when the Landsat NDVI training image was further away (i.e., 11-16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1%) for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet\\'s dense time-series of RGB imagery.

  14. High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

    KAUST Repository

    Houborg, Rasmus; McCabe, Matthew

    2016-01-01

    Planet Labs ("Planet") operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3-5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet's RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 (~9%). The MAD increased to 0.021 (~14%) when the Landsat NDVI training image was further away (i.e., 11-16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1%) for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet's dense time-series of RGB imagery.

  15. Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

    Science.gov (United States)

    Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi

    2010-01-01

    The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

  16. Remote sensing for greenhouse detection from stereo pairs of WorldView-2 satellite

    Directory of Open Access Journals (Sweden)

    M.A. Aguilar

    2014-05-01

    Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.

  17. Identification of the potential gap areas for the developing green infrastructure in the Urban area using High resolution satellite Imagery

    Science.gov (United States)

    Kanaparthi, M. B.

    2017-12-01

    In India urban population is growing day by day which is causing air pollution less air quality finally leading to climate change and global warming. To mitigate the effect of the climate change we need to plant more trees in the urban area. The objective of this study is develop a plan to improve the urban Green Infrastructure (GI) to fight against the climate change and global warming. Improving GI is a challenging and difficult task in the urban areas because land unavailability of land, to overcome the problem greenways is a good the solution. Greenway is a linear open space developed along the rivers, canals, roads in the urban areas to form a network of green spaces. Roads are the most common structures in the urban area. The idea is to develop the greenways alongside the road to connecting the different green spaces. Tree crowns will act as culverts to connect the green spaces. This will require the spatial structure of the green space, distribution of trees along the roads and the gap areas along the road where more trees can be planted. This can be achieved with help of high resolution Satellite Imagery and the object extraction techniques. This study was carried in the city Bhimavaram which is located in state Andhra Pradesh. The final outcome of this study is potential gap areas for planting trees in the city.

  18. Classification of semiurban landscapes from very high-resolution satellite images using a regionalized multiscale segmentation approach

    Science.gov (United States)

    Kavzoglu, Taskin; Erdemir, Merve Yildiz; Tonbul, Hasan

    2017-07-01

    In object-based image analysis, obtaining representative image objects is an important prerequisite for a successful image classification. The major threat is the issue of scale selection due to the complex spatial structure of landscapes portrayed as an image. This study proposes a two-stage approach to conduct regionalized multiscale segmentation. In the first stage, an initial high-level segmentation is applied through a "broadscale," and a set of image objects characterizing natural borders of the landscape features are extracted. Contiguous objects are then merged to create regions by considering their normalized difference vegetation index resemblance. In the second stage, optimal scale values are estimated for the extracted regions, and multiresolution segmentation is applied with these settings. Two satellite images with different spatial and spectral resolutions were utilized to test the effectiveness of the proposed approach and its transferability to different geographical sites. Results were compared to those of image-based single-scale segmentation and it was found that the proposed approach outperformed the single-scale segmentations. Using the proposed methodology, significant improvement in terms of segmentation quality and classification accuracy (up to 5%) was achieved. In addition, the highest classification accuracies were produced using fine-scale values.

  19. HIGH-RESOLUTION SATELLITE IMAGING OF THE 2004 TRANSIT OF VENUS AND ASYMMETRIES IN THE CYTHEREAN ATMOSPHERE

    International Nuclear Information System (INIS)

    Pasachoff, Jay M.; Schneider, Glenn; Widemann, Thomas

    2011-01-01

    This paper presents the only space-borne optical-imaging observations of the 2004 June 8 transit of Venus, the first such transit visible from Earth since AD 1882. The high-resolution, high-cadence satellite images we arranged from NASA's Transition Region and Coronal Explorer (TRACE) reveal the onset of visibility of Venus's atmosphere and give further information about the black-drop effect, whose causes we previously demonstrated from TRACE observations of a transit of Mercury. The atmosphere is gradually revealed before second contact and after third contact, resulting from the changing depth of atmospheric layers refracting the photospheric surface into the observer's direction. We use Venus Express observations to relate the atmospheric arcs seen during the transit to the atmospheric structure of Venus. Finally, we relate the transit images to current and future exoplanet observations, providing a sort of ground truth showing an analog in our solar system to effects observable only with light curves in other solar systems with the Kepler and CoRoT missions and ground-based exoplanet-transit observations.

  20. Use of high-resolution satellite images for characterization of geothermal reservoirs in the Tarapaca Region, Chile

    Science.gov (United States)

    Arellano-Baeza, A. A.; Montenegro A., C.

    2010-12-01

    The use of renewable and clean sources of energy is becoming crucial for sustainable development of all countries, including Chile. Chilean Government plays special attention to the exploration and exploitation of geothermal energy, total electrical power capacity of which could reach 16.000 MW. In Chile the main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the Lansat satellite have been used to characterize the geothermal field in the region of the Puchuldiza geysers, Colchane, Region of Tarapaca, North of Chile, located at the altitude of 4000 m. Structure of lineaments associated to the geothermal field have been extracted from the images using the lineament detection technique developed by authors. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament analysis is a power tool for the detection of faults and joint zones associated to the geothermal fields.

  1. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    Science.gov (United States)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  2. Landuse change detection in a surface coal mine area using multi-temporal high resolution satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Demirel, N.; Duzgun, S.; Kemal Emil, M. [Middle East Technical Univ., Ankara (Turkey). Dept. of Mining Engineering

    2010-07-01

    Changes in the landcover and landuse of a mine area can be caused by surface mining activities, exploitation of ore and stripping and dumping overburden. In order to identify the long-term impacts of mining on the environment and land cover, these changes must be continuously monitored. A facility to regularly observe the progress of surface mining and reclamation is important for effective enforcement of mining and environmental regulations. Remote sensing provides a powerful tool to obtain rigorous data and reduce the need for time-consuming and expensive field measurements. The purpose of this study was to conduct post classification change detection for identifying, quantifying, and analyzing the spatial response of landscape due to surface lignite coal mining activities in Goynuk, Bolu, Turkey, from 2004 to 2008. The paper presented the research algorithm which involved acquiring multi temporal high resolution satellite data; preprocessing the data; performing image classification using maximum likelihood classification algorithm and performing accuracy assessment on the classification results; performing post classification change detection algorithm; and analyzing the results. Specifically, the paper discussed the study area, data and methodology, and image preprocessing using radiometric correction. Image classification and change detection were also discussed. It was concluded that the mine and dump area decreased by 192.5 ha from 2004 to 2008 and was caused by the diminishing reserves in the area and decline in the required production. 5 refs., 2 tabs., 4 figs.

  3. Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

    Science.gov (United States)

    Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

    2018-04-01

    A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

  4. Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?

    DEFF Research Database (Denmark)

    Schumacher, Paul; Mislimshoeva, Bunafsha; Brenning, Alexander

    2016-01-01

    to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically...... red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data...

  5. Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

    Science.gov (United States)

    Huang, Xin; Chen, Huijun; Gong, Jianya

    2018-01-01

    Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

  6. Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

    Science.gov (United States)

    Kim, Y.; Du, J.; Kimball, J. S.

    2017-12-01

    The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb

  7. Employing high resolution satellite imagery to document a rapid glacier surge in the Karakoram - risks and opportunities for hazard assessment

    Science.gov (United States)

    Steiner, J. F.; Kraaijenbrink, P. D. A.; Jiduc, S. G.; Immerzeel, W. W.

    2017-12-01

    Glacier surges occur regularly in the Karakoram but their driving mechanisms, recurrence and its relation to climatic change remain unclear. Since many glacier tongues in the region reach to very low elevations, local populations are often exposed to glacial hazards. While the scientific interpretation of hazard is one challenge, adequately communicating results to possibly affected stakeholders poses a different set of hurdles. Using DEMs as well as Landsat imagery in combination with high-resolution Planet imagery we quantify surface elevation changes and flow velocities to document a glacier surge of the Khurdopin glacier, located in a remote valley in Pakistan, in the first half of 2017. Results reveal that an accumulation of ice mass leads to a rapid surge in peaking with velocities above 5000 m a-1 or 0.5 m h-1 during a few days. Velocities increase steadily during a four-year build-up phase prior to the actual surge, while the remaining 15 years of the recurring cycle the glacier is quiescent. It is hypothesized that the surge is mainly initiated as a result of increased pressure melting caused by ice accumulation. However, surface observations show increased crevassing and disappearance of supra glacial ponds, which could have led to increased lubrication of the glacier bed. As a consequence of the surging tongue blocking the main valley a lake has formed and grown continuously in size over two months at a rate of up to 3000 m2 per day. Using satellite imagery with a frequent overpass rate we are able to (a) characterize the nature of glacier surges in the region with greater detail and (b) monitor the surge as well as the formation of the lake as it develops. Having developed a connection to local stakeholders we were able to provide rapid hazard assessments to affected communities, which can be employed to define possible actions. We show the potential of satellite imagery - freely available Landsat in combination with commercial Planet imagery -, which

  8. Vectorized Shoreline of Tutuila, Ofu, Olosega, Rose, Swains, and Ta'u American Samoa, Derived from IKONOS Imagery, 2001

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — IKONOS imagery was purchased to support the Pacific Islands Geographic Information System (GIS) project and the National Ocean Service's (NOS) coral mapping...

  9. CRED 60 m Gridded bathymetry and IKONOS estimated depths of UTM Zone 2, Northwestern Hawaiian Islands, USA (Arc ASCII format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of the Northwestern Hawaiian Islands, USA within UTM Zone 2. Bottom coverage was...

  10. CRED 20m Gridded bathymetry and IKONOS estimated depths of Pearl and Hermes Atoll, Hawaii, USA (Arc ASCII format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Pearl and Hermes Atoll, Hawaii, USA. Bottom coverage was achieved in depths...

  11. CRED 5 m Gridded bathymetry and IKONOS estimated depths of Pearl and Hermes Atoll, Hawaii, USA (Arc ASCII format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Pearl and Hermes Atoll, Hawaii, USA. Bottom coverage was achieved in depths...

  12. CRED 20 m Gridded bathymetry and IKONOS estimated depths of Pearl and Hermes Atoll, Hawaii, USA (NetCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Pearl and Hermes Atoll, Hawaii, USA. Bottom coverage was achieved in depths...

  13. CRED 5 m Gridded bathymetry and IKONOS estimated depths of Pearl and Hermes Atoll, Hawaii, USA (NetCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Pearl and Hermes Atoll, Hawaii, USA. Bottom coverage was achieved in depths...

  14. CRED 60m Gridded bathymetry and IKONOS estimated depths of UTM Zone 3, Northwestern Hawaiian Islands, USA (Arc ASCII format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of the Northwestern Hawaiian Islands, USA within UTM Zone 3. Bottom coverage was...

  15. Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

    Directory of Open Access Journals (Sweden)

    Shaowei Ning

    2016-10-01

    Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

  16. Spatiotemporal prediction of fine particulate matter using high resolution satellite images in the southeastern U.S 2003–2011

    Science.gov (United States)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure; however, induces measurement error. Land use regression provides spatially resolved predictions but land use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables such as meteorological variables, land use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1 km2 resolution of the southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 through 2011. We divided the study area into 3 regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors (RMSPE) of 2.89, 2.51, and 2.82 μg/m3 for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas due to the paucity of monitors in rural areas. PMID:26082149

  17. Mapping Sub-Saharan African Agriculture in High-Resolution Satellite Imagery with Computer Vision & Machine Learning

    Science.gov (United States)

    Debats, Stephanie Renee

    Smallholder farms dominate in many parts of the world, including Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural landcover. In this thesis, we developed a benchmark labeled data set of high-resolution satellite imagery of agricultural fields in South Africa. We presented a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. The algorithm achieved similar high performance across agricultural types, including spectrally indistinct smallholder fields, and demonstrated the ability to generalize across large geographic areas. In sensitivity analyses, we determined multi-temporal images provided greater performance gains than the addition of multi-spectral bands. We also demonstrated how active learning can be incorporated in the algorithm to create smaller, more efficient training data sets, which reduced computational resources, minimized the need for humans to hand-label data, and boosted performance. We designed a patch-based uncertainty metric to drive the active learning framework, based on the regular grid of a crowdsourcing platform, and demonstrated how subject matter experts can be replaced with fleets of crowdsourcing workers. Our active learning algorithm achieved similar performance as an algorithm trained with randomly selected data, but with 62% less data samples. This thesis furthers the goal of providing accurate agricultural landcover maps, at a scale that is relevant for the dominant smallholder class. Accurate maps are crucial for monitoring and promoting agricultural production. Furthermore, improved agricultural landcover maps will aid a host of other applications, including landcover change assessments, cadastral surveys to strengthen smallholder land rights, and constraints for crop modeling

  18. A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

    Directory of Open Access Journals (Sweden)

    Byongjun Hwang

    2017-07-01

    Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

  19. Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

    Directory of Open Access Journals (Sweden)

    Timothy Shields

    2016-05-01

    Full Text Available Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase. Comparison of the images indicated that 971 (25.4% structures were added and 536 (14.0% removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

  20. A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

    Science.gov (United States)

    Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

    2017-12-01

    Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

  1. Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River

    Directory of Open Access Journals (Sweden)

    Giuseppe Scardozzi

    2011-01-01

    Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.

  2. Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

    Science.gov (United States)

    Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

    2009-12-01

    Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next

  3. Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

    Science.gov (United States)

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-01-01

    Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  4. Design of a High Resolution Open Access Global Snow Cover Web Map Service Using Ground and Satellite Observations

    Science.gov (United States)

    Kadlec, J.; Ames, D. P.

    2014-12-01

    The aim of the presented work is creating a freely accessible, dynamic and re-usable snow cover map of the world by combining snow extent and snow depth datasets from multiple sources. The examined data sources are: remote sensing datasets (MODIS, CryoLand), weather forecasting model outputs (OpenWeatherMap, forecast.io), ground observation networks (CUAHSI HIS, GSOD, GHCN, and selected national networks), and user-contributed snow reports on social networks (cross-country and backcountry skiing trip reports). For adding each type of dataset, an interface and an adapter is created. Each adapter supports queries by area, time range, or combination of area and time range. The combined dataset is published as an online snow cover mapping service. This web service lowers the learning curve that is required to view, access, and analyze snow depth maps and snow time-series. All data published by this service are licensed as open data; encouraging the re-use of the data in customized applications in climatology, hydrology, sports and other disciplines. The initial version of the interactive snow map is on the website snow.hydrodata.org. This website supports the view by time and view by site. In view by time, the spatial distribution of snow for a selected area and time period is shown. In view by site, the time-series charts of snow depth at a selected location is displayed. All snow extent and snow depth map layers and time series are accessible and discoverable through internationally approved protocols including WMS, WFS, WCS, WaterOneFlow and WaterML. Therefore they can also be easily added to GIS software or 3rd-party web map applications. The central hypothesis driving this research is that the integration of user contributed data and/or social-network derived snow data together with other open access data sources will result in more accurate and higher resolution - and hence more useful snow cover maps than satellite data or government agency produced data by

  5. ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Kim

    2012-07-01

    Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

  6. Comparison of the peak resolution and the stationary phase retention between the satellite and the planetary motions using the coil satellite centrifuge with counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives.

    Science.gov (United States)

    Shinomiya, Kazufusa; Zaima, Kazumasa; Harada, Yukina; Yasue, Miho; Harikai, Naoki; Tokura, Koji; Ito, Yoichiro

    2017-01-20

    Coil satellite centrifuge (CSC) produces the complex satellite motion consisting of the triplicate rotation of the coiled column around three axes including the sun axis (the angular velocity, ω 1 ), the planet axis (ω 2 ) and the satellite axis (the central axis of the column) (ω 3 ) according to the following formula: ω 1 =ω 2 +ω 3 . Improved peak resolution in the separation of 4-methylumbelliferyl sugar derivatives was achieved using the conventional multilayer coiled columns with ethyl acetate/1-butanol/water (3: 2: 5, v/v) for the lower mobile phase at the combination of the rotation speeds (ω 1 , ω 2 , ω 3 )=(300, 150, 150rpm), and (1:4:5, v/v) for the upper mobile phase at (300:100:200rpm). The effect of the satellite motion on the peak resolution and the stationary phase retention was evaluated by each CSC separation with the different rotation speeds of ω 2 and ω 3 under the constant revolution speed at ω 1 =300rpm. With the lower mobile phase, almost constant peak resolution and stationary phase retention were yielded regardless of the change of ω 2 and ω 3 , while with the upper mobile phase these two values were sensitively varied according to the different combination of ω 2 and ω 3 . For example, when ω 2 =147 or 200rpm is used, no stationary phase was retained in the coiled column while ω 2 =150rpm could retain enough volume of stationary phase for separation. On the other hand, the combined rotation speeds at (ω 1 , ω 2 , ω 3 )=(300, 300, 0rpm) or (300, 0, 300rpm) produced insufficient peak resolution regardless of the choice of the mobile phase apparently due to the lack of rotation speed except at (300, 0, 300rpm) with the upper mobile phase. At lower rotation speed of ω 1 =300rpm, better peak resolution and stationary phase retention were obtained by the satellite motion (ω 3 ) than by the planetary motion (ω 2 ), or ω 3 >ω 2 . The effect of the hydrophobicity of the two-phase solvent systems on the stationary phase

  7. Shoreline of Kauala Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  8. Benthic Habitats of Kahoolawe Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2007

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  9. Estimating Canopy Structure in an Amazon Forest from Laser Range Finder and IKONOS Satellite Observations

    Science.gov (United States)

    Gregory P. Asner; Michael Palace; Michael Keller; Rodrigo Pereira Jr.; Jose N. M. Silva; Johan C. Zweede

    2002-01-01

    Canopy structural data can be used for biomass estimation and studies of carbon cycling, disturbance, energy balance, and hydrological processes in tropical forest ecosystems. Scarce information on canopy dimensions reflects the difficulties associated with measuring crown height, width, depth, and area in tall, humid tropical forests. New field and spaceborne...

  10. Benthic Habitat of Lanai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  11. Benthic Habitat of Molokai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  12. Benthic Habitat of Niihau Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  13. Shoreline of Niihau Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  14. Shoreline of Molokai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  15. Shoreline of Lanai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  16. Benthic Habitat of Oahu Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  17. Shoreline of Maui Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  18. Shoreline of Hawaii Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  19. Benthic Habitat of Maui Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  20. Benthic Habitats of Hawaii Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2007

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  1. Benthic Habitats of Kauai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  2. Shoreline of Oahu Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  3. Shoreline of Kauai Derived From IKONOS and Quick Bird Satellite Imagery, 2004-2006

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort between the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment,...

  4. Use of multispectral Ikonos imagery for discriminating between conventional and conservation agricultural tillage practices

    Science.gov (United States)

    Vina, Andres; Peters, Albert J.; Ji, Lei

    2003-01-01

    There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.

  5. Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

    OpenAIRE

    Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-01-01

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to...

  6. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  7. Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Hassan Mohamed

    2018-05-01

    Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

  8. HIRS-AMTS satellite sounding system test - Theoretical and empirical vertical resolving power. [High resolution Infrared Radiation Sounder - Advanced Moisture and Temperature Sounder

    Science.gov (United States)

    Thompson, O. E.

    1982-01-01

    The present investigation is concerned with the vertical resolving power of satellite-borne temperature sounding instruments. Information is presented on the capabilities of the High Resolution Infrared Radiation Sounder (HIRS) and a proposed sounding instrument called the Advanced Moisture and Temperature Sounder (AMTS). Two quite different methods for assessing the vertical resolving power of satellite sounders are discussed. The first is the theoretical method of Conrath (1972) which was patterned after the work of Backus and Gilbert (1968) The Backus-Gilbert-Conrath (BGC) approach includes a formalism for deriving a retrieval algorithm for optimizing the vertical resolving power. However, a retrieval algorithm constructed in the BGC optimal fashion is not necessarily optimal as far as actual temperature retrievals are concerned. Thus, an independent criterion for vertical resolving power is discussed. The criterion is based on actual retrievals of signal structure in the temperature field.

  9. Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

    Science.gov (United States)

    Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

    A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto

  10. A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data

    Science.gov (United States)

    Pengra, Bruce; Long, Jordan; Dahal, Devendra; Stehman, Stephen V.; Loveland, Thomas R.

    2015-01-01

    The methodology for selection, creation, and application of a global remote sensing validation dataset using high resolution commercial satellite data is presented. High resolution data are obtained for a stratified random sample of 500 primary sampling units (5 km  ×  5 km sample blocks), where the stratification based on Köppen climate classes is used to distribute the sample globally among biomes. The high resolution data are classified to categorical land cover maps using an analyst mediated classification workflow. Our initial application of these data is to evaluate a global 30 m Landsat-derived, continuous field tree cover product. For this application, the categorical reference classification produced at 2 m resolution is converted to percent tree cover per 30 m pixel (secondary sampling unit)for comparison to Landsat-derived estimates of tree cover. We provide example results (based on a subsample of 25 sample blocks in South America) illustrating basic analyses of agreement that can be produced from these reference data. Commercial high resolution data availability and data quality are shown to provide a viable means of validating continuous field tree cover. When completed, the reference classifications for the full sample of 500 blocks will be released for public use.

  11. Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

    Science.gov (United States)

    Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

    2012-01-01

    Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

  12. Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

    Science.gov (United States)

    Lee, I.-Chieh

    Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be

  13. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-01-01

    MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  14. MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-09-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  15. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

    Science.gov (United States)

    Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

    2015-01-01

    In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532

  16. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  17. Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR, P. R. China

    Directory of Open Access Journals (Sweden)

    K. Leempoel

    2013-08-01

    Full Text Available Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc. to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively. Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36% was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%, the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements (August–September, 2009 as well as spectral reflectance values (obtained from pansharpened GeoEye-1, both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%. In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e

  18. A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

    Science.gov (United States)

    Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

    2018-06-01

    Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

  19. Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

    Science.gov (United States)

    Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

    2018-04-01

    Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

  20. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

    Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

    2016-06-01

    Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

  1. Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

    OpenAIRE

    Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

    2007-01-01

    Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...

  2. Creating Orthographically Rectified Satellite Multi-Spectral Imagery with High Resolution Digital Elevation Model from LiDAR: A Tutorial

    Science.gov (United States)

    2014-08-15

    EGM96 refers to the equipotential gravity field depicting mean-sea-level across the Earth that is commonly called the geoid...raster and commercial satellite MSI data that are combined in the process of making orthoimages, where feature extraction for models of surface material...peaks along the waveform that show a strong returned laser signal reflected from a rela- tively solid terrain surface or subsurface for the entire

  3. High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

    Science.gov (United States)

    Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

    2016-12-01

    The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

  4. Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

    Science.gov (United States)

    Sandborn, A.; Engstrom, R.; Yu, Q.

    2014-12-01

    Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

  5. An integrated scheme to improve pan-sharpening visual quality of satellite images

    Directory of Open Access Journals (Sweden)

    A.K. Helmy

    2015-03-01

    In experiments with IKONOS, Quick Bird and GeoEye satellite data, we demonstrated that our scheme has good spectral quality and efficiency. Spectral and spatial quality metrics in terms of SAM, RASE, RMSE, CC, ERGAS and QNR are used in our experiments. We compared our scheme with the state-of-the-art pan-sharpening techniques and found that our new scheme improved quantitative and qualitative results.

  6. CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    T. Alipour Fard

    2014-10-01

    Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

  7. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  8. Towards high temporal and moderate spatial resolutions in the remote sensing retrieval of evapotranspiration by combining geostationary and polar orbit satellite data

    Science.gov (United States)

    Barrios, José Miguel; Ghilain, Nicolas; Arboleda, Alirio; Gellens-Meulenberghs, Françoise

    2014-05-01

    Evapotranspiration (ET) is the water flux going from the surface into the atmosphere as result of soil and surface water evaporation and plant transpiration. It constitutes a key component of the water cycle and its quantification is of crucial importance for a number of applications like water management, climatic modelling, agriculture monitoring and planning, etc. Estimating ET is not an easy task; specially if large areas are envisaged and various spatio-temporal patterns of ET are present as result of heterogeneity in land cover, land use and climatic conditions. In this respect, spaceborne remote sensing (RS) provides the only alternative to continuously measure surface parameters related to ET over large areas. The Royal Meteorological Institute (RMI) of Belgium, in the framework of EUMETSAT's "Land Surface Analysis-Satellite Application Facility" (LSA-SAF), has developed a model for the estimation of ET. The model is forced by RS data, numerical weather predictions and land cover information. The RS forcing is derived from measurements by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. This ET model is operational and delivers ET estimations over the whole field of view of the MSG satellite (Europe, Africa and Eastern South America) (http://landsaf.meteo.pt) every 30 minutes. The spatial resolution of MSG is 3 x 3 km at subsatellite point and about 4 x 5 km in continental Europe. The spatial resolution of this product may constrain its full exploitation as the interest of potential users (farmers and natural resources scientists) may lie on smaller spatial units. This study aimed at testing methodological alternatives to combine RS imagery (geostationary and polar orbit satellites) for the estimation of ET such that the spatial resolution of the final product is improved. In particular, the study consisted in the implementation of two approaches for combining the current ET estimations with

  9. ROOF TYPE SELECTION BASED ON PATCH-BASED CLASSIFICATION USING DEEP LEARNING FOR HIGH RESOLUTION SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    T. Partovi

    2017-05-01

    Full Text Available 3D building reconstruction from remote sensing image data from satellites is still an active research topic and very valuable for 3D city modelling. The roof model is the most important component to reconstruct the Level of Details 2 (LoD2 for a building in 3D modelling. While the general solution for roof modelling relies on the detailed cues (such as lines, corners and planes extracted from a Digital Surface Model (DSM, the correct detection of the roof type and its modelling can fail due to low quality of the DSM generated by dense stereo matching. To reduce dependencies of roof modelling on DSMs, the pansharpened satellite images as a rich resource of information are used in addition. In this paper, two strategies are employed for roof type classification. In the first one, building roof types are classified in a state-of-the-art supervised pre-trained convolutional neural network (CNN framework. In the second strategy, deep features from deep layers of different pre-trained CNN model are extracted and then an RBF kernel using SVM is employed to classify the building roof type. Based on roof complexity of the scene, a roof library including seven types of roofs is defined. A new semi-automatic method is proposed to generate training and test patches of each roof type in the library. Using the pre-trained CNN model does not only decrease the computation time for training significantly but also increases the classification accuracy.

  10. True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI

    Directory of Open Access Journals (Sweden)

    Hendrik J. van der Woerd

    2015-10-01

    Full Text Available The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10 of narrow (≈10 nm bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α. Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

  11. Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

    Directory of Open Access Journals (Sweden)

    Lili Li

    2015-06-01

    Full Text Available Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD in China. This paper starts with examining ground observations of particulate matter (PM and the relationship between PM10 (particles smaller than 10 μm and aerosol optical thickness (AOT by analyzing observations on the sampling sites in the PRD. A linear regression (R2 = 0.51 is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R2 = 0.55 between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.

  12. Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

    Science.gov (United States)

    Drzewiecki, Wojciech; Wężyk, Piotr; Pierzchalski, Marcin; Szafrańska, Beata

    2014-06-01

    In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km2). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of

  13. Geo-Parcel Based Crop Identification by Integrating High Spatial-Temporal Resolution Imagery from Multi-Source Satellite Data

    Directory of Open Access Journals (Sweden)

    Yingpin Yang

    2017-12-01

    Full Text Available Geo-parcel based crop identification plays an important role in precision agriculture. It meets the needs of refined farmland management. This study presents an improved identification procedure for geo-parcel based crop identification by combining fine-resolution images and multi-source medium-resolution images. GF-2 images with fine spatial resolution of 0.8 m provided agricultural farming plot boundaries, and GF-1 (16 m and Landsat 8 OLI data were used to transform the geo-parcel based enhanced vegetation index (EVI time-series. In this study, we propose a piecewise EVI time-series smoothing method to fit irregular time profiles, especially for crop rotation situations. Global EVI time-series were divided into several temporal segments, from which phenological metrics could be derived. This method was applied to Lixian, where crop rotation was the common practice of growing different types of crops, in the same plot, in sequenced seasons. After collection of phenological features and multi-temporal spectral information, Random Forest (RF was performed to classify crop types, and the overall accuracy was 93.27%. Moreover, an analysis of feature significance showed that phenological features were of greater importance for distinguishing agricultural land cover compared to temporal spectral information. The identification results indicated that the integration of high spatial-temporal resolution imagery is promising for geo-parcel based crop identification and that the newly proposed smoothing method is effective.

  14. Study on Efficiency of Fusion Techniques for IKONOS Images

    International Nuclear Information System (INIS)

    Liu, Yanmei; Yu, Haiyang; Guijun, Yang; Nie, Chenwei; Yang, Xiaodong; Ren, Dong

    2014-01-01

    Many image fusion techniques have been proposed to achieve optimal resolution in the spatial and spectral domains. Six different merging methods were listed in this paper and the efficiency of fusion techniques was assessed in qualitative and quantitative aspect. Both local and global evaluation parameters were used in the spectral quality and a Laplace filter method was used in spatial quality assessment. By simulation, the spectral quality of the images merged by Brovery was demonstrated to be the worst. In contrast, GS and PCA algorithms, especially the Pansharpening provided higher spectral quality than the standard Brovery, wavelet and CN methods. In spatial quality assessment, the CN method represented best compared with that of others, while the Brovery algorithm was worst. The wavelet parameters that performed best achieved acceptable spectral and spatial quality compared to the others

  15. Analysis and Evaluation of IKONOS Image Fusion Algorithm Based on Land Cover Classification

    Institute of Scientific and Technical Information of China (English)

    Xia; JING; Yan; BAO

    2015-01-01

    Different fusion algorithm has its own advantages and limitations,so it is very difficult to simply evaluate the good points and bad points of the fusion algorithm. Whether an algorithm was selected to fuse object images was also depended upon the sensor types and special research purposes. Firstly,five fusion methods,i. e. IHS,Brovey,PCA,SFIM and Gram-Schmidt,were briefly described in the paper. And then visual judgment and quantitative statistical parameters were used to assess the five algorithms. Finally,in order to determine which one is the best suitable fusion method for land cover classification of IKONOS image,the maximum likelihood classification( MLC) was applied using the above five fusion images. The results showed that the fusion effect of SFIM transform and Gram-Schmidt transform were better than the other three image fusion methods in spatial details improvement and spectral information fidelity,and Gram-Schmidt technique was superior to SFIM transform in the aspect of expressing image details. The classification accuracy of the fused image using Gram-Schmidt and SFIM algorithms was higher than that of the other three image fusion methods,and the overall accuracy was greater than 98%. The IHS-fused image classification accuracy was the lowest,the overall accuracy and kappa coefficient were 83. 14% and 0. 76,respectively. Thus the IKONOS fusion images obtained by the Gram-Schmidt and SFIM were better for improving the land cover classification accuracy.

  16. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  17. Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions

    Directory of Open Access Journals (Sweden)

    Jiahui Han

    2017-03-01

    Full Text Available Oilseed rape (Brassica napus L. is one of the three most important oil crops in China, and is regarded as a drought-tolerant oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB of oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the oilseed rape at the experimental plots. Several representative vegetation indices (VIs obtained from multiple satellite sensors were compared with the simultaneously-collected oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77, the smallest root mean square error (RMSE = 104.64 g/m2, and the relative RMSE (rRMSE = 21%. It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the winter oilseed rape growth stages, and can be applied to map the variability of winter oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture.

  18. Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia.

    Science.gov (United States)

    Proisy, Christophe; Viennois, Gaëlle; Sidik, Frida; Andayani, Ariani; Enright, James Anthony; Guitet, Stéphane; Gusmawati, Niken; Lemonnier, Hugues; Muthusankar, Gowrappan; Olagoke, Adewole; Prosperi, Juliana; Rahmania, Rinny; Ricout, Anaïs; Soulard, Benoit; Suhardjono

    2018-06-01

    Revegetation of abandoned aquaculture regions should be a priority for any integrated coastal zone management (ICZM). This paper examines the potential of a matchless time series of 20 very high spatial resolution (VHSR) optical satellite images acquired for mapping trends in the evolution of mangrove forests from 2001 to 2015 in an estuary fragmented into aquaculture ponds. Evolution of mangrove extent was quantified through robust multitemporal analysis based on supervised image classification. Results indicated that mangroves are expanding inside and outside ponds and over pond dykes. However, the yearly expansion rate of vegetation cover greatly varied between replanted ponds. Ground truthing showed that only Rhizophora species had been planted, whereas natural mangroves consist of Avicennia and Sonneratia species. In addition, the dense Rhizophora plantations present very low regeneration capabilities compared with natural mangroves. Time series of VHSR images provide comprehensive and intuitive level of information for the support of ICZM. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

    Science.gov (United States)

    Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

    2013-12-01

    Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this

  20. Potential of High-Resolution Satellite Imagery for Mapping Distribution and Evaluating Ecological Characteristics of Tree Species at the Angkor Monument, Cambodia

    Directory of Open Access Journals (Sweden)

    Tomita Mizuki

    2015-01-01

    Full Text Available Large trees play several vital roles in the Angkor monuments landscape. They protect biodiversity, enhance the tourism experience, and provide various ecosystem services to local residents. A clear understanding of forest composition and distribution of individual species, as well as timely monitoring of changes, is necessary for conservation of these trees. using traditional field work, obtaining this sort of data is time-consuming and labour-intensive. This research investigates classification of very high resolution remote sensing data as a tool for efficient analyses. QuickBird satellite imagery was used to clarify the tree species community in and around Preah Khan temple, to elucidate differences in ecological traits among the three dominant species (Dipterocarpus alatus, Lagerstroemia calyculata and Tetrameles nudiflora, and to identify crowns of the dominant species.

  1. Built-Up Area and Land Cover Extraction Using High Resolution Pleiades Satellite Imagery for Midrand, in Gauteng Province, South Africa

    Science.gov (United States)

    Fundisi, E.; Musakwa, W.

    2017-09-01

    Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

  2. Tidal inundation (“Rob”) investigation using time series of high resolution satellite image data and from institu measurements along northern coast of Java (Pantura)

    Science.gov (United States)

    Andreas, Heri; Usriyah; Zainal Abidin, Hasanuddin; Anggreni Sarsito, Dina

    2017-06-01

    Tidal inundation (in Javanese they call it “Rob”) is now becoming a well known phenomenon along northern coast of Java Indonesia (Pantura). The occurrence of tidal inundation was recognized at least in the early 2000 and even earlier. In the recent years the tidal inundation comes not only at a high tide but even at the regular tide in some area across Pantura. In fact in location such as Pondok Bali, north of Blanakan, north of Pekalongan, north of Semarang and north west of Demak, seems those areas are sinking to the sea through times. Sea level rise and land subsidence are considered as main factors deriving the occurrence of this tidal inundation. We were using time series of high resolution satellite image data and insitu data measurements to mapping the tidal inundation along northern coast of Java. All available data from google data satellite archives (year 2000- recent years) and any available sources being analyze together with field surveys tagging and also from media information. As a result we can see the tidal inundation are taking place in Tanggerang, Jakarta, Bekasi, Cilamaya, Pondok Bali, Blanakan, Indramayu, Cirebon, Brebes, Tegal, Pemalang, Pekalongan, Kendal, Semarang, Demak, Gresik, Surabaya, Sidoarjo and Pasuruan.

  3. BUILT-UP AREA AND LAND COVER EXTRACTION USING HIGH RESOLUTION PLEIADES SATELLITE IMAGERY FOR MIDRAND, IN GAUTENG PROVINCE, SOUTH AFRICA

    Directory of Open Access Journals (Sweden)

    E. Fundisi

    2017-09-01

    Full Text Available Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

  4. Fire Monitoring - The use of medium resolution satellites (AVHRR, MODIS, TET) for long time series processing and the implementation in User Driven Applications and Services

    Science.gov (United States)

    Fuchs, E.-M.; Stein, E.; Strunz, G.; Strobl, C.; Frey, C.

    2015-04-01

    This paper introduces fire monitoring works of two different projects, namely TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long -Term Dynamics In our Natural Environment) and PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services). It describes the evolution from algorithm development from in applied research to the implementation in user driven applications and systems. Concerning TIMELINE, the focus of the work lies on hot spot detection. A detailed description of the choice of a suitable algorithm (round robin approach) will be given. Moreover, strengths and weaknesses of the AVHRR sensor for hot spot detection, a literature review, the study areas and the selected approach will be highlighted. The evaluation showed that the contextual algorithm performed best, and will therefore be used for final implementation. Concerning the PHAROS project, the key aspect is on the use of satellite-based information to provide valuable support to all phases of disaster management. The project focuses on developing a pre-operational sustainable service platform that integrates space-based EO (Earth Observation), terrestrial sensors and communication and navigation assets to enhance the availability of services and products following a multi-hazard approach.

  5. A new generic method for the semi-automatic extraction of river and road networks in low and mid-resolution satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Dillard, Scott [PNNL; Soille, Pierre [EC JRC

    2010-10-21

    This paper addresses the problem of semi-automatic extraction of road or hydrographic networks in satellite images. For that purpose, we propose an approach combining concepts arising from mathematical morphology and hydrology. The method exploits both geometrical and topological characteristics of rivers/roads and their tributaries in order to reconstruct the complete networks. It assumes that the images satisfy the following two general assumptions, which are the minimum conditions for a road/river network to be identifiable and are usually verified in low- to mid-resolution satellite images: (i) visual constraint: most pixels composing the network have similar spectral signature that is distinguishable from most of the surrounding areas; (ii) geometric constraint: a line is a region that is relatively long and narrow, compared with other objects in the image. While this approach fully exploits local (roads/rivers are modeled as elongated regions with a smooth spectral signature in the image and a maximum width) and global (they are structured like a tree) characteristics of the networks, further directional information about the image structures is incorporated. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the target network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given network seed with this metric is combined with hydrological operators for overland flow simulation to extract the paths which contain most line evidence and identify them with the target network.

  6. High-Precision Attitude Post-Processing and Initial Verification for the ZY-3 Satellite

    Directory of Open Access Journals (Sweden)

    Xinming Tang

    2014-12-01

    Full Text Available Attitude data, which is the important data strongly correlated with the geometric accuracy of optical remote sensing satellite images, are generally obtained using a real-time Extended Kalman Filter (EKF with star-tracker and gyro data for current high-resolution satellites, such as Orb-view, IKONOS, Quickbird,Pleiades, and ZY-3.We propose a forward-backward Unscented Kalman Filter (UKF for post-processing, and the proposed method employs UKF to suppress noise by using an unscented transformation (UT rather than an EKF in a nonlinear attitude system. Moreover, this method makes full use of the collected data in the fixed-interval and computational resources on the ground, and it determines optimal attitude results by forward-backward filtering and weighted smoothing with the raw star-tracker and gyro data collected for a fixed period. In this study, the principle and implementation of the proposed method are described. The post-processed attitude was compared with the on-board attitude, and the absolute accuracy was evaluated by the two methods. One method compares the positioning accuracy of the object space coordinates with the post-processed and on-board attitude data without using ground control points (GCPs. The other method compares the tie-point residuals of the image coordinates after a free net adjustment. In addition, the internal and external parameters of the camera were accurately calibrated before use for an objective evaluation of the attitude accuracy. The experimental results reveal that the accuracy of the post-processed attitude is superior to the accuracy of the on-board processed attitude. This method has been applied to the ZiYuan-3 satellite system for processing the raw star-tracker and gyro data daily.

  7. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

  8. Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

    Science.gov (United States)

    Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

    2013-01-01

    Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg

  9. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2

    Directory of Open Access Journals (Sweden)

    J. Joiner

    2013-10-01

    Full Text Available Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2. The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT. GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0

  10. Combining structure-from-motion derived point clouds from satellites and unmanned aircraft systems images with ground-truth data to create high-resolution digital elevation models

    Science.gov (United States)

    Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.

    2016-12-01

    Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.

  11. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2017-12-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a ESPA-Class (50 kg) micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. In this third year of a NASA Instrument incubator program, the compact infrared spectrometer has been integrated into an airborne version of the instrument for high-altitude flights on a NASA ER2. The purpose of these airborne tests is to examine the potential for improved capabilities for tracking atmospheric motion-vector wind tracer features, and determining their height using hyper-spectral sounding and

  12. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for

  13. Important Value of Economic Potency Mangrove Using NDVI Satellite High Resolution Image To Support Eco Tourism Of Pamurbaya Area (Case Study: East Cost of Surabaya)

    Science.gov (United States)

    Sukojo, B. M.; Hidayat, H.; Ratnasari, D.

    2017-12-01

    Indonesia is a vast maritime country; many mangrove conservations is found around coastal areas of Indonesia. Mangroves support the life of a large number of animal species by providing breeding, spawning and feeding. Mangrove forests as one of the unique ecosystems are potential natural resources, supporting the diversity of flora and fauna of terrestrial aquatic communities that directly or indirectly play an important role for human life in economic, social and environmental terms. East Coast Surabaya is an area with the most extensive and diverse mangrove ecosystems along the coast of Surabaya. Currently Pamurbaya used as a recreational object or nature tourism called eco tours. Utilization of mangrove ecosystem as a place of this eco tour bring positive impact on economic potency around pamurbaya area. So, to know the value of the economic potential of mangrove ecosystems for support of nature tourism Pamurbaya region needs to study mapping mangrove ecosystem conditions in the East Coast area of Surabaya. Mapping of mangrove conditions can use remote sensing technology by utilizing satellite image data with high resolution. Data used for mapping mangrove ecosystem conditions on the east coast of Surabaya are high resolution satellite image data of Pleiades 1A and field observation data such as Ground Control Point, soil spectral parameters and water quality. From satellite image data will be classification of mangrove vegetation canopy classification using NDVI vegetation index method using algorithm formula which then will be tested correlation with field observation data on reflectant value of field and water quality parameter. The purpose of this research is to know the condition of mangrove ecosystem to know the economic potential of mangrove ecosystem in supporting Pamurbaya nature tourism. The expected result of this research is the existence of basic geospatial information in the form of mangrove ecosystem condition map. So that can be used as decision

  14. Estimating Invasion Success by Non-Native Trees in a National Park Combining WorldView-2 Very High Resolution Satellite Data and Species Distribution Models

    Directory of Open Access Journals (Sweden)

    Antonio T. Monteiro

    2017-01-01

    Full Text Available Invasion by non-native tree species is an environmental and societal challenge requiring predictive tools to assess invasion dynamics. The frequent scale mismatch between such tools and on-ground conservation is currently limiting invasion management. This study aimed to reduce these scale mismatches, assess the success of non-native tree invasion and determine the environmental factors associated to it. A hierarchical scaling approach combining species distribution models (SDMs and satellite mapping at very high resolution (VHR was developed to assess invasion by Acacia dealbata in Peneda-Gerês National Park, the only national park in Portugal. SDMs were first used to predict the climatically suitable areas for A. dealdata and satellite mapping with the random-forests classifier was then applied to WorldView-2 very-high resolution imagery to determine whether A. dealdata had actually colonized the predicted areas (invasion success. Environmental attributes (topographic, disturbance and canopy-related differing between invaded and non-invaded vegetated areas were then analyzed. The SDM results indicated that most (67% of the study area was climatically suitable for A. dealbata invasion. The onset of invasion was documented to 1905 and satellite mapping highlighted that 12.6% of study area was colonized. However, this species had only colonized 62.5% of the maximum potential range, although was registered within 55.6% of grid cells that were considerable unsuitable. Across these areas, the specific success rate of invasion was mostly below 40%, indicating that A. dealbata invasion was not dominant and effective management may still be possible. Environmental attributes related to topography (slope, canopy (normalized difference vegetation index (ndvi, land surface albedo and disturbance (historical burnt area differed between invaded and non-invaded vegetated area, suggesting that landscape attributes may alter at specific locations with Acacia

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  19. Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

    Science.gov (United States)

    Duan, Limin; Fan, Keke; Li, Wei; Liu, Tingxi

    2017-12-01

    Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25° × 0.25° for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (https://en.wikipedia.org/wiki/Digital_elevation_model) (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50° × 0.50°; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.

  20. Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2015-09-01

    Full Text Available Crop area extent estimates and crop type maps provide crucial information for agricultural monitoring and management. Remote sensing imagery in general and, more specifically, high temporal and high spatial resolution data as the ones which will be available with upcoming systems, such as Sentinel-2, constitute a major asset for this kind of application. The goal of this paper is to assess to what extent state-of-the-art supervised classification methods can be applied to high resolution multi-temporal optical imagery to produce accurate crop type maps at the global scale. Five concurrent strategies for automatic crop type map production have been selected and benchmarked using SPOT4 (Take5 and Landsat 8 data over 12 test sites spread all over the globe (four in Europe, four in Africa, two in America and two in Asia. This variety of tests sites allows one to draw conclusions applicable to a wide variety of landscapes and crop systems. The results show that a random forest classifier operating on linearly temporally gap-filled images can achieve overall accuracies above 80% for most sites. Only two sites showed low performances: Madagascar due to the presence of fields smaller than the pixel size and Burkina Faso due to a mix of trees and crops in the fields. The approach is based on supervised machine learning techniques, which need in situ data collection for the training step, but the map production is fully automatic.

  1. Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

    Science.gov (United States)

    Soti, Valérie; Chevalier, Véronique; Maura, Jonathan; Bégué, Agnès; Lelong, Camille; Lancelot, Renaud; Thiongane, Yaya; Tran, Annelise

    2013-03-01

    Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (premote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale.

  2. CRED 20 m Gridded bathymetry and IKONOS estimated depths of Northampton Seamounts to Laysan Island, Northwestern Hawaiian Islands, USA (NetCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Northampton Seamounts to Laysan Island, Northwestern Hawaiian Islands, Hawaii,...

  3. CRED 60 m Gridded bathymetry and IKONOS estimated depths of UTM Zone 2, Northwestern Hawaiian Islands, USA (NetCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of the Northwestern Hawaiian Islands, USA within UTM Zone 2. Bottom coverage was...

  4. CRED 60 m Gridded bathymetry and IKONOS estimated depths of UTM Zone 3, Northwestern Hawaiian Islands, USA (netCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of the Northwestern Hawaiian Islands, USA within UTM Zone 3. Bottom coverage was...

  5. CRED 60 m Gridded bathymetry and IKONOS estimated depths of UTM Zone 1, Northwestern Hawaiian Islands, USA (NetCDF format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of the Northwestern Hawaiian Islands, USA within UTM Zone 1. Bottom coverage was...

  6. CRED 20 m Gridded bathymetry and IKONOS estimated depths of Northampton Seamounts to Laysan Island, Northwestern Hawaiian Islands, USA (Arc ASCII format)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry and IKONOS estimated depths of the shelf and slope environments of Northampton Seamounts to Laysan Island, Northwestern Hawaiian Islands, Hawaii,...

  7. Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST Using an Ensemble Kalman Filter

    Directory of Open Access Journals (Sweden)

    Takuji Waseda

    2013-06-01

    Full Text Available We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA, focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1 negative temperature bias due to the cloud effects, and (2 the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF. It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within −0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process.

  8. A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery

    Science.gov (United States)

    Fan, Yuanchao; Koukal, Tatjana; Weisberg, Peter J.

    2014-10-01

    Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun-canopy-sensor (SCS) model significantly improved over those based on the sun-terrain-sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun-crown-sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun-crown-sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor Wt also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model

  9. Analysis of High Resolution Satellite imagery to acsees Glacier Mass Balance and Lake Hazards in Sikkim Himalayas

    Science.gov (United States)

    Bhushan, S.; Shean, D. E.; Haritashya, U. K.; Arendt, A. A.; Syed, T. H.; Setiawan, L.

    2017-12-01

    Glacial lake outburst floods can impact downstream communities due to the sudden outflux of huge quantities of stored water. In this study, we develop a hazard assessment of the moraine dammed glacial lakes in Sikkim Himalayas by analyzing the morphometry of proglacial features, and the surface velocity and mass balance of glaciers. We generated high-resolution digital elevation models (DEMs) using the open-source NASA Ames Stereo Pipeline (ASP) and use other open-source tools to calculate surface velocity and patterns of glacier downwasting over time. Geodetic glacier mass balance is obtained for three periods using high-resolution WorldView/GeoEye stereo DEMs (8 m posting, 2014-2016), Cartosat-1 stereo DEMs (10 m, 2006-2008) and SRTM (30 m, 2000). Initial results reveal a region-wide mass balance of -0.31±0.13 m w.eq.a-1 for the 2007-2015 period, with some debris covered glaciers showing a very low mass loss rate. Additionally, 12 annual glacier velocity fields spanning from 1991 to 2017.derived from Landsat imagery are used to explore the relationship between glacier dynamics and changes in proglacial lakes. Multi-temporal glacial lake mapping is conducted using Landsat and Cartosat imagery. Avalanche and rockfall modeling are combined with morphometric analysis of the proglacial lake area to assess the likelihood of glacial lake dam failure. The above parameters are integrated into a decision tree approach enabling categorization of moraine-dammed lakes according to their potential for outburst events.

  10. MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

    Science.gov (United States)

    Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

    2016-12-01

    Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and

  11. A New Image Processing Procedure Integrating PCI-RPC and ArcGIS-Spline Tools to Improve the Orthorectification Accuracy of High-Resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Hongying Zhang

    2016-10-01

    Full Text Available Given the low accuracy of the traditional remote sensing image processing software when orthorectifying satellite images that cover mountainous areas, and in order to make a full use of mutually compatible and complementary characteristics of the remote sensing image processing software PCI-RPC (Rational Polynomial Coefficients and ArcGIS-Spline, this study puts forward a new operational and effective image processing procedure to improve the accuracy of image orthorectification. The new procedure first processes raw image data into an orthorectified image using PCI with RPC model (PCI-RPC, and then the orthorectified image is further processed using ArcGIS with the Spline tool (ArcGIS-Spline. We used the high-resolution CBERS-02C satellite images (HR1 and HR2 scenes with a pixel size of 2 m acquired from Yangyuan County in Hebei Province of China to test the procedure. In this study, when separately using PCI-RPC and ArcGIS-Spline tools directly to process the HR1/HR2 raw images, the orthorectification accuracies (root mean square errors, RMSEs for HR1/HR2 images were 2.94 m/2.81 m and 4.65 m/4.41 m, respectively. However, when using our newly proposed procedure, the corresponding RMSEs could be reduced to 1.10 m/1.07 m. The experimental results demonstrated that the new image processing procedure which integrates PCI-RPC and ArcGIS-Spline tools could significantly improve image orthorectification accuracy. Therefore, in terms of practice, the new procedure has the potential to use existing software products to easily improve image orthorectification accuracy.

  12. Automated protocols for spaceborne sub-meter resolution "Big Data" products for Earth Science

    Science.gov (United States)

    Neigh, C. S. R.; Carroll, M.; Montesano, P.; Slayback, D. A.; Wooten, M.; Lyapustin, A.; Shean, D. E.; Alexandrov, O.; Macander, M. J.; Tucker, C. J.

    2017-12-01

    The volume of available remotely sensed data has grown exceeding Petabytes per year and the cost for data, storage systems and compute power have both dropped exponentially. This has opened the door for "Big Data" processing systems with high-end computing (HEC) such as the Google Earth Engine, NASA Earth Exchange (NEX), and NASA Center for Climate Simulation (NCCS). At the same time, commercial very high-resolution (VHR) satellites have grown into a constellation with global repeat coverage that can support existing NASA Earth observing missions with stereo and super-spectral capabilities. Through agreements with the National Geospatial-Intelligence Agency NASA-Goddard Space Flight Center is acquiring Petabytes of global sub-meter to 4 meter resolution imagery from WorldView-1,2,3 Quickbird-2, GeoEye-1 and IKONOS-2 satellites. These data are a valuable no-direct cost for the enhancement of Earth observation research that supports US government interests. We are currently developing automated protocols for generating VHR products to support NASA's Earth observing missions. These include two primary foci: 1) on demand VHR 1/2° ortho mosaics - process VHR to surface reflectance, orthorectify and co-register multi-temporal 2 m multispectral imagery compiled as user defined regional mosaics. This will provide an easy access dataset to investigate biodiversity, tree canopy closure, surface water fraction, and cropped area for smallholder agriculture; and 2) on demand VHR digital elevation models (DEMs) - process stereo VHR to extract VHR DEMs with the NASA Ames stereo pipeline. This will benefit Earth surface studies on the cryosphere (glacier mass balance, flow rates and snow depth), hydrology (lake/water body levels, landslides, subsidence) and biosphere (forest structure, canopy height/cover) among others. Recent examples of products used in NASA Earth Science projects will be provided. This HEC API could foster surmounting prior spatial-temporal limitations while

  13. Implementación de la metodología Corine Land Cover con imágenes Ikonos The Corine Land Cover method based on Ikonos images

    Directory of Open Access Journals (Sweden)

    Germán Mauricio Valencia Hernández

    2009-07-01

    Full Text Available En Colombia, desde hace algunos años, se viene trabajando en la construcción de cartografía temática de usos del suelo escala 1:100.000, utilizando la metodología desarrollada en Europa y denominada Corine Land Cover (CLC. Esto se ha logrado con el apoyo del Instituto Forestal Nacional de Francia (ONF a varios organismos nacionales, como el Instituto Geográfico Agustín Codazzi (IGAC, la Corporación Autónoma Regional Cormagdalena y el Instituto de Estudios Ambientales (IDEAM. El objetivo de la investigación fue determinar los cambios en el uso del suelo entre 1992 y 2005 para una región de los Andes colombianos, además identificar las potencialidades y limitaciones de la metodología CLC en el ámbito colombiano. Para ello se ajustó la leyenda a las condiciones de Colombia, se mejoró la unidad mínima de mapeo a 0.5 ha, y se utilizaron como fuentes de información escenas Ikonos Geo no ortorrectificadas. Con la metodología aplicada en esta investigación, se encontró entre los años 1992 y 2005, una disminución del área total en fragmentos boscosos, una disminución del área total en pastos, y un aumento en cultivos. Esta metodología puede ser utilizada en tareas de actualización de coberturas del suelo que requieran un alto nivel de detalle, sin embargo, se recomienda disminuir los errores geométricos con imágenes ortorrectificadas al trabajar en zonas de alta pendiente como es el caso de los Andes colombianos.During the last few years, the European Corine Land Cover method has been used in Colombia in order to update land use maps. Four institutes have been involved in this process: The National Forest Institute of France (ONF, El Instituto Geográfico Agustin Codazzi (IGAC, La Corporación Autonoma Regional Cormagdalena, and El instituto de Estudios Ambientales (IDEAM. The goal of this paper was to determine Land use-land cover change based on the CLC method. The study ranges between 1992 and 2005 along a transect of the

  14. High spatial resolution radiation budget for Europe: derived from satellite data, validation of a regional model; Raeumlich hochaufgeloeste Strahlungsbilanz ueber Europa: Ableitung aus Satellitendaten, Validation eines regionalen Modells

    Energy Technology Data Exchange (ETDEWEB)

    Hollmann, R. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    2000-07-01

    Since forty years instruments onboard satellites have been demonstrated their usefulness for many applications in the field of meteorology and oceanography. Several experiments, like ERBE, are dedicated to establish a climatology of the global Earth radiation budget at the top of the atmosphere. Now the focus has been changed to the regional scale, e.g. GEWEX with its regional sub-experiments like BALTEX. To obtain a regional radiation budget for Europe in the first part of the work the well calibrated measurements from ScaRaB (scanner for radiation budget) are used to derive a narrow-to-broadband conversion, which is applicable to the AVHRR (advanced very high resolution radiometer). It is shown, that the accuracy of the method is in the order of that from SCaRaB itself. In the second part of the work, results of REMO have been compared with measurements of ScaRaB and AVHRR for March 1994. The model reproduces the measurements overall well, but it is overestimating the cold areas and underestimating the warm areas in the longwave spectral domain. Similarly it is overestimating the dark areas and underestimating the bright areas in the solar spectral domain. (orig.)

  15. The geomorphological evidences of subsidence in the Nile Delta: Analysis of high resolution topographic DEM and multi-temporal satellite images

    Science.gov (United States)

    El Bastawesy, M.; Cherif, O. H.; Sultan, M.

    2017-12-01

    This paper investigates the relevance of landforms to the subsidence of the Nile Delta using a high resolution topographic digital elevation model (DEM) and sets of multi-temporal Landsat satellite images. 195 topographic map sheets produced in 1946 at 1:25,000 scale were digitized, and the DEM was interpolated. The undertaken processing techniques have distinguished all the natural low-lying closed depressions from the artificial errors induced by the interpolation of the DEM. The local subsidence of these depressions from their surroundings reaches a maximum depth of 2.5 m. The regional subsidence of the Nile Delta has developed inverted topography, where the tracts occupied by the contemporary distributary channels are standing at higher elevations than the areas in between. This inversion could be related to the differences in the hydrological and sedimentological properties of underlying sediments, as the channels are underlain by water-saturated sands while the successions of clay and silt on flood plains are prone to compaction. Furthermore, the analysis of remote sensing and topographic data clearly show significant changes in the land cover and land use, particularly in the northern lagoons and adjacent sabkhas, which are dominated by numerous low subsiding depressions. The areas covered by water logging and ponds are increasing on the expense of agricultural areas, and aquaculture have been practiced instead. The precise estimation of subsidence rates and distribution should be worked out to evaluate probable changes in land cover and land use.

  16. Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes, situated nearly the Pacific coast of the North and South America.

    Science.gov (United States)

    Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

    The Pacific coast of the North and South America is one of the most seismically and volcanically active regions in the world forming part of the so-called Ring of Fire More than 10 earthquakes with the Richter scale magnitude 4 5 were analyzed They were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only High resolution Aster satellite images were used to extract the principal lineaments using The Lineament Extraction and Stripes Statistic Analysis LESSA software package It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately and a few months later the system returns to its initial state This effect increases with the earthquake magnitude and it is much more easily detectable in case of convergent plate boundaries for example Nasca and South American plates The results obtained open the possibility to develop a methodology able to evaluate the seismic risk in the regions with similar geological conditions

  17. The UV-A and visible solar irradiance spectrum: inter-comparison of absolutely calibrated, spectrally medium resolution solar irradiance spectra from balloon- and satellite-borne measurements

    Directory of Open Access Journals (Sweden)

    W. Gurlit

    2005-01-01

    Full Text Available Within the framework of the ENVISAT/-SCIAMACHY satellite validation, solar irradiance spectra are absolutely measured at moderate resolution in the UV/visible spectral range (in the UV from 316.7-418 nm and the visible from 400-652 nm at a full width half maximum resolution of 0.55 nm and 1.48 nm, respectively from aboard the azimuth-controlled LPMA/DOAS balloon gondola at around 32 km balloon float altitude. After accounting for the atmospheric extinction due to Rayleigh scattering and gaseous absorption (O3 and NO2, the measured solar spectra are compared with previous observations. Our solar irradiance spectrum perfectly agrees within +0.03% with the re-calibrated Kurucz et al. (1984 solar spectrum (Fontenla et al., 1999, called MODTRAN 3.7 in the visible spectral range (415-650 nm, but it is +2.1% larger in the (370-415 nm wavelength interval, and -4% smaller in the UV-A spectral range (316.7-370 nm, when the Kurucz spectrum is convolved to the spectral resolution of our instrument. Similar comparisons of the SOLSPEC (Thuillier et al., 1997, 1998a, b and SORCE/SIM (Harder et al., 2000 solar spectra with MODTRAN 3.7 confirms our findings with the values being -0.5%, +2%, and -1.4% for SOLSPEC -0.33%, -0.47%, and -6.2% for SORCE/SIM, respectively. Comparison of the SCIAMACHY solar spectrum from channels 1 to 4 (- re-calibrated by the University of Bremen - with MODTRAN 3.7 indicates an agreement within -0.4% in the visible spectral range (415-585 nm, -1.6% within the 370-415 nm, and -5.7% within 325-370 nm wavelength interval, in agreement with the results of the other sensors. In agreement with findings of Skupin et al. (2002 our study emphasizes that the present ESA SCIAMACHY level 1 calibration is systematically +15% larger in the considered wavelength intervals when compared to all available other solar irradiance measurements.

  18. Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA performance in the Central Andes region and its dependency on spatial and temporal resolution

    Directory of Open Access Journals (Sweden)

    M. L. M. Scheel

    2011-08-01

    Full Text Available Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, for instance, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM Multi-satellite Precipitation Analysis (TMPA to estimate precipitation rates at daily 0.25° × 0.25° scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio.

    The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15- and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggregation to 0.5°, 0.75° and 1° grid box averaged precipitation and its comparison to gauge data of the same areas revealed no significant change in correlation coefficients and estimate performance.

    In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed.

    Different sources of errors and uncertainties introduced by the sensors, sensor

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  7. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  9. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  10. High Resolution Satellite Data reveals Massive Export of Carbon and Nitrogen-Rich Seagrass Wrack from Greater Florida Bay to the Open Ocean after Hurricane Irma

    Science.gov (United States)

    Dierssen, H. M.; Hedley, J. D.; Russell, B. J.; Vaudrey, J. M.; Perry, R. A.

    2017-12-01

    Episodic storms are known to be important drivers of ocean ecosystem processes, but the impacts are notoriously difficult to quantify with traditional sampling techniques. Here, we use stunning high spatial resolution satellite imagery from Sentinel 2A collected 13 September 2017, only days after Hurricane Irma passed directly over the Florida Keys, to quantify massive amounts of floating vegetative material. This Category 4 storm passed directly over the Florida Keys, bringing wind gusts over 35 m s-1 and creating turbulence in the water column that scoured the seafloor. The imagery reveals as initial estimate of 40 km2 of surface drifting material. Although the identity of the brown material cannot be fully determined without a hyperspectral sensor, the accumulations are consistent with our past research showing large aggregations of seagrass leaves or "wrack" advected under high winds from dense beds of Syringodium filiforme within Greater Florida Bay to the oceanic waters of the Atlantic. Using measurements of wrack collected from this area, we estimate that this single event corresponds to a total export of 9.7 x 1010 gC and 2.7 x 109 gN from the seagrass beds. This high amount of export is not considered typical for many types of tropical seagrass meadows that are thought to highly recycle nutrients within the beds. Elemental analysis of seagrass leaves from Greater Florida Bay is consistent with nitrogen-fixation in the beds, which could provide the means to sustain a large export of nitrogen from the meadows. As the wrack travels at the sea surface, some of these nutrients are exuded into the surrounding waters providing a nutrient subsidy of dissolved and particulate carbon and nitrogen and making the wrack an ecological hot spot for organisms. Although wrack can potentially remain floating for months, the ultimate fate of the wrack is to either wash ashore, providing connectivity between marine and terrestrial ecosystems, or sink to the seafloor. If most

  11. Using high-resolution satellite radar to measure lava flow morphology, rheology, effusion rate and subsidence at El Reventador Volcano, Ecuador.

    Science.gov (United States)

    Biggs, J.; Arnold, D. W. D.; Mothes, P. A.; Anderson, K. R.; Albino, F.; Wadge, G.; Vallejo Vargas, S.; Ebmeier, S. K.

    2017-12-01

    There are relatively few studies of active lava flows of an andesitic rather than basaltic composition. The flow field at El Reventador volcano, Ecuador is a good example, but observations are hampered by persistent cloud cover. We use high resolution satellite radar from Radarsat-2 and TanDEM-X to map the dimensions of 43 lava flows extruded between 9 Feb 2012 and 24 Aug 2016. Flow height is measured using the width of radar shadow cast by steep sided features, or the difference in radar phase between two sensors separated in space. The cumulative volume of erupted material was 44.8M m3 dense rock equivalent with an average rate of 0.31 ± 0.02 m3s-1, similar to the long term average. The flows were mostly emplaced over durations shorter than the satellite repeat interval of 24 days and ranged in length from 0.3 to 1.7 km. We use the dimensions of the levees to estimate the flow yield strengths and compare measurements of diversions around barriers with observations from laboratory experiments. The rate of effusion, flow length and flow volume all decrease with time, and simple physics-based models can be equally well fit by a closed reservoir depressurising during the eruption with no magma recharge, or an open reservoir with a time-constant magma recharge rate of up to 0.35 ± 0.01 m3s-1. We propose that the conduit acts as magma capacitor and individual flows are volume-limited. Emplaced flows are subsiding at rates proportional to lava thickness that decay with time following a square-root relationship. Radar observations, such as those presented here, could be used to map and measure properties of evolving lava flow fields at other remote or difficult to monitor volcanoes. Physics-based models can be run into the future, but a sudden increase in flow length in 2017 seen by Sentinel illustrates that changes in magma supply can cause rapid changes in behavior, which remain challenging to forecast.

  12. U.S. Government Open Internet Access to Sub-meter Satellite Data

    Science.gov (United States)

    Neigh, Christopher S. R> Masek, Jeffery G.; Nickeson, Jaime E.

    2012-01-01

    The National Geospatial-Intelligence Agency (NGA) has contracted United States commercial remote sensing companies GeoEye and Digital Globe to provide very high resolution commercial quality satellite imagery to federal/state government agencies and those projects/people who support government interests. Under NextView contract terms, those engaged in official government programs/projects can gain online access to NGA's vast global archive. Additionally, data from vendor's archives of IKONOS-2 (IK-2), OrbView-3 (OB-3), GeoEye-1 (GE-1), QuickBird-1 (QB-1), WorldView-1 (WV-1), and WorldView-2 (WV-2), sensors can also be requested under these agreements. We report here the current extent of this archive, how to gain access, and the applications of these data by Earth science investigators to improve discoverability and community use of these data. Satellite commercial quality imagery (CQI) at very high resolution (source to U.S. federal, state, and local governments for many different purposes. The rapid growth of free global CQI data has been slow to disseminate to NASA Earth Science community and programs such as the Land-Cover Land-Use Change (LCLUC) program which sees potential benefit from unprecedented access. This article evolved from a workshop held on February 23rd, 2012 between representatives from NGA, NASA, and NASA LCLUC Scientists discussion on how to extend this resource to a broader license approved community. Many investigators are unaware of NGA's archive availability or find it difficult to access CQI data from NGA. Results of studies, both quality and breadth, could be improved with CQI data by combining them with other moderate to coarse resolution passive optical Earth observation remote sensing satellites, or with RADAR or LiDAR instruments to better understand Earth system dynamics at the scale of human activities. We provide the evolution of this effort, a guide for qualified user access, and describe current to potential use of these data in

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  19. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  20. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  7. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

  9. The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report

    Science.gov (United States)

    Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John; Koontz, Stephen R.; Hermans, Caroline

    2011-01-01

    Moderate-resolution imagery (MRI), such as that provided by the Landsat satellites, provides unique spatial information for use by many people both within and outside of the United States (U.S.). However, exactly who these users are, how they use the imagery, and the value and benefits derived from the information are, to a large extent, unknown. To explore these issues, social scientists at the USGS Fort Collins Science Center conducted a study of U.S.-based MRI users from 2008 through 2010 in two parts: 1) a user identification and 2) a user survey. The objectives for this study were to: 1) identify and classify U.S.-based users of this imagery; 2) better understand how and why MRI, and specifically Landsat, is being used; and 3) qualitatively and quantitatively measure the value and societal benefits of MRI (focusing on Landsat specifically). The results of the survey revealed that respondents from multiple sectors use Landsat imagery in many different ways, as demonstrated by the breadth of project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance placed on the imagery, the numerous benefits received from projects using Landsat imagery, the negative impacts if Landsat imagery was no longer available, and the substantial willingness to pay for replacement imagery in the event of a data gap. The survey collected information from users who are both part of and apart from the known user community. The diversity of the sample delivered results that provide a baseline of knowledge about the users, uses, and value of Landsat imagery. While the results supply a wealth of information on their own, they can also be built upon through further research to generate a more complete picture of the population of Landsat users as a whole.

  10. Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

    Science.gov (United States)

    Mitri, George H.; Gitas, Ioannis Z.

    2013-02-01

    Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

  11. Monitoring Corals and Submerged Aquatic Vegetation in Western Pacific Using Satellite Remote Sensing Integrated with Field Data

    Science.gov (United States)

    Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.

    2013-12-01

    Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to

  12. Implementing Fast-Haar Wavelet transform on original Ikonos images to perform image fusion: qualitative assessment

    Directory of Open Access Journals (Sweden)

    Javier Medina

    2014-01-01

    Full Text Available Este artículo presenta la transformada rápida de Wavelet Haar (FHWT, de la sigla en inglés algoritmo que se aplica a la fusión de imágenes satelitales. FHWT es aplicado en un par de imágenes, una imagen multiespectral y una imagen pancromática Ikonos, usando el toolbox de procesamiento digital de imágenes y el toolbox de wavelet suministrados por MatLab ® . Los resultados de la fusión son analizados y evaluados cuantitativa. En lo que corresponde a los resultados cuantitativos de la fusión, se utilizan, en primer lugar, el algoritmo de correlación matemática estadística para analizar la ganancia espectral y espacial de las imágenes fusionadas. Posteriormente, tres sub- imágenes de las imágenes fusionadas son binarizadas con el fin de identificar su precisión espacial, y son evaluadas a través del coeficiente kappa. Los resultados demuestran que FHWT supera a las otras wavelets estudiadas (rbio6.8, bior6.8, db7, dmey y haar al fusionar las imágenes. Por otra parte, las imágenes fusionadas con la FHWT mantienen la resolución espectral respecto a la imagen multiespectral original, mientras presentan una ganancia importante en la resolución espacial.

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  14. Glider and satellite high resolution monitoring of a mesoscale eddy in the Algerian basin: effects on the mixed layer depth and biochemistry

    Science.gov (United States)

    Cotroneo, Yuri; Aulicino, Giuseppe; Ruiz, Simón; Pascual, Ananda; Budillon, Giorgio; Fusco, Giannetta; Tintoré, Joaquin

    2016-04-01

    Despite of the extensive bibliography about the circulation of the Mediterranean Sea and its sub-basins, the debate on mesoscale dynamics and its impacts on biochemical processes is still open because of their intrinsic time scales and of the difficulties in sampling. In order to clarify some of these processes, the "Algerian BAsin Circulation Unmanned Survey - ABACUS" project was proposed and realized through access to JERICO Trans National Access (TNA) infrastructures between September and December 2014. In this framework, a deep glider cruise was carried out in the area between Balearic Islands and Algerian coasts to establish an endurance line for monitoring the basin circulation. During the mission, a mesoscale eddy, identified on satellite altimetry maps, was sampled at high-spatial horizontal resolution (4 km) along its main axes and from surface to 1000 m depth. Data were collected by a Slocum glider equipped with a pumped CTD and biochemical sensors that collected about 100 complete casts inside the eddy. In order to describe the structure of the eddy, in situ data were merged with new generation remotely sensed data as daily synoptic sea surface temperature (SST) and chlorophyll concentration (Chl-a) images from MODIS satellites as well as sea surface height and geostrophic velocities from AVISO. From its origin along the Algerian coast in the eastern part of the basin, the eddy propagated to north-west at a mean speed of about 4 km/day with a mean diameter of 112/130 km, a mean elevation of 15.7 cm and clearly distinguished by the surrounding waters thanks to its higher SST and Chl-a values. Temperature and salinity values along the water column confirm the origin of the eddy from the AC showing the presence of recent Atlantic water in the surface layer and Levantine Intermediate Water (LIW) in the deeper layer. Eddy footprint is clearly evident in the multiparametric vertical sections conducted along its main axes. Deepening of temperature, salinity and

  15. An improved automated procedure for informal and temporary dwellings detection and enumeration, using mathematical morphology operators on VHR satellite data

    Science.gov (United States)

    Jenerowicz, Małgorzata; Kemper, Thomas

    2016-10-01

    Every year thousands of people are displaced by conflicts or natural disasters and often gather in large camps. Knowing how many people have been gathered is crucial for an efficient relief operation. However, it is often difficult to collect exact information on the total number of the population. This paper presents the improved morphological methodology for the estimation of dwellings structures located in several Internally Displaced Persons (IDPs) Camps, based on Very High Resolution (VHR) multispectral satellite imagery with pixel sizes of 1 meter or less including GeoEye-1, WorldView-2, QuickBird-2, Ikonos-2, Pléiades-A and Pléiades-B. The main topic of this paper is the approach enhancement with selection of feature extraction algorithm, the improvement and automation of pre-processing and results verification. For the informal and temporary dwellings extraction purpose the high quality of data has to be ensured. The pre-processing has been extended by including the input data hierarchy level assignment and data fusion method selection and evaluation. The feature extraction algorithm follows the procedure presented in Jenerowicz, M., Kemper, T., 2011. Optical data are analysed in a cyclic approach comprising image segmentation, geometrical, textural and spectral class modeling aiming at camp area identification. The successive steps of morphological processing have been combined in a one stand-alone application for automatic dwellings detection and enumeration. Actively implemented, these approaches can provide a reliable and consistent results, independent of the imaging satellite type and different study sites location, providing decision support in emergency response for the humanitarian community like United Nations, European Union and Non-Governmental relief organizations.

  16. China's land cover and land use change from 1700 to 2005: Estimations from high-resolution satellite data and historical archives

    Science.gov (United States)

    Liu, Mingliang; Tian, Hanqin

    2010-09-01

    One of the major limitations in assessing the impacts of human activities on global biogeochemical cycles and climate is a shortage of reliable data on historical land cover and land use change (LCLUC). China had extreme discrepancies in estimating contemporary and historical patterns of LCLUC over the last 3 centuries because of its geographical complexity, long history of land use, and limited national surveys. This study aims to characterize the spatial and temporal patterns of China's LCLUC during 1700-2005 by reconstructing historical gridded data sets from high-resolution satellite data and long-term historical survey data. During this 300 year period, the major characteristics of LCLUC in China have been shrinking forest (decreased by 22%) and expanding cropland (increased by 42%) and urban areas (including urban and rural settlements, factories, quarries, mining, and other built-up land). New cropland areas have come almost equally from both forested and nonforested land. This study also revealed that substantial conversion between forest and woodland can be attributed to forest harvest, forest regeneration, and land degradation. During 1980-2005, LCLUC was characterized by shrinking cropland, expanding urban and forest areas, and large decadal variations on a national level. LCLUC in China showed significant spatial variations during different time periods, which were caused by spatial heterogeneity in vegetation, soils, and climate and regional imbalance in economy development. During 1700-2005, forests shrunk rapidly while croplands expanded in the northeast and southwest of China. During 1980-2005, we found a serious loss of cropland and urban sprawl in the eastern plain, north, and southeast regions of China and a large increase in forested area in the southeast and southwest regions. The reconstructed LCLUC data sets from this study could be used to assess the impacts of land use change on biogeochemical cycles, the water cycle, and the regional

  17. Effects of Atmospheric Water Vapor and Clouds on NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) Satellite Data.

    Science.gov (United States)

    1984-07-01

    the effect of inadequate information about world food supplies. The impact of the Soviet grain buys of 1972 are a case in point. The last ten...First came TIROS-I ( Televison and Infrared Observational Satellite) in the early 1960’s. The TIROS Operational Satellite (TOS) or ESSA 5 (Environmental...these items impact on the calculated VIN. Other than water, most objects in a scene transmit very little visible solar radiation. The energy

  18. GHRSST Level 3P Global Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 3 Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A platform...

  19. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  20. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  1. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  2. Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

    Energy Technology Data Exchange (ETDEWEB)

    Zoran, Maria; Savastru, Roxana; Savastru, Dan [National Institute of R& D for Optoelectronics, MG5 Bucharest-Magurele, 077125 Romania (Romania); Dida, Adrian [University Transylvania of Brasov, Brasov (Romania)

    2016-03-25

    Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

  3. Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

    International Nuclear Information System (INIS)

    Zoran, Maria; Savastru, Roxana; Savastru, Dan; Dida, Adrian

    2016-01-01

    Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

  4. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

    Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli

    2012-01-01

    The classification of high resolution urban remote sensing imagery is addressed with the focus on classification of imagery that has been pansharpened by a number of different pansharpening methods. The pansharpening process introduces some spectral and spatial distortions in the resulting fused...... multispectral image, the amount of which highly varies depending on which pansharpening technique is used. In the majority of the pansharpening techniques that have been proposed, there is a compromise between the spatial enhancement and the spectral consistency. Here we study the effects of the spectral...... information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

  5. Mapping of Agricultural Crops from Single High-Resolution Multispectral Images—Data-Driven Smoothing vs. Parcel-Based Smoothing

    Directory of Open Access Journals (Sweden)

    Asli Ozdarici-Ok

    2015-05-01

    Full Text Available Mapping agricultural crops is an important application of remote sensing. However, in many cases it is based either on hyperspectral imagery or on multitemporal coverage, both of which are difficult to scale up to large-scale deployment at high spatial resolution. In the present paper, we evaluate the possibility of crop classification based on single images from very high-resolution (VHR satellite sensors. The main objective of this work is to expose performance difference between state-of-the-art parcel-based smoothing and purely data-driven conditional random field (CRF smoothing, which is yet unknown. To fulfill this objective, we perform extensive tests with four different classification methods (Support Vector Machines, Random Forest, Gaussian Mixtures, and Maximum Likelihood to compute the pixel-wise data term; and we also test two different definitions of the pairwise smoothness term. We have performed a detailed evaluation on different multispectral VHR images (Ikonos, QuickBird, Kompsat-2. The main finding of this study is that pairwise CRF smoothing comes close to the state-of-the-art parcel-based method that requires parcel boundaries (average difference ≈ 2.5%. Our results indicate that a single multispectral (R, G, B, NIR image is enough to reach satisfactory classification accuracy for six crop classes (corn, pasture, rice, sugar beet, wheat, and tomato in Mediterranean climate. Overall, it appears that crop mapping using only one-shot VHR imagery taken at the right time may be a viable alternative, especially since high-resolution multitemporal or hyperspectral coverage as well as parcel boundaries are in practice often not available.

  6. Super-resolution

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2014-01-01

    Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...

  7. Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS).

    Science.gov (United States)

    Huff, Amy K; Kondragunta, Shobha; Zhang, Hai; Hoff, Raymond M

    2015-01-01

    Increasing development of exo-urban environments and the spread of urbanization into forested areas is making humans and forest ecosystems more susceptible to the risks associated with wildfires. Larger and more damaging wildfires are having a negative impact on forest ecosystem services, and smoke from wildfires adversely affects the public health of people living in exo-urban environments. Satellite aerosol measurements are valuable tools that can track the evolution of wildfires and monitor the transport of smoke plumes. Operational users, such as air quality forecasters and fire management officials, can use satellite observations to complement ground-based and aircraft measurements of wildfire activity. To date, wildfire applications of satellite aerosol products, such as aerosol optical depth (AOD), have been limited by the relatively coarse resolution of available AOD data. However, the new Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite has high-resolution AOD that is ideally suited to monitoring wildfire impacts on the exo-urban scale. Two AOD products are available from VIIRS: the 750-m × 750-m nadir resolution Intermediate Product (IP) and the 6-km × 6-km resolution Environmental Data Record product, which is aggregated from IP measurements. True color (red, green, and blue [RGB]) imagery and a smoke mask at 750-m × 750-m resolution are also available from VIIRS as decision aids for wildfire applications; they serve as counterparts to AOD measurements by providing visible information about areas of smoke in the atmosphere. To meet the needs of operational users, who do not have time to process raw data files and need access to VIIRS products in near-real time (NRT), VIIRS AOD and RGB NRT imagery are available from the Infusing satellite Data into Environmental Applications (IDEA) web site. A key feature of IDEA is an interactive visualization tool that allows users to

  8. Assessing Wildlife Habitat And Range Utilization in Arizona Using Satellite Data

    Science.gov (United States)

    Hutchinson, C. F.; Marsh, S. E.; Krausman, P. R.; Enns, R. M.; Howery, L. D.; Trobia, E.; Wallace, C. S.; Walker, J. J.; Mauz, K.; Boyd, H.; Salazar, H.

    2001-05-01

    Since their reintroduction in 1914, elk (Cervus elaphus) have grown to be a major issue in the western United States. Most land is controlled by federal or state agencies, but individual ranchers have agreements that permit them to graze cattle on much of this land. Elk often compete with cattle for forage, and damage infrastructure (i.e. fences, watering points, and crops). Conversely, environmentalists and hunters also have an interest in the management of elk populations. As a result, consequence of these conflicting interests, there is little agreement about the size of the elk population or the nature, location, and timing of conflicts that elk might cause. This study was intended to provide information that might help managers understand the distribution of elk in Arizona as a consequence of seasonal variation and in response to extreme climatic events (i.e. El Niño and La Niña). The first task involved modeling elk populations over time. There are no long term or large-scale studies of elk movements through continuous observation (i.e. radiocollars). A technique for modeling elk population has been developed that is based on harvest data, gender ratios, and estimates of male mortality. This provided estimates of elk populations for individual game management units (areas for which harvest is reported and within which elk are managed by the Arizona Game and Fish Department). The second task involved the use of satellite data to characterize vegetation responses to seasonal and interannual climate variation among vegetation associations within game management units. This involved the use of NOAA Advanced Very High Resolution Radiometer (AVHRR) time series data to describe temporal vegetation behavior, Landsat and Ikonos data to describe spatial vegetation distribution in conjunction with U.S. Forest Service vegetation maps. Elk population estimates were correlated with satellite-derived vegetation measures by vegetation association through time. The patterns

  9. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar operational environmental satellite data for land surface monitoring in Africa

    DEFF Research Database (Denmark)

    Fensholt, Rasmus; Anyamba, Assaf; Huber Gharib, Silvia

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth’s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often...... is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI...... affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher...

  10. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  11. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  12. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  13. GHRSST Level 2P Global Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset based on multi-channel sea surface temperature (SST) retrievals from the...

  14. GHRSST Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  15. GHRSST Level 2P Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NAVO (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in...

  16. GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface...

  17. GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Cihlar, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Chen, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Toronto, Dept. of Geography, Toronto, Ontario (Canada); Li, Z. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Maryland, Dept of Meteorology, College Park, MD (United States)] [and others

    2002-02-01

    Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

  18. GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

    International Nuclear Information System (INIS)

    Cihlar, J.; Chen, J.; Li, Z.

    2002-01-01

    Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

  19. Land use/land cover mapping using multi-scale texture processing of high resolution data

    Science.gov (United States)

    Wong, S. N.; Sarker, M. L. R.

    2014-02-01

    Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

  20. Land use/land cover mapping using multi-scale texture processing of high resolution data

    International Nuclear Information System (INIS)

    Wong, S N; Sarker, M L R

    2014-01-01

    Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road

  1. Citizen-Enabled Aerosol Measurements for Satellites (CEAMS): A Network for High-Resolution Measurements of PM2.5 and Aerosol Optical Depth

    Science.gov (United States)

    Pierce, J. R.; Volckens, J.; Ford, B.; Jathar, S.; Long, M.; Quinn, C.; Van Zyl, L.; Wendt, E.

    2017-12-01

    Atmospheric particulate matter with diameter smaller than 2.5 μm (PM2.5) is a pollutant that contributes to the development of human disease. Satellite-derived estimates of surface-level PM2.5 concentrations have the potential to contribute greatly to our understanding of how particulate matter affects health globally. However, these satellite-derived PM2.5 estimates are often uncertain due to a lack of information about the ratio of surface PM2.5 to aerosol optical depth (AOD), which is the primary aerosol retrieval made by satellite instruments. While modelling and statistical analyses have improved estimates of PM2.5:AOD, large uncertainties remain in situations of high PM2.5 exposure (such as urban areas and in wildfire-smoke plumes) where the health impacts of PM2.5 may be the greatest. Surface monitoring networks for co-incident PM2.5 and AOD measurements are extremely rare, even in the North America. To provide constraints for the PM2.5:AOD relationship, we have developed a relatively low-cost (application (iOS and Android). Sun photometry is performed across 4 discrete wavelengths that match those reported by the Aerosol Robotic Network (AERONET). Aerosol concentration is reported using both time-integrated filter mass (analyzed in an academic laboratory and reported as a 24-48hr average) and a continuous PM sensor within the instrument. Citizen scientists use the device to report daily AOD and PM2.5 measurements made in their backyards to a central server for data display and download. In this presentation, we provide an overview of (1) AOD and PM2.5 measurement calibration; (2) citizen recruiting and training efforts; and (3) results from our pilot citizen-science measurement campaign.

  2. METHODS FOR MULTITEMPORAL ANALYSIS OF SATELLITE DATA AIMED AT ENVIRONMENTAL RISK MONITORING

    Directory of Open Access Journals (Sweden)

    M. Caprioli

    2012-08-01

    Full Text Available In the last years the topic of Environmental monitoring has raised a particular importance, also according to minor short-term stability and predictability of climatic events. Facing this situation, often in terms of emergency, involves high and unpredictable costs for public Agencies. Prevention of damages caused by natural disasters does not regard only weather forecasts, but requires constant attention and practice of monitoring and control of human activity on territory. Practically, the problem is not knowing if and when an event will affect a determined area, but recognizing the possible damages if this event happened, by adopting the adequate measures to reduce them to a minimum, and requiring the necessary tools for a timely intervention. On the other hand, the surveying technologies should be the most possible accurate and updatable in order to guarantee high standards, involving the analysis of a great amount of data. The management of such data requires the integration and calculation systems with specialized software and fast and reliable connection and communication networks. To solve such requirements, current satellite technology, with recurrent data acquisition for the timely generation of cartographic products updated and coherent to the territorial investigation, offers the possibility to fill the temporal gap between the need of urgent information and official reference information. Among evolved image processing techniques, Change detection analysis is useful to facilitate individuation of environmental temporal variations, contributing to reduce the users intervention by means of the processes automation and improving in a progressive way the qualitative and quantitative accuracy of results. The research investigate automatic methods on land cover transformations by means of "Change detection" techniques executable on satellite data that are heterogeneous for spatial and spectral resolution with homogenization and

  3. Saturn satellites

    International Nuclear Information System (INIS)

    Ruskol, E.L.

    1981-01-01

    The characteristics of the Saturn satellites are discussed. The satellites close to Saturn - Janus, Mimas, Enceladus, Tethys, Dione and Rhea - rotate along the circular orbits. High reflectivity is attributed to them, and the density of the satellites is 1 g/cm 3 . Titan is one of the biggest Saturn satellites. Titan has atmosphere many times more powerful than that of Mars. The Titan atmosphere is a peculiar medium with a unique methane and hydrogen distribution in the whole Solar system. The external satellites - Hyperion, Japetus and Phoebe - are poorly investigated. Neither satellite substance density, nor their composition are known. The experimental data on the Saturn rings obtained on the ''Pioneer-11'' and ''Voyager-1'' satellites are presented [ru

  4. PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS

    Directory of Open Access Journals (Sweden)

    K. Jacobsen

    2017-05-01

    Full Text Available The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC. The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3, WorldView-2 (WV2, Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs. The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the

  5. Problems and Limitations of Satellite Image Orientation for Determination of Height Models

    Science.gov (United States)

    Jacobsen, K.

    2017-05-01

    The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height

  6. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  7. Assessing Wildfire Risk in Cultural Heritage Properties Using High Spatial and Temporal Resolution Satellite Imagery and Spatially Explicit Fire Simulations: The Case of Holy Mount Athos, Greece

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis

    2016-02-01

    Full Text Available Fire management implications and the design of conservation strategies on fire prone landscapes within the UNESCO World Heritage Properties require the application of wildfire risk assessment at landscape level. The objective of this study was to analyze the spatial variation of wildfire risk on Holy Mount Athos in Greece. Mt. Athos includes 20 monasteries and other structures that are threatened by increasing frequency of wildfires. Site-specific fuel models were created by measuring in the field several fuel parameters in representative natural fuel complexes, while the spatial extent of the fuel types was determined using a synergy of high-resolution imagery and high temporal information from medium spatial resolution imagery classified through object-based analysis and a machine learning classifier. The Minimum Travel Time (MTT algorithm, as it is embedded in FlamMap software, was applied in order to evaluate Burn Probability (BP, Conditional Flame Length (CFL, Fire Size (FS, and Source-Sink Ratio (SSR. The results revealed low burn probabilities for the monasteries; however, nine out of the 20 monasteries have high fire potential in terms of fire intensity, which means that if an ignition occurs, an intense fire is expected. The outputs of this study may be used for decision-making for short-term predictions of wildfire risk at an operational level, contributing to fire suppression and management of UNESCO World Heritage Properties.

  8. The High Resolution Stereo Camera (HRSC) of Mars Express and its approach to science analysis and mapping for Mars and its satellites

    Science.gov (United States)

    Gwinner, K.; Jaumann, R.; Hauber, E.; Hoffmann, H.; Heipke, C.; Oberst, J.; Neukum, G.; Ansan, V.; Bostelmann, J.; Dumke, A.; Elgner, S.; Erkeling, G.; Fueten, F.; Hiesinger, H.; Hoekzema, N. M.; Kersten, E.; Loizeau, D.; Matz, K.-D.; McGuire, P. C.; Mertens, V.; Michael, G.; Pasewaldt, A.; Pinet, P.; Preusker, F.; Reiss, D.; Roatsch, T.; Schmidt, R.; Scholten, F.; Spiegel, M.; Stesky, R.; Tirsch, D.; van Gasselt, S.; Walter, S.; Wählisch, M.; Willner, K.

    2016-07-01

    The High Resolution Stereo Camera (HRSC) of ESA's Mars Express is designed to map and investigate the topography of Mars. The camera, in particular its Super Resolution Channel (SRC), also obtains images of Phobos and Deimos on a regular basis. As HRSC is a push broom scanning instrument with nine CCD line detectors mounted in parallel, its unique feature is the ability to obtain along-track stereo images and four colors during a single orbital pass. The sub-pixel accuracy of 3D points derived from stereo analysis allows producing DTMs with grid size of up to 50 m and height accuracy on the order of one image ground pixel and better, as well as corresponding orthoimages. Such data products have been produced systematically for approximately 40% of the surface of Mars so far, while global shape models and a near-global orthoimage mosaic could be produced for Phobos. HRSC is also unique because it bridges between laser altimetry and topography data derived from other stereo imaging instruments, and provides geodetic reference data and geological context to a variety of non-stereo datasets. This paper, in addition to an overview of the status and evolution of the experiment, provides a review of relevant methods applied for 3D reconstruction and mapping, and respective achievements. We will also review the methodology of specific approaches to science analysis based on joint analysis of DTM and orthoimage information, or benefitting from high accuracy of co-registration between multiple datasets, such as studies using multi-temporal or multi-angular observations, from the fields of geomorphology, structural geology, compositional mapping, and atmospheric science. Related exemplary results from analysis of HRSC data will be discussed. After 10 years of operation, HRSC covered about 70% of the surface by panchromatic images at 10-20 m/pixel, and about 97% at better than 100 m/pixel. As the areas with contiguous coverage by stereo data are increasingly abundant, we also

  9. High and Medium Resolution Satellite Imagery to Evaluate Late Holocene Human–Environment Interactions in Arid Lands: A Case Study from the Central Sahara

    Directory of Open Access Journals (Sweden)

    Stefano Biagetti

    2017-04-01

    Full Text Available We present preliminary results of an Earth observation approach for the study of past human occupation and landscape reconstruction in the Central Sahara. This region includes a variety of geomorphological features such as palaeo-oases, dried river beds, alluvial fans and upland plateaux whose geomorphological characteristics, in combination with climate changes, have influenced patterns of human dispersal and sociocultural activities during the late Holocene. In this paper, we discuss the use of medium- and high-resolution remotely sensed data for the mapping of anthropogenic features and paleo- and contemporary hydrology and vegetation. In the absence of field inspection in this inaccessible region, we use different remote sensing methods to first identify and classify archaeological features, and then explore the geomorphological factors that might have influenced their spatial distribution.

  10. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  11. Satellite Remote Sensing of Cropland Characteristics in 30m Resolution: The First North American Continental-Scale Classification on High Performance Computing Platforms

    Science.gov (United States)

    Massey, Richard

    Cropland characteristics and accurate maps of their spatial distribution are required to develop strategies for global food security by continental-scale assessments and agricultural land use policies. North America is the major producer and exporter of coarse grains, wheat, and other crops. While cropland characteristics such as crop types are available at country-scales in North America, however, at continental-scale cropland products are lacking at fine sufficient resolution such as 30m. Additionally, applications of automated, open, and rapid methods to map cropland characteristics over large areas without the need of ground samples are needed on efficient high performance computing platforms for timely and long-term cropland monitoring. In this study, I developed novel, automated, and open methods to map cropland extent, crop intensity, and crop types in the North American continent using large remote sensing datasets on high-performance computing platforms. First, a novel method was developed in this study to fuse pixel-based classification of continental-scale Landsat data using Random Forest algorithm available on Google Earth Engine cloud computing platform with an object-based classification approach, recursive hierarchical segmentation (RHSeg) to map cropland extent at continental scale. Using the fusion method, a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010 was produced. In this map, the total cropland area for North America was estimated at 275.2 million hectares (Mha). This map was assessed for accuracy using randomly distributed samples derived from United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-Food Canada (AAFC) annual crop inventory (ACI), Servicio de Informacion Agroalimentaria y Pesquera (SIAP), Mexico's agricultural boundaries, and photo-interpretation of high-resolution imagery. The overall accuracies of the map are 93.4% with a

  12. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery

    Science.gov (United States)

    Shean, David E.; Alexandrov, Oleg; Moratto, Zachary M.; Smith, Benjamin E.; Joughin, Ian R.; Porter, Claire; Morin, Paul

    2016-06-01

    We adapted the automated, open source NASA Ames Stereo Pipeline (ASP) to generate digital elevation models (DEMs) and orthoimages from very-high-resolution (VHR) commercial imagery of the Earth. These modifications include support for rigorous and rational polynomial coefficient (RPC) sensor models, sensor geometry correction, bundle adjustment, point cloud co-registration, and significant improvements to the ASP code base. We outline a processing workflow for ˜0.5 m ground sample distance (GSD) DigitalGlobe WorldView-1 and WorldView-2 along-track stereo image data, with an overview of ASP capabilities, an evaluation of ASP correlator options, benchmark test results, and two case studies of DEM accuracy. Output DEM products are posted at ˜2 m with direct geolocation accuracy of process individual stereo pairs on a local workstation, the methods presented here were developed for large-scale batch processing in a high-performance computing environment. We are leveraging these resources to produce dense time series and regional mosaics for the Earth's polar regions.

  13. Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

    Science.gov (United States)

    Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars

    2011-11-01

    Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.

  14. Satellite Communications

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'

  15. Satellite constraint for emissions of nitrogen oxides from anthropogenic, lightning and soil sources over East China on a high-resolution grid

    Directory of Open Access Journals (Sweden)

    J.-T. Lin

    2012-03-01

    Full Text Available Vertical column densities (VCDs of tropospheric nitrogen dioxide (NO2 retrieved from space provide valuable information to estimate emissions of nitrogen oxides (NOx inversely. Accurate emission attribution to individual sources, important both for understanding the global biogeochemical cycling of nitrogen and for emission control, remains difficult. This study presents a regression-based multi-step inversion approach to estimate emissions of NOx from anthropogenic, lightning and soil sources individually for 2006 over East China on a 0.25° long × 0.25° lat grid, employing the DOMINO product version 2 retrieved from the Ozone Monitoring Instrument. The inversion is done gridbox by gridbox to derive the respective emissions, taking advantage of differences in seasonality between anthropogenic and natural sources. Lightning and soil emissions are combined together for any given gridbox due to their similar seasonality; and their different spatial distributions are used implicitly for source separation to some extent. The nested GEOS-Chem model for East Asia is used to simulate the seasonal variations of different emission sources and impacts on VCDs of NO2 for the inversion purpose. Sensitivity tests are conducted to evaluate key assumptions embedded in the inversion process. The inverse estimate suggests annual budgets of about 7.1 TgN (±39%, 0.21 TgN (±61%, and 0.38 TgN (±65% for the a posteriori anthropogenic, lightning and soil emissions, respectively, about 18–23% higher than the respective a priori values. The enhancements in anthropogenic emissions are largest in cities and areas with extensive use of coal, particularly in the north in winter, as evident on the high-resolution grid. Derived soil emissions are consistent with recent bottom-up estimates. They are less than 6% of anthropogenic emissions annually, increasing to about 13% for July. Derived lightning emissions are about 3% of

  16. COSMO-SkyMed Very High Resolution Data in support of Key Site Monitoring: A novel approach for characterization of sensitive areas and change direction based on VHR-SAR Coherent Multi-temporal Analysis

    International Nuclear Information System (INIS)

    Britti, F.; Cesarano, L.; Costantini, M.; Gentile, V.; Minati, F.; Pietranera, L.

    2013-01-01

    The COSMO-SkyMed Constellation, four VHR Earth Observation SAR satellites, can be an extremely useful source of information for monitoring programs, and in particular for monitoring of nuclear facilities safeguards, ranging from environmental analysis to human activity characterization. Thanks to its very high revisit coupled with the all weather capability and its dawn to dusk operations, the COSMO-SkyMed constellation is an ideal tool for improving already existing VHR (Very High Resolution) optical satellites monitoring by enhancing classical change detection activities. Thanks to its multi-mode acquisition capability with resolution up to one meter, the COSMO-SkyMed constellation can cover large areas in a very short time to monitor nuclear sites and surrounding areas, thereby providing additional information for the potential detection of undeclared nuclear activities. In particular, thanks to the interferometric capabilities of the SAR sensor, coherence analysis introduces additional information closely related to the changes occurred and occurring over the area of interest within the desired time interval (up to one day at best conditions). Indeed, thanks to the high sensitivity to variations of this added-value product, available only with SAR data, guaranteed by the wavelength used by COSMO-SkyMed sensors (3 cm), in-time analysis through coherence can be a strong indicator of human activity, particularly over areas characterized by a stable environment (i.e. coherent areas), such as deserts/arid zones or ice or snow-covered areas. The aim of this work is to provide a detailed description of how COSMO-SkyMed data and e-GEOS added-value products are able to improve intelligence analysis over critical sites (and their surrounding areas), allowing: -) enhanced change detection through both amplitude and coherence information, -) high frequency site monitoring, -) data integration with other sources of information (optical or on-ground measurements). e-GEOS, a

  17. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  18. Modelagem de dados do satélite Ikonos II para estimativa de micronutrientes na floresta ombrófila mista montana

    OpenAIRE

    Acco, Mônica

    2004-01-01

    O presente trabalho teve como objetivo desenvolver uma metodologia utilizando imagens do satélite IKONOS II para realizar estimativas de micronutrientes na Floresta Ombrófila Mista Montana. Para o desenvolvimento desta metodologia utilizou-se de material coletado no município de General Carneiro (PR) na propriedade das Indústrias Pedro N. Pizzatto Ltda em 20 unidades amostrais primárias de 12 x 12 metros. Os materiais coletados foram separados, secos e pesados, obtendo-se, então, os teores de...

  19. Asteroid Satellites

    Science.gov (United States)

    Merline, W. J.

    2001-11-01

    Discovery and study of small satellites of asteroids or double asteroids can yield valuable information about the intrinsic properties of asteroids themselves and about their history and evolution. Determination of the orbits of these moons can provide precise masses of the primaries, and hence reliable estimates of the fundamental property of bulk density. This reveals much about the composition and structure of the primary and will allow us to make comparisons between, for example, asteroid taxonomic type and our inventory of meteorites. The nature and prevalence of these systems will also give clues as to the collisional environment in which they formed, and have further implications for the role of collisions in shaping our solar system. A decade ago, binary asteroids were more of a theoretical curiosity. In 1993, the Galileo spacecraft allowed the first undeniable detection of an asteroid moon, with the discovery of Dactyl, a small moon of Ida. Since that time, and particularly in the last year, the number of known binaries has risen dramatically. Previously odd-shaped and lobate near-Earth asteroids, observed by radar, have given way to signatures indicating, almost certainly, that at least four NEAs are binary systems. The tell-tale lightcurves of several other NEAs reveal a high likelihood of being double. Indications are that among the NEAs, there may be a binary frequency of several tens of percent. Among the main-belt asteroids, we now know of 6 confirmed binary systems, although their overall frequency is likely to be low, perhaps a few percent. The detections have largely come about because of significant advances in adaptive optics systems on large telescopes, which can now reduce the blurring of the Earth's atmosphere to compete with the spatial resolution of space-based imaging (which itself, via HST, is now contributing valuable observations). Most of these binary systems have similarities, but there are important exceptions. Searches among other

  20. Developing status of satellite remote sensing and its application

    International Nuclear Information System (INIS)

    Zhang Wanliang; Liu Dechang

    2005-01-01

    This paper has discussed the latest development of satellite remote sensing in sensor resolutions, satellite motion models, load forms, data processing and its application. The authors consider that sensor resolutions of satellite remote sensing have increased largely. Valid integration of multisensors is a new idea and technology of satellite remote sensing in the 21st century, and post-remote sensing application technology is the important part of deeply applying remote sensing information and has great practical significance. (authors)

  1. Satellite myths

    Science.gov (United States)

    Easton, Roger L.; Hall, David

    2008-01-01

    Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.

  2. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....

  3. Boomerang Satellites

    Science.gov (United States)

    Hesselbrock, Andrew; Minton, David A.

    2017-10-01

    We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.

  4. Shadow imaging of geosynchronous satellites

    Science.gov (United States)

    Douglas, Dennis Michael

    Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

  5. Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2010-10-01

    Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images

  6. Satellite Radio

    Indian Academy of Sciences (India)

    Satellites have been a highly effective platform for multi- form broadcasts. This has led to a ... diversity offormats, languages, genre, and a universal reach that cannot be met by .... programs can be delivered to whom it is intended. In the case of.

  7. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

    Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

  8. Guam and Commonwealth of the Northern Mariana Islands (CNMI) Benthic Habitat Maps Prepared by Visual Interpretation from IKONOS satellite imagery procured by NOAA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This project is a cooperative effort among the National Ocean Service, National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment; the...

  9. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  10. Scientific Satellites

    Science.gov (United States)

    1967-01-01

    noise signal level exceeds 10 times the normal background. EXPERIMENTS FOR SATELLITE ASTRONOMY 615 ANTENNA MONOPOLE -., PREAMPLFE = BANDPASS-FILTER...OUTPUT TO AND DETECTOR TELEMETRYCHANNELS (18) CALIBRATION NOISE MATRIX CLOCK NOISE SOURCE ’ON’ SOURCE COMMAND F ROM PROGRAMERP ANTENNA MONOPOLE FIGURE 13...Animal Tempera- ture Sensing for Studying the Effect of Prolonged Orbital Flight on the Circadian Rhythms of Pocket Mice . Unmanned Spacecraft Meeting

  11. Solar satellites

    Energy Technology Data Exchange (ETDEWEB)

    Poher, C.

    1982-01-01

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  12. Solar satellites

    Science.gov (United States)

    Poher, C.

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  13. GHRSST Level 3P North Atlantic Regional Subskin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for HIgh Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) from the Advanced Very High Resolution Radiometer (AVHRR) on...

  14. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-18 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  15. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  16. GHRSST Level 2P North Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-17 satellite produced by NEODAAS (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Level 2P swath-based Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic area from the Advanced Very High Resolution...

  17. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  18. GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR)...

  19. Mapping mangrove leaf area index at the species level using IKONOS and LAI-2000 sensors for the Agua Brava Lagoon, Mexican Pacific

    Science.gov (United States)

    Kovacs, John M.; Wang, Jinfei; Flores-Verdugo, Francisco

    2005-01-01

    Using both IKONOS and in situ LAI-2000 sensor data, a map of estimated LAI, based on NDVI, was created for the Agua Brava Lagoon, Mexican Pacific. The LAI values were then aggregated according to four classes; red mangrove ( Rhizophora mangle), healthy white mangrove ( Laguncularia racemosa), poor condition white mangrove and dead mangrove. Of the live mangrove, calculated at approximately 85% of the forest, mean LAI values of 2.49, 1.74 and 0.85 were determined for the red, healthy white and poor condition white mangrove, respectively. Excluding the dead areas, an overall estimated mangrove LAI value of 1.81 was ascertained for the 71 km 2 of mapped mangrove forest. Although the results do suggest the technique as a very rapid and effective method for monitoring the condition of mangroves at the species level, potential limitations are also discussed.

  20. Resolution Enhancement of Multilook Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Galbraith, Amy E. [Univ. of Arizona, Tucson, AZ (United States)

    2004-07-01

    This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The importan