WorldWideScience

Sample records for satellite based multispectral

  1. Multi-spectral band selection for satellite-based systems

    International Nuclear Information System (INIS)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-01-01

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed

  2. Predictions of malaria vector distribution in Belize based on multispectral satellite data.

    Science.gov (United States)

    Roberts, D R; Paris, J F; Manguin, S; Harbach, R E; Woodruff, R; Rejmankova, E; Polanco, J; Wullschleger, B; Legters, L J

    1996-03-01

    Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

  3. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  4. Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude

    Science.gov (United States)

    Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.

    2018-05-01

    One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.

  5. 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.

  6. BEE FORAGE MAPPING BASED ON MULTISPECTRAL IMAGES LANDSAT

    Directory of Open Access Journals (Sweden)

    A. Moskalenko

    2016-10-01

    Full Text Available Possibilities of bee forage identification and mapping based on multispectral images have been shown in the research. Spectral brightness of bee forage has been determined with the use of satellite images. The effectiveness of some methods of image classification for mapping of bee forage is shown. Keywords: bee forage, mapping, multispectral images, image classification.

  7. Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

    Science.gov (United States)

    Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

    1993-01-01

    This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

  8. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  9. Synchronous atmospheric radiation correction of GF-2 satellite multispectral image

    Science.gov (United States)

    Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan

    2018-02-01

    GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.

  10. Empirical water depth predictions in Dublin Bay based on satellite EO multispectral imagery and multibeam data using spatially weighted geographical analysis

    Science.gov (United States)

    Monteys, Xavier; Harris, Paul; Caloca, Silvia

    2014-05-01

    The coastal shallow water zone can be a challenging and expensive environment within which to acquire bathymetry and other oceanographic data using traditional survey methods. Dangers and limited swath coverage make some of these areas unfeasible to survey using ship borne systems, and turbidity can preclude marine LIDAR. As a result, an extensive part of the coastline worldwide remains completely unmapped. Satellite EO multispectral data, after processing, allows timely, cost efficient and quality controlled information to be used for planning, monitoring, and regulating coastal environments. It has the potential to deliver repetitive derivation of medium resolution bathymetry, coastal water properties and seafloor characteristics in shallow waters. Over the last 30 years satellite passive imaging methods for bathymetry extraction, implementing analytical or empirical methods, have had a limited success predicting water depths. Different wavelengths of the solar light penetrate the water column to varying depths. They can provide acceptable results up to 20 m but become less accurate in deeper waters. The study area is located in the inner part of Dublin Bay, on the East coast of Ireland. The region investigated is a C-shaped inlet covering an area of 10 km long and 5 km wide with water depths ranging from 0 to 10 m. The methodology employed on this research uses a ratio of reflectance from SPOT 5 satellite bands, differing to standard linear transform algorithms. High accuracy water depths were derived using multibeam data. The final empirical model uses spatially weighted geographical tools to retrieve predicted depths. The results of this paper confirm that SPOT satellite scenes are suitable to predict depths using empirical models in very shallow embayments. Spatial regression models show better adjustments in the predictions over non-spatial models. The spatial regression equation used provides realistic results down to 6 m below the water surface, with

  11. Methods of Evaluating Thermodynamic Properties of Landscape Cover Using Multispectral Reflected Radiation Measurements by the Landsat Satellite

    Directory of Open Access Journals (Sweden)

    Yuriy Puzachenko

    2013-09-01

    Full Text Available The paper discusses methods of evaluating thermodynamic properties of landscape cover based on multi-spectral measurements by the Landsat satellites. Authors demonstrate how these methods could be used for studying functionality of landscapes and for spatial interpolation of Flux NET system measurements.

  12. Changes of glacier, glacier-fed rivers and lakes in Altai Tavan Bogd National Park, Western Mongolia, based on multispectral satellite data from 1990 to 2017

    Science.gov (United States)

    Batsaikhan, B.; Lkhamjav, O.; Batsaikhan, N.

    2017-12-01

    Impacts on glaciers and water resource management have been altering through climate changes in Mongolia territory characterized by dry and semi-arid climate with low precipitation. Melting glaciers are early indicators of climate change unlike the response of the forests which is slower and takes place over a long period of time. Mountain glaciers are important environmental components of local, regional, and global hydrological cycles. The study calculates an overview of changes for glacier, glacier-fed rivers and lakes in Altai Tavan Bogd mountain, the Western Mongolia, based on the indexes of multispectral data and the methods typically applied in glacier studies. Were utilized an integrated approach of Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI) to combine Landsat, MODIS imagery and digital elevation model, to identify glacier cover are and quantify water storage change in lakes, and compared that with and climate parameters including precipitation, land surface temperature, evaporation, moisture. Our results show that melts of glacier at the study area has contributed to significantly increase of water storage of lakes in valley of The Altai Tavan Bogd mountain. There is hydrologic connection that lake basin is directly fed by glacier meltwater.

  13. Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

    Science.gov (United States)

    Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

    We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

  14. 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.

  15. 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...

  16. 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...

  17. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

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

  18. 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.

  19. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  20. Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

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    Jin Li

    2014-01-01

    Full Text Available Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC combined with image data compression (IDC approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE. Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS-based algorithm has better compression performance than the traditional compression approaches.

  1. Multispectral image compression based on DSC combined with CCSDS-IDC.

    Science.gov (United States)

    Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

    2014-01-01

    Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

  2. Multispectral image pansharpening based on the contourlet transform

    Energy Technology Data Exchange (ETDEWEB)

    Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

    2010-02-01

    Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

  3. PAN-SHARPENING APPROACHES BASED ON UNMIXING OF MULTISPECTRAL REMOTE SENSING IMAGERY

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    G. Palubinskas

    2016-06-01

    Full Text Available Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods ‘better’ satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale and spatial consistency for multispectral data (so-called Wald’s protocol first property or relationship between multispectral data in different resolution scales. Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property ‘better’ should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

  4. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields

    NARCIS (Netherlands)

    Hamzeh, Saied; Naseri, Abd Ali; Alavipanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-01-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image

  5. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

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    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  6. Observing lowermost tropospheric ozone pollution with a new multispectral synergic approach of IASI infrared and GOME-2 ultraviolet satellite measurements

    Science.gov (United States)

    Cuesta, Juan; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Coman, Adriana; Gaubert, Benjamin; Beekmann, Matthias; Liu, Xiong; Cai, Zhaonan; Von Clarmann, Thomas; Spurr, Robert; Flaud, Jean-Marie

    2014-05-01

    Tropospheric ozone is currently one of the air pollutants posing greatest threats to human health and ecosystems. Monitoring ozone pollution at the regional, continental and global scale is a crucial societal issue. Only spaceborne remote sensing is capable of observing tropospheric ozone at such scales. The spatio-temporal coverage of new satellite-based instruments, such as IASI or GOME-2, offer a great potential for monitoring air quality by synergism with regional chemistry-transport models, for both inter-validation and full data assimilation. However, current spaceborne observations using single-band either UV or IR measurements show limited sensitivity to ozone in the atmospheric boundary layer, which is the major concern for air quality. Very recently, we have developed an innovative multispectral approach, so-called IASI+GOME-2, which combines IASI and GOME-2 observations, respectively in the IR and UV. This unique multispectral approach has allowed the observation of ozone plumes in the lowermost troposphere (LMT, below 3 km of altitude) over Europe, for the first time from space. Our first analyses are focused on typical ozone pollution events during the summer of 2009 over Europe. During these events, LMT ozone plumes at different regions are produced photo-chemically in the boundary layer, transported upwards to the free troposphere and also downwards from the stratosphere. We have analysed them using IASI+GOME-2 observations, in comparison with single-band methods (IASI, GOME-2 and OMI). Only IASI+GOME-2 depicts ozone plumes located below 3 km of altitude (both over land and ocean). Indeed, the multispectral sensitivity in the LMT is greater by 40% and it peaks at 2 to 2.5 km of altitude over land, thus at least 0.8 to 1 km below that for all single-band methods. Over Europe during the summer of 2009, IASI+GOME-2 shows 1% mean bias and 21% precision for direct comparisons with ozonesondes and also good agreement with CHIMERE model simulations

  7. Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Clark, B.

    2010-07-01

    The Taita Hills in southeastern Kenya form the northernmost part of Africa's Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor (rho{sub s}). Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable (rho{sub s}) throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular (rho{sub s}) field measurements were taken and where horizontal visibility meteorological data concurrent with image

  8. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  9. 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...

  10. 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...

  11. 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...

  12. 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)...

  13. Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

    Science.gov (United States)

    Masini, Nicola; Lasaponara, Rosa

    2015-04-01

    The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series

  14. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    Science.gov (United States)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  15. Neural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenario

    Directory of Open Access Journals (Sweden)

    Matteo Picchiani

    2015-03-01

    Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event. 

  16. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.

    2000-01-03

    Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

  17. The development of a specialized processor for a space-based multispectral earth imager

    Science.gov (United States)

    Khedr, Mostafa E.

    2008-10-01

    This work was done in the Department of Computer Engineering, Lvov Polytechnic National University, Lvov, Ukraine, as a thesis entitled "Space Imager Computer System for Raw Video Data Processing" [1]. This work describes the synthesis and practical implementation of a specialized computer system for raw data control and processing onboard a satellite MultiSpectral earth imager. This computer system is intended for satellites with resolution in the range of one meter with 12-bit precession. The design is based mostly on general off-the-shelf components such as (FPGAs) plus custom designed software for interfacing with PC and test equipment. The designed system was successfully manufactured and now fully functioning in orbit.

  18. Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

    Science.gov (United States)

    Trimble, S. M.; Houser, C.; Brander, R.; Chirico, P.

    2015-12-01

    Rip currents are strong, narrow seaward flows of water that originate in the surf zones of many global beaches. They are related to hundreds of international drownings each year, but exact numbers are difficult to calculate due to logistical difficulties in obtaining accurate incident reports. Annual average rip current fatalities are estimated to be ~100, 53 and 21 in the United States (US), Costa Rica, and Australia respectively. Current warning systems (e.g. National Weather Service) do not account for fine resolution nearshore bathymetry because it is difficult to capture. The method shown here could provide frequent, high resolution maps of nearshore bathymetry at a scale required for improved rip prediction and warning. This study demonstrates a method for mapping bathymetry in the surf zone (20m deep and less), specifically within rip channels, because rips form at topographically low spots in the bathymetry as a result of feedback amongst waves, substrate, and antecedent bathymetry. The methods employ the Digital Globe WorldView2 (WV2) multispectral satellite and field measurements of depth to generate maps of the changing bathymetry at two embayed, rip-prone beaches: Playa Cocles, Puerto Viejo de Talamanca, Costa Rica, and Bondi Beach, Sydney, Australia. WV2 has a 1.1 day pass-over rate with 1.84m ground pixel resolution of 8 bands, including 'yellow' (585-625 nm) and 'coastal blue' (400-450 nm). The data is used to classify bottom type and to map depth to the return in multiple bands. The methodology is tested at each site for algorithm consistency between dates, and again for applicability between sites.

  19. Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectance

    Institute of Scientific and Technical Information of China (English)

    TAO Bangyi; PAN Delu; MAO Zhihua; SHEN Yuzhang; ZHU Qiankun; CHEN Jianyu

    2013-01-01

    Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang (Yangtze) River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguish-ing dinoflagellate blooms from diatom (Skeletonema costatum) blooms is desired. On the basis of measure-ments of remote sensing reflectance [Rrs(λ)] and inherent optical parameters, the potential of using a mul-tispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R1 =Rrs(560)/Rrs(532) and R2 =Rrs(708)/Rrs(665)], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense: (1) R1 >1.55 and R2 1.75 and R2 ?1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organic matter (CDOM) as well as changes in the backscattering ratio (bbp/bp) on the efficacy of this multispectral approach. Results indicate that the intensity and inherent op-tical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of Rrs(λ), especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of bbp/bp. Since a CDOM(440) in coastal areas of the ECS is typically lower than 1.0 m−1 in most situations, the presence of CDOM does not interfere with this discrimination, even as SCDOM varies from 0.01 to 0.026 nm−1. Despite all of these effects, the dis-crimination of P. donghaiense blooms from diatom blooms based on multispectral

  20. Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators.

    Science.gov (United States)

    Restaino, Rocco; Vivone, Gemine; Dalla Mura, Mauro; Chanussot, Jocelyn

    2016-04-20

    Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor.

  1. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    Science.gov (United States)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  2. Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

    Science.gov (United States)

    Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

    2018-03-01

    Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

  3. Cloud-based processing of multi-spectral imaging data

    Science.gov (United States)

    Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

    2017-03-01

    Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

  4. Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

    Science.gov (United States)

    Moody, Daniela Irina

    2018-04-17

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  5. Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Czapski Paweł

    2015-09-01

    Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

  6. Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

    Science.gov (United States)

    Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

    2014-02-01

    A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

  7. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  8. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  9. 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.

  10. Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei

    Science.gov (United States)

    Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo

    2017-08-01

    Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

  11. Multispectral thermal imaging

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W. [Los Alamos National Lab., NM (United States). Space and Remote Sensing Sciences Group; Garrett, A.; Pendergast, M.M. [Westinghouse Savannah River Corp., Aiken, SC (United States). Savannah River Technology Center; Kay, R.R. [Sandia National Lab., Albuquerque, NM (United States). Monitoring Systems and Technology Center

    1998-12-01

    Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

  12. Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

    Science.gov (United States)

    Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

    2017-05-01

    This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

  13. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  14. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Science.gov (United States)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  15. A methodology for calibration of hyperspectral and multispectral satellite data in coastal areas

    Science.gov (United States)

    Pennucci, Giuliana; Fargion, Giulietta; Alvarez, Alberto; Trees, Charles; Arnone, Robert

    2012-06-01

    The objective of this work is to determine the location(s) in any given oceanic area during different temporal periods where in situ sampling for Calibration/Validation (Cal/Val) provides the best capability to retrieve accurate radiometric and derived product data (lowest uncertainties). We present a method to merge satellite imagery with in situ measurements, to determine the best in situ sampling strategy suitable for satellite Cal/Val and to evaluate the present in situ locations through uncertainty indices. This analysis is required to determine if the present in situ sites are adequate for assessing uncertainty and where additional sites and ship programs should be located to improve Calibration/Validation (Cal/Val) procedures. Our methodology uses satellite acquisitions to build a covariance matrix encoding the spatial-temporal variability of the area of interest. The covariance matrix is used in a Bayesian framework to merge satellite and in situ data providing a product with lower uncertainty. The best in situ location for Cal/Val is then identified by using a design principle (A-optimum design) that looks for minimizing the estimated variance of the merged products. Satellite products investigated in this study include Ocean Color water leaving radiance, chlorophyll, and inherent and apparent optical properties (retrieved from MODIS and VIIRS). In situ measurements are obtained from systems operated on fixed deployment platforms (e.g., sites of the Ocean Color component of the AErosol RObotic NETwork- AERONET-OC), moorings (e.g, Marine Optical Buoy-MOBY), ships or autonomous vehicles (such as Autonomous Underwater Vehicles and/or Gliders).

  16. Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

    Science.gov (United States)

    García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

    2018-04-01

    Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

  17. PROCEDURES FOR ACCURATE PRODUCTION OF COLOR IMAGES FROM SATELLITE OR AIRCRAFT MULTISPECTRAL DIGITAL DATA.

    Science.gov (United States)

    Duval, Joseph S.

    1985-01-01

    Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.

  18. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    International Nuclear Information System (INIS)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-01-01

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  19. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    Energy Technology Data Exchange (ETDEWEB)

    Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

    2016-07-15

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  20. 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

  1. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  2. 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.

  3. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Science.gov (United States)

    Yang, Jianping; Li, Jun

    2018-02-01

    Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

  4. Determining the best phenological state for accurate mapping of Phragmites australis in wetlands using time series multispectral satellite data

    Science.gov (United States)

    Rupasinghe, P. A.; Markle, C. E.; Marcaccio, J. V.; Chow-Fraser, P.

    2017-12-01

    Phragmites australis (European common reed), is a relatively recent invader of wetlands and beaches in Ontario. It can establish large homogenous stands within wetlands and disperse widely throughout the landscape by wind and vehicular traffic. A first step in managing this invasive species includes accurate mapping and quantification of its distribution. This is challenging because Phragimtes is distributed in a large spatial extent, which makes the mapping more costly and time consuming. Here, we used freely available multispectral satellite images taken monthly (cloud free images as available) for the calendar year to determine the optimum phenological state of Phragmites that would allow it to be accurately identified using remote sensing data. We analyzed time series, Landsat-8 OLI and Sentinel-2 images for Big Creek Wildlife Area, ON using image classification (Support Vector Machines), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). We used field sampling data and high resolution image collected using Unmanned Aerial Vehicle (UAV; 8 cm spatial resolution) as training data and for the validation of the classified images. The accuracy for all land cover classes and for Phragmites alone were low at both the start and end of the calendar year, but reached overall accuracy >85% by mid to late summer. The highest classification accuracies for Landsat-8 OLI were associated with late July and early August imagery. We observed similar trends using the Sentinel-2 images, with higher overall accuracy for all land cover classes and for Phragmites alone from late July to late September. During this period, we found the greatest difference between Phragmites and Typha, commonly confused classes, with respect to near-infrared and shortwave infrared reflectance. Therefore, the unique spectral signature of Phragmites can be attributed to both the level of greenness and factors related to water content in the leaves during late

  5. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  6. Self-training-based spectral image reconstruction for art paintings with multispectral imaging.

    Science.gov (United States)

    Xu, Peng; Xu, Haisong; Diao, Changyu; Ye, Zhengnan

    2017-10-20

    A self-training-based spectral reflectance recovery method was developed to accurately reconstruct the spectral images of art paintings with multispectral imaging. By partitioning the multispectral images with the k-means clustering algorithm, the training samples are directly extracted from the art painting itself to restrain the deterioration of spectral estimation caused by the material inconsistency between the training samples and the art painting. Coordinate paper is used to locate the extracted training samples. The spectral reflectances of the extracted training samples are acquired indirectly with a spectroradiometer, and the circle Hough transform is adopted to detect the circle measuring area of the spectroradiometer. Through simulation and a practical experiment, the implementation of the proposed method is explained in detail, and it is verified to have better reflectance recovery performance than that using the commercial target and is comparable to the approach using a painted color target.

  7. Satellite-based laser windsounder

    International Nuclear Information System (INIS)

    Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R.

    1997-01-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

  8. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  9. [A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

    Science.gov (United States)

    Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

    2015-07-01

    Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

  10. 14 CFR 141.91 - Satellite bases.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor is...

  11. Detecting weather radar clutter using satellite-based nowcasting products

    DEFF Research Database (Denmark)

    Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

    2006-01-01

    This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

  12. Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

    Science.gov (United States)

    Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

    2017-04-01

    This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

  13. Rare earth-based low-index films for IR and multispectral thin film solutions

    Science.gov (United States)

    Stolze, Markus; Neff, Joe; Waibel, Friedrich

    2017-10-01

    Non-thoriated rare-earth fluoride based coating solutions involving DyF3 and YbF3 based films as well as non-wetting fluorohydrocarbon cap layers on such films, have been deposited, analyzed and partly optimized. Intermediate results for DyF3 based films from ion assisted e-gun deposition with O2 and N2 alone and as base for the non-wetting to-player as well as for YbF3 starting material with or without admixtures of CaF2 are discussed for low-loss LWIR and multispectral solutions.

  14. Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

    Science.gov (United States)

    Xiao, P.; Kelly, M.; Guo, Q.

    2014-12-01

    This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

  15. Multispectral iris recognition based on group selection and game theory

    Science.gov (United States)

    Ahmad, Foysal; Roy, Kaushik

    2017-05-01

    A commercially available iris recognition system uses only a narrow band of the near infrared spectrum (700-900 nm) while iris images captured in the wide range of 405 nm to 1550 nm offer potential benefits to enhance recognition performance of an iris biometric system. The novelty of this research is that a group selection algorithm based on coalition game theory is explored to select the best patch subsets. In this algorithm, patches are divided into several groups based on their maximum contribution in different groups. Shapley values are used to evaluate the contribution of patches in different groups. Results show that this group selection based iris recognition

  16. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  17. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal [Albuquerque, NM

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  18. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    Science.gov (United States)

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  19. Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

    Science.gov (United States)

    Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

    2017-07-01

    A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770-810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.

  20. Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

    Science.gov (United States)

    Moody, Daniela; Wohlberg, Brendt

    2018-01-02

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  1. [Multispectral Radiation Algorithm Based on Emissivity Model Constraints for True Temperature Measurement].

    Science.gov (United States)

    Liang, Mei; Sun, Xiao-gang; Luan, Mei-sheng

    2015-10-01

    Temperature measurement is one of the important factors for ensuring product quality, reducing production cost and ensuring experiment safety in industrial manufacture and scientific experiment. Radiation thermometry is the main method for non-contact temperature measurement. The second measurement (SM) method is one of the common methods in the multispectral radiation thermometry. However, the SM method cannot be applied to on-line data processing. To solve the problems, a rapid inversion method for multispectral radiation true temperature measurement is proposed and constraint conditions of emissivity model are introduced based on the multispectral brightness temperature model. For non-blackbody, it can be drawn that emissivity is an increasing function in the interval if the brightness temperature is an increasing function or a constant function in a range and emissivity satisfies an inequality of emissivity and wavelength in that interval if the brightness temperature is a decreasing function in a range, according to the relationship of brightness temperatures at different wavelengths. The construction of emissivity assumption values is reduced from multiclass to one class and avoiding the unnecessary emissivity construction with emissivity model constraint conditions on the basis of brightness temperature information. Simulation experiments and comparisons for two different temperature points are carried out based on five measured targets with five representative variation trends of real emissivity. decreasing monotonically, increasing monotonically, first decreasing with wavelength and then increasing, first increasing and then decreasing and fluctuating with wavelength randomly. The simulation results show that compared with the SM method, for the same target under the same initial temperature and emissivity search range, the processing speed of the proposed algorithm is increased by 19.16%-43.45% with the same precision and the same calculation results.

  2. Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

    Science.gov (United States)

    Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

    2012-06-01

    The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

  3. 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.

  4. Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

    Science.gov (United States)

    Butera, M. K.

    1979-01-01

    The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.

  5. Operational Satellite-based Surface Oil Analyses (Invited)

    Science.gov (United States)

    Streett, D.; Warren, C.

    2010-12-01

    During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as

  6. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, 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....

  7. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    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....

  8. [Responses of vegetation changes to climatic variations in Panxi area based on the MODIS multispectral data].

    Science.gov (United States)

    Shao, Huai-Yong; Wu, Jin-Hui; Liu, Meng; Yang, Wu-Nian

    2014-01-01

    It is an important research area to quantitatively studying the relationship between global climatic change and vegetation change based on the remote sensing technology. Panxi area is the ecological barrier of the upper reaches of the Yangtze River, and it is essential for the stability of the ecological environment of Sichuan as well as that of the whole China. The present article analyzes the vegetation change in 2001-2008 and the relationship between vegetation change and climatic variations of Panxi area, based on MODIS multispectral data and meteorological data. The results indicate that NDVI is positively correlated with temperature and precipitation. The precipitation is the major factor that affects the change of vegetation in the Panxi region and the trend of NDVI is similar with autumn precipitation; while at the same time the influence of climate has a one-month-time-lag.

  9. Earth-based and Galileo SSI multispectral observations of eastern mare serenitatis and the Apollo 17 landing site

    Science.gov (United States)

    Hiesinger, H.; Jaumann, R.; Neukum, G.

    1993-01-01

    Both the Apollo 17 and the Mare Serenitatis region were observed by Galileo during its fly-by in December 1992. We used earth-based multispectral data to define mare units which then can be compared with the results of the Galileo SSI data evaluation.

  10. Use of multispectral satellite remote sensing to assess mixing of suspended sediment downstream of large river confluences

    Science.gov (United States)

    Umar, M.; Rhoads, Bruce L.; Greenberg, Jonathan A.

    2018-01-01

    Although past work has noted that contrasts in turbidity often are detectable on remotely sensed images of rivers downstream from confluences, no systematic methodology has been developed for assessing mixing over distance of confluent flows with differing surficial suspended sediment concentrations (SSSC). In contrast to field measurements of mixing below confluences, satellite remote-sensing can provide detailed information on spatial distributions of SSSC over long distances. This paper presents a methodology that uses remote-sensing data to estimate spatial patterns of SSSC downstream of confluences along large rivers and to determine changes in the amount of mixing over distance from confluences. The method develops a calibrated Random Forest (RF) model by relating training SSSC data from river gaging stations to derived spectral indices for the pixels corresponding to gaging-station locations. The calibrated model is then used to predict SSSC values for every river pixel in a remotely sensed image, which provides the basis for mapping of spatial variability in SSSCs along the river. The pixel data are used to estimate average surficial values of SSSC at cross sections spaced uniformly along the river. Based on the cross-section data, a mixing metric is computed for each cross section. The spatial pattern of change in this metric over distance can be used to define rates and length scales of surficial mixing of suspended sediment downstream of a confluence. This type of information is useful for exploring the potential influence of various controlling factors on mixing downstream of confluences, for evaluating how mixing in a river system varies over time and space, and for determining how these variations influence water quality and ecological conditions along the river.

  11. Water Quality Determination of Küçükçekmece Lake, Turkey by Using Multispectral Satellite Data

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan

    2009-01-01

    Full Text Available This study focuses on the analysis of the Landsat-5 TM + SPOT-Pan (1992, IRS-1C/D LISS + Pan (2000, and Landsat-5 TM (2006 satellite images that reflect the drastic land use/land cover changes in the Küçükçekmece Lake region, Istanbul. Landsat-5 TM satellite data dated 2006 was used for mapping water quality. A multiple regression analysis was carried out between the unitless planetary reflectance values derived from the satellite image and in situ water quality parameters chlorophyll a, total phosphorus, total nitrogen, turbidity, and biological and chemical oxygen demand measured at a number of stations homogenously distributed over the lake surface. The results of this study provided valuable information to local administrators on the water quality of Küçükçekmece Lake, which is a large water resource of the Istanbul Metropolitan Area. Results also show that such a methodology structured by use of reflectance values provided from satellite imagery, in situ water quality measurements, and basin land use/land cover characteristics obtained from images can serve as a powerful and rapid monitoring tool for the drinking water basins that suffer from rapid urbanization and pollution, all around the world.

  12. 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

  13. Multispectral imaging for biometrics

    Science.gov (United States)

    Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

    2005-03-01

    Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

  14. Predicting Electron Population Characteristics in 2-D Using Multispectral Ground-Based Imaging

    Science.gov (United States)

    Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Jahn, Jorg-Micha

    2018-01-01

    Ground-based imaging and in situ sounding rocket data are compared to electron transport modeling for an active inverted-V type auroral event. The Ground-to-Rocket Electrodynamics-Electrons Correlative Experiment (GREECE) mission successfully launched from Poker Flat, Alaska, on 3 March 2014 at 11:09:50 UT and reached an apogee of approximately 335 km over the aurora. Multiple ground-based electron-multiplying charge-coupled device (EMCCD) imagers were positioned at Venetie, Alaska, and aimed toward magnetic zenith. The imagers observed the intensity of different auroral emission lines (427.8, 557.7, and 844.6 nm) at the magnetic foot point of the rocket payload. Emission line intensity data are correlated with electron characteristics measured by the GREECE onboard electron spectrometer. A modified version of the GLobal airglOW (GLOW) model is used to estimate precipitating electron characteristics based on optical emissions. GLOW predicted the electron population characteristics with 20% error given the observed spectral intensities within 10° of magnetic zenith. Predictions are within 30% of the actual values within 20° of magnetic zenith for inverted-V-type aurora. Therefore, it is argued that this technique can be used, at least in certain types of aurora, such as the inverted-V type presented here, to derive 2-D maps of electron characteristics. These can then be used to further derive 2-D maps of ionospheric parameters as a function of time, based solely on multispectral optical imaging data.

  15. Leo satellite-based telecommunication network concepts

    Science.gov (United States)

    Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

    1991-01-01

    Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

  16. Multispectral embedding-based deep neural network for three-dimensional human pose recovery

    Science.gov (United States)

    Yu, Jialin; Sun, Jifeng

    2018-01-01

    Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

  17. A Space Based Solar Power Satellite System

    Science.gov (United States)

    Engel, J. M.; Polling, D.; Ustamujic, F.; Yaldiz, R.; et al.

    2002-01-01

    (SPoTS) supplying other satellites with energy. SPoTS is due to be commercially viable and operative in 2020. of Technology designed the SPoTS during a full-time design period of six weeks as a third year final project. The team, organized according to the principles of systems engineering, first conducted a literature study on space wireless energy transfer to select the most suitable candidates for use on the SPoTS. After that, several different system concepts have been generated and evaluated, the most promising concept being worked out in greater detail. km altitude. Each SPoTS satellite has a 50m diameter inflatable solar collector that focuses all received sunlight. Then, the received sunlight is further redirected by means of four pointing mirrors toward four individual customer satellites. A market-analysis study showed, that providing power to geo-stationary communication satellites during their eclipse would be most beneficial. At arrival at geo-stationary orbit, the focused beam has expended to such an extent that its density equals one solar flux. This means that customer satellites can continue to use their regular solar arrays during their eclipse for power generation, resulting in a satellite battery mass reduction. the customer satellites in geo-stationary orbit, the transmitted energy beams needs to be pointed with very high accuracy. Computations showed that for this degree of accuracy, sensors are needed, which are not mainstream nowadays. Therefore further research must be conducted in this area in order to make these high-accuracy-pointing systems commercially attractive for use on the SPoTS satellites around 2020. Total 20-year system lifetime cost for 18 SPoT satellites are estimated at approximately USD 6 billion [FY2001]. In order to compete with traditional battery-based satellite power systems or possible ground based wireless power transfer systems the price per kWh for the customer must be significantly lower than the present one

  18. Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence.

    Science.gov (United States)

    Li, Sui-Xian

    2018-05-07

    Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI). However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ₂ norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

  19. Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence

    Directory of Open Access Journals (Sweden)

    Sui-Xian Li

    2018-05-01

    Full Text Available Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI. However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ2 norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

  20. An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chenghai Yang

    2014-06-01

    Full Text Available This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

  1. Multispectral photoacoustic characterization of ICG and porcine blood using an LED-based photoacoustic imaging system

    Science.gov (United States)

    Shigeta, Yusuke; Sato, Naoto; Kuniyil Ajith Singh, Mithun; Agano, Toshitaka

    2018-02-01

    Photoacoustic imaging is a hybrid biomedical imaging modality that has emerged over the last decade. In photoacoustic imaging, pulsed-light absorbed by the target emits ultrasound that can be detected using a conventional ultrasound array. This ultrasound data can be used to reconstruct the location and spatial details of the intrinsic/extrinsic light absorbers in the tissue. Recently we reported on the development of a multi-wavelength high frame-rate LED-based photoacoustic/ultrasound imaging system (AcousticX). In this work, we photoacoustically characterize the absorption spectrum of ICG and porcine blood using LED arrays with multiple wavelengths (405, 420, 470, 520, 620, 660, 690, 750, 810, 850, 925, 980 nm). Measurements were performed in a simple reflection mode configuration in which LED arrays where fixed on both sides of the linear array ultrasound probe. Phantom used consisted of micro-test tubes filled with ICG and porcine blood, which were placed in a tank filled with water. The photoacoustic spectrum obtained from our measurements matches well with the reference absorption spectrum. These results demonstrate the potential capability of our system in performing clinical/pre-clinical multispectral photoacoustic imaging.

  2. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Directory of Open Access Journals (Sweden)

    Liang Lu

    2018-03-01

    Full Text Available Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

  3. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Science.gov (United States)

    Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

    2018-01-01

    Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

  4. Simulation-based investigation of the generality of Lyzenga's multispectral bathymetry formula in Case-1 coral reef water

    Science.gov (United States)

    Manessa, Masita Dwi Mandini; Kanno, Ariyo; Sagawa, Tatsuyuki; Sekine, Masahiko; Nurdin, Nurjannah

    2018-01-01

    Lyzenga's multispectral bathymetry formula has attracted considerable interest due to its simplicity. However, there has been little discussion of the effect that variation in optical conditions and bottom types-which commonly appears in coral reef environments-has on this formula's results. The present paper evaluates Lyzenga's multispectral bathymetry formula for a variety of optical conditions and bottom types. A noiseless dataset of above-water remote sensing reflectance from WorldView-2 images over Case-1 shallow coral reef water is simulated using a radiative transfer model. The simulation-based assessment shows that Lyzenga's formula performs robustly, with adequate generality and good accuracy, under a range of conditions. As expected, the influence of bottom type on depth estimation accuracy is far greater than the influence of other optical parameters, i.e., chlorophyll-a concentration and solar zenith angle. Further, based on the simulation dataset, Lyzenga's formula estimates depth when the bottom type is unknown almost as accurately as when the bottom type is known. This study provides a better understanding of Lyzenga's multispectral bathymetry formula under various optical conditions and bottom types.

  5. Optical burst switching based satellite backbone network

    Science.gov (United States)

    Li, Tingting; Guo, Hongxiang; Wang, Cen; Wu, Jian

    2018-02-01

    We propose a novel time slot based optical burst switching (OBS) architecture for GEO/LEO based satellite backbone network. This architecture can provide high speed data transmission rate and high switching capacity . Furthermore, we design the control plane of this optical satellite backbone network. The software defined network (SDN) and network slice (NS) technologies are introduced. Under the properly designed control mechanism, this backbone network is flexible to support various services with diverse transmission requirements. Additionally, the LEO access and handoff management in this network is also discussed.

  6. Landscape functioning assessment using Landsat multispectral remote sensing data

    OpenAIRE

    Hesslerová, Petra

    2009-01-01

    The main aim of the dissertation thesis was to develop method, based on the use of multispectral satellite data and the theory of dissipation, allowing the analysis of landscape functioning. The theoretical basis is Prigogine's theory of dissipation and self-organization of structures in which energy dissipation is seen as the transformation of solar energy to other forms of energy. In this process the essential role play water availability and vegetation, which is able to bind solar radiatio...

  7. SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    A. Sharma

    2015-03-01

    Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

  8. Multispectral imaging system based on laser-induced fluorescence for security applications

    Science.gov (United States)

    Caneve, L.; Colao, F.; Del Franco, M.; Palucci, A.; Pistilli, M.; Spizzichino, V.

    2016-10-01

    The development of portable sensors for fast screening of crime scenes is required to reduce the number of evidences useful to be collected, optimizing time and resources. Laser based spectroscopic techniques are good candidates to this scope due to their capability to operate in field, in remote and rapid way. In this work, the prototype of a multispectral imaging LIF (Laser Induced Fluorescence) system able to detect evidence of different materials on large very crowded and confusing areas at distances up to some tens of meters will be presented. Data collected as both 2D fluorescence images and LIF spectra are suitable to the identification and the localization of the materials of interest. A reduced scan time, preserving at the same time the accuracy of the results, has been taken into account as a main requirement in the system design. An excimer laser with high energy and repetition rate coupled to a gated high sensitivity ICCD assures very good performances for this purpose. Effort has been devoted to speed up the data processing. The system has been tested in outdoor and indoor real scenarios and some results will be reported. Evidence of the plastics polypropylene (PP) and polyethilene (PE) and polyester have been identified and their localization on the examined scenes has been highlighted through the data processing. By suitable emission bands, the instrument can be used for the rapid detection of other material classes (i.e. textiles, woods, varnishes). The activities of this work have been supported by the EU-FP7 FORLAB project (Forensic Laboratory for in-situ evidence analysis in a post blast scenario).

  9. HYDROPT: A fast and flexible method to retrieve chlorophyll-a from multispectral satellite observations of optically complex coastal waters

    NARCIS (Netherlands)

    van der Woerd, H.J.; Pasterkamp, R.

    2008-01-01

    We present a generic innovative algorithm for remote sensing of coastal waters that can deal with a large range of concentrations of chlorophyll-a, SPM and CDOM and their inherent optical properties. The algorithm is based on the exact solutions of the HYDROLIGHT numerical radiative transfer model

  10. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

    2011-01-01

    For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

  11. System for critical infrastructure security based on multispectral observation-detection module

    Science.gov (United States)

    Trzaskawka, Piotr; Kastek, Mariusz; Życzkowski, Marek; Dulski, Rafał; Szustakowski, Mieczysław; Ciurapiński, Wiesław; Bareła, Jarosław

    2013-10-01

    Recent terrorist attacks and possibilities of such actions in future have forced to develop security systems for critical infrastructures that embrace sensors technologies and technical organization of systems. The used till now perimeter protection of stationary objects, based on construction of a ring with two-zone fencing, visual cameras with illumination are efficiently displaced by the systems of the multisensor technology that consists of: visible technology - day/night cameras registering optical contrast of a scene, thermal technology - cheap bolometric cameras recording thermal contrast of a scene and active ground radars - microwave and millimetre wavelengths that record and detect reflected radiation. Merging of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. Important technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as target identification and alerting. Based on "plug and play" architecture, this system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provide high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering. The paper presents

  12. Satellite Contamination and Materials Outgassing Knowledge base

    Science.gov (United States)

    Minor, Jody L.; Kauffman, William J. (Technical Monitor)

    2001-01-01

    Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

  13. Ground test of satellite constellation based quantum communication

    OpenAIRE

    Liao, Sheng-Kai; Yong, Hai-Lin; Liu, Chang; Shentu, Guo-Liang; Li, Dong-Dong; Lin, Jin; Dai, Hui; Zhao, Shuang-Qiang; Li, Bo; Guan, Jian-Yu; Chen, Wei; Gong, Yun-Hong; Li, Yang; Lin, Ze-Hong; Pan, Ge-Sheng

    2016-01-01

    Satellite based quantum communication has been proven as a feasible way to achieve global scale quantum communication network. Very recently, a low-Earth-orbit (LEO) satellite has been launched for this purpose. However, with a single satellite, it takes an inefficient 3-day period to provide the worldwide connectivity. On the other hand, similar to how the Iridium system functions in classic communication, satellite constellation (SC) composed of many quantum satellites, could provide global...

  14. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  15. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  16. Satellite-based Tropical Cyclone Monitoring Capabilities

    Science.gov (United States)

    Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

    2012-12-01

    Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

  17. Generating Multispectral VIIRS Imagery in Near Real-Time for Use by the National Weather Service in Alaska

    Science.gov (United States)

    Broderson, D.; Dierking, C.; Stevens, E.; Heinrichs, T. A.; Cherry, J. E.

    2016-12-01

    The Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks (UAF) uses two direct broadcast antennas to receive data from a number of polar-orbiting weather satellites, including the Suomi National Polar Partnership (S-NPP) satellite. GINA uses data from S-NPP's Visible Infrared Imaging Radiometer Suite (VIIRS) to generate a variety of multispectral imagery products developed with the needs of the National Weather Service operational meteorologist in mind. Multispectral products have two primary advantages over single-channel products. First, they can more clearly highlight some terrain and meteorological features which are less evident in the component single channels. Second, multispectral present the information from several bands through just one image, thereby sparing the meteorologist unnecessary time interrogating the component single bands individually. With 22 channels available from the VIIRS instrument, the number of possible multispectral products is theoretically huge. A small number of products will be emphasized in this presentation, with the products chosen based on their proven utility in the forecasting environment. Multispectral products can be generated upstream of the end user or by the end user at their own workstation. The advantage and disadvantages of both approaches will be outlined. Lastly, the technique of improving the appearance of multispectral imagery by correcting for atmospheric reflectance at the shorter wavelengths will be described.

  18. Satellite based Ocean Forecasting, the SOFT project

    Science.gov (United States)

    Stemmann, L.; Tintoré, J.; Moneris, S.

    2003-04-01

    The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

  19. Multispectral data compression through transform coding and block quantization

    Science.gov (United States)

    Ready, P. J.; Wintz, P. A.

    1972-01-01

    Transform coding and block quantization techniques are applied to multispectral aircraft scanner data, and digitized satellite imagery. The multispectral source is defined and an appropriate mathematical model proposed. The Karhunen-Loeve, Fourier, and Hadamard encoders are considered and are compared to the rate distortion function for the equivalent Gaussian source and to the performance of the single sample PCM encoder.

  20. Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

    Science.gov (United States)

    Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

    2017-07-01

    Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R 2 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

  1. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

    2009-01-01

    -based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...

  2. Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

    Science.gov (United States)

    Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

    2018-03-01

    Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

  3. Using satellite-based measurements to explore ...

    Science.gov (United States)

    New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently spatially averaged) measurements of atmospheric conditions to diagnose the occurrence of NPF and NPF characteristics. We demonstrate the potential for using satellite-measurements of insolation (UV), trace gas concentrations (sulfur dioxide (SO2), nitrogen dioxide (NO2), ammonia (NH3), formaldehyde (HCHO), ozone (O3)), aerosol optical properties (aerosol optical depth (AOD), Ångström exponent (AE)), and a proxy of biogenic volatile organic compound emissions (leaf area index (LAI), temperature (T)) as predictors for NPF characteristics: formation rates, growth rates, survival probabilities, and ultrafine particle (UFP) concentrations at five locations across North America. NPF at all sites is most frequent in spring, exhibits a one-day autocorrelation, and is associated with low condensational sink (AOD×AE) and HCHO concentrations, and high UV. However, there are important site-to-site variations in NPF frequency and characteristics, and in which of the predictor variables (particularly gas concentrations) significantly contribute to the explanatory power of regression models built to predict those characteristics. This finding may provide a partial explanation for the reported spatia

  4. Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

    Science.gov (United States)

    Heleno, S.; Matias, M.; Pina, P.; Sousa, A. J.

    2015-09-01

    A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

  5. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    Science.gov (United States)

    Heleno, Sandra; Matias, Magda; Pina, Pedro; Sousa, António Jorge

    2016-04-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

  6. A satellite-based global landslide model

    Directory of Open Access Journals (Sweden)

    A. Farahmand

    2013-05-01

    Full Text Available Landslides are devastating phenomena that cause huge damage around the world. This paper presents a quasi-global landslide model derived using satellite precipitation data, land-use land cover maps, and 250 m topography information. This suggested landslide model is based on the Support Vector Machines (SVM, a machine learning algorithm. The National Aeronautics and Space Administration (NASA Goddard Space Flight Center (GSFC landslide inventory data is used as observations and reference data. In all, 70% of the data are used for model development and training, whereas 30% are used for validation and verification. The results of 100 random subsamples of available landslide observations revealed that the suggested landslide model can predict historical landslides reliably. The average error of 100 iterations of landslide prediction is estimated to be approximately 7%, while approximately 2% false landslide events are observed.

  7. SAW based systems for mobile communications satellites

    Science.gov (United States)

    Peach, R. C.; Miller, N.; Lee, M.

    1993-01-01

    Modern mobile communications satellites, such as INMARSAT 3, EMS, and ARTEMIS, use advanced onboard processing to make efficient use of the available L-band spectrum. In all of these cases, high performance surface acoustic wave (SAW) devices are used. SAW filters can provide high selectivity (100-200 kHz transition widths), combined with flat amplitude and linear phase characteristics; their simple construction and radiation hardness also makes them especially suitable for space applications. An overview of the architectures used in the above systems, describing the technologies employed, and the use of bandwidth switchable SAW filtering (BSSF) is given. The tradeoffs to be considered when specifying a SAW based system are analyzed, using both theoretical and experimental data. Empirical rules for estimating SAW filter performance are given. Achievable performance is illustrated using data from the INMARSAT 3 engineering model (EM) processors.

  8. Multispectral imaging based on a Smartphone with an external C-MOS camera for detection of seborrheic dermatitis on the scalp

    Science.gov (United States)

    Kim, Manjae; Kim, Sewoong; Hwang, Minjoo; Kim, Jihun; Je, Minkyu; Jang, Jae Eun; Lee, Dong Hun; Hwang, Jae Youn

    2017-02-01

    To date, the incident rates of various skin diseases have increased due to hereditary and environmental factors including stress, irregular diet, pollution, etc. Among these skin diseases, seborrheic dermatitis and psoriasis are a chronic/relapsing dermatitis involving infection and temporary alopecia. However, they typically exhibit similar symptoms, thus resulting in difficulty in discrimination between them. To prevent their associated complications and appropriate treatments for them, it is crucial to discriminate between seborrheic dermatitis and psoriasis with high specificity and sensitivity and further continuously/quantitatively to monitor the skin lesions during their treatment at other locations besides a hospital. Thus, we here demonstrate a mobile multispectral imaging system connected to a smartphone for selfdiagnosis of seborrheic dermatitis and further discrimination between seborrheic dermatitis and psoriasis on the scalp, which is the more challenging case. Using the system developed, multispectral imaging and analysis of seborrheic dermatitis and psoriasis on the scalp was carried out. It was here found that the spectral signatures of seborrheic dermatitis and psoriasis were discernable and thus seborrheic dermatitis on the scalp could be distinguished from psoriasis by using the system. In particular, the smartphone-based multispectral imaging and analysis moreover offered better discrimination between seborrheic dermatitis and psoriasis than the RGB imaging and analysis. These results suggested that the multispectral imaging system based on a smartphone has the potential for self-diagnosis of seborrheic dermatitis with high portability and specificity.

  9. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  10. Computational multispectral video imaging [Invited].

    Science.gov (United States)

    Wang, Peng; Menon, Rajesh

    2018-01-01

    Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

  11. Satellite Based Cropland Carbon Monitoring System

    Science.gov (United States)

    Bandaru, V.; Jones, C. D.; Sedano, F.; Sahajpal, R.; Jin, H.; Skakun, S.; Pnvr, K.; Kommareddy, A.; Reddy, A.; Hurtt, G. C.; Izaurralde, R. C.

    2017-12-01

    Agricultural croplands act as both sources and sinks of atmospheric carbon dioxide (CO2); absorbing CO2 through photosynthesis, releasing CO2 through autotrophic and heterotrophic respiration, and sequestering CO2 in vegetation and soils. Part of the carbon captured in vegetation can be transported and utilized elsewhere through the activities of food, fiber, and energy production. As well, a portion of carbon in soils can be exported somewhere else by wind, water, and tillage erosion. Thus, it is important to quantify how land use and land management practices affect the net carbon balance of croplands. To monitor the impacts of various agricultural activities on carbon balance and to develop management strategies to make croplands to behave as net carbon sinks, it is of paramount importance to develop consistent and high resolution cropland carbon flux estimates. Croplands are typically characterized by fine scale heterogeneity; therefore, for accurate carbon flux estimates, it is necessary to account for the contribution of each crop type and their spatial distribution. As part of NASA CMS funded project, a satellite based Cropland Carbon Monitoring System (CCMS) was developed to estimate spatially resolved crop specific carbon fluxes over large regions. This modeling framework uses remote sensing version of Environmental Policy Integrated Climate Model and satellite derived crop parameters (e.g. leaf area index (LAI)) to determine vertical and lateral carbon fluxes. The crop type LAI product was developed based on the inversion of PRO-SAIL radiative transfer model and downscaled MODIS reflectance. The crop emergence and harvesting dates were estimated based on MODIS NDVI and crop growing degree days. To evaluate the performance of CCMS framework, it was implemented over croplands of Nebraska, and estimated carbon fluxes for major crops (i.e. corn, soybean, winter wheat, grain sorghum, alfalfa) grown in 2015. Key findings of the CCMS framework will be presented

  12. Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

    Science.gov (United States)

    Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

    2017-11-27

    We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

  13. Quantitative mouse brain phenotyping based on single and multispectral MR protocols

    Science.gov (United States)

    Badea, Alexandra; Gewalt, Sally; Avants, Brian B.; Cook, James J.; Johnson, G. Allan

    2013-01-01

    Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrasts yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov random field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain. PMID:22836174

  14. New perspectives for satellite-based archaeological research in the ancient territory of Hierapolis (Turkey

    Directory of Open Access Journals (Sweden)

    R. Lasaponara

    2008-11-01

    Full Text Available This paper deals with the use of satellite QuickBird images to find traces of past human activity in the ancient territory of Hierapolis (Turkey. This is one of the most important archaeological sites in Turkey, and in 1988 it was inscribed in the UNESCO World Heritage list. Although over the years the archaeological site of Hierapolis has been excavated, restored and well documented, up to now the territory around the ancient urban area is still largely unknown. The current research project, still in progress, aims to search the area neighbouring Hierapolis believed to have been under the control of the city for a long time and, therefore, expected to be very rich in archaeological evidence. In order to investigate a large area around the ancient Hierapolis and discover potential archaeological remains, QuickBird images were adopted.

    Results from satellite-based analysis allowed us to find several unknown rural settlements dating back to early Imperial Roman and the Byzantine age. Two significant test sites were focused on in this paper in order to characterize the different spectral responses observed for different types of archaeological features (shadow and soil marks. Principal Component Analysis and spectral indices were computed to enhance archaeological marks and make identification easier. The capability of the QuickBird data set (panchromatic, multispectral channel, PCA and spectral indices in searching for archaeological marks was assessed in a quantitative way by using a specific indicator.

  15. Satellite-based monitoring of cotton evapotranspiration

    Science.gov (United States)

    Dalezios, Nicolas; Dercas, Nicholas; Tarquis, Ana Maria

    2016-04-01

    Water for agricultural use represents the largest share among all water uses. Vulnerability in agriculture is influenced, among others, by extended periods of water shortage in regions exposed to droughts. Advanced technological approaches and methodologies, including remote sensing, are increasingly incorporated for the assessment of irrigation water requirements. In this paper, remote sensing techniques are integrated for the estimation and monitoring of crop evapotranspiration ETc. The study area is Thessaly central Greece, which is a drought-prone agricultural region. Cotton fields in a small agricultural sub-catchment in Thessaly are used as an experimental site. Daily meteorological data and weekly field data are recorded throughout seven (2004-2010) growing seasons for the computation of reference evapotranspiration ETo, crop coefficient Kc and cotton crop ETc based on conventional data. Satellite data (Landsat TM) for the corresponding period are processed to estimate cotton crop coefficient Kc and cotton crop ETc and delineate its spatiotemporal variability. The methodology is applied for monitoring Kc and ETc during the growing season in the selected sub-catchment. Several error statistics are used showing very good agreement with ground-truth observations.

  16. 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...

  17. 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...

  18. 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...

  19. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  20. 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...

  1. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral 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 — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  2. 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...

  3. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, 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....

  4. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  5. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  6. 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....

  7. Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

    Science.gov (United States)

    Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

    2015-03-01

    Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

  8. An automated fog monitoring system for the Indo-Gangetic Plains based on satellite measurements

    Science.gov (United States)

    Patil, Dinesh; Chourey, Reema; Rizvi, Sarwar; Singh, Manoj; Gautam, Ritesh

    2016-05-01

    Fog is a meteorological phenomenon that causes reduction in regional visibility and affects air quality, thus leading to various societal and economic implications, especially disrupting air and rail transportation. The persistent and widespread winter fog impacts the entire the Indo-Gangetic Plains (IGP), as frequently observed in satellite imagery. The IGP is a densely populated region in south Asia, inhabiting about 1/6th of the world's population, with a strong upward pollution trend. In this study, we have used multi-spectral radiances and aerosol/cloud retrievals from Terra/Aqua MODIS data for developing an automated web-based fog monitoring system over the IGP. Using our previous and existing methodologies, and ongoing algorithm development for the detection of fog and retrieval of associated microphysical properties (e.g. fog droplet effective radius), we characterize the widespread fog detection during both daytime and nighttime. Specifically, for the night time fog detection, the algorithm employs a satellite-based bi-spectral brightness temperature difference technique between two spectral channels: MODIS band-22 (3.9μm) and band-31 (10.75μm). Further, we are extending our algorithm development to geostationary satellites, for providing continuous monitoring of the spatial-temporal variation of fog. We anticipate that the ongoing and future development of a fog monitoring system would be of assistance to air, rail and vehicular transportation management, as well as for dissemination of fog information to government agencies and general public. The outputs of fog detection algorithm and related aerosol/cloud parameters are operationally disseminated via http://fogsouthasia.com/.

  9. Global trends in satellite-based emergency mapping

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-01-01

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

  10. Digital, Satellite-Based Aeronautical Communication

    Science.gov (United States)

    Davarian, F.

    1989-01-01

    Satellite system relays communication between aircraft and stations on ground. System offers better coverage with direct communication between air and ground, costs less and makes possible new communication services. Carries both voice and data. Because many data exchanged between aircraft and ground contain safety-related information, probability of bit errors essential.

  11. In vivo wide-field multispectral dosimeter for use in ALA-PpIX based photodynamic therapy of skin

    Science.gov (United States)

    LaRochelle, Ethan P. M.; Davis, Scott C.; de Souza, Ana Luiza Ribeiro; Pogue, Brian W.

    2017-02-01

    Photodynamic therapy (PDT) for Actinic Kertoses (AK) using aminoluvelinic acid (ALA) is an FDA-approved treatment, which is generally effective, yet response rates vary. The origin of the variability is not well characterized, but may be related to inter-patient variability in the production of protoporphyrin IX (PpIX). While fiber-based point probe systems provide a method for measuring PpIX production, these measurements have demonstrated large spatial and inter-operator variability. Thus, in an effort to improve patient-specific dosimetry and treatment it is important to develop a robust system that accounts for spatial variability and reduces the chance of operator errors. To address this need, a wide-field multispectral imaging system was developed that is capable of quantifying maps of PpIX in both liquid phantoms and in vivo experiments, focusing on high sensitivity light signals. The system uses both red and blue excitation to elicit a fluorescent response at varying skin depths. A ten-position filter wheel with bandpass filters ranging from 635nm to 710nm are used to capture images along the emission band. A linear least-square spectral fitting algorithm provides the ability to decouple background autofluorescence from PpIX fluorescence, which has improved the system sensitivity by an order of magnitude, detecting nanomolar PpIX concentrations in liquid phantoms in the presence of 2% whole blood and 2% intralipid.

  12. Remote quantitative analysis of minerals based on multispectral line-calibrated laser-induced breakdown spectroscopy (LIBS).

    Science.gov (United States)

    Wan, Xiong; Wang, Peng

    2014-01-01

    Laser-induced breakdown spectroscopy (LIBS) is a feasible remote sensing technique used for mineral analysis in some unapproachable places where in situ probing is needed, such as analysis of radioactive elements in a nuclear leak or the detection of elemental compositions and contents of minerals on planetary and lunar surfaces. Here a compact custom 15 m focus optical component, combining a six times beam expander with a telescope, has been built, with which the laser beam of a 1064 nm Nd ; YAG laser is focused on remote minerals. The excited LIBS signals that reveal the elemental compositions of minerals are collected by another compact single lens-based signal acquisition system. In our remote LIBS investigations, the LIBS spectra of an unknown ore have been detected, from which the metal compositions are obtained. In addition, a multi-spectral line calibration (MSLC) method is proposed for the quantitative analysis of elements. The feasibility of the MSLC and its superiority over a single-wavelength determination have been confirmed by comparison with traditional chemical analysis of the copper content in the ore.

  13. Efficient chaotic based satellite power supply subsystem

    International Nuclear Information System (INIS)

    Ramos Turci, Luiz Felipe; Macau, Elbert E.N.; Yoneyama, Takashi

    2009-01-01

    In this work, we investigate the use of the Dynamical System Theory to increase the efficiency of the satellite power supply subsystems. The core of a satellite power subsystem relies on its DC/DC converter. This is a very nonlinear system that presents a multitude of phenomena ranging from bifurcations, quasi-periodicity, chaos, coexistence of attractors, among others. The traditional power subsystem design techniques try to avoid these nonlinear phenomena so that it is possible to use linear system theory in small regions about the equilibrium points. Here, we show that more efficiency can be drawn from a power supply subsystem if the DC/DC converter operates in regions of high nonlinearity. In special, if it operates in a chaotic regime, is has an intrinsic sensitivity that can be exploited to efficiently drive the power subsystem over high ranges of power requests by using control of chaos techniques.

  14. Efficient chaotic based satellite power supply subsystem

    Energy Technology Data Exchange (ETDEWEB)

    Ramos Turci, Luiz Felipe [Technological Institute of Aeronautics (ITA), Sao Jose dos Campos, SP (Brazil)], E-mail: felipeturci@yahoo.com.br; Macau, Elbert E.N. [National Institute of Space Research (Inpe), Sao Jose dos Campos, SP (Brazil)], E-mail: elbert@lac.inpe.br; Yoneyama, Takashi [Technological Institute of Aeronautics (ITA), Sao Jose dos Campos, SP (Brazil)], E-mail: takashi@ita.br

    2009-10-15

    In this work, we investigate the use of the Dynamical System Theory to increase the efficiency of the satellite power supply subsystems. The core of a satellite power subsystem relies on its DC/DC converter. This is a very nonlinear system that presents a multitude of phenomena ranging from bifurcations, quasi-periodicity, chaos, coexistence of attractors, among others. The traditional power subsystem design techniques try to avoid these nonlinear phenomena so that it is possible to use linear system theory in small regions about the equilibrium points. Here, we show that more efficiency can be drawn from a power supply subsystem if the DC/DC converter operates in regions of high nonlinearity. In special, if it operates in a chaotic regime, is has an intrinsic sensitivity that can be exploited to efficiently drive the power subsystem over high ranges of power requests by using control of chaos techniques.

  15. A Dynamic Enhancement With Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection

    Science.gov (United States)

    Miller, Steven D.; Bankert, Richard L.; Solbrig, Jeremy E.; Forsythe, John M.; Noh, Yoo-Jeong; Grasso, Lewis D.

    2017-12-01

    This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multispectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0, 1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color red/green/blue imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

  16. A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

    Science.gov (United States)

    Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

    2017-12-01

    The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

  17. Multispectral Microimager for Astrobiology

    Science.gov (United States)

    Sellar, R. Glenn; Farmer, Jack D.; Kieta, Andrew; Huang, Julie

    2006-01-01

    A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

  18. 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.

  19. Satellite based wind resource assessment over the South China Sea

    DEFF Research Database (Denmark)

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

    2014-01-01

    variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...

  20. Multispectral biometrics systems and applications

    CERN Document Server

    Zhang, David; Gong, Yazhuo

    2016-01-01

    Describing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author’s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.

  1. Fine-tuning satellite-based rainfall estimates

    Science.gov (United States)

    Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

    2018-05-01

    Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

  2. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  3. Target Detection Based on EBPSK Satellite Passive Radar

    Directory of Open Access Journals (Sweden)

    Lu Zeyuan

    2015-05-01

    Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.

  4. GPS-based satellite tracking system for precise positioning

    Science.gov (United States)

    Yunck, T. P.; Melbourne, W. G.; Thornton, C. L.

    1985-01-01

    NASA is developing a Global Positioning System (GPS) based measurement system to provide precise determination of earth satellite orbits, geodetic baselines, ionospheric electron content, and clock offsets between worldwide tracking sites. The system will employ variations on the differential GPS observing technique and will use a network of nine fixed ground terminals. Satellite applications will require either a GPS flight receiver or an on-board GPS beacon. Operation of the system for all but satellite tracking will begin by 1988. The first major satellite application will be a demonstration of decimeter accuracy in determining the altitude of TOPEX in the early 1990's. By then the system is expected to yield long-baseline accuracies of a few centimeters and instantaneous time synchronization to 1 ns.

  5. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  6. Acquisition performance of LAPAN-A3/IPB multispectral imager in real-time mode of operation

    Science.gov (United States)

    Hakim, P. R.; Permala, R.; Jayani, A. P. S.

    2018-05-01

    LAPAN-A3/IPB satellite was launched in June 2016 and its multispectral imager has been producing Indonesian coverage images. In order to improve its support for remote sensing application, the imager should produce images with high quality and quantity. To improve the quantity of LAPAN-A3/IPB multispectral image captured, image acquisition could be executed in real-time mode from LAPAN ground station in Bogor when the satellite passes west Indonesia region. This research analyses the performance of LAPAN-A3/IPB multispectral imager acquisition in real-time mode, in terms of image quality and quantity, under assumption of several on-board and ground segment limitations. Results show that with real-time operation mode, LAPAN-A3/IPB multispectral imager could produce twice as much as image coverage compare to recorded mode. However, the images produced in real-time mode will have slightly degraded quality due to image compression process involved. Based on several analyses that have been done in this research, it is recommended to use real-time acquisition mode whenever it possible, unless for some circumstances that strictly not allow any quality degradation of the images produced.

  7. Satellite-based technique for nowcasting of thunderstorms over ...

    Indian Academy of Sciences (India)

    Suman Goyal

    2017-08-31

    Aug 31, 2017 ... Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila ... of actual development of cumulonimbus clouds, ... MCS over Indian region using Infrared Channel ... (2016) based on case study of.

  8. POTENTIAL OF UAV-BASED LASER SCANNER AND MULTISPECTRAL CAMERA DATA IN BUILDING INSPECTION

    Directory of Open Access Journals (Sweden)

    D. Mader

    2016-06-01

    Full Text Available Conventional building inspection of bridges, dams or large constructions in general is rather time consuming and often cost expensive due to traffic closures and the need of special heavy vehicles such as under-bridge inspection units or other large lifting platforms. In consideration that, an unmanned aerial vehicle (UAV will be more reliable and efficient as well as less expensive and simpler to operate. The utilisation of UAVs as an assisting tool in building inspections is obviously. Furthermore, light-weight special sensors such as infrared and thermal cameras as well as laser scanner are available and predestined for usage on unmanned aircraft systems. Such a flexible low-cost system is realized in the ADFEX project with the goal of time-efficient object exploration, monitoring and damage detection. For this purpose, a fleet of UAVs, equipped with several sensors for navigation, obstacle avoidance and 3D object-data acquisition, has been developed and constructed. This contribution deals with the potential of UAV-based data in building inspection. Therefore, an overview of the ADFEX project, sensor specifications and requirements of building inspections in general are given. On the basis of results achieved in practical studies, the applicability and potential of the UAV system in building inspection will be presented and discussed.

  9. An interdisciplinary analysis of multispectral satellite data for selected cover types in the Colorado Mountains, using automatic data processing techniques. [geological lineaments and mineral exploration

    Science.gov (United States)

    Hoffer, R. M. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. One capability which has been recognized by many geologists working with space photography is the ability to see linear features and alinements which were previously not apparent. To the exploration geologist, major lineaments seen on satellite images are of particular interest. A portion of ERTS-1 frame 1407-17193 (3 Sept. 1973) was used for mapping lineaments and producing an iso-lineament intersection map. Skylab photography over the area of prime area was not useable due to snow cover. Once the lineaments were mapped, a grid with 2.5 km spacing was overlayed on the map and the lineament intersections occurring within each grid square were counted and the number plotted in the center of the grid square. These numbers were then contoured producing a contour map of equal lineament intersection. It is believed that the areas of high intersection concentration would be the most favorable area for ore mineralization if favorable host rocks are also present. These highly fractured areas would act as conduits for carrying the ore forming solutions to the site of deposition in a favorable host rock. Two of the six areas of high intersection concentration are over areas of present or past mining camps and small claims are known to exist near the others. These would be prime target areas for future mineral exploration.

  10. A multilevel multispectral data set analysis in the visible and infrared wavelength regions. [for land use remote sensing

    Science.gov (United States)

    Biehl, L. L.; Silva, L. F.

    1975-01-01

    Skylab multispectral scanner data, digitized Skylab color infrared (IR) photography, digitized Skylab black and white multiband photography, and Earth Resources Technology Satellite (ERTS) multispectral scanner data collected within a 24-hr time period over an area in south-central Indiana near Bloomington on June 9 and 10, 1973, were compared in a machine-aided land use analysis of the area. The overall classification performance results, obtained with nine land use classes, were 87% correct classification using the 'best' 4 channels of the Skylab multispectral scanner, 80% for the channels on the Skylab multispectral scanner which are spectrally comparable to the ERTS multispectral scanner, 88% for the ERTS multispectral scanner, 83% for the digitized color IR photography, and 76% for the digitized black and white multiband photography. The results indicate that the Skylab multispectral scanner may yield even higher classification accuracies when a noise-filtered multispectral scanner data set becomes available in the near future.

  11. Tracking target objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  12. SOFT project: a new forecasting system based on satellite data

    Science.gov (United States)

    Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

  13. Quantifying the Spatio-temporal Impacts of Sea Level Rise on Carbon Storage Using Repeat Lidar Surveys and Multispectral Satellite Imagery

    Science.gov (United States)

    Smart, L.; Taillie, P. J.; Smith, J. W.; Meentemeyer, R. K.

    2017-12-01

    Sound coastal land-use policy and management decisions to mitigate or adapt to sea level rise impacts depend on understanding vegetation responses to sea level rise over large extents. Accurate methodologies to quantify these changes are necessary to understand the continued production of the ecosystem services upon which human health and well-being depend. This research quantifies spatio-temporal changes in aboveground biomass altered by sea level rise across North Carolina's coastal plain using a combination of repeat-acquisition lidar data and multi-temporal satellite imagery. Using field data from across the study area, we evaluated the reliability of multi-temporal lidar data with disparate densities and accuracies to detect changes along a coastal vegetation gradient from marsh to forested wetland. Despite an 18 fold increase in lidar point density between survey years (2001, 2014), the relationships between lidar-derived heights and field-measured heights were similar (adjusted r2; 0.6 -0.7). Random Forest, a machine learning algorithm, was used to separately predict above-ground biomass pools at the landscape-scale for the two time periods using the 98 field plots as reference data. Models performed well for both years (adjusted r2; 0.67-0.85). The 2001 model required the addition of Landsat spectral indices to meet the same adjusted r2 values as the 2014 model, which utilized lidar-derived metrics alone. Of the many potential lidar-derived predictor metrics, median and mean vegetation height were the best predictors in both time periods. To measure the spatial patterns of biomass change across the landscape, we subtracted the 2001 biomass model from the 2014 model and found significant spatial heterogeneity in biomass change across both the vegetation gradient and across the peninsula over the 12-year time period. In forested areas, we found a mean increase in aboveground biomass whereas in transition zones, marshes and freshwater emergent wetlands we

  14. Combining Landsat TM multispectral satellite imagery and different modelling approaches for mapping post-fire erosion changes in a Mediterranean site

    Science.gov (United States)

    Petropoulos, George P.; Kairis, Orestis; Karamesouti, Mina; Papanikolaou, Ioannis D.; Kosmas, Constantinos

    2013-04-01

    South European countries are naturally vulnerable to wildfires. Their natural resources such as soil, vegetation and water may be severely affected by wildfires, causing an imminent environmental deterioration due to the complex interdependence among biophysical components. Soil surface water erosion is a natural process essential for soil formation that is affected by such interdependences. Accelerated erosion due to wildfires, constitutes a major restrictive factor for ecosystem sustainability. In 2007, South European countries were severely affected by wildfires, with more than 500,000 hectares of land burnt in that year alone, well above the average of the last 30 years. The present work examines the changes in spatial variability of soil erosion rates as a result of a wildfire event that took place in Greece in 2007, one of the most devastating years in terms of wildfire hazards. Regional estimates of soil erosion rates before and after the fire outbreak were derived from the Revised Universal Soil Loss Equation (RUSLE, Renard et al. 1991) and the Pan-European Soil Erosion Risk Assessment model (PESERA, Kirkby, 1999; Kirkby et al., 2000). Inputs for both models included climatic, land-use, soil type, topography and land use management data. Where appropriate, both models were also fed with input data derived from the analysis of LANDSAT TM satellite imagery available in our study area, acquired before and shortly after the fire suppression. Our study was compiled and performed in a GIS environment. In overall, the loss of vegetation from the fire outbreak caused a substantial increase of soil erosion rates in the affected area, particularly towards the steep slopes. Both tested models were compared to each other and noticeable differences were observed in the soil erosion predictions before and after the fire event. These are attributed to the different parameterization requirements of the 2 models. This quantification of sediment supply through the river

  15. Validation of an Innovative Satellite-Based UV Dosimeter

    Science.gov (United States)

    Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

    2016-08-01

    We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

  16. Engineering satellite-based navigation and timing global navigation satellite systems, signals, and receivers

    CERN Document Server

    Betz, J

    2016-01-01

    This book describes the design and performance analysis of satnav systems, signals, and receivers. It also provides succinct descriptions and comparisons of all the world’s satnav systems. Its comprehensive and logical structure addresses all satnav signals and systems in operation and being developed. Engineering Satellite-Based Navigation and Timing: Global Navigation Satellite Systems, Signals, and Receivers provides the technical foundation for designing and analyzing satnav signals, systems, and receivers. Its contents and structure address all satnav systems and signals: legacy, modernized, and new. It combines qualitative information with detailed techniques and analyses, providing a comprehensive set of insights and engineering tools for this complex multidisciplinary field. Part I describes system and signal engineering including orbital mechanics and constellation design, signal design principles and underlying considerations, link budgets, qua tifying receiver performance in interference, and e...

  17. Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

    Directory of Open Access Journals (Sweden)

    Peder Heiselberg

    2017-11-01

    Full Text Available The European Space Agency Sentinel-2 satellites provide multispectral images with pixel sizes down to 10 m. This high resolution allows for fast and frequent detection, classification and discrimination of various objects in the sea, which is relevant in general and specifically for the vast Arctic environment. We analyze several sets of multispectral image data from Denmark and Greenland fall and winter, and describe a supervised search and classification algorithm based on physical parameters that successfully finds and classifies all objects in the sea with reflectance above a threshold. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however, the false alarm rate dominates for small non-sailing boats.

  18. A Prototype Knowledge-Based System for Satellite Mission Planning.

    Science.gov (United States)

    1986-12-01

    used by different groups in an operational environment. 6 II. Literature Review As management science has recognized, it is not practical to separate...schedule only one satellite per set of requirements. A -4 .............. er.- Appendix B O9perational Conce~t Usin a Knowlede -Based System There are many

  19. Proposed systems configurations for a satellite based ISDN

    Science.gov (United States)

    Capece, M.; Pavesi, B.; Tozzi, P.; Galligan, K. P.

    This paper summarizes concepts developed during a study for the ESA in which the evolution of ISDN capability and the impact in the satellite land mobile area are examined. Following the progressive steps of the expected ISDN implementation and the potential market penetration, a space based system capable of satisfying particular user services classes has been investigated. The approach used is to establish a comparison between the requirements of potential mobile users and the services already envisaged by ISDN, identifying the service subclasses that might be adopted in a mobile environment through a satellite system. Two system alternatives, with different ISDN compatibility, have been identified. The first option allows a partial compatibility, by providing the central stations of the earth segment with suitable interface units. The second option permits a full integration, operating on the satellite on-board capabilities.

  20. Trellis-coded CPM for satellite-based mobile communications

    Science.gov (United States)

    Abrishamkar, Farrokh; Biglieri, Ezio

    1988-01-01

    Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

  1. Stigmergy based behavioural coordination for satellite clusters

    Science.gov (United States)

    Tripp, Howard; Palmer, Phil

    2010-04-01

    Multi-platform swarm/cluster missions are an attractive prospect for improved science return as they provide a natural capability for temporal, spatial and signal separation with further engineering and economic advantages. As spacecraft numbers increase and/or the round-trip communications delay from Earth lengthens, the traditional "remote-control" approach begins to break down. It is therefore essential to push control into space; to make spacecraft more autonomous. An autonomous group of spacecraft requires coordination, but standard terrestrial paradigms such as negotiation, require high levels of inter-spacecraft communication, which is nontrivial in space. This article therefore introduces the principals of stigmergy as a novel method for coordinating a cluster. Stigmergy is an agent-based, behavioural approach that allows for infrequent communication with decisions based on local information. Behaviours are selected dynamically using a genetic algorithm onboard. supervisors/ground stations occasionally adjust parameters and disseminate a "common environment" that is used for local decisions. After outlining the system, an analysis of some crucial parameters such as communications overhead and number of spacecraft is presented to demonstrate scalability. Further scenarios are considered to demonstrate the natural ability to deal with dynamic situations such as the failure of spacecraft, changing mission objectives and responding to sudden bursts of high priority tasks.

  2. 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.

  3. Dual light-emitting diode-based multichannel microscopy for whole-slide multiplane, multispectral and phase imaging.

    Science.gov (United States)

    Liao, Jun; Wang, Zhe; Zhang, Zibang; Bian, Zichao; Guo, Kaikai; Nambiar, Aparna; Jiang, Yutong; Jiang, Shaowei; Zhong, Jingang; Choma, Michael; Zheng, Guoan

    2018-02-01

    We report the development of a multichannel microscopy for whole-slide multiplane, multispectral and phase imaging. We use trinocular heads to split the beam path into 6 independent channels and employ a camera array for parallel data acquisition, achieving a maximum data throughput of approximately 1 gigapixel per second. To perform single-frame rapid autofocusing, we place 2 near-infrared light-emitting diodes (LEDs) at the back focal plane of the condenser lens to illuminate the sample from 2 different incident angles. A hot mirror is used to direct the near-infrared light to an autofocusing camera. For multiplane whole-slide imaging (WSI), we acquire 6 different focal planes of a thick specimen simultaneously. For multispectral WSI, we relay the 6 independent image planes to the same focal position and simultaneously acquire information at 6 spectral bands. For whole-slide phase imaging, we acquire images at 3 focal positions simultaneously and use the transport-of-intensity equation to recover the phase information. We also provide an open-source design to further increase the number of channels from 6 to 15. The reported platform provides a simple solution for multiplexed fluorescence imaging and multimodal WSI. Acquiring an instant focal stack without z-scanning may also enable fast 3-dimensional dynamic tracking of various biological samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Assessment of satellite-based precipitation estimates over Paraguay

    Science.gov (United States)

    Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

    2018-04-01

    Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

  5. Evaluating the hydrological consistency of satellite based water cycle components

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2016-06-15

    Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

  6. Land use change detection based on multi-date imagery from different satellite sensor systems

    Science.gov (United States)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  7. Laser Guidestar Satellite for Ground-based Adaptive Optics Imaging of Geosynchronous Satellites and Astronomical Targets

    Science.gov (United States)

    Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.

    2015-12-01

    Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x

  8. Programmable Ultra-Lightweight System Adaptable Radio Satellite Base Station

    Science.gov (United States)

    Varnavas, Kosta; Sims, Herb

    2015-01-01

    With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.

  9. Multi-spectral optical scanners for commercial earth observation missions

    Science.gov (United States)

    Schröter, Karin; Engel, Wolfgang; Berndt, Klaus

    2017-11-01

    In recent years, a number of commercial Earth observation missions have been initiated with the aim to gather data in the visible and near-infrared wavelength range. Some of these missions aim at medium resolution (5 to 10 m) multi-spectral imaging with the special background of daily revisiting. Typical applications aim at monitoring of farming area for growth control and harvest prediction, irrigation control, or disaster monitoring such as hail damage in farming, or flood survey. In order to arrive at profitable business plans for such missions, it is mandatory to establish the space segment, i.e. the spacecraft with their opto -electronic payloads, at minimum cost while guaranteeing maximum reliability for mission success. As multiple spacecraft are required for daily revisiting, the solutions are typically based on micro-satellites. This paper presents designs for multi-spectral opto-electric scanners for this type of missions. These designs are drive n by minimum mass and power budgets of microsatellites, and the need for minimum cost. As a consequence, it is mandatory to arrive at thermally robust, compact telescope designs. The paper gives a comparison between refractive, catadioptric, and TMA optics. For mirror designs, aluminium and Zerodur mirror technologies are briefly discussed. State-of-the art focal plane designs are presented. The paper also addresses the choice of detector technologies such as CCDs and CMOS Active Pixel Sensors. The electronics of the multi-spectral scanners represent the main design driver regarding power consumption, reliability, and (most often) cost. It can be subdivided into the detector drive electronics, analog and digital data processing chains, the data mass memory unit, formatting and down - linking units, payload control electronics, and local power supply. The paper gives overviews and trade-offs between data compression strategies and electronics solutions, mass memory unit designs, and data formatting approaches

  10. SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

    2016-04-01

    Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

  11. [Surveying a zoological facility through satellite-based geodesy].

    Science.gov (United States)

    Böer, M; Thien, W; Tölke, D

    2000-06-01

    In the course of a thesis submitted for a diploma degree within the Fachhochschule Oldenburg the Serengeti Safaripark was surveyed in autumn and winter 1996/97 laying in the planning foundations for the application for licences from the controlling authorities. Taking into consideration the special way of keeping animals in the Serengeti Safaripark (game ranching, spacious walk-through-facilities) the intention was to employ the outstanding satellite based geodesy. This technology relies on special aerials receiving signals from 24 satellites which circle around the globe. These data are being gathered and examined. This examination produces the exact position of this aerial in a system of coordinates which allows depicting this point on a map. This procedure was used stationary (from a strictly defined point) as well as in the movement (in a moving car). Additionally conventional procedures were used when the satellite based geodesy came to its limits. Finally a detailed map of the Serengeti Safaripark was created which shows the position and size of stables and enclosures as well as wood and water areas and the sectors of the leisure park. Furthermore the established areas of the enclosures together with an already existing animal databank have flown into an information system with the help of which the stock of animals can be managed enclosure-orientated.

  12. Satellite Imagery Assisted Road-Based Visual Navigation System

    Science.gov (United States)

    Volkova, A.; Gibbens, P. W.

    2016-06-01

    There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

  13. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  14. Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Samuel Ortega-Farías

    2016-08-01

    Full Text Available A field experiment was carried out to implement a remote sensing energy balance (RSEB algorithm for estimating the incoming solar radiation (Rsi, net radiation (Rn, sensible heat flux (H, soil heat flux (G and latent heat flux (LE over a drip-irrigated olive (cv. Arbequina orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level. For this study, a helicopter-based unmanned aerial vehicle (UAV was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI and surface temperature (Tsurface at very high resolution (6 cm × 6 cm. Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon. The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE and mean absolute error (MAE for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.

  15. Dissemination of satellite-based river discharge and flood data

    Science.gov (United States)

    Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

    2014-12-01

    In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

  16. Water Mapping Using Multispectral Airborne LIDAR Data

    Science.gov (United States)

    Yan, W. Y.; Shaker, A.; LaRocque, P. E.

    2018-04-01

    This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

  17. Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

    Science.gov (United States)

    Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

    2015-01-01

    The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

  18. Multispectral analytical image fusion

    International Nuclear Information System (INIS)

    Stubbings, T.C.

    2000-04-01

    With new and advanced analytical imaging methods emerging, the limits of physical analysis capabilities and furthermore of data acquisition quantities are constantly pushed, claiming high demands to the field of scientific data processing and visualisation. Physical analysis methods like Secondary Ion Mass Spectrometry (SIMS) or Auger Electron Spectroscopy (AES) and others are capable of delivering high-resolution multispectral two-dimensional and three-dimensional image data; usually this multispectral data is available in form of n separate image files with each showing one element or other singular aspect of the sample. There is high need for digital image processing methods enabling the analytical scientist, confronted with such amounts of data routinely, to get rapid insight into the composition of the sample examined, to filter the relevant data and to integrate the information of numerous separate multispectral images to get the complete picture. Sophisticated image processing methods like classification and fusion provide possible solution approaches to this challenge. Classification is a treatment by multivariate statistical means in order to extract analytical information. Image fusion on the other hand denotes a process where images obtained from various sensors or at different moments of time are combined together to provide a more complete picture of a scene or object under investigation. Both techniques are important for the task of information extraction and integration and often one technique depends on the other. Therefore overall aim of this thesis is to evaluate the possibilities of both techniques regarding the task of analytical image processing and to find solutions for the integration and condensation of multispectral analytical image data in order to facilitate the interpretation of the enormous amounts of data routinely acquired by modern physical analysis instruments. (author)

  19. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  20. Object-Based Assessment of Satellite Precipitation Products

    Directory of Open Access Journals (Sweden)

    Jingjing Li

    2016-06-01

    Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

  1. Development and validation of satellite based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2015-10-01

    A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  2. An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

    Directory of Open Access Journals (Sweden)

    Yady Tatiana Solano-Correa

    2018-03-01

    Full Text Available This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations, which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1 confirm the effectiveness of the proposed approach.

  3. Novel wearable-type biometric devices based on skin tissue optics with multispectral LED-photodiode matrix

    Science.gov (United States)

    Jo, Young Chang; Kim, Hae Na; Kang, Jae Hwan; Hong, Hyuck Ki; Choi, Yeon Shik; Jung, Suk Won; Kim, Sung Phil

    2017-04-01

    In this study, we examined the possibility of using a multispectral skin photomatrix (MSP) module as a novel biometric device. The MSP device measures optical patterns of the wrist skin tissue. Optical patterns consist of 2 × 8 photocurrent intensities of photodiode arrays, which are generated by optical transmission and diffuse reflection of photons from LED light sources with variable wavelengths into the wrist skin tissue. Optical patterns detected by the MSP device provide information on both the surface and subsurface characteristics of the human skin tissue. We found that in the 21 subjects we studied, they showed their unique characteristics, as determined using several wavelengths of light. The experimental results show that the best personal identification accuracy can be acquired using a combination of infrared light and yellow light. This novel biometric device, the MSP module, exhibited an excellent false acceptance rate (FAR) of 0.3% and a false rejection rate (FRR) of 0.0%, which are better than those of commercialized biometric devices such as a fingerprint biometric system. From these experimental results, we found that people exhibit unique optical patterns of their inner-wrist skin tissue and this uniqueness could be used for developing novel high-accuracy personal identification devices.

  4. Korea Earth Observation Satellite Program

    Science.gov (United States)

    Baek, Myung-Jin; Kim, Zeen-Chul

    via Korea Aerospace Research Institute (KARI) as the prime contractor in the area of Korea earth observation satellite program to enhance Korea's space program development capability. In this paper, Korea's on-going and future earth observation satellite programs are introduced: KOMPSAT- 1 (Korea Multi Purpose Satellite-1), KOMPSAT-2 and Communication, Broadcasting and Meteorological Satellite (CBMS) program. KOMPSAT-1 satellite successfully launched in December 1999 with Taurus launch vehicle. Since launch, KOMPSAT-1 is downlinking images of Korea Peninsular every day. Until now, KOMPSAT-1 has been operated more than 2 and half years without any major hardware malfunction for the mission operation. KOMPSAT-1 payload has 6.6m panchromatic spatial resolution at 685 km on-orbit and the spacecraft bus had NASA TOMS-EP (Total Ozone Mapping Spectrometer-Earth Probe) spacecraft bus heritage designed and built by TRW, U.S.A.KOMPSAT-1 program was international co-development program between KARI and TRW funded by Korean Government. be launched in 2004. Main mission objective is to provide geo-information products based on the multi-spectral high resolution sensor called Multi-Spectral Camera (MSC) which will provide 1m panchromatic and 4m multi-spectral high resolution images. ELOP of Israel is the prime contractor of the MSC payload system and KARI is the total system prime contractor including spacecraft bus development and ground segment. KARI also has the contract with Astrium of Europe for the purpose of technical consultation and hardware procurement. Based on the experience throughout KOMPSAT-1 and KOMPSAT-2 space system development, Korea is expecting to establish the infrastructure of developing satellite system. Currently, KOMPSAT-2 program is in the critical design stage. are scheduled to launch in 2008 and in 2014, respectively. The mission of CBMS consists of two areas. One is of space technology test for the communications mission, and the other is of a real

  5. Active Multispectral Band Selection and Reflectance Measurement System

    National Research Council Canada - National Science Library

    Rennich, Bradley

    1999-01-01

    .... To aid in the selection of these bands, a novel multispectral band selection technique is presented based on the cross-correlation of the material class reflectance spectra over a wavelength range of 1 - 5 microns...

  6. NASA Operational Simulator for Small Satellites: Tools for Software Based Validation and Verification of Small Satellites

    Science.gov (United States)

    Grubb, Matt

    2016-01-01

    The NASA Operational Simulator for Small Satellites (NOS3) is a suite of tools to aid in areas such as software development, integration test (IT), mission operations training, verification and validation (VV), and software systems check-out. NOS3 provides a software development environment, a multi-target build system, an operator interface-ground station, dynamics and environment simulations, and software-based hardware models. NOS3 enables the development of flight software (FSW) early in the project life cycle, when access to hardware is typically not available. For small satellites there are extensive lead times on many of the commercial-off-the-shelf (COTS) components as well as limited funding for engineering test units (ETU). Considering the difficulty of providing a hardware test-bed to each developer tester, hardware models are modeled based upon characteristic data or manufacturers data sheets for each individual component. The fidelity of each hardware models is such that FSW executes unaware that physical hardware is not present. This allows binaries to be compiled for both the simulation environment, and the flight computer, without changing the FSW source code. For hardware models that provide data dependent on the environment, such as a GPS receiver or magnetometer, an open-source tool from NASA GSFC (42 Spacecraft Simulation) is used to provide the necessary data. The underlying infrastructure used to transfer messages between FSW and the hardware models can also be used to monitor, intercept, and inject messages, which has proven to be beneficial for VV of larger missions such as James Webb Space Telescope (JWST). As hardware is procured, drivers can be added to the environment to enable hardware-in-the-loop (HWIL) testing. When strict time synchronization is not vital, any number of combinations of hardware components and software-based models can be tested. The open-source operator interface used in NOS3 is COSMOS from Ball Aerospace. For

  7. Geometric Calibration and Radiometric Correction of the Maia Multispectral Camera

    Science.gov (United States)

    Nocerino, E.; Dubbini, M.; Menna, F.; Remondino, F.; Gattelli, M.; Covi, D.

    2017-10-01

    Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.

  8. An integrated compact airborne multispectral imaging system using embedded computer

    Science.gov (United States)

    Zhang, Yuedong; Wang, Li; Zhang, Xuguo

    2015-08-01

    An integrated compact airborne multispectral imaging system using embedded computer based control system was developed for small aircraft multispectral imaging application. The multispectral imaging system integrates CMOS camera, filter wheel with eight filters, two-axis stabilized platform, miniature POS (position and orientation system) and embedded computer. The embedded computer has excellent universality and expansibility, and has advantages in volume and weight for airborne platform, so it can meet the requirements of control system of the integrated airborne multispectral imaging system. The embedded computer controls the camera parameters setting, filter wheel and stabilized platform working, image and POS data acquisition, and stores the image and data. The airborne multispectral imaging system can connect peripheral device use the ports of the embedded computer, so the system operation and the stored image data management are easy. This airborne multispectral imaging system has advantages of small volume, multi-function, and good expansibility. The imaging experiment results show that this system has potential for multispectral remote sensing in applications such as resource investigation and environmental monitoring.

  9. Optimal wavelength band clustering for multispectral iris recognition.

    Science.gov (United States)

    Gong, Yazhuo; Zhang, David; Shi, Pengfei; Yan, Jingqi

    2012-07-01

    This work explores the possibility of clustering spectral wavelengths based on the maximum dissimilarity of iris textures. The eventual goal is to determine how many bands of spectral wavelengths will be enough for iris multispectral fusion and to find these bands that will provide higher performance of iris multispectral recognition. A multispectral acquisition system was first designed for imaging the iris at narrow spectral bands in the range of 420 to 940 nm. Next, a set of 60 human iris images that correspond to the right and left eyes of 30 different subjects were acquired for an analysis. Finally, we determined that 3 clusters were enough to represent the 10 feature bands of spectral wavelengths using the agglomerative clustering based on two-dimensional principal component analysis. The experimental results suggest (1) the number, center, and composition of clusters of spectral wavelengths and (2) the higher performance of iris multispectral recognition based on a three wavelengths-bands fusion.

  10. Estimation of PV energy production based on satellite data

    Science.gov (United States)

    Mazurek, G.

    2015-09-01

    Photovoltaic (PV) technology is an attractive source of power for systems without connection to power grid. Because of seasonal variations of solar radiation, design of such a power system requires careful analysis in order to provide required reliability. In this paper we present results of three-year measurements of experimental PV system located in Poland and based on polycrystalline silicon module. Irradiation values calculated from results of ground measurements have been compared with data from solar radiation databases employ calculations from of satellite observations. Good convergence level of both data sources has been shown, especially during summer. When satellite data from the same time period is available, yearly and monthly production of PV energy can be calculated with 2% and 5% accuracy, respectively. However, monthly production during winter seems to be overestimated, especially in January. Results of this work may be helpful in forecasting performance of similar PV systems in Central Europe and allow to make more precise forecasts of PV system performance than based only on tables with long time averaged values.

  11. STAR: FPGA-based software defined satellite transponder

    Science.gov (United States)

    Davalle, Daniele; Cassettari, Riccardo; Saponara, Sergio; Fanucci, Luca; Cucchi, Luca; Bigongiari, Franco; Errico, Walter

    2013-05-01

    This paper presents STAR, a flexible Telemetry, Tracking & Command (TT&C) transponder for Earth Observation (EO) small satellites, developed in collaboration with INTECS and SITAEL companies. With respect to state-of-the-art EO transponders, STAR includes the possibility of scientific data transfer thanks to the 40 Mbps downlink data-rate. This feature represents an important optimization in terms of hardware mass, which is important for EO small satellites. Furthermore, in-flight re-configurability of communication parameters via telecommand is important for in-orbit link optimization, which is especially useful for low orbit satellites where visibility can be as short as few hundreds of seconds. STAR exploits the principles of digital radio to minimize the analog section of the transceiver. 70MHz intermediate frequency (IF) is the interface with an external S/X band radio-frequency front-end. The system is composed of a dedicated configurable high-speed digital signal processing part, the Signal Processor (SP), described in technology-independent VHDL working with a clock frequency of 184.32MHz and a low speed control part, the Control Processor (CP), based on the 32-bit Gaisler LEON3 processor clocked at 32 MHz, with SpaceWire and CAN interfaces. The quantization parameters were fine-tailored to reach a trade-off between hardware complexity and implementation loss which is less than 0.5 dB at BER = 10-5 for the RX chain. The IF ports require 8-bit precision. The system prototype is fitted on the Xilinx Virtex 6 VLX75T-FF484 FPGA of which a space-qualified version has been announced. The total device occupation is 82 %.

  12. Low SWaP multispectral sensors using dichroic filter arrays

    Science.gov (United States)

    Dougherty, John; Varghese, Ron

    2015-06-01

    The benefits of multispectral imaging are well established in a variety of applications including remote sensing, authentication, satellite and aerial surveillance, machine vision, biomedical, and other scientific and industrial uses. However, many of the potential solutions require more compact, robust, and cost-effective cameras to realize these benefits. The next generation of multispectral sensors and cameras needs to deliver improvements in size, weight, power, portability, and spectral band customization to support widespread deployment for a variety of purpose-built aerial, unmanned, and scientific applications. A novel implementation uses micro-patterning of dichroic filters1 into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. This approach can be implemented across a variety of wavelength ranges and on a variety of detector types including linear, area, silicon, and InGaAs. This dichroic filter array approach can also reduce payloads and increase range for unmanned systems, with the capability to support both handheld and autonomous systems. Recent examples and results of 4 band RGB + NIR dichroic filter arrays in multispectral cameras are discussed. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and scalable production.

  13. Suspended sediment concentration and optical property observations of mixed-turbidity, coastal waters through multispectral ocean color inversion

    Science.gov (United States)

    Multispectral satellite ocean color data from high-turbidity areas of the coastal ocean contain information about the surface concentrations and optical properties of suspended sediments and colored dissolved organic matter (CDOM). Empirical and semi-analytical inversion algorit...

  14. Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT

    Directory of Open Access Journals (Sweden)

    Svetlana N. Losa

    2017-07-01

    Full Text Available We derive the chlorophyll a concentration (Chla for three main phytoplankton functional types (PFTs – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS, an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

  15. Planning for a data base system to support satellite conceptual design

    Science.gov (United States)

    Claydon, C. R.

    1976-01-01

    The conceptual design of an automated satellite design data base system is presented. The satellite catalog in the system includes data for all earth orbital satellites funded to the hardware stage for launch between 1970 and 1980, and provides a concise compilation of satellite capabilities and design parameters. The cost of satellite subsystems and components will be added to the base. Data elements are listed and discussed. Sensor and science and applications opportunities catalogs will be included in the data system. Capabilities of the BASIS storage, retrieval, and analysis system are used in the system design.

  16. Ground-Based Global Navigation Satellite System (GNSS) GLONASS Broadcast Ephemeris Data (hourly files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GLObal NAvigation Satellite System (GLONASS) Broadcast Ephemeris Data (hourly files)...

  17. Ground-based observations coordinated with Viking satellite measurements

    International Nuclear Information System (INIS)

    Opgenoorth, H.J.; Kirkwood, S.

    1989-01-01

    The instrumentation and the orbit of the Viking satellite made this first Swedish satellite mission ideally suited for coordinated observations with the dense network of ground-based stations in northern Scandinavia. Several arrays of complementing instruments such as magnetometers, all-sky cameras, riometers and doppler radars monitored on a routine basis the ionosphere under the magnetospheric region passed by Viking. For a large number of orbits the Viking passages close to Scandinavia were covered by the operation of specially designed programmes at the European incoherent-scatter facility (EISCAT). First results of coordinated observations on the ground and aboard Viking have shed new light on the most spectacular feature of substorm expansion, the westward-travelling surge. The end of a substorm and the associated decay of a westward-travelling surge have been analysed. EISCAT measurements of high spatial and temporal resolution indicate that the conductivities and electric fields associated with westward-travelling surges are not represented correctly by the existing models. (author)

  18. A satellite and model based flood inundation climatology of Australia

    Science.gov (United States)

    Schumann, G.; Andreadis, K.; Castillo, C. J.

    2013-12-01

    To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

  19. LEOPACK The integrated services communications system based on LEO satellites

    Science.gov (United States)

    Negoda, A.; Bunin, S.; Bushuev, E.; Dranovsky, V.

    LEOPACK is yet another LEO satellite project which provides global integrated services for 'business' communications. It utilizes packet rather then circuit switching in both terrestrial and satellite chains as well as cellular approach for frequencies use. Original multiple access protocols and decentralized network control make it possible to organize regionally or logically independent and world-wide networks. Relatively small number of satellites (28) provides virtually global network coverage.

  20. Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

    Directory of Open Access Journals (Sweden)

    Grant Connette

    2016-10-01

    Full Text Available We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area and lowland evergreen forest (21.6%. However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover <80%, 66.0% of mangrove forest and 47.5% of the region’s biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi’s unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning.

  1. Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

    Science.gov (United States)

    Yang, Jie; Messinger, David W.; Dube, Roger R.

    2018-03-01

    Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

  2. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  3. Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

    Science.gov (United States)

    Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

    2013-08-01

    Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

  4. Dsm Based Orientation of Large Stereo Satellite Image Blocks

    Science.gov (United States)

    d'Angelo, P.; Reinartz, P.

    2012-07-01

    High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

  5. Building a satellite climate diagnostics data base for real-time climate monitoring

    International Nuclear Information System (INIS)

    Ropelewski, C.F.

    1991-01-01

    The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Object Classification Using Airborne Multispectral LiDAR Data

    Directory of Open Access Journals (Sweden)

    PAN Suoyan

    2018-02-01

    Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

  8. Advances In Global Aerosol Modeling Applications Through Assimilation of Satellite-Based Lidar Measurements

    Science.gov (United States)

    Campbell, James; Hyer, Edward; Zhang, Jianglong; Reid, Jeffrey; Westphal, Douglas; Xian, Peng; Vaughan, Mark

    2010-05-01

    Modeling the instantaneous three-dimensional aerosol field and its downwind transport represents an endeavor with many practical benefits foreseeable to air quality, aviation, military and science agencies. The recent proliferation of multi-spectral active and passive satellite-based instruments measuring aerosol physical properties has served as an opportunity to develop and refine the techniques necessary to make such numerical modeling applications possible. Spurred by high-resolution global mapping of aerosol source regions, and combined with novel multivariate data assimilation techniques designed to consider these new data streams, operational forecasts of visibility and aerosol optical depths are now available in near real-time1. Active satellite-based aerosol profiling, accomplished using lidar instruments, represents a critical element for accurate analysis and transport modeling. Aerosol source functions, alone, can be limited in representing the macrophysical structure of injection scenarios within a model. Two-dimensional variational (2D-VAR; x, y) assimilation of aerosol optical depth from passive satellite observations significantly improves the analysis of the initial state. However, this procedure can not fully compensate for any potential vertical redistribution of mass required at the innovation step. The expense of an inaccurate vertical analysis of aerosol structure is corresponding errors downwind, since trajectory paths within successive forecast runs will likely diverge with height. In this paper, the application of a newly-designed system for 3D-VAR (x,y,z) assimilation of vertical aerosol extinction profiles derived from elastic-scattering lidar measurements is described [Campbell et al., 2009]. Performance is evaluated for use with the U. S. Navy Aerosol Analysis and Prediction System (NAAPS) by assimilating NASA/CNES satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 0.532 μm measurements [Winker et al., 2009

  9. Network design consideration of a satellite-based mobile communications system

    Science.gov (United States)

    Yan, T.-Y.

    1986-01-01

    Technical considerations for the Mobile Satellite Experiment (MSAT-X), the ground segment testbed for the low-cost spectral efficient satellite-based mobile communications technologies being developed for the 1990's, are discussed. The Network Management Center contains a flexible resource sharing algorithm, the Demand Assigned Multiple Access scheme, which partitions the satellite transponder bandwidth among voice, data, and request channels. Satellite use of multiple UHF beams permits frequency reuse. The backhaul communications and the Telemetry, Tracking and Control traffic are provided through a single full-coverage SHF beam. Mobile Terminals communicate with the satellite using UHF. All communications including SHF-SHF between Base Stations and/or Gateways, are routed through the satellite. Because MSAT-X is an experimental network, higher level network protocols (which are service-specific) will be developed only to test the operation of the lowest three levels, the physical, data link, and network layers.

  10. Evaluating the hydrological consistency of satellite based water cycle components

    KAUST Repository

    Lopez Valencia, Oliver Miguel; Houborg, Rasmus; McCabe, Matthew

    2016-01-01

    observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating

  11. Satellite-based Drought Reporting on the Navajo Nation

    Science.gov (United States)

    McCullum, A. J. K.; Schmidt, C.; Ly, V.; Green, R.; McClellan, C.

    2017-12-01

    The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

  12. Wireless electricity (Power) transmission using solar based power satellite technology

    International Nuclear Information System (INIS)

    Maqsood, M; Nasir, M Nauman

    2013-01-01

    In the near future due to extensive use of energy, limited supply of resources and the pollution in environment from present resources e.g. (wood, coal, fossil fuel) etc, alternative sources of energy and new ways to generate energy which are efficient, cost effective and produce minimum losses are of great concern. Wireless electricity (Power) transmission (WET) has become a focal point as research point of view and nowadays lies at top 10 future hot burning technologies that are under research these days. In this paper, we present the concept of transmitting power wirelessly to reduce transmission and distribution losses. The wired distribution losses are 70 – 75% efficient. We cannot imagine the world without electric power which is efficient, cost effective and produce minimum losses is of great concern. This paper tells us the benefits of using WET technology specially by using Solar based Power satellites (SBPS) and also focuses that how we make electric system cost effective, optimized and well organized. Moreover, attempts are made to highlight future issues so as to index some emerging solutions.

  13. Satellite Image Time Series Decomposition Based on EEMD

    Directory of Open Access Journals (Sweden)

    Yun-long Kong

    2015-11-01

    Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

  14. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    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....

  15. Population-based geographic access to parent and satellite National Cancer Institute Cancer Center Facilities.

    Science.gov (United States)

    Onega, Tracy; Alford-Teaster, Jennifer; Wang, Fahui

    2017-09-01

    Satellite facilities of National Cancer Institute (NCI) cancer centers have expanded their regional footprints. This study characterized geographic access to parent and satellite NCI cancer center facilities nationally overall and by sociodemographics. Parent and satellite NCI cancer center facilities, which were geocoded in ArcGIS, were ascertained. Travel times from every census tract in the continental United States and Hawaii to the nearest parent and satellite facilities were calculated. Census-based population attributes were used to characterize measures of geographic access for sociodemographic groups. From the 62 NCI cancer centers providing clinical care in 2014, 76 unique parent locations and 211 satellite locations were mapped. The overall proportion of the population within 60 minutes of a facility was 22% for parent facilities and 32.7% for satellite facilities. When satellites were included for potential access, the proportion of some racial groups for which a satellite was the closest NCI cancer center facility increased notably (Native Americans, 22.6% with parent facilities and 39.7% with satellite facilities; whites, 34.8% with parent facilities and 50.3% with satellite facilities; and Asians, 40.0% with parent facilities and 54.0% with satellite facilities), with less marked increases for Hispanic and black populations. Rural populations of all categories had dramatically low proportions living within 60 minutes of an NCI cancer center facility of any type (1.0%-6.6%). Approximately 14% of the population (n = 43,033,310) lived more than 180 minutes from a parent or satellite facility, and most of these individuals were Native Americans and/or rural residents (37% of Native Americans and 41.7% of isolated rural residents). Racial/ethnic and rural populations showed markedly improved geographic access to NCI cancer center care when satellite facilities were included. Cancer 2017;123:3305-11. © 2017 American Cancer Society. © 2017 American

  16. Interference and deception detection technology of satellite navigation based on deep learning

    Science.gov (United States)

    Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

    2017-10-01

    Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

  17. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

    2017-10-01

    The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

  18. Satellite and Ground Based Monitoring of Aerosol Plumes

    International Nuclear Information System (INIS)

    Doyle, Martin; Dorling, Stephen

    2002-01-01

    Plumes of atmospheric aerosol have been studied using a range of satellite and ground-based techniques. The Sea-viewing WideField-of-view Sensor (SeaWiFS) has been used to observe plumes of sulphate aerosol and Saharan dust around the coast of the United Kingdom. Aerosol Optical Thickness (AOT) was retrieved from SeaWiFS for two events; a plume of Saharan dust transported over the United Kingdom from Western Africa and a period of elevated sulphate experienced over the Easternregion of the UK. Patterns of AOT are discussed and related to the synoptic and mesoscale weather conditions. Further observation of the sulphate aerosol event was undertaken using the Advanced Very High Resolution Radiometer instrument(AVHRR). Atmospheric back trajectories and weather conditions were studied in order to identify the meteorological conditions which led to this event. Co-located ground-based measurements of PM 10 and PM 2.5 were obtained for 4sites within the UK and PM 2.5/10 ratios were calculated in order to identify any unusually high or low ratios(indicating the dominant size fraction within the plume)during either of these events. Calculated percentiles ofPM 2.5/10 ratios during the 2 events examined show that these events were notable within the record, but were in noway unique or unusual in the context of a 3 yr monitoring record. Visibility measurements for both episodes have been examined and show that visibility degradation occurred during both the sulphate aerosol and Saharan dust episodes

  19. Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

    International Nuclear Information System (INIS)

    Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

    1999-01-01

    The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: ''End-to-end modeling and analysis (EEM).'' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term ''end-to-end modeling and analysis.'' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable

  20. TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    K. Bakuła

    2016-06-01

    Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

  1. Satellite data transferring subsystem based on system 'Materik'

    International Nuclear Information System (INIS)

    Belogub, V.P.; Kal'schikov, I.B.; Kirillov, Yu.K.; Kulikov, V.N.; Shumov, A.N.

    1998-01-01

    One of the most important indicators of successful function of the International Monitoring System is existence of highly reliable communication channels providing transfer data from observation points in a real time scales. Up to present, the most communication channels were provided with existing VF-channels (Voice Frequency) that are relatively low-speedy in transfer process (4.8-9.6 kbit/sec.). In addition, reliability of the channels is insufficient because of many retransmission points. In connection with it, the special control service of MD RF decided to improve the information transfer system (ITS) installed between the observation point and National Data Center (Dubna-city). The improvement of the ITS comprises replacement of wire lines of VF-channels with satellite ones within the framework of the computer-aided satellite communication system (CASCS) M aterik . Besides it was considered to be expedient that the satellite system of data transfer from NPP to the Crisis Center of 'ROSENERGOATOM' Concern would be combined with CASCS M aterik , using the facilities of the Central Earth Station of Satellite Communication (CESSC) in Dubna. Such approach to the creation of Satellite communication has advantages in solution of radiation safety and global monitoring issues

  2. RETRIEVAL OF AEROSOL MICROPHYSICAL PROPERTIES BASED ON THE OPTIMAL ESTIMATION METHOD: INFORMATION CONTENT ANALYSIS FOR SATELLITE POLARIMETRIC REMOTE SENSING MEASUREMENTS

    Directory of Open Access Journals (Sweden)

    W. Z. Hou

    2018-04-01

    Full Text Available This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

  3. Retrieval of Aerosol Microphysical Properties Based on the Optimal Estimation Method: Information Content Analysis for Satellite Polarimetric Remote Sensing Measurements

    Science.gov (United States)

    Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.

    2018-04-01

    This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

  4. Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

    Science.gov (United States)

    Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

    2017-04-01

    Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

  5. Global Crop Monitoring: A Satellite-Based Hierarchical Approach

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

    Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

  6. Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

    Science.gov (United States)

    Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.; hide

    2014-01-01

    Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

  7. Satellite altimetry based rating curves throughout the entire Amazon basin

    Science.gov (United States)

    Paris, A.; Calmant, S.; Paiva, R. C.; Collischonn, W.; Silva, J. S.; Bonnet, M.; Seyler, F.

    2013-05-01

    The Amazonian basin is the largest hydrological basin all over the world. In the recent past years, the basin has experienced an unusual succession of extreme draughts and floods, which origin is still a matter of debate. Yet, the amount of data available is poor, both over time and space scales, due to factor like basin's size, access difficulty and so on. One of the major locks is to get discharge series distributed over the entire basin. Satellite altimetry can be used to improve our knowledge of the hydrological stream flow conditions in the basin, through rating curves. Rating curves are mathematical relationships between stage and discharge at a given place. The common way to determine the parameters of the relationship is to compute the non-linear regression between the discharge and stage series. In this study, the discharge data was obtained by simulation through the entire basin using the MGB-IPH model with TRMM Merge input rainfall data and assimilation of gage data, run from 1998 to 2010. The stage dataset is made of ~800 altimetry series at ENVISAT and JASON-2 virtual stations. Altimetry series span between 2002 and 2010. In the present work we present the benefits of using stochastic methods instead of probabilistic ones to determine a dataset of rating curve parameters which are consistent throughout the entire Amazon basin. The rating curve parameters have been computed using a parameter optimization technique based on Markov Chain Monte Carlo sampler and Bayesian inference scheme. This technique provides an estimate of the best parameters for the rating curve, but also their posterior probability distribution, allowing the determination of a credibility interval for the rating curve. Also is included in the rating curve determination the error over discharges estimates from the MGB-IPH model. These MGB-IPH errors come from either errors in the discharge derived from the gage readings or errors in the satellite rainfall estimates. The present

  8. Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

    Science.gov (United States)

    Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

    2016-01-01

    This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

  9. Multispectral histogram normalization contrast enhancement

    Science.gov (United States)

    Soha, J. M.; Schwartz, A. A.

    1979-01-01

    A multispectral histogram normalization or decorrelation enhancement which achieves effective color composites by removing interband correlation is described. The enhancement procedure employs either linear or nonlinear transformations to equalize principal component variances. An additional rotation to any set of orthogonal coordinates is thus possible, while full histogram utilization is maintained by avoiding the reintroduction of correlation. For the three-dimensional case, the enhancement procedure may be implemented with a lookup table. An application of the enhancement to Landsat multispectral scanning imagery is presented.

  10. A near real-time satellite-based global drought climate data record

    International Nuclear Information System (INIS)

    AghaKouchak, Amir; Nakhjiri, Navid

    2012-01-01

    Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

  11. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  12. Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

    Science.gov (United States)

    Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene

    1993-01-01

    Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

  13. Fusion of multispectral and panchromatic images using multirate filter banks

    Institute of Scientific and Technical Information of China (English)

    Wang Hong; Jing Zhongliang; Li Jianxun

    2005-01-01

    In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.

  14. A proposed architecture for a satellite-based mobile communications network - The lowest three layers

    Science.gov (United States)

    Yan, T. Y.; Naderi, F. M.

    1986-01-01

    Architecture for a commercial mobile satellite network is proposed. The mobile satellite system (MSS) is composed of a network management center, mobile terminals, base stations, and gateways; the functions of each component are described. The satellite is a 'bent pipe' that performs frequency translations, and it has multiple UHF beams. The development of the MSS design based on the seven-layer open system interconnection model is examined. Consideration is given to the functions of the physical, data link, and network layers and the integrated adaptive mobile access protocol.

  15. Ground-Based Global Navigation Satellite System Combined Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) Combined Broadcast Ephemeris Data (daily files of all distinct navigation messages...

  16. Highlights of satellite-based forest change recognition and tracking using the ForWarn System

    Science.gov (United States)

    Steven P. Norman; William W. Hargrove; Joseph P. Spruce; William M. Christie; Sean W. Schroeder

    2013-01-01

    For a higher resolution version of this file, please use the following link: www.geobabble.orgSatellite-based remote sensing can assist forest managers with their need to recognize disturbances and track recovery. Despite the long...

  17. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Yearly Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  18. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Seasonal Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  19. Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

    Science.gov (United States)

    Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

    2016-01-01

    We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

  20. Highly Protable Airborne Multispectral Imaging System

    Science.gov (United States)

    Lehnemann, Robert; Mcnamee, Todd

    2001-01-01

    A portable instrumentation system is described that includes and airborne and a ground-based subsytem. It can acquire multispectral image data over swaths of terrain ranging in width from about 1.5 to 1 km. The system was developed especially for use in coastal environments and is well suited for performing remote sensing and general environmental monitoring. It includes a small,munpilotaed, remotely controlled airplance that carries a forward-looking camera for navigation, three downward-looking monochrome video cameras for imaging terrain in three spectral bands, a video transmitter, and a Global Positioning System (GPS) reciever.

  1. The multispectral instrument of the Sentinel2 program

    Science.gov (United States)

    Cazaubiel, V.; Chorvalli, Vincent; Miesch, Christophe

    2017-11-01

    The Sentinel-2 program will provide a permanent record of comprehensive data to help inform the agricul-tural sector (utilisation, coverage), forestry industry (population, damage, forest fires), disaster control (management, early warning) and humanitarian relief programmes. Sentinel-2 will also be able to observe natural disasters such as floods, volcanic eruptions, subsidence and landslides. In the Sentinel-2 mission programme, Astrium in Friedrichshafen is responsible for the satellite's system design and platform, as well as for satellite integration and testing. Astrium Toulouse will supply the Multi-Spectral imaging Instrument (MSI), and Astrium Spain will be in charge of the satellite's structure and will produce its thermal equipment and cable harness. The industrial core team also comprises Jena Optronik (Germany), Boostec (France), Sener and GMV (Spain). Sentinel-2 is intended to image the Earth's landmasses from its orbit for at least 7.25 years. In addition, its onboardresources will be designed so that the mission can be prolonged by an extra five years. From 2012 onwards, the 1.1-metric-ton satellite will circle the Earth in a sun-synchronous, polar orbit at an altitude of 786kilometres, fully covering the planet's landmasses in just ten days. The multi-spectral instrument (MSI) will generate optical images in 13 spectral channels in the visible and shortwave infrared range down to a resolution of 10 metres with an image width of 290 kilometres. The instrument is composed of two main parts: • The telescope assembly , combining in one instrument both VNIR and SWIR channels, is mounted on the upper plate of the Bus • The Video and Compression Electronic Units mounted inside the Bus. This telescope is based on a Three Mirror Anastigmat optical concept. This three mirror optical combination is corrected from spherical aberration, coma and astigmatism. It provides a large field of view with very good optical quality. The telescope mirrors and

  2. Research on Coal Exploration Technology Based on Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xiao

    2016-01-01

    Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.

  3. Connecting Satellite-Based Precipitation Estimates to Users

    Science.gov (United States)

    Huffman, George J.; Bolvin, David T.; Nelkin, Eric

    2018-01-01

    Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

  4. Multispectral Landsat images of Antartica

    Energy Technology Data Exchange (ETDEWEB)

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

    1988-01-01

    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  5. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

    Science.gov (United States)

    Stow, Douglas A; Lippitt, Christopher D; Weeks, John R

    2010-08-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA.

  6. New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery

    Directory of Open Access Journals (Sweden)

    Qiong Zheng

    2018-03-01

    Full Text Available Yellow rust is one of the most destructive diseases for winter wheat and has led to a significant decrease in winter wheat quality and yield. Identifying and monitoring yellow rust is of great importance for guiding agricultural production over large areas. Compared with traditional crop disease discrimination methods, remote sensing technology has proven to be a useful tool for accomplishing such a task at large scale. This study explores the potential of the Sentinel-2 Multispectral Instrument (MSI, a newly launched satellite with refined spatial resolution and three red-edge bands, for discriminating between yellow rust infection severities (i.e., healthy, slight, and severe in winter wheat. The corresponding simulative multispectral bands for the Sentinel-2 sensor were calculated by the sensor’s relative spectral response (RSR function based on the in situ hyperspectral data acquired at the canopy level. Three Sentinel-2 spectral bands, including B4 (Red, B5 (Re1, and B7 (Re3, were found to be sensitive bands using the random forest (RF method. A new multispectral index, the Red Edge Disease Stress Index (REDSI, which consists of these sensitive bands, was proposed to detect yellow rust infection at different severity levels. The overall identification accuracy for REDSI was 84.1% and the kappa coefficient was 0.76. Moreover, REDSI performed better than other commonly used disease spectral indexes for yellow rust discrimination at the canopy scale. The optimal threshold method was adopted for mapping yellow rust infection at regional scales based on realistic Sentinel-2 multispectral image data to further assess REDSI’s ability for yellow rust detection. The overall accuracy was 85.2% and kappa coefficient was 0.67, which was found through validation against a set of field survey data. This study suggests that the Sentinel-2 MSI has the potential for yellow rust discrimination, and the newly proposed REDSI has great robustness and

  7. New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery.

    Science.gov (United States)

    Zheng, Qiong; Huang, Wenjiang; Cui, Ximin; Shi, Yue; Liu, Linyi

    2018-03-15

    Yellow rust is one of the most destructive diseases for winter wheat and has led to a significant decrease in winter wheat quality and yield. Identifying and monitoring yellow rust is of great importance for guiding agricultural production over large areas. Compared with traditional crop disease discrimination methods, remote sensing technology has proven to be a useful tool for accomplishing such a task at large scale. This study explores the potential of the Sentinel-2 Multispectral Instrument (MSI), a newly launched satellite with refined spatial resolution and three red-edge bands, for discriminating between yellow rust infection severities (i.e., healthy, slight, and severe) in winter wheat. The corresponding simulative multispectral bands for the Sentinel-2 sensor were calculated by the sensor's relative spectral response (RSR) function based on the in situ hyperspectral data acquired at the canopy level. Three Sentinel-2 spectral bands, including B4 (Red), B5 (Re1), and B7 (Re3), were found to be sensitive bands using the random forest (RF) method. A new multispectral index, the Red Edge Disease Stress Index (REDSI), which consists of these sensitive bands, was proposed to detect yellow rust infection at different severity levels. The overall identification accuracy for REDSI was 84.1% and the kappa coefficient was 0.76. Moreover, REDSI performed better than other commonly used disease spectral indexes for yellow rust discrimination at the canopy scale. The optimal threshold method was adopted for mapping yellow rust infection at regional scales based on realistic Sentinel-2 multispectral image data to further assess REDSI's ability for yellow rust detection. The overall accuracy was 85.2% and kappa coefficient was 0.67, which was found through validation against a set of field survey data. This study suggests that the Sentinel-2 MSI has the potential for yellow rust discrimination, and the newly proposed REDSI has great robustness and generalized ability

  8. Assessing satellite-based start-of-season trends in the US High Plains

    International Nuclear Information System (INIS)

    Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

    2014-01-01

    To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

  9. Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

    Directory of Open Access Journals (Sweden)

    Hakan Kartal

    2018-06-01

    Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

  10. Multi-spectral endogenous fluorescence imaging for bacterial differentiation

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

    2017-07-01

    In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

  11. Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

    Science.gov (United States)

    Xu, Peiliang

    2018-06-01

    The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

  12. Validation of satellite based precipitation over diverse topography of Pakistan

    Science.gov (United States)

    Iqbal, Muhammad Farooq; Athar, H.

    2018-03-01

    This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the

  13. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  14. UKF-based attitude determination method for gyroless satellite

    Institute of Scientific and Technical Information of China (English)

    张红梅; 邓正隆

    2004-01-01

    UKF (unscented Kalman filtering) is a new filtering method suitable to nonlinear systems. The method need not linearize nonlinear systems at the prediction stage of filtering, which is indispensable in EKF (extended Kalman filtering). As a result, the linearization error is avoided, and the filtering accuracy is greatly improved. UKF is applied to the attitude determination for gyroless satellite. Simulations are made to compare the new filter with the traditional EKF.The results indicate that under same conditions, compared with EKF, UKF has faster convergence speed, higher filtering accuracy and more stable estimation performance.

  15. GPS-based system for satellite tracking and geodesy

    Science.gov (United States)

    Bertiger, Willy I.; Thornton, Catherine L.

    1989-01-01

    High-performance receivers and data processing systems developed for GPS are reviewed. The GPS Inferred Positioning System (GIPSY) and the Orbiter Analysis and Simulation Software (OASIS) are described. The OASIS software is used to assess GPS system performance using GIPSY for data processing. Consideration is given to parameter estimation for multiday arcs, orbit repeatability, orbit prediction, daily baseline repeatability, agreement with VLBI, and ambiguity resolution. Also, the dual-frequency Rogue receiver, which can track up to eight GPS satellites simultaneously, is discussed.

  16. Satellite -Based Networks for U-Health & U-Learning

    Science.gov (United States)

    Graschew, G.; Roelofs, T. A.; Rakowsky, S.; Schlag, P. M.

    2008-08-01

    The use of modern Information and Communication Technologies (ICT) as enabling tools for healthcare services (eHealth) introduces new ways of creating ubiquitous access to high-level medical care for all, anytime and anywhere (uHealth). Satellite communication constitutes one of the most flexible methods of broadband communication offering high reliability and cost-effectiveness of connections meeting telemedicine communication requirements. Global networks and the use of computers for educational purposes stimulate and support the development of virtual universities for e-learning. Especially real-time interactive applications can play an important role in tailored and personalised services.

  17. Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

    Science.gov (United States)

    Clark, J.

    1981-01-01

    In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

  18. LANDSAT 8 MULTISPECTRAL AND PANSHARPENED IMAGERY PROCESSING ON THE STUDY OF CIVIL ENGINEERING ISSUES

    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou

    2016-06-01

    Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  19. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    Science.gov (United States)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  20. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2007-01-01

    based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

  1. A Satellite-Based Lagrangian View on Phytoplankton Dynamics

    Science.gov (United States)

    Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan

    2018-01-01

    The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter—the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.

  2. A Satellite-Based Lagrangian View on Phytoplankton Dynamics.

    Science.gov (United States)

    Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan

    2018-01-03

    The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter-the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.

  3. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  4. Radiometric Cross-Calibration of GF-4 in Multispectral Bands

    Directory of Open Access Journals (Sweden)

    Aixia Yang

    2017-03-01

    Full Text Available The GaoFen-4 (GF-4, launched at the end of December 2015, is China’s first high-resolution geostationary optical satellite. A panchromatic and multispectral sensor (PMS is onboard the GF-4 satellite. Unfortunately, the GF-4 has no onboard calibration assembly, so on-orbit radiometric calibration is required. Like the charge-coupled device (CCD onboard HuanJing-1 (HJ or the wide field of view sensor (WFV onboard GaoFen-1 (GF-1, GF-4 also has a wide field of view, which provides challenges for cross-calibration with narrow field of view sensors, like the Landsat series. A new technique has been developed and used to calibrate HJ-1/CCD and GF-1/WFV, which is verified viable. The technique has three key steps: (1 calculate the surface using the bi-directional reflectance distribution function (BRDF characterization of a site, taking advantage of its uniform surface material and natural topographic variation using Landsat Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI imagery and digital elevation model (DEM products; (2 calculate the radiance at the top-of-the atmosphere (TOA with the simulated surface reflectance using the atmosphere radiant transfer model; and (3 fit the calibration coefficients with the TOA radiance and corresponding Digital Number (DN values of the image. This study attempts to demonstrate the technique is also feasible to calibrate GF-4 multispectral bands. After fitting the calibration coefficients using the technique, extensive validation is conducted by cross-validation using the image pairs of GF-4/PMS and Landsat-8/OLI with similar transit times and close view zenith. The validation result indicates a higher accuracy and frequency than that given by the China Centre for Resources Satellite Data and Application (CRESDA using vicarious calibration. The study shows that the new technique is also quite feasible for GF-4 multispectral bands as a routine long-term procedure.

  5. DebriSat - A Planned Laboratory-Based Satellite Impact Experiment for Breakup Fragment Characterizations

    Science.gov (United States)

    Liou, Jer-Chyi; Clark, S.; Fitz-Coy, N.; Huynh, T.; Opiela, J.; Polk, M.; Roebuck, B.; Rushing, R.; Sorge, M.; Werremeyer, M.

    2013-01-01

    The goal of the DebriSat project is to characterize fragments generated by a hypervelocity collision involving a modern satellite in low Earth orbit (LEO). The DebriSat project will update and expand upon the information obtained in the 1992 Satellite Orbital Debris Characterization Impact Test (SOCIT), which characterized the breakup of a 1960 s US Navy Transit satellite. There are three phases to this project: the design and fabrication of DebriSat - an engineering model representing a modern, 60-cm/50-kg class LEO satellite; conduction of a laboratory-based hypervelocity impact to catastrophically break up the satellite; and characterization of the properties of breakup fragments down to 2 mm in size. The data obtained, including fragment size, area-to-mass ratio, density, shape, material composition, optical properties, and radar cross-section distributions, will be used to supplement the DoD s and NASA s satellite breakup models to better describe the breakup outcome of a modern satellite.

  6. Research on orbit prediction for solar-based calibration proper satellite

    Science.gov (United States)

    Chen, Xuan; Qi, Wenwen; Xu, Peng

    2018-03-01

    Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

  7. Ground-Based Global Navigation Satellite System GLONASS (GLObal NAvigation Satellite System) Combined Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GLONASS Combined Broadcast Ephemeris Data (daily files of all distinct navigation...

  8. Improving Understanding of Spatial Heterogeneity in Mountain Ecohydrology with Multispectral Unmanned Aerial Systems (UAS).

    Science.gov (United States)

    Wigmore, O.; Molotch, N. P.

    2017-12-01

    Mountain regions are a critical component of the hydrologic system. These regions are extremely heterogeneous, with dramatic topographic, climatic, ecologic and hydrologic variations occurring over very short distances. This heterogeneity makes understanding changes in these environments difficult. Commonly used satellite data are often too coarse to resolve processes at appropriate scales and point measurements are typically unrepresentative of the wider region. The rapid rise of Unmanned Aerial Systems (UAS) offers a potential solution to the scale-related inadequacies of satellite and ground-based observing systems. Using UAS, spatially distributed datasets can be collected at high resolution (i.e. cm), on demand, and can therefore facilitate improved understanding of mountain ecohydrology. We deployed a custom built multispectral - visible (RGB), near infrared (NIR) and thermal infrared (TIR) - UAS at a weekly interval over the Niwot Ridge Long Term Ecological Research (NWT LTER) saddle catchment at 3500masl in the Colorado Rockies. This system was used to map surface water pathways, land cover and topography, and quantify ecohydrologic variables including, snow depth, vegetation productivity and surface soil moisture at 5-50cm resolution across an 80ha study area. This presentation will discuss the techniques, methods and merits of using UAS derived multispectral data for ecohydrologic research in mountain regions. We will also present preliminary findings from our survey time series at NWT LTER and a discussion of the potential insights that these datasets can provide. Key questions to be addressed are: 1) how does spatial variability in snow depth impact soil moisture and vegetation productivity, 2) how can UAS help us to identify ecohydrologic `hotspots' and `hot moments' across heterogeneous landscapes.

  9. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  10. Integration of a satellite ground support system based on analysis of the satellite ground support domain

    Science.gov (United States)

    Pendley, R. D.; Scheidker, E. J.; Levitt, D. S.; Myers, C. R.; Werking, R. D.

    1994-11-01

    This analysis defines a complete set of ground support functions based on those practiced in real space flight operations during the on-orbit phase of a mission. These functions are mapped against ground support functions currently in use by NASA and DOD. Software components to provide these functions can be hosted on RISC-based work stations and integrated to provide a modular, integrated ground support system. Such modular systems can be configured to provide as much ground support functionality as desired. This approach to ground systems has been widely proposed and prototyped both by government institutions and commercial vendors. The combined set of ground support functions we describe can be used as a standard to evaluate candidate ground systems. This approach has also been used to develop a prototype of a modular, loosely-integrated ground support system, which is discussed briefly. A crucial benefit to a potential user is that all the components are flight-qualified, thus giving high confidence in their accuracy and reliability.

  11. Attractive manifold-based adaptive solar attitude control of satellites in elliptic orbits

    Science.gov (United States)

    Lee, Keum W.; Singh, Sahjendra N.

    2011-01-01

    The paper presents a novel noncertainty-equivalent adaptive (NCEA) control system for the pitch attitude control of satellites in elliptic orbits using solar radiation pressure (SRP). The satellite is equipped with two identical solar flaps to produce control moments. The adaptive law is based on the attractive manifold design using filtered signals for synthesis, which is a modification of the immersion and invariance (I&I) method. The control system has a modular controller-estimator structure and has separate tunable gains. A special feature of this NCEA law is that the trajectories of the satellite converge to a manifold in an extended state space, and the adaptive law recovers the performance of a deterministic controller. This recovery of performance cannot be obtained with certainty-equivalent adaptive (CEA) laws. Simulation results are presented which show that the NCEA law accomplishes precise attitude control of the satellite in an elliptic orbit, despite large parameter uncertainties.

  12. Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

    Science.gov (United States)

    Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

    2014-01-01

    The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. PMID:25215324

  13. Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

    Directory of Open Access Journals (Sweden)

    Hong Yin

    2014-01-01

    Full Text Available The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved.

  14. 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. ...

  15. Development of a PC-based ground support system for a small satellite instrument

    Science.gov (United States)

    Deschambault, Robert L.; Gregory, Philip R.; Spenler, Stephen; Whalen, Brian A.

    1993-11-01

    The importance of effective ground support for the remote control and data retrieval of a satellite instrument cannot be understated. Problems with ground support may include the need to base personnel at a ground tracking station for extended periods, and the delay between the instrument observation and the processing of the data by the science team. Flexible solutions to such problems in the case of small satellite systems are provided by using low-cost, powerful personal computers and off-the-shelf software for data acquisition and processing, and by using Internet as a communication pathway to enable scientists to view and manipulate satellite data in real time at any ground location. The personal computer based ground support system is illustrated for the case of the cold plasma analyzer flown on the Freja satellite. Commercial software was used as building blocks for writing the ground support equipment software. Several levels of hardware support, including unit tests and development, functional tests, and integration were provided by portable and desktop personal computers. Satellite stations in Saskatchewan and Sweden were linked to the science team via phone lines and Internet, which provided remote control through a central point. These successful strategies will be used on future small satellite space programs.

  16. DebriSat - A Planned Laboratory-Based Satellite Impact Experiment for Breakup Fragment Characterization

    Science.gov (United States)

    Liou, J.-C.; Fitz-Coy, N.; Werremeyer, M.; Huynh, T.; Voelker, M.; Opiela, J.

    2012-01-01

    DebriSat is a planned laboratory ]based satellite hypervelocity impact experiment. The goal of the project is to characterize the orbital debris that would be generated by a hypervelocity collision involving a modern satellite in low Earth orbit (LEO). The DebriSat project will update and expand upon the information obtained in the 1992 Satellite Orbital Debris Characterization Impact Test (SOCIT), which characterized the breakup of a 1960 's US Navy Transit satellite. There are three phases to this project: the design and fabrication of an engineering model representing a modern, 50-cm/50-kg class LEO satellite known as DebriSat; conduction of a laboratory-based hypervelocity impact to catastrophically break up the satellite; and characterization of the properties of breakup fragments down to 2 mm in size. The data obtained, including fragment size, area ]to ]mass ratio, density, shape, material composition, optical properties, and radar cross ]section distributions, will be used to supplement the DoD fs and NASA fs satellite breakup models to better describe the breakup outcome of a modern satellite. Updated breakup models will improve mission planning, environmental models, and event response. The DebriSat project is sponsored by the Air Force fs Space and Missile Systems Center and the NASA Orbital Debris Program Office. The design and fabrication of DebriSat is led by University of Florida with subject matter experts f support from The Aerospace Corporation. The major milestones of the project include the complete fabrication of DebriSat by September 2013, the hypervelocity impact of DebriSat at the Air Force fs Arnold Engineering Development Complex in early 2014, and fragment characterization and data analyses in late 2014.

  17. Simulation and Analysis of Autonomous Time Synchronization Based on Asynchronism Two-way Inter-satellite Link

    Science.gov (United States)

    Fang, L.; Yang, X. H.; Sun, B. Q.; Qin, W. J.; Kong, Y.

    2013-09-01

    The measurement of the inter-satellite link is one of the key techniques in the autonomous operation of satellite navigation system. Based on the asynchronism inter-satellite two-way measurement mode in GPS constellation, the reduction formula of the inter-satellite time synchronization is built in this paper. Moreover, the corrective method of main systematic errors is proposed. Inter-satellite two-way time synchronization is simulated on the basis of IGS (International GNSS Service) precise ephemeris. The impacts of the epoch domestication of asynchronism inter-satellite link pseudo-range, the initial orbit, and the main systematic errors on satellite time synchronization are analyzed. Furthermore, the broadcast clock error of each satellite is calculated by the ``centralized'' inter-satellite autonomous time synchronization. Simulation results show that the epoch domestication of asynchronism inter-satellite link pseudo-range and the initial orbit have little impact on the satellite clock errors, and thus they needn't be taken into account. The errors caused by the relativistic effect and the asymmetry of path travel have large impact on the satellite clock errors. These should be corrected with theoretical formula. Compared with the IGS precise clock error, the root mean square of the broadcast clock error of each satellite is about 0.4 ns.

  18. Implementing earth observation and advanced satellite based atmospheric sounders for water resource and climate modelling

    DEFF Research Database (Denmark)

    Boegh, E.; Dellwik, Ebba; Hahmann, Andrea N.

    2010-01-01

    This paper discusses preliminary remote sensing (MODIS) based hydrological modelling results for the Danish island Sjælland (7330 km2) in relation to project objectives and methodologies of a new research project “Implementing Earth observation and advanced satellite based atmospheric sounders....... For this purpose, a) internal catchment processes will be studied using a Distributed Temperature Sensing (DTS) system, b) Earth observations will be used to upscale from field to regional scales, and c) at the largest scale, satellite based atmospheric sounders and meso-scale climate modelling will be used...

  19. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  20. Multispectral Panoramic Imaging System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — International Electronic Machines Corporation, a leader in the design of precision imaging systems, will develop an innovative multispectral, panoramic imaging...

  1. A Novel Perceptual Hash Algorithm for Multispectral Image Authentication

    Directory of Open Access Journals (Sweden)

    Kaimeng Ding

    2018-01-01

    Full Text Available The perceptual hash algorithm is a technique to authenticate the integrity of images. While a few scholars have worked on mono-spectral image perceptual hashing, there is limited research on multispectral image perceptual hashing. In this paper, we propose a perceptual hash algorithm for the content authentication of a multispectral remote sensing image based on the synthetic characteristics of each band: firstly, the multispectral remote sensing image is preprocessed with band clustering and grid partition; secondly, the edge feature of the band subsets is extracted by band fusion-based edge feature extraction; thirdly, the perceptual feature of the same region of the band subsets is compressed and normalized to generate the perceptual hash value. The authentication procedure is achieved via the normalized Hamming distance between the perceptual hash value of the recomputed perceptual hash value and the original hash value. The experiments indicated that our proposed algorithm is robust compared to content-preserved operations and it efficiently authenticates the integrity of multispectral remote sensing images.

  2. An orbit determination algorithm for small satellites based on the magnitude of the earth magnetic field

    Science.gov (United States)

    Zagorski, P.; Gallina, A.; Rachucki, J.; Moczala, B.; Zietek, S.; Uhl, T.

    2018-06-01

    Autonomous attitude determination systems based on simple measurements of vector quantities such as magnetic field and the Sun direction are commonly used in very small satellites. However, those systems always require knowledge of the satellite position. This information can be either propagated from orbital elements periodically uplinked from the ground station or measured onboard by dedicated global positioning system (GPS) receiver. The former solution sacrifices satellite autonomy while the latter requires additional sensors which may represent a significant part of mass, volume, and power budget in case of pico- or nanosatellites. Hence, it is thought that a system for onboard satellite position determination without resorting to GPS receivers would be useful. In this paper, a novel algorithm for determining the satellite orbit semimajor-axis is presented. The methods exploit only the magnitude of the Earth magnetic field recorded onboard by magnetometers. This represents the first step toward an extended algorithm that can determine all orbital elements of the satellite. The method is validated by numerical analysis and real magnetic field measurements.

  3. In-Space Internet-Based Communications for Space Science Platforms Using Commercial Satellite Networks

    Science.gov (United States)

    Kerczewski, Robert J.; Bhasin, Kul B.; Fabian, Theodore P.; Griner, James H.; Kachmar, Brian A.; Richard, Alan M.

    1999-01-01

    The continuing technological advances in satellite communications and global networking have resulted in commercial systems that now can potentially provide capabilities for communications with space-based science platforms. This reduces the need for expensive government owned communications infrastructures to support space science missions while simultaneously making available better service to the end users. An interactive, high data rate Internet type connection through commercial space communications networks would enable authorized researchers anywhere to control space-based experiments in near real time and obtain experimental results immediately. A space based communications network architecture consisting of satellite constellations connecting orbiting space science platforms to ground users can be developed to provide this service. The unresolved technical issues presented by this scenario are the subject of research at NASA's Glenn Research Center in Cleveland, Ohio. Assessment of network architectures, identification of required new or improved technologies, and investigation of data communications protocols are being performed through testbed and satellite experiments and laboratory simulations.

  4. Satellite-Based actual evapotranspiration over drying semiarid terrain in West-Africa

    NARCIS (Netherlands)

    Schuttemeyer, D.; Schillings, Ch.; Moene, A.F.; Bruin, de H.A.R.

    2007-01-01

    A simple satellite-based algorithm for estimating actual evaporation based on Makkink¿s equation is applied to a seasonal cycle in 2002 at three test sites in Ghana, West Africa: at a location in the humid tropical southern region and two in the drier northern region. The required input for the

  5. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    As accuracy of satellite precipitation estimates improves and observation frequency increases, application of those data to societal benefit areas, such as weather forecasts and flood predictions, is expected, in addition to research of precipitation climatology to analyze precipitation systems. There is, however, limitation on single satellite observation in coverage and frequency. Currently, the Global Precipitation Measurement (GPM) mission is scheduled under international collaboration to fulfill various user requirements that cannot be achieved by the single satellite, like the Tropical Rainfall Measurement Mission (TRMM). The GPM mission is an international mission to achieve high-accurate and high-frequent rainfall observation over a global area. GPM is composed of a TRMM-like non-sun-synchronous orbit satellite (GPM core satellite) and constellation of satellites carrying microwave radiometer instruments. The GPM core satellite carries the Dual-frequency Precipitation Radar (DPR), which is being developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and microwave radiometer provided by the National Aeronautics and Space Administration (NASA). Development of DPR instrument is in good progress for scheduled launch in 2013, and DPR Critical Design Review has completed in July - September 2009. Constellation satellites, which carry a microwave imager and/or sounder, are planned to be launched around 2013 by each partner agency for its own purpose, and will contribute to extending coverage and increasing frequency. JAXA's future mission, the Global Change Observation Mission (GCOM) - Water (GCOM-W) satellite will be one of constellation satellites. The first generation of GCOM-W satellite is scheduled to be launched in 2011, and it carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is being developed based on the experience of the AMSR-E on EOS Aqua satellite

  6. Analysis of Satellite Drag Coefficient Based on Wavelet Transform

    Science.gov (United States)

    Liu, Wei; Wang, Ronglan; Liu, Siqing

    Abstract: Drag coefficient sequence was obtained by solving Tiangong1 continuous 55days GPS orbit data with different arc length. The same period solar flux f10.7 and geomagnetic index Ap ap series were high and low frequency multi-wavelet decomposition. Statistical analysis results of the layers sliding correlation between space environmental parameters and decomposition of Cd, showed that the satellite drag coefficient sequence after wavelet decomposition and the corresponding level of f10.7 Ap sequence with good lag correlation. It also verified that the Cd prediction is feasible. Prediction residuals of Cd with different regression models and different sample length were analysed. The results showed that the case was best when setting sample length 20 days and f10.7 regression model were used. It also showed that NRLMSIS-00 model's response in the region of 350km (Tiangong's altitude) and low-middle latitude (Tiangong's inclination) is excessive in ascent stage of geomagnetic activity Ap and is inadequate during fall off segment. Additionally, the low-frequency decomposition components NRLMSIS-00 model's response is appropriate in f10.7 rising segment. High frequency decomposition section, Showed NRLMSIS-00 model's response is small-scale inadequate during f10.7 ascent segment and is reverse in decline of f10.7. Finally, the potential use of a summary and outlook were listed; This method has an important reference value to improve the spacecraft orbit prediction accuracy. Key words: wavelet transform; drag coefficient; lag correlation; Tiangong1;space environment

  7. Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

    2012-12-01

    Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

  8. A MEMS-based Adaptive AHRS for Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Hussain, Dil Muhammed Akbar; Soltani, Mohsen

    2015-01-01

    Satellite tracking is a challenging task for marine applications. An attitude determination system should estimate the wave disturbances on the ship body accurately. To achieve this, an Attitude Heading Reference System (AHRS) based on Micro-Electro-Mechanical Systems (MEMS) sensors, composed...... of three-axis gyroscope, accelerometer and magnetometer, is developed for Marine Satellite Tracking Antenna (MSTA). In this paper, the attitude determination algorithm is improved using an adaptive mechanism that tunes the attitude estimator parameters based on an estimation of ship motion frequency...

  9. Application of support vector machine for classification of multispectral data

    International Nuclear Information System (INIS)

    Bahari, Nurul Iman Saiful; Ahmad, Asmala; Aboobaider, Burhanuddin Mohd

    2014-01-01

    In this paper, support vector machine (SVM) is used to classify satellite remotely sensed multispectral data. The data are recorded from a Landsat-5 TM satellite with resolution of 30x30m. SVM finds the optimal separating hyperplane between classes by focusing on the training cases. The study area of Klang Valley has more than 10 land covers and classification using SVM has been done successfully without any pixel being unclassified. The training area is determined carefully by visual interpretation and with the aid of the reference map of the study area. The result obtained is then analysed for the accuracy and visual performance. Accuracy assessment is done by determination and discussion of Kappa coefficient value, overall and producer accuracy for each class (in pixels and percentage). While, visual analysis is done by comparing the classification data with the reference map. Overall the study shows that SVM is able to classify the land covers within the study area with a high accuracy

  10. Radiation exposure near Chernobyl based on analysis of satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Marvin; Ustin, Susan [University of California, Laboratory for Energy-related Health Research, CA (United States); Warman, Edward A [Stone and Webster Engineering Corp., Boston, MA (United States)

    1987-12-01

    Radiation-induced damage in conifers adjacent to the damaged Chernobyl nuclear power plant has been evaluated using LANDSAT Thematic Mapper satellite images. Eight images acquired between April 22, 1986 and May 15, 1987 were used to assess the extent and magnitude of radiation effects on pine trees within 10 km of the reactor site. The timing and spatial extent of vegetation damaged was used to estimate the radiation doses in the near field around the Chernobyl nuclear power station and to derive dose rates as a function of time during and after the accident. A normalized vegetation index was developed from the TM spectral band data to visually demonstrate the damage and mortality to nearby conifer stands. The earliest date showing detectable injury 1 km west of the reactor unit was June 16, 1986. Subsequent dates revealed continued expansion of the affected areas to the west, north, and south. The greatest aerial expansion of this area occurred by October 15, 1986, with vegetation changes evident up to 5 km west, 2 km south, and 2 km north of the damaged Reactor Unit 4. By May 11, 1987, further scene changes were due principally to removal and mitigation efforts by the Soviet authorities. Areas showing spectral evidence of vegetation damage during the previous growing season do not show evidence of recovery and reflectance in the TM Bands 4 and 3 remain higher than surrounding vegetation, which infers that the trees are dead. The patterns of spectral change indicative of vegetation stress are consistent with changes expected for radiation injury and mortality. The extent and the timing of these effects enabled developing an integrated radiation dose estimate, which was combined with the information regarding the characteristics of radionuclide mix to provide an estimate of maximum dose rates during the early period of the accident. The derived peak dose rates during the 10-day release in the accident are high and are estimated at about 0.5 to 1 rad per hour. These

  11. RIGOROUS GEOREFERENCING OF ALSAT-2A PANCHROMATIC AND MULTISPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    I. Boukerch

    2013-04-01

    Full Text Available The exploitation of the full geometric capabilities of the High-Resolution Satellite Imagery (HRSI, require the development of an appropriate sensor orientation model. Several authors studied this problem; generally we have two categories of geometric models: physical and empirical models. Based on the analysis of the metadata provided with ALSAT-2A, a rigorous pushbroom camera model can be developed. This model has been successfully applied to many very high resolution imagery systems. The relation between the image and ground coordinates by the time dependant collinearity involving many coordinates systems has been tested. The interior orientation parameters must be integrated in the model, the interior parameters can be estimated from the viewing angles corresponding to the pointing directions of any detector, these values are derived from cubic polynomials provided in the metadata. The developed model integrates all the necessary elements with 33 unknown. All the approximate values of the 33 unknowns parameters may be derived from the informations contained in the metadata files provided with the imagery technical specifications or they are simply fixed to zero, so the condition equation is linearized and solved using SVD in a least square sense in order to correct the initial values using a suitable number of well-distributed GCPs. Using Alsat-2A images over the town of Toulouse in the south west of France, three experiments are done. The first is about 2D accuracy analysis using several sets of parameters. The second is about GCPs number and distribution. The third experiment is about georeferencing multispectral image by applying the model calculated from panchromatic image.

  12. Multispectral colormapping using penalized least square regression

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

    2010-01-01

    The authors propose a novel method to map a multispectral image into the device independent color space CIE-XYZ. This method provides a way to visualize multispectral images by predicting colorvalues from spectral values while maintaining interpretability and is tested on a light emitting diode...... that the interpretability improves significantly but comes at the cost of slightly worse predictability....

  13. Multispectral imaging of wok fried vegetables

    DEFF Research Database (Denmark)

    Løje, Hanne; Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder

    2011-01-01

    This paper shows how multispectral images can be used to assess color change over time in wok fried vegetables. We present results where feature selection was performed with sparse methods from the multispectral images to detect the color changes of wok fried carrots and celeriac stored at +5°C...

  14. Wetland Vegetation Integrity Assessment with Low Altitude Multispectral Uav Imagery

    Science.gov (United States)

    Boon, M. A.; Tesfamichael, S.

    2017-08-01

    The use of multispectral sensors on Unmanned Aerial Vehicles (UAVs) was until recently too heavy and bulky although this changed in recent times and they are now commercially available. The focus on the usage of these sensors is mostly directed towards the agricultural sector where the focus is on precision farming. Applications of these sensors for mapping of wetland ecosystems are rare. Here, we evaluate the performance of low altitude multispectral UAV imagery to determine the state of wetland vegetation in a localised spatial area. Specifically, NDVI derived from multispectral UAV imagery was used to inform the determination of the integrity of the wetland vegetation. Furthermore, we tested different software applications for the processing of the imagery. The advantages and disadvantages we experienced of these applications are also shortly presented in this paper. A JAG-M fixed-wing imaging system equipped with a MicaScene RedEdge multispectral camera were utilised for the survey. A single surveying campaign was undertaken in early autumn of a 17 ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa. Structure-from-motion photogrammetry software was used to reconstruct the camera position's and terrain features to derive a high resolution orthoretified mosaic. MicaSense Atlas cloud-based data platform, Pix4D and PhotoScan were utilised for the processing. The WET-Health level one methodology was followed for the vegetation assessment, where wetland health is a measure of the deviation of a wetland's structure and function from its natural reference condition. An on-site evaluation of the vegetation integrity was first completed. Disturbance classes were then mapped using the high resolution multispectral orthoimages and NDVI. The WET-Health vegetation module completed with the aid of the multispectral UAV products indicated that the vegetation of the wetland is largely modified ("D" PES Category) and that the condition is expected to

  15. Multispectral image enhancement processing for microsat-borne imager

    Science.gov (United States)

    Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

    2017-10-01

    With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

  16. Effectiveness evaluation of double-layered satellite network with laser and microwave hybrid links based on fuzzy analytic hierarchy process

    Science.gov (United States)

    Zhang, Wei; Rao, Qiaomeng

    2018-01-01

    In order to solve the problem of high speed, large capacity and limited spectrum resources of satellite communication network, a double-layered satellite network with global seamless coverage based on laser and microwave hybrid links is proposed in this paper. By analyzing the characteristics of the double-layered satellite network with laser and microwave hybrid links, an effectiveness evaluation index system for the network is established. And then, the fuzzy analytic hierarchy process, which combines the analytic hierarchy process and the fuzzy comprehensive evaluation theory, is used to evaluate the effectiveness of the double-layered satellite network with laser and microwave hybrid links. Furthermore, the evaluation result of the proposed hybrid link network is obtained by simulation. The effectiveness evaluation process of the proposed double-layered satellite network with laser and microwave hybrid links can help to optimize the design of hybrid link double-layered satellite network and improve the operating efficiency of the satellite system.

  17. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  18. Using satellite imagery to evaluate land-based camouflage assets

    CSIR Research Space (South Africa)

    Baumbach, J

    2006-02-01

    Full Text Available to Evaluate Land-based Camouflage Assets J BAUMBACH, M LUBBE CSIR Defence, Peace, Safety and security, PO Box 395, Pretoria, 0001, South Africa Email: jbaumbac@csir.co.za ABSTRACT A camouflage field trial experiment was conducted. For the experiment... analysis, change detection, un-supervised classification, supervised classification and object based classification. RESULTS The following table shows a summary of the different targets, and whether it was detected ( ) or not detected (x), using...

  19. Identification of High-Variation Fields based on Open Satellite Imagery

    DEFF Research Database (Denmark)

    Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus

    2017-01-01

    . The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update......This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective...

  20. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gotseff, Peter [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  1. The Huber’s Method-based Gas Concentration Reconstruction in Multicomponent Gas Mixtures from Multispectral Laser Measurements under Noise Overshoot Conditions

    Directory of Open Access Journals (Sweden)

    V. A. Gorodnichev

    2016-01-01

    Full Text Available Laser gas analysers are the most promising for the rapid quantitative analysis of gaseous air pollution. A laser gas analysis problem is that there are instable results in reconstruction of gas mixture components concentration under real noise in the recorded laser signal. This necessitates using the special processing algorithms. When reconstructing the quantitative composition of multi-component gas mixtures from the multispectral laser measurements are efficiently used methods such as Tikhonov regularization, quasi-solution search, and finding of Bayesian estimators. These methods enable using the single measurement results to determine the quantitative composition of gas mixtures under measurement noise. In remote sensing the stationary gas formations or in laboratory analysis of the previously selected (when the gas mixture is stationary air samples the reconstruction procedures under measurement noise of gas concentrations in multicomponent mixtures can be much simpler. The paper considers a problem of multispectral laser analysis of stationary gas mixtures for which it is possible to conduct a series of measurements. With noise overshoots in the recorded laser signal (and, consequently, overshoots of gas concentrations determined by a single measurement must be used stable (robust estimation techniques for substantial reducing an impact of the overshoots on the estimate of required parameters. The paper proposes the Huber method to determine gas concentrations in multicomponent mixtures under signal overshoot. To estimate the value of Huber parameter and the efficiency of Huber's method to find the stable estimates of gas concentrations in multicomponent stationary mixtures from the laser measurements the mathematical modelling was conducted. Science & Education of the Bauman MSTU 108 The mathematical modelling results show that despite the considerable difference among the errors of the mixture gas components themselves a character of

  2. Satellite-based empirical models linking river plume dynamics with hypoxic area andvolume

    Science.gov (United States)

    Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 < 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and ...

  3. Motivating Students to Develop Satellites in a Problem and Project-Based Learning Environment

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Nielsen, Jens Frederik Dalsgaard; Zhou, Chunfang

    2013-01-01

    During the last decade, a total of three student satellites have been developed by engineering students in a Problem and Project-Based Learning (PBL) environment at Aalborg University (AAU), Denmark. As solving such a complex project, we emphasize that a high level of motivation is needed for the...

  4. Satellites vs. fiber optics based networks and services - Road map to strategic planning

    Science.gov (United States)

    Marandi, James H. R.

    An overview of a generic telecommunications network and its components is presented, and the current developments in satellite and fiber optics technologies are discussed with an eye on the trends in industry. A baseline model is proposed, and a cost comparison of fiber- vs satellite-based networks is made. A step-by-step 'road map' to the successful strategic planning of telecommunications services and facilities is presented. This road map provides for optimization of the current and future networks and services through effective utilization of both satellites and fiber optics. The road map is then applied to different segments of the telecommunications industry and market place, to show its effectiveness for the strategic planning of executives of three types: (1) those heading telecommunications manufacturing concerns, (2) those leading communication service companies, and (3) managers of telecommunication/MIS departments of major corporations. Future networking issues, such as developments in integrated-services digital network standards and technologies, are addressed.

  5. A Framework for Building an Interactive Satellite TV Based M-Learning Environment

    Directory of Open Access Journals (Sweden)

    Ghassan Issa

    2010-07-01

    Full Text Available This paper presents a description of an interactive satellite TV based mobile learning (STV-ML framework, in which a satellite TV station is used as an integral part of a comprehensive interactive mobile learning (M-Learning environment. The proposed framework assists in building a reliable, efficient, and cost-effective environment to meet the growing demands of M-Learning all over the world, especially in developing countries. It utilizes recent advances in satellite reception, broadcasting technologies, and interactive TV to facilitate the delivery of gigantic learning materials. This paper also proposed a simple and flexible three-phase implementation methodology which includes construction of earth station, expansion of broadcasting channels, and developing true user interactivity. The proposed framework and implementation methodology ensure the construction of a true, reliable, and cost effective M-Learning system that can be used efficiently and effectively by a wide range of users and educational institutions to deliver ubiquitous learning.

  6. Rapid core field variations during the satellite era: Investigations using stochastic process based field models

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Gillet, Nicolas

    We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to tradition...... physical hypotheses can be tested by asking questions of the entire ensemble of core field models, rather than by interpreting any single model.......We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to traditional...... regularization methods based on minimizing the square of second or third time derivative. We invert satellite and observatory data directly by adopting the external field and crustal field modelling framework of the CHAOS model, but apply the stochastic process method of Gillet et al. (2013) to the core field...

  7. A Large Scale Problem Based Learning inter-European Student Satellite Construction Project

    DEFF Research Database (Denmark)

    Nielsen, Jens Frederik Dalsgaard; Alminde, Lars; Bisgaard, Morten

    2006-01-01

    that electronic communication technology was vital within the project. Additionally the SSETI EXPRESS project implied the following problems it didn’t fit to a standard semester - 18 months for the satellite project compared to 5/6 months for a “normal” semester project. difficulties in integrating the tasks......A LARGE SCALE PROBLEM BASED LEARNING INTER-EUROPEAN STUDENT SATELLITE CONSTRUCTION PROJECT This paper describes the pedagogical outcome of a large scale PBL experiment. ESA (European Space Agency) Education Office launched January 2004 an ambitious project: Let students from all over Europe build....... The satellite was successfully launched on October 27th 2005 (http://www.express.space.aau.dk). The project was a student driven project with student project responsibility adding at lot of international experiences and project management skills to the outcome of more traditional one semester, single group...

  8. (Multiawesome) Multispectral Multiprobe Monitoring

    International Nuclear Information System (INIS)

    Scheibelhofer, Otto; Hohl, Roland; Sacher, Stefan; Menezes, Jose; Khinast, Johannes

    2012-01-01

    Full text: In the food and pharmaceutical industry, near-infrared spectroscopy is a more and more frequently used tool for process monitoring. This is motivated by its fast and non-invasive nature. Further on, no extensive sample preparation is needed, enabling the use as an online process analytical tool. However, this comes with the drawback of large amounts of correlated data, often influenced by many external factors. Therefore, a lot of effort has to be invested in the correct use of mathematical tools to extract the information of interest. Here we put to use a new prototype NIR spectrometer (by EVK, Raaba, Austria), based on an established chemical imaging system, to enable the reading of several attached probes at the same time. However, even when investigating the same sample, there are slight differences from one probe to another. On the one hand, this is caused by their different eld of view; on the other hand, these are to be avoided disturbances, on nominally similar probes. Therefore, it is necessary to identify these disturbances and consider them in the spectral interpretation. This should allow the monitoring of processes at different positions, as well as the simultaneous monitoring of different processes, with one measurement system. In this work, data from the prototype system are presented in use on a pharmaceutical process. It is shown how to overcome some of the appearing difficulties when dealing with a multiprobe system, in order to enable fast and robust process monitoring, and render process control. (author)

  9. Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

    Science.gov (United States)

    Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

    2017-11-01

    Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

  10. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge

  11. A Satellite-Based Sunshine Duration Climate Data Record for Europe and Africa

    Directory of Open Access Journals (Sweden)

    Steffen Kothe

    2017-05-01

    Full Text Available Besides 2 m - temperature and precipitation, sunshine duration is one of the most important and commonly used parameter in climatology, with measured time series of partly more than 100 years in length. EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF presents a climate data record for daily and monthly sunshine duration (SDU for Europe and Africa. Basis for the advanced retrieval is a highly resolved satellite product of the direct solar radiation from measurements by Meteosat satellites 2 to 10. The data record covers the time period 1983 to 2015 with a spatial resolution of 0.05° × 0.05°. The comparison against ground-based data shows high agreement but also some regional differences. Sunshine duration is overestimated by the satellite-based data in many regions, compared to surface data. In West and Central Africa, low clouds seem to be the reason for a stronger overestimation of sunshine duration in this region (up to 20% for monthly sums. For most stations, the overestimation is low, with a bias below 7.5 h for monthly sums and below 0.4 h for daily sums. A high correlation of 0.91 for daily SDU and 0.96 for monthly SDU also proved the high agreement with station data. As SDU is based on a stable and homogeneous climate data record of more than 30 years length, it is highly suitable for climate applications, such as trend estimates.

  12. Introducing the VISAGE project - Visualization for Integrated Satellite, Airborne, and Ground-based data Exploration

    Science.gov (United States)

    Gatlin, P. N.; Conover, H.; Berendes, T.; Maskey, M.; Naeger, A. R.; Wingo, S. M.

    2017-12-01

    A key component of NASA's Earth observation system is its field experiments, for intensive observation of particular weather phenomena, or for ground validation of satellite observations. These experiments collect data from a wide variety of airborne and ground-based instruments, on different spatial and temporal scales, often in unique formats. The field data are often used with high volume satellite observations that have very different spatial and temporal coverage. The challenges inherent in working with such diverse datasets make it difficult for scientists to rapidly collect and analyze the data for physical process studies and validation of satellite algorithms. The newly-funded VISAGE project will address these issues by combining and extending nascent efforts to provide on-line data fusion, exploration, analysis and delivery capabilities. A key building block is the Field Campaign Explorer (FCX), which allows users to examine data collected during field campaigns and simplifies data acquisition for event-based research. VISAGE will extend FCX's capabilities beyond interactive visualization and exploration of coincident datasets, to provide interrogation of data values and basic analyses such as ratios and differences between data fields. The project will also incorporate new, higher level fused and aggregated analysis products from the System for Integrating Multi-platform data to Build the Atmospheric column (SIMBA), which combines satellite and ground-based observations into a common gridded atmospheric column data product; and the Validation Network (VN), which compiles a nationwide database of coincident ground- and satellite-based radar measurements of precipitation for larger scale scientific analysis. The VISAGE proof-of-concept will target "golden cases" from Global Precipitation Measurement Ground Validation campaigns. This presentation will introduce the VISAGE project, initial accomplishments and near term plans.

  13. Multivariate alteration detection (MAD) in multispectral, bi-temporal image data: A new approach to change detction studies

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut

    This paper introduces a new orthogonal transformation, the multivariate alteration detection (MAD) transformation, based on an established multivariate statistical technique canonical correlation analysis. The theory for canonical correlation analysis is sketched and a result necessary...... for the definition of the MAD transformation is proven. As opposed to traditional univariate change detection schemes our scheme transforms two sets of multivariate observations (e.g. two multispectral satellite images covering the same geographical area acquired at different points in time) into a difference...... between two linear combinations of the original variables explaining maximal change (i.e. the difference explaining maximal variance) in all variables simultaneously. The MAD transformation is invariant to linear scaling. The MAD transformation can be used iteratively. First, it can be used to detect...

  14. Solar Power Satellites: Reconsideration as Renewable Energy Source Based on Novel Approaches

    Science.gov (United States)

    Ellery, Alex

    2017-04-01

    Solar power satellites (SPS) are a solar energy generation mechanism that captures solar energy in space and converts this energy into microwave for transmission to Earth-based rectenna arrays. They offer a constant, high integrated energy density of 200 W/m2 compared to <10 W/m2 for other renewable energy sources. Despite this promise as a clean energy source, SPS have been relegated out of consideration due to their enormous cost and technological challenge. It has been suggested that for solar power satellites to become economically feasible, launch costs must decrease from their current 20,000/kg to <200/kg. Even with the advent of single-stage-to-orbit launchers which propose launch costs dropping to 2,000/kg, this will not be realized. Yet, the advantages of solar power satellites are many including the provision of stable baseload power. Here, I present a novel approach to reduce the specific cost of solar power satellites to 1/kg by leveraging two enabling technologies - in-situ resource utilization of lunar material and 3D printing of this material. Specifically, we demonstrate that electric motors may be constructed from lunar material through 3D printing representing a major step towards the development of self-replicating machines. Such machines have the capacity to build solar power satellites on the Moon, thereby bypassing the launch cost problem. The productive capacity of self-replicating machines favours the adoption of large constellations of small solar power satellites. This opens up additional clean energy options for combating climate change by meeting the demands for future global energy.

  15. CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    C. T. Liao

    2012-07-01

    Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  16. Classification by Using Multispectral Point Cloud Data

    Science.gov (United States)

    Liao, C. T.; Huang, H. H.

    2012-07-01

    Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  17. First Earth-based observations of Neptune's satellite Proteus

    Science.gov (United States)

    Colas, F.; Buil, C.

    1992-08-01

    Proteus (Neptune III) was discovered from Voyager Spacecraft images in 1989 (Smith, 1989). It was never observed from ground-based observatories because of its magnitude (m = 20.3) and closeness to Neptune (maximum elongation = 6 arcsec). In October 1991, we used the 2.2 m telescope at the European Southern Observatory (La Silla, Chile) to look for it. The observation success is mainly due to the use of an anti blooming CCD and to good seeing conditions (less than 1 arcsec). We give the differential positions of Proteus referred to Neptune and we compare with theoretical positions issued from Voyager's data (Owen et al., 1991). We found that the rms orbital residual was about 0.1 arcsec.

  18. Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

    Science.gov (United States)

    Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

    2013-12-01

    Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

  19. A Satellite-Based Multi-Pollutant Index of Global Air Quality

    Science.gov (United States)

    Cooper, Mathew J.; Martin, Randall V.; vanDonkelaar, Aaron; Lamsal, Lok; Brauer, Michael; Brook, Jeffrey R.

    2012-01-01

    Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

  20. Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present

    OpenAIRE

    Tarnavsky, Elena; Grimes, David; Maidment, Ross; Black, Emily; Allan, Richard; Stringer, Marc; Chadwick, Robin; Kayitakire, Francois

    2014-01-01

    Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the produ...

  1. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

    Science.gov (United States)

    Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

    2006-01-01

    We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

  2. A MODIS-Based Robust Satellite Technique (RST for Timely Detection of Oil Spilled Areas

    Directory of Open Access Journals (Sweden)

    Teodosio Lacava

    2017-02-01

    Full Text Available Natural crude-oil seepages, together with the oil released into seawater as a consequence of oil exploration/production/transportation activities, and operational discharges from tankers (i.e., oil dumped during cleaning actions represent the main sources of sea oil pollution. Satellite remote sensing can be a useful tool for the management of such types of marine hazards, namely oil spills, mainly owing to the synoptic view and the good trade-off between spatial and temporal resolution, depending on the specific platform/sensor system used. In this paper, an innovative satellite-based technique for oil spill detection, based on the general robust satellite technique (RST approach, is presented. It exploits the multi-temporal analysis of data acquired in the visible channels of the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua satellite in order to automatically and quickly detect the presence of oil spills on the sea surface, with an attempt to minimize “false detections” caused by spurious effects associated with, for instance, cloud edges, sun/satellite geometries, sea currents, etc. The oil spill event that occurred in June 2007 off the south coast of Cyprus in the Mediterranean Sea has been considered as a test case. The resulting data, the reliability of which has been evaluated by both carrying out a confutation analysis and comparing them with those provided by the application of another independent MODIS-based method, showcase the potential of RST in identifying the presence of oil with a high level of accuracy.

  3. Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

    Science.gov (United States)

    Xi, B.; Dong, X.; Wu, P.; Qiu, S.

    2017-12-01

    A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

  4. Integration between terrestrial-based and satellite-based land mobile communications systems

    Science.gov (United States)

    Arcidiancono, Antonio

    1990-01-01

    A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

  5. Volcview: A Web-Based Platform for Satellite Monitoring of Volcanic Activity and Eruption Response

    Science.gov (United States)

    Schneider, D. J.; Randall, M.; Parker, T.

    2014-12-01

    The U.S. Geological Survey (USGS), in cooperation with University and State partners, operates five volcano observatories that employ specialized software packages and computer systems to process and display real-time data coming from in-situ geophysical sensors and from near-real-time satellite sources. However, access to these systems both inside and from outside the observatory offices are limited in some cases by factors such as software cost, network security, and bandwidth. Thus, a variety of Internet-based tools have been developed by the USGS Volcano Science Center to: 1) Improve accessibility to data sources for staff scientists across volcano monitoring disciplines; 2) Allow access for observatory partners and for after-hours, on-call duty scientists; 3) Provide situational awareness for emergency managers and the general public. Herein we describe VolcView (volcview.wr.usgs.gov), a freely available, web-based platform for display and analysis of near-real-time satellite data. Initial geographic coverage is of the volcanoes in Alaska, the Russian Far East, and the Commonwealth of the Northern Mariana Islands. Coverage of other volcanoes in the United States will be added in the future. Near-real-time satellite data from NOAA, NASA and JMA satellite systems are processed to create image products for detection of elevated surface temperatures and volcanic ash and SO2 clouds. VolcView uses HTML5 and the canvas element to provide image overlays (volcano location and alert status, annotation, and location information) and image products that can be queried to provide data values, location and measurement capabilities. Use over the past year during the eruptions of Pavlof, Veniaminof, and Cleveland volcanoes in Alaska by the Alaska Volcano Observatory, the National Weather Service, and the U.S. Air Force has reinforced the utility of shared situational awareness and has guided further development. These include overlay of volcanic cloud trajectory and

  6. A Novel Strategy for Very-Large-Scale Cash-Crop Mapping in the Context of Weather-Related Risk Assessment, Combining Global Satellite Multispectral Datasets, Environmental Constraints, and In Situ Acquisition of Geospatial Data.

    Science.gov (United States)

    Dell'Acqua, Fabio; Iannelli, Gianni Cristian; Torres, Marco A; Martina, Mario L V

    2018-02-14

    Cash crops are agricultural crops intended to be sold for profit as opposed to subsistence crops, meant to support the producer, or to support livestock. Since cash crops are intended for future sale, they translate into large financial value when considered on a wide geographical scale, so their production directly involves financial risk. At a national level, extreme weather events including destructive rain or hail, as well as drought, can have a significant impact on the overall economic balance. It is thus important to map such crops in order to set up insurance and mitigation strategies. Using locally generated data-such as municipality-level records of crop seeding-for mapping purposes implies facing a series of issues like data availability, quality, homogeneity, etc. We thus opted for a different approach relying on global datasets. Global datasets ensure homogeneity and availability of data, although sometimes at the expense of precision and accuracy. A typical global approach makes use of spaceborne remote sensing, for which different land cover classification strategies are available in literature at different levels of cost and accuracy. We selected the optimal strategy in the perspective of a global processing chain. Thanks to a specifically developed strategy for fusing unsupervised classification results with environmental constraints and other geospatial inputs including ground-based data, we managed to obtain good classification results despite the constraints placed. The overall production process was composed using "good-enough" algorithms at each step, ensuring that the precision, accuracy, and data-hunger of each algorithm was commensurate to the precision, accuracy, and amount of data available. This paper describes the tailored strategy developed on the occasion as a cooperation among different groups with diverse backgrounds, a strategy which is believed to be profitably reusable in other, similar contexts. The paper presents the problem

  7. A Novel Strategy for Very-Large-Scale Cash-Crop Mapping in the Context of Weather-Related Risk Assessment, Combining Global Satellite Multispectral Datasets, Environmental Constraints, and In Situ Acquisition of Geospatial Data

    Directory of Open Access Journals (Sweden)

    Fabio Dell’Acqua

    2018-02-01

    Full Text Available Cash crops are agricultural crops intended to be sold for profit as opposed to subsistence crops, meant to support the producer, or to support livestock. Since cash crops are intended for future sale, they translate into large financial value when considered on a wide geographical scale, so their production directly involves financial risk. At a national level, extreme weather events including destructive rain or hail, as well as drought, can have a significant impact on the overall economic balance. It is thus important to map such crops in order to set up insurance and mitigation strategies. Using locally generated data—such as municipality-level records of crop seeding—for mapping purposes implies facing a series of issues like data availability, quality, homogeneity, etc. We thus opted for a different approach relying on global datasets. Global datasets ensure homogeneity and availability of data, although sometimes at the expense of precision and accuracy. A typical global approach makes use of spaceborne remote sensing, for which different land cover classification strategies are available in literature at different levels of cost and accuracy. We selected the optimal strategy in the perspective of a global processing chain. Thanks to a specifically developed strategy for fusing unsupervised classification results with environmental constraints and other geospatial inputs including ground-based data, we managed to obtain good classification results despite the constraints placed. The overall production process was composed using “good-enough" algorithms at each step, ensuring that the precision, accuracy, and data-hunger of each algorithm was commensurate to the precision, accuracy, and amount of data available. This paper describes the tailored strategy developed on the occasion as a cooperation among different groups with diverse backgrounds, a strategy which is believed to be profitably reusable in other, similar contexts. The

  8. MULTISPECTRAL PANSHARPENING APPROACH USING PULSE-COUPLED NEURAL NETWORK SEGMENTATION

    Directory of Open Access Journals (Sweden)

    X. J. Li

    2018-04-01

    Full Text Available The paper proposes a novel pansharpening method based on the pulse-coupled neural network segmentation. In the new method, uniform injection gains of each region are estimated through PCNN segmentation rather than through a simple square window. Since PCNN segmentation agrees with the human visual system, the proposed method shows better spectral consistency. Our experiments, which have been carried out for both suburban and urban datasets, demonstrate that the proposed method outperforms other methods in multispectral pansharpening.

  9. Advantages of geosynchronous solar power satellites for terrestrial base-load electrical supply compared to other renewable energy sources - or why civilization needs solar power satellites

    Energy Technology Data Exchange (ETDEWEB)

    Strickland, J.K. Jr. [Texas Univ., Austin, TX (United States)

    1998-06-01

    The arguments in favour of using solar power satellites for primary base-load electrical supply are presented and compared with the advantages and drawbacks of other renewable energy sources, especially ground solar and wind systems. Popular misconceptions about energy use and the importation of space solar energy to the Earth`s surface are examined and discounted. Finally an optimal mix of space solar (focusing on geosynchronous solar power satellites), ground solar, and other energy sources is described which, it is argued, would be capable to meet future global energy demand. (UK)

  10. A Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

    Directory of Open Access Journals (Sweden)

    Young-Tack Park

    1997-06-01

    Full Text Available Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

  11. Developing a sustainable satellite-based environmental monitoring system In Nigeria

    Science.gov (United States)

    Akinyede, J. O.; Adepoju, K. A.; Akinluyi, F. O.; Anifowose, A. Y. B.

    2015-10-01

    Increased anthropogenic activities over the year have remained a major factor of the Earth changing environment. This phenomenon has given rise to a number of environmental degraded sites that characterize the Nigeria's landscape. The human-induced elements include gully erosion, mangrove ecosystems degradation, desertification and deforestation, particularly in the south east, Niger Delta, north east and south west of Nigeria respectively, as well as river flooding/flood plain inundation and land degradation around Kainji lake area. Because of little or no effective management measures, the attendant environmental hazards have been extremely damaging to the infrastructures and socio-economic development of the affected area. Hence, a concerted effort, through integrated and space-based research, is being intensified to manage and monitor the environment in order to restore the stability, goods and services of the environment. This has justified Nigeria's investment in its space programme, especially the launch of NigeriaSat-1, an Earth observation micro-satellite in constellation with five (5) other similar satellites, Alsat-1, China DMC, Bilsat-1, DEMOS and UK DMC belonging to Algeria, China, Turkey, Spain and United Kingdom respectively. The use of data from these satellites, particularly NigeriaSat-1, in conjunction with associated technologies has proved to be very useful in understanding the influence of both natural and human activities on the Nigeria's ecosystems and environment. The results of some researches on specific applications of Nigerian satellites are presented in this paper. Appropriate sustainable land and water resources management in the affected areas, based on Nigeria's satellite data capture and integration, are also discussed.

  12. Current trends in satellite based emergency mapping - the need for harmonisation

    Science.gov (United States)

    Voigt, Stefan

    2013-04-01

    During the past years, the availability and use of satellite image data to support disaster management and humanitarian relief organisations has largely increased. The automation and data processing techniques are greatly improving as well as the capacity in accessing and processing satellite imagery in getting better globally. More and more global activities via the internet and through global organisations like the United Nations or the International Charter Space and Major Disaster engage in the topic, while at the same time, more and more national or local centres engage rapid mapping operations and activities. In order to make even more effective use of this very positive increase of capacity, for the sake of operational provision of analysis results, for fast validation of satellite derived damage assessments, for better cooperation in the joint inter agency generation of rapid mapping products and for general scientific use, rapid mapping results in general need to be better harmonized, if not even standardized. In this presentation, experiences from various years of rapid mapping gained by the DLR Center for satellite based Crisis Information (ZKI) within the context of the national activities, the International Charter Space and Major Disasters, GMES/Copernicus etc. are reported. Furthermore, an overview on how automation, quality assurance and optimization can be achieved through standard operation procedures within a rapid mapping workflow is given. Building on this long term rapid mapping experience, and building on the DLR initiative to set in pace an "International Working Group on Satellite Based Emergency Mapping" current trends in rapid mapping are discussed and thoughts on how the sharing of rapid mapping information can be optimized by harmonizing analysis results and data structures are presented. Such an harmonization of analysis procedures, nomenclatures and representations of data as well as meta data are the basis to better cooperate within

  13. AMFIC Web Data Base - A Satellite System for the Monitoring and Forecasting of Atmospheric Pollution

    Directory of Open Access Journals (Sweden)

    P. Symeonidis

    2008-01-01

    Full Text Available In this work we present the contribution of the Laboratory of Atmospheric Pollution and Pollution Control Engineering of Democritus University of Thrace in the AMFIC-Air Monitoring and Forecasting In China European project. Within the framework of this project our laboratory in co-operation with DRAXIS company will create and manage a web satellite data base. This system will host atmospheric pollution satellite data for China and for the whole globe in general. Atmospheric pollution data with different spatial resolution such as O3 and NO2 total columns and measurements of other important trace gasses from GOME (ERS-2, SCIAMACHY (ENVISAT and OMI (EOS-AURA along with aerosol total load estimates from AATSR (ENVISAT will be brought to a common spatial and temporal resolution and become available to the scientific community in simple ascii files and maps format. Available will also be the results from the validation procedure of the satellite data with the use of ground-based observations and a set of high resolution maps and forecasts emerging from atmospheric pollution models. Data will be available for two geographical clusters. The one cluster includes the greater area of China and the other the whole globe. This integrated satellite system will be fully operational within the next two years and will also include a set of innovative tools that allow easy manipulation and analysis of the data. Automatic detection of features such as plumes and monitoring of their evolution, data covariance analysis enabling the detection of emission signatures of different sources, cluster analysis etc will be possible through those tools. The AMFIC satellite system shares a set of characteristics with its predecessor, AIRSAT. Here, we present some of these characteristics in order to bring out the contribution of such a system in atmospheric sciences.

  14. Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

    Science.gov (United States)

    Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

    2015-12-01

    One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

  15. A space weather forecasting system with multiple satellites based on a self-recognizing network.

    Science.gov (United States)

    Tokumitsu, Masahiro; Ishida, Yoshiteru

    2014-05-05

    This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  16. Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

    Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

  17. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

    Directory of Open Access Journals (Sweden)

    Masahiro Tokumitsu

    2014-05-01

    Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  18. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

    2017-04-01

    We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

  19. The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

    Science.gov (United States)

    Ronald E. McRoberts

    2010-01-01

    Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

  20. The attitude inversion method of geostationary satellites based on unscented particle filter

    Science.gov (United States)

    Du, Xiaoping; Wang, Yang; Hu, Heng; Gou, Ruixin; Liu, Hao

    2018-04-01

    The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.

  1. Satellite single-axis attitude determination based on Automatic Dependent Surveillance - Broadcast signals

    Science.gov (United States)

    Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei

    2017-10-01

    The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.

  2. Use of multispectral images and chemometrics in tomato seed studies

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

    During the production of tomato seeds, green tomatoes are normally discarded before seed extraction irrespective of their maturity stage. Studies indicate that seeds from green tomatoes may reach be able to reach full germination capacity. Thus the potential of multispectral imaging for non......-destructive discrimination of seeds based on their germination capacity was investigated. A total of 840 seeds extracted from green and red tomatoes were divided into two sets; a training set and a test set consisting of 648 and 192 seeds respectively. Each set consisted of 96 seeds from green tomatoes. The multispectral...... images of the seeds were captured and normalized canonical discriminant analysis was used to analyse the images. Germination tests were performed and seeds that subsequently germinated were recorded as viable. The viable seeds were classified with 99% and 98% accuracy for the training and test set...

  3. Multispectral and polarimetric photodetection using a plasmonic metasurface

    Science.gov (United States)

    Pelzman, Charles; Cho, Sang-Yeon

    2018-01-01

    We present a metasurface-integrated Si 2-D CMOS sensor array for multispectral and polarimetric photodetection applications. The demonstrated sensor is based on the polarization selective extraordinary optical transmission from periodic subwavelength nanostructures, acting as artificial atoms, known as meta-atoms. The meta-atoms were created by patterning periodic rectangular apertures that support optical resonance at the designed spectral bands. By spatially separating meta-atom clusters with different lattice constants and orientations, the demonstrated metasurface can convert the polarization and spectral information of an optical input into a 2-D intensity pattern. As a proof-of-concept experiment, we measured the linear components of the Stokes parameters directly from captured images using a CMOS camera at four spectral bands. Compared to existing multispectral polarimetric sensors, the demonstrated metasurface-integrated CMOS system is compact and does not require any moving components, offering great potential for advanced photodetection applications.

  4. Vicarious Calibration of Beijing-1 Multispectral Imagers

    Directory of Open Access Journals (Sweden)

    Zhengchao Chen

    2014-02-01

    Full Text Available For on-orbit calibration of the Beijing-1 multispectral imagers (Beijing-1/MS, a field calibration campaign was performed at the Dunhuang calibration site during September and October of 2008. Based on the in situ data and images from Beijing-1 and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS, three vicarious calibration methods (i.e., reflectance-based, irradiance-based, and cross-calibration were used to calculate the top-of-atmosphere (TOA radiance of Beijing-1. An analysis was then performed to determine or identify systematic and accidental errors, and the overall uncertainty was assessed for each individual method. The findings show that the reflectance-based method has an uncertainty of more than 10% if the aerosol optical depth (AOD exceeds 0.2. The cross-calibration method is able to reach an error level within 7% if the images are selected carefully. The final calibration coefficients were derived from the irradiance-based data for 6 September 2008, with an uncertainty estimated to be less than 5%.

  5. A WebGIS system on the base of satellite data processing system for marine application

    Science.gov (United States)

    Gong, Fang; Wang, Difeng; Huang, Haiqing; Chen, Jianyu

    2007-10-01

    From 2002 to 2004, a satellite data processing system for marine application had been built up in State Key Laboratory of Satellite Ocean Environment Dynamics (Second Institute of Oceanography, State Oceanic Administration). The system received satellite data from TERRA, AQUA, NOAA-12/15/16/17/18, FY-1D and automatically generated Level3 products and Level4 products(products of single orbit and merged multi-orbits products) deriving from Level0 data, which is controlled by an operational control sub-system. Currently, the products created by this system play an important role in the marine environment monitoring, disaster monitoring and researches. Now a distribution platform has been developed on this foundation, namely WebGIS system for querying and browsing of oceanic remote sensing data. This system is based upon large database system-Oracle. We made use of the space database engine of ArcSDE and other middleware to perform database operation in addition. J2EE frame was adopted as development model, and Oracle 9.2 DBMS as database background and server. Simply using standard browsers(such as IE6.0), users can visit and browse the public service information that provided by system, including browsing for oceanic remote sensing data, and enlarge, contract, move, renew, traveling, further data inquiry, attribution search and data download etc. The system is still under test now. Founding of such a system will become an important distribution platform of Chinese satellite oceanic environment products of special topic and category (including Sea surface temperature, Concentration of chlorophyll, and so on), for the exaltation of satellite products' utilization and promoting the data share and the research of the oceanic remote sensing platform.

  6. Air traffic management system design using satellite based geo-positioning and communications assets

    Science.gov (United States)

    Horkin, Phil

    1995-01-01

    The current FAA and ICAO FANS vision of Air Traffic Management will transition the functions of Communications, Navigation, and Surveillance to satellite based assets in the 21st century. Fundamental to widespread acceptance of this vision is a geo-positioning system that can provide worldwide access with best case differential GPS performance, but without the associated problems. A robust communications capability linking-up aircraft and towers to meet the voice and data requirements is also essential. The current GPS constellation does not provide continuous global coverage with a sufficient number of satellites to meet the precision landing requirements as set by the world community. Periodic loss of the minimum number of satellites in view creates an integrity problem, which prevents GPS from becoming the primary system for navigation. Furthermore, there is reluctance on the part of many countries to depend on assets like GPS and GLONASS which are controlled by military communities. This paper addresses these concerns and provides a system solving the key issues associated with navigation, automatic dependent surveillance, and flexible communications. It contains an independent GPS-like navigation system with 27 satellites providing global coverage with a minimum of six in view at all times. Robust communications is provided by a network of TDMA/FDMA communications payloads contained on these satellites. This network can support simultaneous communications for up to 30,000 links, nearly enough to simultaneously support three times the current global fleet of jumbo air passenger aircraft. All of the required hardware is directly traceable to existing designs.

  7. Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

    Science.gov (United States)

    Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

    2014-11-01

    Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

  8. Evaluation of the MiKlip decadal prediction system using satellite based cloud products

    Directory of Open Access Journals (Sweden)

    Thomas Spangehl

    2016-12-01

    Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

  9. Cyclone track forecasting based on satellite images using artificial neural networks

    OpenAIRE

    Kovordanyi, Rita; Roy, Chandan

    2009-01-01

    Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...

  10. Satellite-enabled educational services specification and requirements analysis based on user feedback

    OpenAIRE

    Tsekeridou, Sofia; Tiropanis, Thanassis; Rorris, Dimitris; Constantinos, Makropoulos; Serif, Tacha; Stergioulas, Lampros

    2008-01-01

    Advanced tele-education services provision in remote geographically dispersed user communities (such as agriculture and maritime), based on the specific needs and requirements of such communities, implies significant infrastructural and broadband connectivity requirements for rich media, timely and quality-assured content delivery and interactivity. The solution to broadband access anywhere is provided by satellite-enabled communication infrastructures. This paper aims to present such satelli...

  11. The relationship of multispectral satellite imagery to immediate fire effects

    Science.gov (United States)

    Andrew T. Hudak; Penelope Morgan; Michael J. Bobbitt; Allstair M. S. Smith; Sarah A. Lewis; Leigh B. Lentile; Peter R. Robichaud; Jess T. Clark; Randy A. McKinley

    2007-01-01

    The Forest Service Remote Sensing Applications Center (RSAC) and the U.S. Geological Survey Earth Resources Observation and Science (EROS) Data Center produce Burned Area Reflectance Classification (BARC) maps for use by Burned Area Emergency Response (BAER) teams in rapid response to wildfires. BAER teams desire maps indicative of fire effects on soils, but green and...

  12. Estimation of Maize grain yield using multispectral satellite data sets ...

    African Journals Online (AJOL)

    Dr-Adeline

    Crop yield prediction is production estimates that are made a couple of months or ... involving the effect of biotic and abiotic factors cumulatively which could however ...... Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence.

  13. Quality assessment of butter cookies applying multispectral imaging

    Science.gov (United States)

    Andresen, Mette S; Dissing, Bjørn S; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center. PMID:24804036

  14. Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

    Directory of Open Access Journals (Sweden)

    Ahmad Chaddad

    Full Text Available This paper proposes to characterize the continuum of colorectal cancer (CRC using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma.In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG filter, discrete wavelets (DW and gray level co-occurrence matrices (GLCM. To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models.Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01. Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%.These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images.

  15. Benthic Habitat Mapping Using Multispectral High-Resolution Imagery: Evaluation of Shallow Water Atmospheric Correction Techniques

    Directory of Open Access Journals (Sweden)

    Francisco Eugenio

    2017-11-01

    Full Text Available Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2, can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones.

  16. From extended integrity monitoring to the safety evaluation of satellite-based localisation system

    International Nuclear Information System (INIS)

    Legrand, Cyril; Beugin, Julie; Marais, Juliette; Conrard, Blaise; El-Koursi, El-Miloudi; Berbineau, Marion

    2016-01-01

    Global Navigation Satellite Systems (GNSS) such as GPS, already used in aeronautics for safety-related applications, can play a major role in railway safety by allowing a train to locate itself safely. However, in order to implement this positioning solution in any embedded system, its performances must be evaluated according to railway standards. The evaluation of GNSS performances is not based on the same attributes class than RAMS evaluation. Face to these diffculties, we propose to express the integrity attribute, performance of satellite-based localisation. This attribute comes from aeronautical standards and for a hybridised GNSS with inertial system. To achieve this objective, the integrity attribute must be extended to this kind of system and algorithms initially devoted to GNSS integrity monitoring only must be adapted. Thereafter, the formalisation of this integrity attribute permits us to analyse the safety quantitatively through the probabilities of integrity risk and wrong-side failure. In this paper, after an introductory discussion about the use of localisation systems in railway safety context together with integrity issues, a particular integrity monitoring is proposed and described. The detection events of this algorithm permit us to conclude about safety level of satellite-based localisation system.

  17. VHR satellite imagery for humanitarian crisis management: a case study

    Science.gov (United States)

    Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

    2017-09-01

    During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

  18. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

    Science.gov (United States)

    Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

    2015-01-01

    Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

  19. Environmental Testing Philosophy for a Sandia National Laboratories' Small Satellite Project - A Retrospective

    Energy Technology Data Exchange (ETDEWEB)

    CAP,JEROME S.

    2000-08-24

    Sandia has recently completed the flight certification test series for the Multi-Spectral Thermal Imaging satellite (MTI), which is a small satellite for which Sandia was the system integrator. A paper was presented at the 16th Aerospace Testing Seminar discussing plans for performing the structural dynamics certification program for that satellite. The testing philosophy was originally based on a combination of system level vibroacoustic tests and component level shock and vibration tests. However, the plans evolved to include computational analyses using both Finite Element Analysis and Statistical Energy Analysis techniques. This paper outlines the final certification process and discuss lessons learned including both things that went well and things that should/could have been done differently.

  20. Simulation of seagrass bed mapping by satellite images based on the radiative transfer model

    Science.gov (United States)

    Sagawa, Tatsuyuki; Komatsu, Teruhisa

    2015-06-01

    Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.

  1. The first estimates of global nucleation mode aerosol concentrations based on satellite measurements

    Directory of Open Access Journals (Sweden)

    M. Kulmala

    2011-11-01

    Full Text Available Atmospheric aerosols play a key role in the Earth's climate system by scattering and absorbing solar radiation and by acting as cloud condensation nuclei. Satellites are increasingly used to obtain information on properties of aerosol particles with a diameter larger than about 100 nm. However, new aerosol particles formed by nucleation are initially much smaller and grow into the optically active size range on time scales of many hours. In this paper we derive proxies, based on process understanding and ground-based observations, to determine the concentrations of these new particles and their spatial distribution using satellite data. The results are applied to provide seasonal variation of nucleation mode concentration. The proxies describe the concentration of nucleation mode particles over continents. The source rates are related to both regional nucleation and nucleation associated with more restricted sources. The global pattern of nucleation mode particle number concentration predicted by satellite data using our proxies is compared qualitatively against both observations and global model simulations.

  2. Simultaneous Observations of pi 2 Pulsations on the Satellite and Geound-Based Measurements

    Directory of Open Access Journals (Sweden)

    S. H. Lee

    1997-12-01

    Full Text Available We have investigated Pi2 pulsations which were observed both on ground magnetometer array and by satellites. On November 9th in 1994, pi2 pulsations appeared globally on the 190/210 magnetometer chain and Hermanus station when two satellites(EXOS-D and ETS-VI were located near the magnetic meridian of the 210 array. The local time of measurements covers form morning(LT=8.47hr to afternoon(LT=20.3hr and the bandwidth of peak frequency is found relatively small. The signals of the electric field measurement of board the EXOS-D, which is located inside the plasmasphere(L=2.35, are highly coherent with the ground-based observations with the out of phase oscillations. However, the magnetic field measurement on the ETS-VI in the outer magnetosphere(L=6.60 shows no signature of pi2 pulsations over the same time interval and the correlation with any of ground-based stations is found to be very weak, even though both satellites and magnetometer chain are located close to each other in local time. We suggest that this event may be a direct evidence of Pi2 pulsations as virtual resonant modes which are localized in the plasmasphere(Lee 1996. The results show that the cavity mode oscillations can occur in the inner magnetosphere with less spectral noise compared to the outer magnetospheric case.

  3. Research of remote control for Chinese Antarctica Telescope based on iridium satellite communication

    Science.gov (United States)

    Xu, Lingzhe; Yang, Shihai

    2010-07-01

    Astronomers are ever dreaming of sites with best seeing on the Earth surface for celestial observation, and the Antarctica is one of a few such sites only left owing to the global air pollution. However, Antarctica region is largely unaccessible for human being due to lacking of fundamental living conditions, travel facilities and effective ways of communication. Worst of all, the popular internet source as a general way of communication scarcely exists there. Facing such a dilemma and as a solution remote control and data transmission for telescopes through iridium satellite communication has been put forward for the Chinese network Antarctic Schmidt Telescopes 3 (AST3), which is currently under all round research and development. This paper presents iridium satellite-based remote control application adapted to telescope control. The pioneer work in China involves hardware and software configuration utilizing techniques for reliable and secure communication, which is outlined in the paper too.

  4. Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America

    Directory of Open Access Journals (Sweden)

    D. Loyola

    2008-01-01

    Full Text Available Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash into the atmosphere, as well as several gases, including sulphur dioxide (SO2. These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO2 plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellite-based SO2 detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments.

  5. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    Directory of Open Access Journals (Sweden)

    Takuto Sakamoto

    Full Text Available Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

  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. Gridded sunshine duration climate data record for Germany based on combined satellite and in situ observations

    Science.gov (United States)

    Walawender, Jakub; Kothe, Steffen; Trentmann, Jörg; Pfeifroth, Uwe; Cremer, Roswitha

    2017-04-01

    The purpose of this study is to create a 1 km2 gridded daily sunshine duration data record for Germany covering the period from 1983 to 2015 (33 years) based on satellite estimates of direct normalised surface solar radiation and in situ sunshine duration observations using a geostatistical approach. The CM SAF SARAH direct normalized irradiance (DNI) satellite climate data record and in situ observations of sunshine duration from 121 weather stations operated by DWD are used as input datasets. The selected period of 33 years is associated with the availability of satellite data. The number of ground stations is limited to 121 as there are only time series with less than 10% of missing observations over the selected period included to keep the long-term consistency of the output sunshine duration data record. In the first step, DNI data record is used to derive sunshine hours by applying WMO threshold of 120 W/m2 (SDU = DNI ≥ 120 W/m2) and weighting of sunny slots to correct the sunshine length between two instantaneous image data due to cloud movement. In the second step, linear regression between SDU and in situ sunshine duration is calculated to adjust the satellite product to the ground observations and the output regression coefficients are applied to create a regression grid. In the last step regression residuals are interpolated with ordinary kriging and added to the regression grid. A comprehensive accuracy assessment of the gridded sunshine duration data record is performed by calculating prediction errors (cross-validation routine). "R" is used for data processing. A short analysis of the spatial distribution and temporal variability of sunshine duration over Germany based on the created dataset will be presented. The gridded sunshine duration data are useful for applications in various climate-related studies, agriculture and solar energy potential calculations.

  8. An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases

    International Nuclear Information System (INIS)

    Maillard, Pauline; Delcroix, Nicolas; Crivello, Fabrice; Gicquel, Sebastien; Joliot, Marc; Tzourio-Mazoyer, Nathalie; Dufouil, Carole; Alperovitch, Annick; Tzourio, Christophe; Mazoyer, Bernard

    2008-01-01

    An automated procedure for the detection, quantification, localization and statistical mapping of white matter hyperintensities (WMH) on T2-weighted magnetic resonance (MR) images is presented and validated based on the results of a between-centre reproducibility study. The first step is the identification of white matter (WM) tissue using a multispectral (T1, T2, PD) segmentation. In a second step, WMH are identified within the WM tissue by segmenting T2 images, isolating two different classes of WMH voxels - low- and high-contrast WMH voxels, respectively. The reliability of the whole procedure was assessed by applying it to the analysis of two large MR imaging databases (n = 650 and n710, respectively) of healthy elderly subjects matched for demographic characteristics. Average overall WMH load and spatial distribution were found to be similar in the two samples, (1.81 and 1.79% of the WM volume, respectively). White matter hyperintensity load was found to be significantly associated with both age and high blood pressure, with similar effects in both samples. With specific reference to the 650 subject cohort, we also found that WMH load provided by this automated procedure was significantly associated with visual grading of the severity of WMH, as assessed by a trained neurologist. The results show that this method is sensitive, well correlated with semi-quantitative visual rating and highly reproducible. (orig.)

  9. An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases

    Energy Technology Data Exchange (ETDEWEB)

    Maillard, Pauline; Delcroix, Nicolas; Crivello, Fabrice; Gicquel, Sebastien; Joliot, Marc; Tzourio-Mazoyer, Nathalie [GIP Cyceron, Centre d' Imagerie-Neurosciences et Applications aux Pathologies, CI-NAPS, CNRS, CEA, Universite de Caen/Universite Paris Descartes, Boulevard Becquerel, BP 5229, Caen (France); Dufouil, Carole; Alperovitch, Annick; Tzourio, Christophe [Universite Pierre et Marie Curie, INSERM U708, Neuroepidemiologie, Paris (France); Mazoyer, Bernard [GIP Cyceron, Centre d' Imagerie-Neurosciences et Applications aux Pathologies, CI-NAPS, CNRS, CEA, Universite de Caen/Universite Paris Descartes, Boulevard Becquerel, BP 5229, Caen (France); Institut Universitaire de France, Paris (France); CHU du Caen, Unite IRM, Caen (France)

    2008-01-15

    An automated procedure for the detection, quantification, localization and statistical mapping of white matter hyperintensities (WMH) on T2-weighted magnetic resonance (MR) images is presented and validated based on the results of a between-centre reproducibility study. The first step is the identification of white matter (WM) tissue using a multispectral (T1, T2, PD) segmentation. In a second step, WMH are identified within the WM tissue by segmenting T2 images, isolating two different classes of WMH voxels - low- and high-contrast WMH voxels, respectively. The reliability of the whole procedure was assessed by applying it to the analysis of two large MR imaging databases (n = 650 and n= 710, respectively) of healthy elderly subjects matched for demographic characteristics. Average overall WMH load and spatial distribution were found to be similar in the two samples, (1.81 and 1.79% of the WM volume, respectively). White matter hyperintensity load was found to be significantly associated with both age and high blood pressure, with similar effects in both samples. With specific reference to the 650 subject cohort, we also found that WMH load provided by this automated procedure was significantly associated with visual grading of the severity of WMH, as assessed by a trained neurologist. The results show that this method is sensitive, well correlated with semi-quantitative visual rating and highly reproducible. (orig.)

  10. Exploring the relationship between monitored ground-based and satellite aerosol measurements over the City of Johannesburg

    CSIR Research Space (South Africa)

    Garland, Rebecca M

    2012-09-01

    Full Text Available This project studied the relationship between aerosol optical depth (AOD) from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on the Terra satellite, and ground-based monitored particulate matter (PM) mass concentrations measured...

  11. Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 4. Operational Description and Qualitative Assessment.

    Science.gov (United States)

    1974-02-01

    The volume presents a description of how the Satellite-Based Advanced Air Traffic Management System (SAATMS) operates and a qualitative assessment of the system. The operational description includes the services, functions, and tasks performed by the...

  12. Ground-Based Global Navigation Satellite System (GNSS) GPS Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GPS Broadcast Ephemeris Data (daily files) from the NASA Crustal Dynamics Data...

  13. Ground-Based Global Navigation Satellite System Mixed Broadcast Ephemeris Data (sub-hourly files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) Mixed Broadcast Ephemeris Data (sub-hourly files) from the NASA Crustal Dynamics Data...

  14. Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation

    Science.gov (United States)

    New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently ...

  15. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  16. Development and validation of satellite-based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2016-02-01

    A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  17. Geographically weighted regression based methods for merging satellite and gauge precipitation

    Science.gov (United States)

    Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

    2018-03-01

    Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

  18. Systematical estimation of GPM-based global satellite mapping of precipitation products over China

    Science.gov (United States)

    Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

    2018-03-01

    As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

  19. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  20. Satellite-based climate data records of surface solar radiation from the CM SAF

    Science.gov (United States)

    Trentmann, Jörg; Cremer, Roswitha; Kothe, Steffen; Müller, Richard; Pfeifroth, Uwe

    2017-04-01

    The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth's energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF is freely available via www.cmsaf.eu. Here we present the regional and the global climate data records of surface solar radiation from the CM SAF. The regional climate data record SARAH (Surface Solar Radiation Dataset - Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002) is based on observations from the series of Meteosat satellites. SARAH provides 30-min, daily- and monthly-averaged data of the effective cloud albedo, the solar irradiance (incl. spectral information), the direct solar radiation (horizontal and normal), and the sunshine duration from 1983 to 2015 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05° allowing for detailed regional studies. The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002) is based on observations from the series of AVHRR satellite instruments. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from 1982 to 2015 with a spatial resolution of 0.25°. In addition to the solar surface

  1. Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

    Science.gov (United States)

    Gautam, Nitin

    The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global

  2. Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

    Science.gov (United States)

    Poon, P.; Kinoshita, A. M.

    2017-12-01

    Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

  3. A Web-based Google-Earth Coincident Imaging Tool for Satellite Calibration and Validation

    Science.gov (United States)

    Killough, B. D.; Chander, G.; Gowda, S.

    2009-12-01

    The Group on Earth Observations (GEO) is coordinating international efforts to build a Global Earth Observation System of Systems (GEOSS) to meet the needs of its nine “Societal Benefit Areas”, of which the most demanding, in terms of accuracy, is climate. To accomplish this vision, satellite on-orbit and ground-based data calibration and validation (Cal/Val) of Earth observation measurements are critical to our scientific understanding of the Earth system. Existing tools supporting space mission Cal/Val are often developed for specific campaigns or events with little desire for broad application. This paper describes a web-based Google-Earth based tool for the calculation of coincident satellite observations with the intention to support a diverse international group of satellite missions to improve data continuity, interoperability and data fusion. The Committee on Earth Observing Satellites (CEOS), which includes 28 space agencies and 20 other national and international organizations, are currently operating and planning over 240 Earth observation satellites in the next 15 years. The technology described here will better enable the use of multiple sensors to promote increased coordination toward a GEOSS. The CEOS Systems Engineering Office (SEO) and the Working Group on Calibration and Validation (WGCV) support the development of the CEOS Visualization Environment (COVE) tool to enhance international coordination of data exchange, mission planning and Cal/Val events. The objective is to develop a simple and intuitive application tool that leverages the capabilities of Google-Earth web to display satellite sensor coverage areas and for the identification of coincident scene locations along with dynamic menus for flexibility and content display. Key features and capabilities include user-defined evaluation periods (start and end dates) and regions of interest (rectangular areas) and multi-user collaboration. Users can select two or more CEOS missions from a

  4. Analysis of orbit determination from Earth-based tracking for relay satellites in a perturbed areostationary orbit

    Science.gov (United States)

    Romero, P.; Pablos, B.; Barderas, G.

    2017-07-01

    Areostationary satellites are considered a high interest group of satellites to satisfy the telecommunications needs of the foreseen missions to Mars. An areostationary satellite, in an areoequatorial circular orbit with a period of 1 Martian sidereal day, would orbit Mars remaining at a fixed location over the Martian surface, analogous to a geostationary satellite around the Earth. This work addresses an analysis of the perturbed orbital motion of an areostationary satellite as well as a preliminary analysis of the aerostationary orbit estimation accuracy based on Earth tracking observations. First, the models for the perturbations due to the Mars gravitational field, the gravitational attraction of the Sun and the Martian moons, Phobos and Deimos, and solar radiation pressure are described. Then, the observability from Earth including possible occultations by Mars of an areostationary satellite in a perturbed areosynchronous motion is analyzed. The results show that continuous Earth-based tracking is achievable using observations from the three NASA Deep Space Network Complexes in Madrid, Goldstone and Canberra in an occultation-free scenario. Finally, an analysis of the orbit determination accuracy is addressed considering several scenarios including discontinuous tracking schedules for different epochs and different areoestationary satellites. Simulations also allow to quantify the aerostationary orbit estimation accuracy for various tracking series durations and observed orbit arc-lengths.

  5. IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

    Directory of Open Access Journals (Sweden)

    Gongliang Liu

    2014-01-01

    Full Text Available In order to overcome the shortcomings of existing medium access control (MAC protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput.

  6. An intercomparison and validation of satellite-based surface radiative energy flux estimates over the Arctic

    Science.gov (United States)

    Riihelä, Aku; Key, Jeffrey R.; Meirink, Jan Fokke; Kuipers Munneke, Peter; Palo, Timo; Karlsson, Karl-Göran

    2017-05-01

    Accurate determination of radiative energy fluxes over the Arctic is of crucial importance for understanding atmosphere-surface interactions, melt and refreezing cycles of the snow and ice cover, and the role of the Arctic in the global energy budget. Satellite-based estimates can provide comprehensive spatiotemporal coverage, but the accuracy and comparability of the existing data sets must be ascertained to facilitate their use. Here we compare radiative flux estimates from Clouds and the Earth's Radiant Energy System (CERES) Synoptic 1-degree (SYN1deg)/Energy Balanced and Filled, Global Energy and Water Cycle Experiment (GEWEX) surface energy budget, and our own experimental FluxNet / Satellite Application Facility on Climate Monitoring cLoud, Albedo and RAdiation (CLARA) data against in situ observations over Arctic sea ice and the Greenland Ice Sheet during summer of 2007. In general, CERES SYN1deg flux estimates agree best with in situ measurements, although with two particular limitations: (1) over sea ice the upwelling shortwave flux in CERES SYN1deg appears to be underestimated because of an underestimated surface albedo and (2) the CERES SYN1deg upwelling longwave flux over sea ice saturates during midsummer. The Advanced Very High Resolution Radiometer-based GEWEX and FluxNet-CLARA flux estimates generally show a larger range in retrieval errors relative to CERES, with contrasting tendencies relative to each other. The largest source of retrieval error in the FluxNet-CLARA downwelling shortwave flux is shown to be an overestimated cloud optical thickness. The results illustrate that satellite-based flux estimates over the Arctic are not yet homogeneous and that further efforts are necessary to investigate the differences in the surface and cloud properties which lead to disagreements in flux retrievals.

  7. Multispectral analysis of multimodal images

    Energy Technology Data Exchange (ETDEWEB)

    Kvinnsland, Yngve; Brekke, Njaal (Dept. of Surgical Sciences, Univ. of Bergen, Bergen (Norway)); Taxt, Torfinn M.; Gruener, Renate (Dept. of Biomedicine, Univ. of Bergen, Bergen (Norway))

    2009-02-15

    An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. Materials and methods. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. Results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentation that seem to be sensible. Discussion. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

  8. A Direct and Fast Methodology for Ship Recognition in Sentinel-2 Multispectral Imagery

    Directory of Open Access Journals (Sweden)

    Henning Heiselberg

    2016-12-01

    Full Text Available The European Space Agency satellite Sentinel-2 provides multispectral images with pixel sizes down to 10 m. This high resolution allows for ship detection and recognition by determining a number of important ship parameters. We are able to show how a ship position, its heading, length and breadth can be determined down to a subpixel resolution. If the ship is moving, its velocity can also be determined from its Kelvin waves. The 13 spectrally different visual and infrared images taken using multispectral imagery (MSI are “fingerprints” that allow for the recognition and identification of ships. Furthermore, the multispectral image profiles along the ship allow for discrimination between the ship, its turbulent wakes, and the Kelvin waves, such that the ship’s length and breadth can be determined more accurately even when sailing. The ship’s parameters are determined by using satellite imagery taken from several ships, which are then compared to known values from the automatic identification system. The agreement is on the order of the pixel resolution or better.

  9. Satellite versus ground-based estimates of burned area: A comparison between MODIS based burned area and fire agency reports over North America in 2007

    Science.gov (United States)

    Stephane Mangeon; Robert Field; Michael Fromm; Charles McHugh; Apostolos Voulgarakis

    2015-01-01

    North American wildfire management teams routinely assess burned area on site during firefighting campaigns; meanwhile, satellite observations provide systematic and global burned-area data. Here we compare satellite and ground-based daily burned area for wildfire events for selected large fires across North America in 2007 on daily timescales. In a sample of 26 fires...

  10. Taking the Politics Out of Satellite and Space-Based Communications Protocols

    Science.gov (United States)

    Ivancic, William D.

    2006-01-01

    After many years of studies, experimentation, and deployment, large amounts of misinformation and misconceptions remain regarding applicability of various communications protocols for use in satellite and space-based networks. This paper attempts to remove much of the politics, misconceptions, and misinformation that have plagued spacebased communications protocol development and deployment. This paper provides a common vocabulary for communications; a general discussion of the requirements for various communication environments; an evaluation of tradeoffs between circuit and packet-switching technologies, and the pros and cons of various link, network, transport, application, and security protocols. Included is the applicability of protocol enhancing proxies to NASA, Department of Defense (DOD), and commercial space communication systems.

  11. Radiation-hardened optical amplifier based on multicore fiber for telecommunication satellites

    Science.gov (United States)

    Filipowicz, M.; Napierała, M.; Murawski, M.; Ostrowski, L.; Szostkiewicz, L.; Mergo, P.; Kechagias, M.; Farzana, J.; Stampoulidis, L.; Kehayas, E.; Crabb, J.; Nasilowski, T.

    2017-10-01

    Our research results concerning a space-dedicated C-band optical amplifier for application in telecommunication satellites are presented in this article. The device is based on a 7-core microstructured fiber where independent access to each core is granted by an all fiber fan-in/ fan-out coupler. The amplifier properties are described as well as its performance after irradiation to a maximal dose of 100 kRad. Also the difference between two kinds of fiber material compositions is discussed with regard to radiation resistance.

  12. A Novel Efficient Cluster-Based MLSE Equalizer for Satellite Communication Channels with -QAM Signaling

    Directory of Open Access Journals (Sweden)

    Dalakas Vassilis

    2006-01-01

    Full Text Available In satellites, nonlinear amplifiers used near saturation severely distort the transmitted signal and cause difficulties in its reception. Nevertheless, the nonlinearities introduced by memoryless bandpass amplifiers preserve the symmetries of the -ary quadrature amplitude modulation ( -QAM constellation. In this paper, a cluster-based sequence equalizer (CBSE that takes advantage of these symmetries is presented. The proposed equalizer exhibits enhanced performance compared to other techniques, including the conventional linear transversal equalizer, Volterra equalizers, and RBF network equalizers. Moreover, this gain in performance is obtained at a substantially lower computational cost.

  13. Comparison of total column ozone obtained by the IASI-MetOp satellite with ground-based and OMI satellite observations in the southern tropics and subtropics

    Directory of Open Access Journals (Sweden)

    A. M. Toihir

    2015-09-01

    Full Text Available This paper presents comparison results of the total column ozone (TCO data product over 13 southern tropical and subtropical sites recorded from the Infrared Atmospheric Sounder Interferometer (IASI onboard the EUMETSAT (European organization for the exploitation of METeorological SATellite MetOp (Meteorological Operational satellite program satellite. TCO monthly averages obtained from IASI between June 2008 and December 2012 are compared with collocated TCO measurements from the Ozone Monitoring Instrument (OMI on the OMI/Aura satellite and the Dobson and SAOZ (Système d'Analyse par Observation Zénithale ground-based instruments. The results show that IASI displays a positive bias with an average less than 2 % with respect to OMI and Dobson observations, but exhibits a negative bias compared to SAOZ over Bauru with a bias around 2.63 %. There is a good agreement between IASI and the other instruments, especially from 15° S southward where a correlation coefficient higher than 0.87 is found. IASI exhibits a seasonal dependence, with an upward trend in autumn and a downward trend during spring, especially before September 2010. After September 2010, the autumn seasonal bias is considerably reduced due to changes made to the retrieval algorithm of the IASI level 2 (L2 product. The L2 product released after August (L2 O3 version 5 (v5 matches TCO from the other instruments better compared to version 4 (v4, which was released between June 2008 and August 2010. IASI bias error recorded from September 2010 is estimated to be at 1.5 % with respect to OMI and less than ±1 % with respect to the other ground-based instruments. Thus, the improvement made by O3 L2 version 5 (v5 product compared with version 4 (v4, allows IASI TCO products to be used with confidence to study the distribution and interannual variability of total ozone in the southern tropics and subtropics.

  14. Multispectral code excited linear prediction coding and its application in magnetic resonance images.

    Science.gov (United States)

    Hu, J H; Wang, Y; Cahill, P T

    1997-01-01

    This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

  15. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  16. The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

    Science.gov (United States)

    Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

    2017-05-01

    The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

  17. Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

    Directory of Open Access Journals (Sweden)

    Lujiang Liu

    2016-06-01

    Full Text Available Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective.

  18. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  19. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-06-15

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  20. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Directory of Open Access Journals (Sweden)

    Haris Akram Bhatti

    2016-06-01

    Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  1. Visual attention based detection of signs of anthropogenic activities in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-10-13

    With increasing deployment of satellite imaging systems, only a small fraction of collected data can be subject to expert scrutiny. We present and evaluate a two-tier approach to broad area search for signs of anthropogenic activities in high-resolution commercial satellite imagery. The method filters image information using semantically oriented interest points by combining Harris corner detection and spatial pyramid matching. The idea is that anthropogenic structures, such as rooftop outlines, fence corners, road junctions, are locally arranged in specific angular relations to each other. They are often oriented at approximately right angles to each other (which is known as rectilinearity relation). Detecting the rectilinearity provides an opportunity to highlight regions most likely to contain anthropogenic activity. This is followed by supervised classification of regions surrounding the detected corner points as man-made vs. natural scenes. We consider, in particular, a search for anthropogenic activities in uncluttered areas. In this paper, we proposed and evaluated a two-tier approach to broad area search for signs of anthropogenic activities. Results from experiments on high-resolution ({approx}0.6m) commercial satellite image data showed the potential applicability of this approach and its ability of achieving both high precision and recall rates. The main advantage of combining corner-based cueing with general object recognition is that the incorporation of domain specific knowledge even in its more general form, such as presence of comers, provides a useful cue to narrow the focus of search for signs of anthropogenic activities. Combination of comer based cueing with spatial pyramid matching addressed the issue of comer categorization. An important practical issue for further research is optimizing the balance between false positive and false negative rates. While the results presented in the paper are encouraging, the problem of an automated broad area

  2. Categorizing natural disaster damage assessment using satellite-based geospatial techniques

    Science.gov (United States)

    Myint, S.W.; Yuan, M.; Cerveny, R.S.; Giri, C.

    2008-01-01

    Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

  3. GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

    Directory of Open Access Journals (Sweden)

    M. Ern

    2018-04-01

    Full Text Available Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs and chemistry climate models (CCMs usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE. GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER. Typical distributions (zonal averages and global maps of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658.

  4. Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

    Science.gov (United States)

    Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul A; Verger, Aleixandre; Samimi, Cyrus; Fensholt, Rasmus

    2015-04-01

    After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. © 2014 John Wiley & Sons Ltd.

  5. 20 Years of Total and Tropical Ozone Time Series Based on European Satellite Observations

    Science.gov (United States)

    Loyola, D. G.; Heue, K. P.; Coldewey-Egbers, M.

    2016-12-01

    Ozone is an important trace gas in the atmosphere, while the stratospheric ozone layer protects the earth surface from the incident UV radiation, the tropospheric ozone acts as green house gas and causes health damages as well as crop loss. The total ozone column is dominated by the stratospheric column, the tropospheric columns only contributes about 10% to the total column.The ozone column data from the European satellite instruments GOME, SCIAMACHY, OMI, GOME-2A and GOME-2B are available within the ESA Climate Change Initiative project with a high degree of inter-sensor consistency. The tropospheric ozone columns are based on the convective cloud differential algorithm. The datasets encompass a period of more than 20 years between 1995 and 2015, for the trend analysis the data sets were harmonized relative to one of the instruments. For the tropics we found an increase in the tropospheric ozone column of 0.75 ± 0.12 DU decade^{-1} with local variations between 1.8 and -0.8. The largest trends were observed over southern Africa and the Atlantic Ocean. A seasonal trend analysis led to the assumption that the increase is caused by additional forest fires.The trend for the total column was not that certain, based on model predicted trend data and the measurement uncertainty we estimated that another 10 to 15 years of observations will be required to observe a statistical significant trend. In the mid latitudes the trends are currently hidden in the large variability and for the tropics the modelled trends are low. Also the possibility of diverging trends at different altitudes must be considered; an increase in the tropospheric ozone might be accompanied by decreasing stratospheric ozone.The European satellite data record will be extended over the next two decades with the atmospheric satellite missions Sentinel 5 Precursor (launch end of 2016), Sentinel 4 and Sentinel 5.

  6. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-01-01

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

  7. GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

    Science.gov (United States)

    Ern, Manfred; Trinh, Quang Thai; Preusse, Peter; Gille, John C.; Mlynczak, Martin G.; Russell, James M., III; Riese, Martin

    2018-04-01

    Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658" target="_blank">https://doi.org/10.1594/PANGAEA.879658.

  8. Suborbital Reusable Launch Vehicles as an Opportunity to Consolidate and Calibrate Ground Based and Satellite Instruments

    Science.gov (United States)

    Papadopoulos, K.

    2014-12-01

    XCOR Aerospace, a commercial space company, is planning to provide frequent, low cost access to near-Earth space on the Lynx suborbital Reusable Launch Vehicle (sRLV). Measurements in the external vacuum environment can be made and can launch from most runways on a limited lead time. Lynx can operate as a platform to perform suborbital in situ measurements and remote sensing to supplement models and simulations with new data points. These measurements can serve as a quantitative link to existing instruments and be used as a basis to calibrate detectors on spacecraft. Easier access to suborbital data can improve the longevity and cohesiveness of spacecraft and ground-based resources. A study of how these measurements can be made on Lynx sRLV will be presented. At the boundary between terrestrial and space weather, measurements from instruments on Lynx can help develop algorithms to optimize the consolidation of ground and satellite based data as well as assimilate global models with new data points. For example, current tides and the equatorial electrojet, essential to understanding the Thermosphere-Ionosphere system, can be measured in situ frequently and on short notice. Furthermore, a negative-ion spectrometer and a Faraday cup, can take measurements of the D-region ion composition. A differential GPS receiver can infer the spatial gradient of ionospheric electron density. Instruments and optics on spacecraft degrade over time, leading to calibration drift. Lynx can be a cost effective platform for deploying a reference instrument to calibrate satellites with a frequent and fast turnaround and a successful return of the instrument. A calibrated reference instrument on Lynx can make collocated observations as another instrument and corrections are made for the latter, thus ensuring data consistency and mission longevity. Aboard a sRLV, atmospheric conditions that distort remotely sensed data (ground and spacecraft based) can be measured in situ. Moreover, an

  9. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

    Science.gov (United States)

    Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

    2017-12-01

    Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

  10. Multi-spectral CCD camera system for ocean water color and seacoast observation

    Science.gov (United States)

    Zhu, Min; Chen, Shiping; Wu, Yanlin; Huang, Qiaolin; Jin, Weiqi

    2001-10-01

    One of the earth observing instruments on HY-1 Satellite which will be launched in 2001, the multi-spectral CCD camera system, is developed by Beijing Institute of Space Mechanics & Electricity (BISME), Chinese Academy of Space Technology (CAST). In 798 km orbit, the system can provide images with 250 m ground resolution and a swath of 500 km. It is mainly used for coast zone dynamic mapping and oceanic watercolor monitoring, which include the pollution of offshore and coast zone, plant cover, watercolor, ice, terrain underwater, suspended sediment, mudflat, soil and vapor gross. The multi- spectral camera system is composed of four monocolor CCD cameras, which are line array-based, 'push-broom' scanning cameras, and responding for four spectral bands. The camera system adapts view field registration; that is, each camera scans the same region at the same moment. Each of them contains optics, focal plane assembly, electrical circuit, installation structure, calibration system, thermal control and so on. The primary features on the camera system are: (1) Offset of the central wavelength is better than 5 nm; (2) Degree of polarization is less than 0.5%; (3) Signal-to-noise ratio is about 1000; (4) Dynamic range is better than 2000:1; (5) Registration precision is better than 0.3 pixel; (6) Quantization value is 12 bit.

  11. On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

    Science.gov (United States)

    Lasaponara, R.

    2012-04-01

    , Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1

  12. Online Multi-Spectral Meat Inspection

    DEFF Research Database (Denmark)

    Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo

    2013-01-01

    We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...

  13. Multispectral Imaging of Wok-Fried Vegetables

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Dissing, Bjørn Skovlund; Hyldig, Grethe

    2012-01-01

    Quality control in the food industry is often performed by measuring various chemical compounds in the food involved. The authors propose an imaging concept for acquiring high-quality multispectral images to evaluate optical reflection changes in carrots and celeriac over a period of 14 days....... For comparison, sensory analysis was performed on the same samples. Prior to multispectral image recording, the vegetables were prefried and frozen at -30 °C for 4 months. During the 14 days of image recording, the vegetables were kept at +5 °C. In this period, surface changes and thereby reflectance properties...

  14. Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

    Science.gov (United States)

    Sheffield, J.; Lobell, D. B.; Wood, E. F.

    2010-12-01

    Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

  15. Attitude Model of a Reaction Wheel/Fixed Thruster Based Satellite Using Telemetry Data

    National Research Council Canada - National Science Library

    Smith, Jason E

    2005-01-01

    .... While there are a multitude of ways to determine a satellite's orientation, very little research has been done on determining if the attitude of a satellite can be determined directly from telemetry...

  16. A survey of classical methods and new trends in pansharpening of multispectral images

    Directory of Open Access Journals (Sweden)

    Katsaggelos Aggelos

    2011-01-01

    Full Text Available Abstract There exist a number of satellites on different earth observation platforms, which provide multispectral images together with a panchromatic image, that is, an image containing reflectance data representative of a wide range of bands and wavelengths. Pansharpening is a pixel-level fusion technique used to increase the spatial resolution of the multispectral image while simultaneously preserving its spectral information. In this paper, we provide a review of the pan-sharpening methods proposed in the literature giving a clear classification of them and a description of their main characteristics. Finally, we analyze how the quality of the pansharpened images can be assessed both visually and quantitatively and examine the different quality measures proposed for that purpose.

  17. Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

    2015-08-01

    Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

  18. Multitemporal Monitoring of the Air Quality in Bulgaria by Satellite Based Instruments

    Science.gov (United States)

    Nikolov, Hristo; Borisova, Denitsa

    2015-04-01

    Nowadays the effect on climate changes on the population and environment caused by air pollutants at local and regional scale by pollution concentrations higher than allowed is undisputable. Main sources of gas releases are due to anthropogenic emissions caused by the economic and domestic activities of the inhabitants, and to less extent having natural origin. Complementary to pollutants emissions the local weather parameters such as temperature, precipitation, wind speed, clouds, atmospheric water vapor, and wind direction control the chemical reactions in the atmosphere. It should be noted that intrinsic property of the air pollution is its "transboundary-ness" and this is why the air quality (AQ) is not affecting the population of one single country only. This why the exchange of information concerning AQ at EU level is subject to well established legislation and one of EU flagship initiatives for standardization in data exchange, namely INSPIRE, has to cope with. It should be noted that although good reporting mechanism with regard to AQ is already established between EU member states national networks suffer from a serious disadvantage - they don't form a regular grid which is a prerequisite for verification of pollutants transport modeling. Alternative sources of information for AQ are the satellite observations (i.e. OMI, TOMS instruments) providing daily data for ones of the major contributors to air pollution such as O3, NOX and SO2. Those data form regular grids and are processed the same day of the acquisition so they could be used in verification of the outputs generated by numerical modeling of the AQ and pollution transfer. In this research we present results on multitemporal monitoring of several regional "hot spots" responsible for greenhouse gases emissions in Bulgaria with emphasis on satellite-based instruments. Other output from this study is a method for validation of the AQ forecasts and also providing feedback to the service that prepares

  19. Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

    Science.gov (United States)

    Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

    2013-12-01

    Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output

  20. Mission planning for space based satellite surveillance experiments with the MSX

    Science.gov (United States)

    Sridharan, R.; Fishman, T.; Robinson, E.; Viggh, H.; Wiseman, A.

    1994-01-01

    The Midcourse Space Experiment is a BMDO-sponsored scientific satellite set for launch within the year. The satellite will collect phenomenology data on missile targets, plumes, earth limb backgrounds and deep space backgrounds in the LWIR, visible and ultra-violet spectral bands. It will also conduct functional demonstrations for space-based space surveillance. The Space-Based Visible sensor, built by Lincoln Laboratory, Massachusetts Institute of Technology, is the primary sensor on board the MSX for demonstration of space surveillance. The SBV Processing, Operations and Control Center (SPOCC) is the mission planning and commanding center for all space surveillance experiments using the SBV and other MSX instruments. The guiding principle in the SPOCC Mission Planning System was that all routine functions be automated. Manual analyst input should be minimal. Major concepts are: (I) A high level language, called SLED, for user interface to the system; (2) A group of independent software processes which would generally be run in a pipe-line mode for experiment commanding but can be run independently for analyst assessment; (3) An integrated experiment cost computation function that permits assessment of the feasibility of the experiment. This paper will report on the design, implementation and testing of the Mission Planning System.

  1. Geometric Positioning Accuracy Improvement of ZY-3 Satellite Imagery Based on Statistical Learning Theory

    Directory of Open Access Journals (Sweden)

    Niangang Jiao

    2018-05-01

    Full Text Available With the increasing demand for high-resolution remote sensing images for mapping and monitoring the Earth’s environment, geometric positioning accuracy improvement plays a significant role in the image preprocessing step. Based on the statistical learning theory, we propose a new method to improve the geometric positioning accuracy without ground control points (GCPs. Multi-temporal images from the ZY-3 satellite are tested and the bias-compensated rational function model (RFM is applied as the block adjustment model in our experiment. An easy and stable weight strategy and the fast iterative shrinkage-thresholding (FIST algorithm which is widely used in the field of compressive sensing are improved and utilized to define the normal equation matrix and solve it. Then, the residual errors after traditional block adjustment are acquired and tested with the newly proposed inherent error compensation model based on statistical learning theory. The final results indicate that the geometric positioning accuracy of ZY-3 satellite imagery can be improved greatly with our proposed method.

  2. Error analysis of satellite attitude determination using a vision-based approach

    Science.gov (United States)

    Carozza, Ludovico; Bevilacqua, Alessandro

    2013-09-01

    Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects' spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object. This work presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome. We believe that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).

  3. A GPS Satellite Clock Offset Prediction Method Based on Fitting Clock Offset Rates Data

    Directory of Open Access Journals (Sweden)

    WANG Fuhong

    2016-12-01

    Full Text Available It is proposed that a satellite atomic clock offset prediction method based on fitting and modeling clock offset rates data. This method builds quadratic model or linear model combined with periodic terms to fit the time series of clock offset rates, and computes the model coefficients of trend with the best estimation. The clock offset precisely estimated at the initial prediction epoch is directly adopted to calculate the model coefficient of constant. The clock offsets in the rapid ephemeris (IGR provided by IGS are used as modeling data sets to perform certain experiments for different types of GPS satellite clocks. The results show that the clock prediction accuracies of the proposed method for 3, 6, 12 and 24 h achieve 0.43, 0.58, 0.90 and 1.47 ns respectively, which outperform the traditional prediction method based on fitting original clock offsets by 69.3%, 61.8%, 50.5% and 37.2%. Compared with the IGU real-time clock products provided by IGS, the prediction accuracies of the new method have improved about 15.7%, 23.7%, 27.4% and 34.4% respectively.

  4. Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

    Science.gov (United States)

    Jin, Z.; Azzari, G.; Lobell, D. B.

    2016-12-01

    Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

  5. A graph-based approach to detect spatiotemporal dynamics in satellite image time series

    Science.gov (United States)

    Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

    2017-08-01

    Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

  6. 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.

  7. Improved GPS-based Satellite Relative Navigation Using Femtosecond Laser Relative Distance Measurements

    Directory of Open Access Journals (Sweden)

    Hyungjik Oh

    2016-03-01

    Full Text Available This study developed an approach for improving Carrier-phase Differential Global Positioning System (CDGPS based realtime satellite relative navigation by applying laser baseline measurement data. The robustness against the space operational environment was considered, and a Synthetic Wavelength Interferometer (SWI algorithm based on a femtosecond laser measurement model was developed. The phase differences between two laser wavelengths were combined to measure precise distance. Generated laser data were used to improve estimation accuracy for the float ambiguity of CDGPS data. Relative navigation simulations in real-time were performed using the extended Kalman filter algorithm. The GPS and laser-combined relative navigation accuracy was compared with GPS-only relative navigation solutions to determine the impact of laser data on relative navigation. In numerical simulations, the success rate of integer ambiguity resolution increased when laser data was added to GPS data. The relative navigational errors also improved five-fold and two-fold, relative to the GPS-only error, for 250 m and 5 km initial relative distances, respectively. The methodology developed in this study is suitable for application to future satellite formation-flying missions.

  8. OLFAR, a radio telescope based on nano satellites in moon orbit

    NARCIS (Netherlands)

    Engelen, S.; Verhoeven, C.J.M.; Bentum, Marinus Jan

    2010-01-01

    It seems very likely that missions with nano-satellites in professional scientific or commercial applications will not be single-satellite missions. Well structured formations or less structured swarms of nano-satellites will be able to perform tasks that cannot be done in the “traditional‿ way. The

  9. Passivity Based Nonlinear Attitude Control of the Rømer Satellite

    DEFF Research Database (Denmark)

    Quottrup, Michael Melholt; Krogh-Sørensen, J.; Wisniewski, Rafal

    2001-01-01

    This paper suggests nonlinear attitude control of the Danish satellite Rømer. This satellite will be designed to fulfil two scientific objectives: The observation of stellar oscillations and the detection and localisation of gamma-ray bursts. The satellite will be equipped with a tetrahedron...

  10. Studying Vegetation Salinity: From the Field View to a Satellite-Based Perspective

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2017-02-01

    Full Text Available Salinization of irrigated lands in the semi-arid Jezreel Valley, Northern Israel results in soil-structure deterioration and crop damage. We formulated a generic rule for estimating salinity of different vegetation types by studying the relationship between Cl/Na and different spectral slopes in the visible–near infrared–shortwave infrared (VIS–NIR–SWIR spectral range using both field measurements and satellite imagery (Sentinel-2. For the field study, the slope-based model was integrated with conventional partial least squares (PLS analyses. Differences in 14 spectral ranges, indicating changes in salinity levels, were identified across the VIS–NIR–SWIR region (350–2500 nm. Next, two different models were run using PLS regression: (i using spectral slope data across these ranges; and (ii using preprocessed spectral reflectance. The best model for predicting Cl content was based on continuum removal reflectance (R2 = 0.84. Satisfactory correlations were obtained using the slope-based PLS model (R2 = 0.77 for Cl and R2 = 0.63 for Na. Thus, salinity contents in fresh plants could be estimated, despite masking of some spectral regions by water absorbance. Finally, we estimated the most sensitive spectral channels for monitoring vegetation salinity from a satellite perspective. We evaluated the recently available Sentinel-2 imagery’s ability to distinguish variability in vegetation salinity levels. The best estimate of a Sentinel-2-based vegetation salinity index was generated based on a ratio between calculated slopes: the 490–665 nm and 705–1610 nm. This index was denoted as the Sentinel-2-based vegetation salinity index (SVSI (band 4 − band 2/(band 5 + band 11.

  11. Object-Based Image Analysis of WORLDVIEW-2 Satellite Data for the Classification of Mangrove Areas in the City of SÃO LUÍS, MARANHÃO State, Brazil

    Science.gov (United States)

    Kux, H. J. H.; Souza, U. D. V.

    2012-07-01

    Taking into account the importance of mangrove environments for the biodiversity of coastal areas, the objective of this paper is to classify the different types of irregular human occupation on the areas of mangrove vegetation in São Luis, capital of Maranhão State, Brazil, considering the OBIA (Object-based Image Analysis) approach with WorldView-2 satellite data and using InterIMAGE, a free image analysis software. A methodology for the study of the area covered by mangroves at the northern portion of the city was proposed to identify the main targets of this area, such as: marsh areas (known locally as Apicum), mangrove forests, tidal channels, blockhouses (irregular constructions), embankments, paved streets and different condominiums. Initially a databank including information on the main types of occupation and environments was established for the area under study. An image fusion (multispectral bands with panchromatic band) was done, to improve the information content of WorldView-2 data. Following an ortho-rectification was made with the dataset used, in order to compare with cartographical data from the municipality, using Ground Control Points (GCPs) collected during field survey. Using the data mining software GEODMA, a series of attributes which characterize the targets of interest was established. Afterwards the classes were structured, a knowledge model was created and the classification performed. The OBIA approach eased mapping of such sensitive areas, showing the irregular occupations and embankments of mangrove forests, reducing its area and damaging the marine biodiversity.

  12. Strategies for satellite-based monitoring of CO2 from distributed area and point sources

    Science.gov (United States)

    Schwandner, Florian M.; Miller, Charles E.; Duren, Riley M.; Natraj, Vijay; Eldering, Annmarie; Gunson, Michael R.; Crisp, David

    2014-05-01

    Atmospheric CO2 budgets are controlled by the strengths, as well as the spatial and temporal variabilities of CO2 sources and sinks. Natural CO2 sources and sinks are dominated by the vast areas of the oceans and the terrestrial biosphere. In contrast, anthropogenic and geogenic CO2 sources are dominated by distributed area and point sources, which may constitute as much as 70% of anthropogenic (e.g., Duren & Miller, 2012), and over 80% of geogenic emissions (Burton et al., 2013). Comprehensive assessments of CO2 budgets necessitate robust and highly accurate satellite remote sensing strategies that address the competing and often conflicting requirements for sampling over disparate space and time scales. Spatial variability: The spatial distribution of anthropogenic sources is dominated by patterns of production, storage, transport and use. In contrast, geogenic variability is almost entirely controlled by endogenic geological processes, except where surface gas permeability is modulated by soil moisture. Satellite remote sensing solutions will thus have to vary greatly in spatial coverage and resolution to address distributed area sources and point sources alike. Temporal variability: While biogenic sources are dominated by diurnal and seasonal patterns, anthropogenic sources fluctuate over a greater variety of time scales from diurnal, weekly and seasonal cycles, driven by both economic and climatic factors. Geogenic sources typically vary in time scales of days to months (geogenic sources sensu stricto are not fossil fuels but volcanoes, hydrothermal and metamorphic sources). Current ground-based monitoring networks for anthropogenic and geogenic sources record data on minute- to weekly temporal scales. Satellite remote sensing solutions would have to capture temporal variability through revisit frequency or point-and-stare strategies. Space-based remote sensing offers the potential of global coverage by a single sensor. However, no single combination of orbit

  13. Improvement of Ka-band satellite link availability for real-time IP-based video contribution

    Directory of Open Access Journals (Sweden)

    G. Berretta

    2017-09-01

    Full Text Available New High Throughput Satellite (HTS systems allow high throughput IP uplinks/contribution at Ka-band frequencies for relatively lower costs when compared to broadcasting satellite uplinks at Ku band. This technology offers an advantage for live video contribution from remote areas, where the terrestrial infrastructure may not be adequate. On the other hand, the Ka-band is more subject to impairments due to rain or bad weather. This paper addresses the target system specification and provides an optimized approach for the transmission of IP-based video flows through HTS commercial services operating at Ka-band frequencies. In particular, the focus of this study is on the service requirements and the propagation analysis that provide a reference architecture to improve the overall link availability. The approach proposed herein leads to the introduction of a new concept of live service contribution using pairs of small satellite antennas and cheap satellite terminals.

  14. Satellite Map of Port-au-Prince, Haiti-2010-Infrared

    Science.gov (United States)

    Cole, Christopher J.; Sloan, Jeff

    2010-01-01

    The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

  15. Multispectral mid-infrared imaging using frequency upconversion

    DEFF Research Database (Denmark)

    Sanders, Nicolai Højer; Dam, Jeppe Seidelin; Jensen, Ole Bjarlin

    2013-01-01

    It has recently been shown that it is possible to upconvert infrared images to the near infrared region with high quantum efficiency and low noise by three-wave mixing with a laser field [1]. If the mixing laser is single-frequency, the upconverted image is simply a band-pass filtered version...... parameter, allowing for fast tuning and hence potentially fast image acquisition, paving the way for upconversion based real time multispectral imaging. In the present realization the upconversion module consists of an external cavity tapered diode laser in a Littrow configuration with a computer controlled...

  16. Empirical global model of upper thermosphere winds based on atmosphere and dynamics explorer satellite data

    Science.gov (United States)

    Hedin, A. E.; Spencer, N. W.; Killeen, T. L.

    1988-01-01

    Thermospheric wind data obtained from the Atmosphere Explorer E and Dynamics Explorer 2 satellites have been used to generate an empirical wind model for the upper thermosphere, analogous to the MSIS model for temperature and density, using a limited set of vector spherical harmonics. The model is limited to above approximately 220 km where the data coverage is best and wind variations with height are reduced by viscosity. The data base is not adequate to detect solar cycle (F10.7) effects at this time but does include magnetic activity effects. Mid- and low-latitude data are reproduced quite well by the model and compare favorably with published ground-based results. The polar vortices are present, but not to full detail.

  17. Ground-and satellite-based evidence of the biophysical mechanisms behind the greening Sahel

    DEFF Research Database (Denmark)

    Brandt, Martin Stefan; Mbow, Cheikh; Diouf, Abdoul A.

    2015-01-01

    After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness...... over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass...... remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass...

  18. The method of multispectral image processing of phytoplankton processing for environmental control of water pollution

    Science.gov (United States)

    Petruk, Vasil; Kvaternyuk, Sergii; Yasynska, Victoria; Kozachuk, Anastasia; Kotyra, Andrzej; Romaniuk, Ryszard S.; Askarova, Nursanat

    2015-12-01

    The paper presents improvement of the method of environmental monitoring of water bodies based on bioindication by phytoplankton, which identify phytoplankton particles carried out on the basis of comparison array multispectral images using Bayesian classifier of solving function based on Mahalanobis distance. It allows to evaluate objectively complex anthropogenic and technological impacts on aquatic ecosystems.

  19. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-05-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks.

  20. Sea Ice Drift Monitoring in the Bohai Sea Based on GF4 Satellite

    Science.gov (United States)

    Zhao, Y.; Wei, P.; Zhu, H.; Xing, B.

    2018-04-01

    The Bohai Sea is the inland sea with the highest latitude in China. In winter, the phenomenon of freezing occurs in the Bohai Sea due to frequent cold wave influx. According to historical records, there have been three serious ice packs in the Bohai Sea in the past 50 years which caused heavy losses to our economy. Therefore, it is of great significance to monitor the drift of sea ice and sea ice in the Bohai Sea. The GF4 image has the advantages of short imaging time and high spatial resolution. Based on the GF4 satellite images, the three methods of SIFT (Scale invariant feature - the transform and Scale invariant feature transform), MCC (maximum cross-correlation method) and sift combined with MCC are used to monitor sea ice drift and calculate the speed and direction of sea ice drift, the three calculation results are compared and analyzed by using expert interpretation and historical statistical data to carry out remote sensing monitoring of sea ice drift results. The experimental results show that the experimental results of the three methods are in accordance with expert interpretation and historical statistics. Therefore, the GF4 remote sensing satellite images have the ability to monitor sea ice drift and can be used for drift monitoring of sea ice in the Bohai Sea.

  1. 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.

  2. Satellite based hydroclimatic understanding of evolution of Dengue and Zika virus

    Science.gov (United States)

    Khan, R.; Jutla, A.; Colwell, R. R.

    2017-12-01

    Vector-borne diseases are prevalent in tropical and subtropical regions especially in Africa, South America, and Asia. Vector eradication is perhaps not possible since pathogens adapt to local environment. In absence of appropriate vaccinations for Dengue and Zika virus, burden of these two infections continue to increase in several geographical locations. Aedes spp. is one of the major vectors for Dengue and Zika viruses. Etiologies on Dengue and Zika viruses are evolving, however the key question remains as to how one species of mosquito can transmit two different infections? We argue that a set of conducive environmental condition, modulated by regional climatic and weather processes, may lead to abundance of a specific virus. Using satellite based rainfall (TRMM/GPM), land surface temperature (MODIS) and dew point temperature (AIRS/MERRA), we have identified appropriate thresholds that can provide estimate on risk of abundance of Dengue or Zika viruses at least few weeks in advance. We will discuss a framework coupling satellite derived hydroclimatic and societal processes to predict environmental niches of favorability of conditions of Dengue or Zika risk in human population on a global scale.

  3. Satellite imagery-based monitoring of archaeological site damage in the Syrian civil war.

    Science.gov (United States)

    Casana, Jesse; Laugier, Elise Jakoby

    2017-01-01

    Since the start of the Syrian civil war in 2011, the rich archaeological heritage of Syria and northern Iraq has faced severe threats, including looting, combat-related damage, and intentional demolition of monuments. However, the inaccessibility of the conflict zone to archaeologists or cultural heritage specialists has made it difficult to produce accurate damage assessments, impeding efforts to develop mitigation strategies and policies. This paper presents results of a project, undertaken in collaboration with the American Schools of Oriental Research (ASOR) and the US Department of State, to monitor damage to archaeological sites in Syria, northern Iraq, and southern Turkey using recent, high-resolution satellite imagery. Leveraging a large database of archaeological and heritage sites throughout the region, as well as access to continually updated satellite imagery from DigitalGlobe, this project has developed a flexible and efficient methodology to log observations of damage in a manner that facilitates spatial and temporal queries. With nearly 5000 sites carefully evaluated, analysis reveals unexpected patterns in the timing, severity, and location of damage, helping us to better understand the evolving cultural heritage crisis in Syria and Iraq. Results also offer a model for future remote sensing-based archaeological and heritage monitoring efforts in the Middle East and beyond.

  4. Satellite imagery-based monitoring of archaeological site damage in the Syrian civil war.

    Directory of Open Access Journals (Sweden)

    Jesse Casana

    Full Text Available Since the start of the Syrian civil war in 2011, the rich archaeological heritage of Syria and northern Iraq has faced severe threats, including looting, combat-related damage, and intentional demolition of monuments. However, the inaccessibility of the conflict zone to archaeologists or cultural heritage specialists has made it difficult to produce accurate damage assessments, impeding efforts to develop mitigation strategies and policies. This paper presents results of a project, undertaken in collaboration with the American Schools of Oriental Research (ASOR and the US Department of State, to monitor damage to archaeological sites in Syria, northern Iraq, and southern Turkey using recent, high-resolution satellite imagery. Leveraging a large database of archaeological and heritage sites throughout the region, as well as access to continually updated satellite imagery from DigitalGlobe, this project has developed a flexible and efficient methodology to log observations of damage in a manner that facilitates spatial and temporal queries. With nearly 5000 sites carefully evaluated, analysis reveals unexpected patterns in the timing, severity, and location of damage, helping us to better understand the evolving cultural heritage crisis in Syria and Iraq. Results also offer a model for future remote sensing-based archaeological and heritage monitoring efforts in the Middle East and beyond.

  5. The Accuracy Assessment of Determining the Axis of Railway Track Basing on the Satellite Surveying

    Science.gov (United States)

    Koc, Władysław; Specht, Cezary; Chrostowski, Piotr; Palikowska, Katarzyna

    2012-09-01

    In 2009, at the Gdansk University of Technology there have been carried out, for the first time, continuous satellite surveying of railway track by the use of the relative phase method based on geodesic active network ASG-EUPOS and NAVGEO service. Still continuing research works focused on the GNSS multi-receivers platform evaluation for projecting and stock-taking. In order to assess the accuracy of the railway track axis position, the values of deviations of transverse position XTE (Cross Track Error) were evaluated. In order to eliminate the influence of random measurement errors and to obtain the coordinates representing the actual shape of the track, the XTE variable was analyzed by signal analysis methods (Chebyshev low-pass filtering and fast Fourier transform). At the end the paper presents the module of the computer software SATTRACK which currently has been developing at the Gdansk University of Technology. The program serves visualization, assessment and design process of railway track, adapted to the technique of continuous satellite surveying. The module called TRACK STRAIGHT is designed to assess the straight sections. A description of its operation as well as examples of its functions has been presented.

  6. Geostationary satellite estimation of biomass burning in Amazonia during BASE-A

    International Nuclear Information System (INIS)

    Menzel, W.P.; Cutrim, E.C.; Prins, E.M.

    1991-01-01

    This chapter presents the results of using Geostationary Operational Environmental Satellite (GOES) Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) infrared window (3.9 and 11.2 microns) data to monitor biomass burning several times per day in Amazonia. The technique of Matson and Dozier using two window channels was adapted to GOES VAS infrared data to estimate the size and temperature of fires associated with deforestation in the vicinity of Alta Floresta, Brazil, during the Biomass Burning Airborne and Spaceborne Experiment - Amazonia (BASE-A). Although VAS data do not offer the spatial resolution available with AVHRR data 97 km versus 1 km, respectively, this decreased resolution does not seem to hinder the ability of the VAS instrument to detect fires; in some cases it proves to be advantageous in that saturation does not occur as often. VAS visible data are additionally helpful in verifying that the hot spots sensed in the infrared are actually related to fires. Furthermore, the fire plumes can be tracked in time to determine their motion and extent. In this way, the GOES satellite offers a unique ability to monitor diurnal variations in fire activity and transport of related aerosols

  7. Proportional fair scheduling algorithm based on traffic in satellite communication system

    Science.gov (United States)

    Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

    2018-02-01

    In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

  8. Satellite-based trends of solar radiation and cloud parameters in Europe

    Science.gov (United States)

    Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

    2018-04-01

    Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

  9. The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

    Science.gov (United States)

    Nedoluha, Gerald E.; Kiefer, Michael; Lossow, Stefan; Gomez, R. Michael; Kämpfer, Niklaus; Lainer, Martin; Forkman, Peter; Christensen, Ole Martin; Oh, Jung Jin; Hartogh, Paul; Anderson, John; Bramstedt, Klaus; Dinelli, Bianca M.; Garcia-Comas, Maya; Hervig, Mark; Murtagh, Donal; Raspollini, Piera; Read, William G.; Rosenlof, Karen; Stiller, Gabriele P.; Walker, Kaley A.

    2017-12-01

    As part of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically ˜ 1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0-1 % yr-1. In particular, MLS shows a trend of between 0.5 % yr-1 and 0.7 % yr-1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr-1 (at Mauna Loa, Hawaii) and -0.1 % yr-1 (at Lauder, New Zealand).

  10. The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

    Directory of Open Access Journals (Sweden)

    G. E. Nedoluha

    2017-12-01

    Full Text Available As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate water vapor assessment (WAVAS-II, we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii and −0.1 % yr−1 (at Lauder, New Zealand.

  11. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2017-01-01

    The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.

  12. High-speed multispectral videography with a periscope array in a spectral shaper.

    Science.gov (United States)

    Hashimoto, Kazuki; Mizuno, Hikaru; Nakagawa, Keiichi; Horisaki, Ryoichi; Iwasaki, Atsushi; Kannari, Fumihiko; Sakuma, Ichiro; Goda, Keisuke

    2014-12-15

    We present a simple method for continuous snapshot multispectral imaging or multispectral videography that achieves high-speed spectral video recording without the need for mechanical scanning and much computation for datacube construction. The enabling component of this method is an array of periscopes placed in a prism-based spectral shaper that spectrally separates the image without image deformation. As a proof-of-principle demonstration, we show five-color multispectral video recording in the visible range (200×200 pixels per spectral image frame) at a record high frame rate of at least 2800 frames per second. Our experimental results indicate that this method holds promise for various industrial and biomedical applications such as remote sensing, food inspection, and endoscopy.

  13. Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations.

    Science.gov (United States)

    Checchi, Francesco; Stewart, Barclay T; Palmer, Jennifer J; Grundy, Chris

    2013-01-23

    Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Our method consisted of multiplying (i) manual counts of assumed residential structures on a satellite image and (ii) estimates of the mean number of people per structure (structure occupancy) obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons' camps and two urban neighbourhoods with a mixture of residents and displaced) ranging in population from 1,969 to 90,547, and compared these to "gold standard" reference population figures from census or other robust methods. Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of layout. For each site, estimates were produced in 2-5 working person-days. In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method's development.

  14. Advances in the Validation of Satellite-Based Maps of Volcanic Sulfur Dioxide Plumes

    Science.gov (United States)

    Realmuto, V. J.; Berk, A.; Acharya, P. K.; Kennett, R.

    2013-12-01

    The monitoring of volcanic gas emissions with gas cameras, spectrometer arrays, tethersondes, and UAVs presents new opportunities for the validation of satellite-based retrievals of gas concentrations. Gas cameras and spectrometer arrays provide instantaneous observations of the gas burden, or concentration along an optical path, over broad sections of a plume, similar to the observations acquired by nadir-viewing satellites. Tethersondes and UAVs provide us with direct measurements of the vertical profiles of gas concentrations within plumes. This presentation will focus on our current efforts to validate ASTER-based maps of sulfur dioxide plumes at Turrialba and Kilauea Volcanoes (located in Costa Rica and Hawaii, respectively). These volcanoes, which are the subjects of comprehensive monitoring programs, are challenging targets for thermal infrared (TIR) remote sensing due the warm and humid atmospheric conditions. The high spatial resolution of ASTER in the TIR (90 meters) allows us to map the plumes back to their source vents, but also requires us to pay close attention to the temperature and emissivity of the surfaces beneath the plumes. Our knowledge of the surface and atmospheric conditions is never perfect, and we employ interactive mapping techniques that allow us to evaluate the impact of these uncertainties on our estimates of plume composition. To accomplish this interactive mapping we have developed the Plume Tracker tool kit, which integrates retrieval procedures, visualization tools, and a customized version of the MODTRAN radiative transfer (RT) model under a single graphics user interface (GUI). We are in the process of porting the RT calculations to graphics processing units (GPUs) with the goal of achieving a 100-fold increase in the speed of computation relative to conventional CPU-based processing. We will report on our progress with this evolution of Plume Tracker. Portions of this research were conducted at the Jet Propulsion Laboratory

  15. Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    Science.gov (United States)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2016-03-01

    Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

  16. Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

    Science.gov (United States)

    Liu, Z.; Shie, C. L.; Meyer, D. J.

    2017-12-01

    Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

  17. Automated detection and mapping of crown discolouration caused by jack pine budworm with 2.5 m resolution multispectral imagery

    Science.gov (United States)

    Leckie, Donald G.; Cloney, Ed; Joyce, Steve P.

    2005-05-01

    Jack pine budworm ( Choristoneura pinus pinus (Free.)) is a native insect defoliator of mainly jack pine ( Pinus banksiana Lamb.) in North America east of the Rocky Mountains. Periodic outbreaks of this insect, which generally last two to three years, can cause growth loss and mortality and have an important impact ecologically and economically in terms of timber production and harvest. The jack pine budworm prefers to feed on current year needles. Their characteristic feeding habits cause discolouration or reddening of the canopy. This red colouration is used to map the distribution and intensity of defoliation that has taken place that year (current defoliation). An accurate and consistent map of the distribution and intensity of budworm defoliation (as represented by the red discolouration) at the stand and within stand level is desirable. Automated classification of multispectral imagery, such as is available from airborne and new high resolution satellite systems, was explored as a viable tool for objectively classifying current discolouration. Airborne multispectral imagery was acquired at a 2.5 m resolution with the Multispectral Electro-optical Imaging Sensor (MEIS). It recorded imagery in six nadir looking spectral bands specifically designed to detect discolouration caused by budworm and a near-infrared band viewing forward at 35° was also used. A 2200 nm middle infrared image was acquired with a Daedalus scanner. Training and test areas of different levels of discolouration were created based on field observations and a maximum likelihood supervized classification was used to estimate four classes of discolouration (nil-trace, light, moderate and severe). Good discrimination was achieved with an overall accuracy of 84% for the four discolouration levels. The moderate discolouration class was the poorest at 73%, because of confusion with both the severe and light classes. Accuracy on a stand basis was also good, and regional and within stand

  18. Satellite and ground-based sensors for the Urban Heat Island analysis in the city of Rome

    DEFF Research Database (Denmark)

    Fabrizi, Roberto; Bonafoni, Stefania; Biondi, Riccardo

    2010-01-01

    In this work, the trend of the Urban Heat Island (UHI) of Rome is analyzed by both ground-based weather stations and a satellite-based infrared sensor. First, we have developed a suitable algorithm employing satellite brightness temperatures for the estimation of the air temperature belonging...... and nighttime scenes taken between 2003 and 2006 have been processed. Analysis of the Canopy Layer Heat Island (CLHI) during summer months reveals a mean growth in magnitude of 3-4 K during nighttime and a negative or almost zero CLHI intensity during daytime, confirmed by the weather stations. © 2010...... by the authors; licensee MDPI, Basel, Switzerland. Keyword: Thermal pollution,Summer months,Advanced-along track scanning radiometers,Urban heat island,Remote sensing,Canopy layer,Atmospheric temperature,Ground based sensors,Weather information services,Satellite remote sensing,Infra-red sensor,Weather stations...

  19. Application of fractal modeling and PCA method for hydrothermal alteration mapping in the Saveh area (Central Iran) based on ASTER multispectral data

    OpenAIRE

    Mirko Ahmadfaraj; Mirsaleh Mirmohammadi; Peyman Afzal

    2016-01-01

    The aim of this study is determination and separation of alteration zones using Concentration-Area (C-A) fractal model based on remote sensing data which has been extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The studied area is on the SW part of Saveh, 1:250,000 geological map, which is located in Urumieh-Dokhtar magmatic belt, Central Iran. The pixel values were computed by Principal Component Analysis (PCA) method used to determine phyllic, a...

  20. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  1. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  2. Space situational awareness satellites and ground based radiation counting and imaging detector technology

    International Nuclear Information System (INIS)

    Jansen, Frank; Behrens, Joerg; Pospisil, Stanislav; Kudela, Karel

    2011-01-01

    We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

  3. Satellite DNA-based artificial chromosomes for use in gene therapy.

    Science.gov (United States)

    Hadlaczky, G

    2001-04-01

    Satellite DNA-based artificial chromosomes (SATACs) can be made by induced de novo chromosome formation in cells of different mammalian species. These artificially generated accessory chromosomes are composed of predictable DNA sequences and they contain defined genetic information. Prototype human SATACs have been successfully constructed in different cell types from 'neutral' endogenous DNA sequences from the short arm of the human chromosome 15. SATACs have already passed a number of hurdles crucial to their further development as gene therapy vectors, including: large-scale purification; transfer of purified artificial chromosomes into different cells and embryos; generation of transgenic animals and germline transmission with purified SATACs; and the tissue-specific expression of a therapeutic gene from an artificial chromosome in the milk of transgenic animals.

  4. Space situational awareness satellites and ground based radiation counting and imaging detector technology

    Energy Technology Data Exchange (ETDEWEB)

    Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)

    2011-05-15

    We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

  5. Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

    Science.gov (United States)

    1989-01-01

    This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

  6. ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou

    2016-06-01

    Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

  7. Addressing and Presenting Quality of Satellite Data via Web-Based Services

    Science.gov (United States)

    Leptoukh, Gregory; Lynnes, C.; Ahmad, S.; Fox, P.; Zednik, S.; West, P.

    2011-01-01

    With the recent attention to climate change and proliferation of remote-sensing data utilization, climate model and various environmental monitoring and protection applications have begun to increasingly rely on satellite measurements. Research application users seek good quality satellite data, with uncertainties and biases provided for each data point. However, different communities address remote sensing quality issues rather inconsistently and differently. We describe our attempt to systematically characterize, capture, and provision quality and uncertainty information as it applies to the NASA MODIS Aerosol Optical Depth data product. In particular, we note the semantic differences in quality/bias/uncertainty at the pixel, granule, product, and record levels. We outline various factors contributing to uncertainty or error budget; errors. Web-based science analysis and processing tools allow users to access, analyze, and generate visualizations of data while alleviating users from having directly managing complex data processing operations. These tools provide value by streamlining the data analysis process, but usually shield users from details of the data processing steps, algorithm assumptions, caveats, etc. Correct interpretation of the final analysis requires user understanding of how data has been generated and processed and what potential biases, anomalies, or errors may have been introduced. By providing services that leverage data lineage provenance and domain-expertise, expert systems can be built to aid the user in understanding data sources, processing, and the suitability for use of products generated by the tools. We describe our experiences developing a semantic, provenance-aware, expert-knowledge advisory system applied to NASA Giovanni web-based Earth science data analysis tool as part of the ESTO AIST-funded Multi-sensor Data Synergy Advisor project.

  8. How ground-based observations can support satellite greenhouse gas retrievals

    Science.gov (United States)

    Butler, J. H.; Tans, P. P.; Sweeney, C.; Dlugokencky, E. J.

    2012-04-01

    Global society will eventually accelerate efforts to reduce greenhouse gas emissions in a variety of ways. These would likely involve international treaties, national policies, and regional strategies that will affect a number of economic, social, and environmental sectors. Some strategies will work better than others and some will not work at all. Because trillions of dollars will be involved in pursuing greenhouse gas emission reductions - through realignment of energy production, improvement of efficiencies, institution of taxes, implementation of carbon trading markets, and use of offsets - it is imperative that society be given all the tools at its disposal to ensure the ultimate success of these efforts. Providing independent, globally coherent information on the success of these efforts will give considerable strength to treaties, policies, and strategies. Doing this will require greenhouse gas observations greatly expanded from what we have today. Satellite measurements may ultimately be indispensable in achieving global coverage, but the requirements for accuracy and continuity of measurements over time are demanding if the data are to be relevant. Issues such as those associated with sensor drift, aging electronics, and retrieval artifacts present challenges that can be addressed in part by close coordination with ground-based and in situ systems. This presentation identifies the information that ground-based systems provide very well, but it also looks at what would be deficient even in a greatly expanded surface system, where satellites can fill these gaps, and how on-going, ground and in situ measurements can aid in addressing issues associated with accuracy, long-term continuity, and retrieval artifacts.

  9. Costs and benefits of satellite-based tools for irrigation management

    Directory of Open Access Journals (Sweden)

    Francesco eVuolo

    2015-07-01

    Full Text Available This paper presents the results of a collaborative work with farmers and a cost-benefit analysis of geospatial technologies applied to irrigation water management in the semi-arid agricultural area in Lower Austria. We use Earth observation (EO data to estimate crop evapotranspiration (ET and webGIS technologies to deliver maps and irrigation advice to farmers. The study reports the technical and qualitative evaluation performed during a demonstration phase in 2013 and provides an outlook to future developments. The calculation of the benefits is based on a comparison of the irrigation volumes estimated from satellite vs. the irrigation supplied by the farmers. In most cases, the amount of water supplied was equal to the maximum amount of water required by crops. At the same time high variability was observed for the different irrigation units and crop types. Our data clearly indicates that economic benefits could be achieved by reducing irrigation volumes, especially for water-intensive crops. Regarding the qualitative evaluation, most of the farmers expressed a very positive interest in the provided information. In particular, information related to crop ET was appreciated as this helps to make better informed decisions on irrigation. The majority of farmers (54% also expressed a general willingness to pay, either directly or via cost sharing, for such a service. Based on different cost scenarios, we calculated the cost of the service. Considering 20,000 ha regularly irrigated land, the advisory service would cost between 2.5 and 4.3 €/ha per year depending on the type of satellite data used. For comparison, irrigation costs range between 400 and 1000 €/ha per year for a typical irrigation volume of 2,000 cubic meters per ha. With a correct irrigation application, more than 10% of the water and energy could be saved in water-intensive crops, which is equivalent to an economic benefit of 40-100 €/ha per year.

  10. Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems

    Science.gov (United States)

    Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.

    2017-12-01

    Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning

  11. IR-BASED SATELLITE PRODUCTS FOR THE MONITORING OF ATMOSPHERIC WATER VAPOR OVER THE BLACK SEA

    Directory of Open Access Journals (Sweden)

    VELEA LILIANA

    2016-03-01

    Full Text Available The amount of precipitable water (TPW in the atmospheric column is one of the important information used weather forecasting. Some of the studies involving the use of TPW relate to issues like lightning warning system in airports, tornadic events, data assimilation in numerical weather prediction models for short-range forecast, TPW associated with intense rain episodes. Most of the available studies on TPW focus on properties and products at global scale, with the drawback that regional characteristics – due to local processes acting as modulating factors - may be lost. For the Black Sea area, studies on the climatological features of atmospheric moisture are available from sparse or not readily available observational databases or from global reanalysis. These studies show that, although a basin of relatively small dimensions, the Black Sea presents features that may significantly impact on the atmospheric circulation and its general characteristics. Satellite observations provide new opportunities for extending the knowledge on this area and for monitoring atmospheric properties at various scales. In particular, observations in infrared (IR spectrum are suitable for studies on small-scale basins, due to the finer spatial sampling and reliable information in the coastal areas. As a first step toward the characterization of atmospheric moisture over the Black Sea from satellite-based information, we investigate three datasets of IR-based products which contain information on the total amount of moisture and on its vertical distribution, available in the area of interest. The aim is to provide a comparison of these data with regard to main climatological features of moisture in this area and to highlight particular strengths and limits of each of them, which may be helpful in the choice of the most suitable dataset for a certain application.

  12. Accuracy and impact of spatial aids based upon satellite enumeration to improve indoor residual spraying spatial coverage.

    Science.gov (United States)

    Bridges, Daniel J; Pollard, Derek; Winters, Anna M; Winters, Benjamin; Sikaala, Chadwick; Renn, Silvia; Larsen, David A

    2018-02-23

    Indoor residual spraying (IRS) is a key tool in the fight to control, eliminate and ultimately eradicate malaria. IRS protection is based on a communal effect such that an individual's protection primarily relies on the community-level coverage of IRS with limited protection being provided by household-level coverage. To ensure a communal effect is achieved through IRS, achieving high and uniform community-level coverage should be the ultimate priority of an IRS campaign. Ensuring high community-level coverage of IRS in malaria-endemic areas is challenging given the lack of information available about both the location and number of households needing IRS in any given area. A process termed 'mSpray' has been developed and implemented and involves use of satellite imagery for enumeration for planning IRS and a mobile application to guide IRS implementation. This study assessed (1) the accuracy of the satellite enumeration and (2) how various degrees of spatial aid provided through the mSpray process affected community-level IRS coverage during the 2015 spray campaign in Zambia. A 2-stage sampling process was applied to assess accuracy of satellite enumeration to determine number and location of sprayable structures. Results indicated an overall sensitivity of 94% for satellite enumeration compared to finding structures on the ground. After adjusting for structure size, roof, and wall type, households in Nchelenge District where all types of satellite-based spatial aids (paper-based maps plus use of the mobile mSpray application) were used were more likely to have received IRS than Kasama district where maps used were not based on satellite enumeration. The probability of a household being sprayed in Nchelenge district where tablet-based maps were used, did not differ statistically from that of a household in Samfya District, where detailed paper-based spatial aids based on satellite enumeration were provided. IRS coverage from the 2015 spray season benefited from

  13. Water availability forecasting for Naryn River using ground-based and satellite snow cover data

    Directory of Open Access Journals (Sweden)

    O. Y. Kalashnikova

    2017-01-01

    Full Text Available The main source of river nourishment in arid regions of Central Asia is the melting of seasonal snow accu‑ mulated in mountains during the cold period. In this study, we analyzed data on seasonal snow cover by ground‑based observations from Kyrgyzhydromet network, as well as from MODIS satellite imagery for the period of 2000–2015. This information was used to compile the forecast methods of water availability of snow‑ice and ice‑snow fed rivers for the vegetation period. The Naryn river basin was chosen as a study area which is the main tributary of Syrdarya River and belongs to the Aral Sea basin. The representative mete‑ orological stati