Assessing Temporal Stability for Coarse Scale Satellite Moisture Validation in the Maqu Area, Tibet

Science.gov (United States)

Bhatti, Haris Akram; Rientjes, Tom; Verhoef, Wouter; Yaseen, Muhammad

2013-01-01

This study evaluates if the temporal stability concept is applicable to a time series of satellite soil moisture images so to extend the common procedure of satellite image validation. The area of study is the Maqu area, which is located in the northeastern part of the Tibetan plateau. The network serves validation purposes of coarse scale (25–50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. The study period is 2009. The temporal stability concept is applied to all five depths of the soil moisture measuring network and to a time series of satellite-based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E). The in-situ network is also assessed by Pearsons's correlation analysis. Assessments by the temporal stability concept proved to be useful and results suggest that probe measurements at 10 cm depth best match to the satellite observations. The Mean Relative Difference plot for satellite pixels shows that a RMSM pixel can be identified but in our case this pixel does not overlay any in-situ station. Also, the RMSM pixel does not overlay any of the Representative Mean Soil Moisture (RMSM) stations of the five probe depths. Pearson's correlation analysis on in-situ measurements suggests that moisture patterns over time are more persistent than over space. Since this study presents first results on the application of the temporal stability concept to a series of satellite images, we recommend further tests to become more conclusive on effectiveness to broaden the procedure of satellite validation. PMID:23959237

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.

Downscaling Coarse Scale Microwave Soil Moisture Product using Machine Learning

Science.gov (United States)

Abbaszadeh, P.; Moradkhani, H.; Yan, H.

2016-12-01

Soil moisture (SM) is a key variable in partitioning and examining the global water-energy cycle, agricultural planning, and water resource management. It is also strongly coupled with climate change, playing an important role in weather forecasting and drought monitoring and prediction, flood modeling and irrigation management. Although satellite retrievals can provide an unprecedented information of soil moisture at a global-scale, the products might be inadequate for basin scale study or regional assessment. To improve the spatial resolution of SM, this work presents a novel approach based on Machine Learning (ML) technique that allows for downscaling of the satellite soil moisture to fine resolution. For this purpose, the SMAP L-band radiometer SM products were used and conditioned on the Variable Infiltration Capacity (VIC) model prediction to describe the relationship between the coarse and fine scale soil moisture data. The proposed downscaling approach was applied to a western US basin and the products were compared against the available SM data from in-situ gauge stations. The obtained results indicated a great potential of the machine learning technique to derive the fine resolution soil moisture information that is currently used for land data assimilation applications.

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Accounting for surface reflectance anisotropy in satellite retrievals of tropospheric NO₂

NARCIS (Netherlands)

Zhou, Yipin; Brunner, D.; Spurr, R.J.D.; Boersma, K.F.; Sneep, M.; Popp, C.; Buchmann, B.

2010-01-01

Surface reflectance is a key parameter in satellite trace gas retrievals in the UV/visible range and in particular for the retrieval of nitrogen dioxide (NO2) vertical tropospheric columns (VTCs). Current operational retrievals rely on coarse-resolution reflectance data and do not account for the

Classification of high resolution satellite images

OpenAIRE

Karlsson, Anders

2003-01-01

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

Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

International Nuclear Information System (INIS)

Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

2011-01-01

Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

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

Science.gov (United States)

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

2017-12-01

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

Global High Resolution Sea Surface Flux Parameters From Multiple Satellites

Science.gov (United States)

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

2007-05-01

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

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

Science.gov (United States)

Fishman, Moshe

1999-12-01

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

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

Science.gov (United States)

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

2018-04-13

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

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.

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

Science.gov (United States)

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

Landslide detection using very high-resolution satellite imageries

Science.gov (United States)

Suga, Yuzo; Konishi, Tomohisa

2012-10-01

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

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

Science.gov (United States)

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

2007-09-01

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

Framework of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

Xiaohua Tong

2014-05-01

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

A method for generating high resolution satellite image time series

Science.gov (United States)

Guo, Tao

2014-10-01

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

People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users' perceptions of their changing environment in Senegal

Directory of Open Access Journals (Sweden)

Stefanie M. Herrmann

2014-09-01

Full Text Available Mounting evidence from satellite observations of a re-greening across much of the Sahel and Sudan zones over the past three decades has raised questions about the extent and reversibility of desertification. Historical ground data that could help in interpreting the re-greening are scarce. To fill that void, we tapped into the collective memories of local land users from central and western Senegal in 39 focus groups and assessed the spatial association between their perceptions of vegetation changes over time and remote sensing-derived trends. To provide context to the vegetation changes, we also explored the land users' perspective on the evolution of other environmental and human variables that are potentially related to the greening, using participatory research methods. While increases in vegetation were confirmed by the study participants for certain areas, which spatially corresponded to satellite-observed re-greening, vegetation degradation dominated their perceptions of change. This degradation, although spatially extensive according to land users, flies under the radar of coarse-resolution remote sensing data because it is not necessarily associated with a decrease in biomass but rather with undesired changes in species composition. Few significant differences were found in the perceived trends of population pressure, environmental, and livelihood variables between communities that have greened up according to satellite data and those that have not. Our findings challenge the prevailing chain of assumptions of the satellite-observed greening trend indicating an improvement of environmental conditions in the sense of a rehabilitation of the vegetation cover after the great droughts of the 1970s and 1980s, and the improvement of environmental conditions possibly translating into more stable livelihoods and greater well-being of the populations. For monitoring desertification and rehabilitation, there is a need to develop remote sensing

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

Data.gov (United States)

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

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

Science.gov (United States)

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

2017-11-01

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

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Z. Xia

2018-04-01

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

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

Directory of Open Access Journals (Sweden)

Aoran Xiao

2018-04-01

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

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

Directory of Open Access Journals (Sweden)

Lili Li

2015-06-01

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

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

Directory of Open Access Journals (Sweden)

K. Gong

2017-05-01

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

Ambiguity resolution for satellite Doppler positioning systems

Science.gov (United States)

Argentiero, P.; Marini, J.

1979-01-01

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

Spectroscopic Characterization of GEO Satellites with Gunma LOW Resolution Spectrograph

Science.gov (United States)

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

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

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.

Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment

Directory of Open Access Journals (Sweden)

Guiping Wu

2015-11-01

Full Text Available The availability of water surface inundation with high spatial resolution is of fundamental importance in several applications such as hydrology, meteorology and ecology. Medium spatial resolution sensors, like MODerate-resolution Imaging Spectroradiometer (MODIS, exhibit a significant potential to study inundation dynamics over large areas because of their high temporal resolution. However, the low spatial resolution provided by MODIS is not appropriate to accurately delineate inundation over small scale. Successful downscaling of water inundation from coarse to fine resolution would be crucial for improving our understanding of complex inundation characteristics over the regional scale. Therefore, in this study, we propose an innovative downscaling method based on the normalized difference water index (NDWI statistical regression algorithm towards generating small-scale resolution inundation maps from MODIS data. The method was then applied to the Poyang Lake of China. To evaluate the performance of the proposed downscaling method, qualitative and quantitative comparisons were conducted between the inundation extent of MODIS (250 m, Landsat (30 m and downscaled MODIS (30 m. The results indicated that the downscaled MODIS (30 m inundation showed significant improvement over the original MODIS observations when compared with simultaneous Landsat (30 m inundation. The edges of the lakes become smoother than the results from original MODIS image and some undetected water bodies were delineated with clearer shapes in the downscaled MODIS (30 m inundation map. With respect to high-resolution Landsat TM/ETM+ derived inundation, the downscaling procedure has significantly increased the R2 and reduced RMSE and MAE both for the inundation area and for the value of landscape metrics. The main conclusion of this study is that the downscaling algorithm is promising and quite feasible for the inundation mapping over small-scale lakes.

Modeling the Self-assembly and Stability of DHPC Micelles using Atomic Resolution and Coarse Grained MD Simulations

DEFF Research Database (Denmark)

Kraft, Johan Frederik; Vestergaard, Mikkel; Schiøtt, Birgit

2012-01-01

Membrane mimics such as micelles and bicelles are widely used in experiments involving membrane proteins. With the aim of being able to carry out molecular dynamics simulations in environments comparable to experimental conditions, we set out to test the ability of both coarse grained and atomistic...... resolution force fields to model the experimentally observed behavior of the lipid 1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC), which is a widely used lipid for biophysical characterization of membrane proteins. It becomes clear from our results that a satisfactory modeling of DHPC aggregates...

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

Science.gov (United States)

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

2009-12-01

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

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

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Oscar Rojas

2013-04-01

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

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

Science.gov (United States)

AlShamsi, Meera R.

2016-10-01

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

Asian Dust Weather Categorization with Satellite and Surface Observations

Science.gov (United States)

Lin, Tang-Huang; Hsu, N. Christina; Tsay, Si-Chee; Huang, Shih-Jen

2011-01-01

This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with China s weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

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

Science.gov (United States)

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

2007-01-01

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

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

Science.gov (United States)

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

2017-11-01

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

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

African Journals Online (AJOL)

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

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

Science.gov (United States)

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

2009-01-01

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

A high-resolution and observationally constrained OMI NO2 satellite retrieval

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

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

2017-11-01

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

GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

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Catherine Mering

2011-05-01

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

Autonomous Sun-Direction Estimation Using Partially Underdetermined Coarse Sun Sensor Configurations

Science.gov (United States)

O'Keefe, Stephen A.

In recent years there has been a significant increase in interest in smaller satellites as lower cost alternatives to traditional satellites, particularly with the rise in popularity of the CubeSat. Due to stringent mass, size, and often budget constraints, these small satellites rely on making the most of inexpensive hardware components and sensors, such as coarse sun sensors (CSS) and magnetometers. More expensive high-accuracy sun sensors often combine multiple measurements, and use specialized electronics, to deterministically solve for the direction of the Sun. Alternatively, cosine-type CSS output a voltage relative to the input light and are attractive due to their very low cost, simplicity to manufacture, small size, and minimal power consumption. This research investigates using coarse sun sensors for performing robust attitude estimation in order to point a spacecraft at the Sun after deployment from a launch vehicle, or following a system fault. As an alternative to using a large number of sensors, this thesis explores sun-direction estimation techniques with low computational costs that function well with underdetermined sets of CSS. Single-point estimators are coupled with simultaneous nonlinear control to achieve sun-pointing within a small percentage of a single orbit despite the partially underdetermined nature of the sensor suite. Leveraging an extensive analysis of the sensor models involved, sequential filtering techniques are shown to be capable of estimating the sun-direction to within a few degrees, with no a priori attitude information and using only CSS, despite the significant noise and biases present in the system. Detailed numerical simulations are used to compare and contrast the performance of the five different estimation techniques, with and without rate gyro measurements, their sensitivity to rate gyro accuracy, and their computation time. One of the key concerns with reducing the number of CSS is sensor degradation and failure. In

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

Directory of Open Access Journals (Sweden)

TONG Xiaohua

2017-10-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

Directory of Open Access Journals (Sweden)

P. Agrafiotis

2015-03-01

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

A method for optical ground station reduce alignment error in satellite-ground quantum experiments

Science.gov (United States)

He, Dong; Wang, Qiang; Zhou, Jian-Wei; Song, Zhi-Jun; Zhong, Dai-Jun; Jiang, Yu; Liu, Wan-Sheng; Huang, Yong-Mei

2018-03-01

A satellite dedicated for quantum science experiments, has been developed and successfully launched from Jiuquan, China, on August 16, 2016. Two new optical ground stations (OGSs) were built to cooperate with the satellite to complete satellite-ground quantum experiments. OGS corrected its pointing direction by satellite trajectory error to coarse tracking system and uplink beacon sight, therefore fine tracking CCD and uplink beacon optical axis alignment accuracy was to ensure that beacon could cover the quantum satellite in all time when it passed the OGSs. Unfortunately, when we tested specifications of the OGSs, due to the coarse tracking optical system was commercial telescopes, the change of position of the target in the coarse CCD was up to 600μrad along with the change of elevation angle. In this paper, a method of reduce alignment error between beacon beam and fine tracking CCD is proposed. Firstly, OGS fitted the curve of target positions in coarse CCD along with the change of elevation angle. Secondly, OGS fitted the curve of hexapod secondary mirror positions along with the change of elevation angle. Thirdly, when tracking satellite, the fine tracking error unloaded on the real-time zero point position of coarse CCD which computed by the firstly calibration data. Simultaneously the positions of the hexapod secondary mirror were adjusted by the secondly calibration data. Finally the experiment result is proposed. Results show that the alignment error is less than 50μrad.

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

Directory of Open Access Journals (Sweden)

Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

KAUST Repository

Altaf, Muhammad; Jana, Raghavendra Belur; Hoteit, Ibrahim; McCabe, Matthew

2016-01-01

on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

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M. Tom

2018-05-01

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

Lake Ice Detection in Low-Resolution Optical Satellite Images

Science.gov (United States)

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

2018-05-01

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

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

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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.

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

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

2014-12-01

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

A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

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Yinping Long

2016-07-01

Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

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

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

2017-12-01

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

Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS).

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Huff, Amy K; Kondragunta, Shobha; Zhang, Hai; Hoff, Raymond M

2015-01-01

Increasing development of exo-urban environments and the spread of urbanization into forested areas is making humans and forest ecosystems more susceptible to the risks associated with wildfires. Larger and more damaging wildfires are having a negative impact on forest ecosystem services, and smoke from wildfires adversely affects the public health of people living in exo-urban environments. Satellite aerosol measurements are valuable tools that can track the evolution of wildfires and monitor the transport of smoke plumes. Operational users, such as air quality forecasters and fire management officials, can use satellite observations to complement ground-based and aircraft measurements of wildfire activity. To date, wildfire applications of satellite aerosol products, such as aerosol optical depth (AOD), have been limited by the relatively coarse resolution of available AOD data. However, the new Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite has high-resolution AOD that is ideally suited to monitoring wildfire impacts on the exo-urban scale. Two AOD products are available from VIIRS: the 750-m × 750-m nadir resolution Intermediate Product (IP) and the 6-km × 6-km resolution Environmental Data Record product, which is aggregated from IP measurements. True color (red, green, and blue [RGB]) imagery and a smoke mask at 750-m × 750-m resolution are also available from VIIRS as decision aids for wildfire applications; they serve as counterparts to AOD measurements by providing visible information about areas of smoke in the atmosphere. To meet the needs of operational users, who do not have time to process raw data files and need access to VIIRS products in near-real time (NRT), VIIRS AOD and RGB NRT imagery are available from the Infusing satellite Data into Environmental Applications (IDEA) web site. A key feature of IDEA is an interactive visualization tool that allows users to

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

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R. Kaczynski

2012-07-01

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

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

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Xueke Li

2016-05-01

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

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

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Zhao, J.; Ghedira, H.

2013-12-01

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

Estimating the maritime component of aerosol optical depth and its dependency on surface wind speed using satellite data

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Y. Lehahn

2010-07-01

Full Text Available Six years (2003–2008 of satellite measurements of aerosol parameters from the Moderate Resolution Imaging Spectroradiometer (MODIS and surface wind speeds from Quick Scatterometer (QuikSCAT, the Advanced Microwave Scanning Radiometer (AMSR-E, and the Special Sensor Microwave Imager (SSM/I, are used to provide a comprehensive perspective on the link between surface wind speed and marine aerosol optical depth over tropical and subtropical oceanic regions. A systematic comparison between the satellite derived fields in these regions allows to: (i separate the relative contribution of wind-induced marine aerosol to the aerosol optical depth; (ii extract an empirical linear equation linking coarse marine aerosol optical depth and wind intensity; and (iii identify a time scale for correlating marine aerosol optical depth and surface wind speed. The contribution of wind induced marine aerosol to aerosol optical depth is found to be dominated by the coarse mode elements. When wind intensity exceeds 4 m/s, coarse marine aerosol optical depth is linearly correlated with the surface wind speed, with a remarkably consistent slope of 0.009±0.002 s/m. A detailed time scale analysis shows that the linear correlation between the fields is well kept within a 12 h time frame, while sharply decreasing when the time lag between measurements is longer. The background aerosol optical depth, associated with aerosols that are not produced in-situ through wind driven processes, can be used for estimating the contributions of terrestrial and biogenic marine aerosol to over-ocean satellite retrievals of aerosol optical depth.

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

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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.

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

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

2017-09-01

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

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

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

2016-06-01

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

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

Science.gov (United States)

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

2014-06-01

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

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Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

2017-12-01

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product

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

Science.gov (United States)

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

2010-05-01

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

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

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Hester, David Barry

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

Leishmaniasis transmission: distribution and coarse-resolution ecology of two vectors and two parasites in Egypt

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Abdallah M. Samy

2014-01-01

Full Text Available Introduction: In past decades, leishmaniasis burden has been low across Egypt; however, changing environment and land use has placed several parts of the country at risk. As a consequence, leishmaniasis has become a particularly difficult health problem, both for local inhabitants and for multinational military personnel. Methods: To evaluate coarse-resolution aspects of the ecology of leishmaniasis transmission, collection records for sandflies and Leishmania species were obtained from diverse sources. To characterize environmental variation across the country, we used multitemporal Land Surface Temperature (LST and Normalized Difference Vegetation Index (NDVI data from the Moderate Resolution Imaging Spectroradiometer (MODIS for 2005-2011. Ecological niche models were generated using MaxEnt, and results were analyzed using background similarity tests to assess whether associations among vectors and parasites (i.e., niche similarity can be detected across broad geographic regions. Results: We found niche similarity only between one vector species and its corresponding parasite species (i.e., Phlebotomus papatasi with Leishmania major, suggesting that geographic ranges of zoonotic cutaneous leishmaniasis and its potential vector may overlap, but under distinct environmental associations. Other associations (e.g., P. sergenti with L. major were not supported. Mapping suitable areas for each species suggested that northeastern Egypt is particularly at risk because both parasites have potential to circulate. Conclusions: Ecological niche modeling approaches can be used as a first-pass assessment of vector-parasite interactions, offering useful insights into constraints on the geography of transmission patterns of leishmaniasis.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

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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.

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

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

2015-12-01

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

THE IMPACT OF SPATIAL AND TEMPORAL RESOLUTIONS IN TROPICAL SUMMER RAINFALL DISTRIBUTION: PRELIMINARY RESULTS

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Q. Liu

2017-10-01

Full Text Available The abundance or lack of rainfall affects peoples’ life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007, accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG. However, the models’ resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days and monthly resolutions. The probability distributions (PDF and cumulative distribution functions(CDF of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

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Liu, Q.; Chiu, L. S.; Hao, X.

2017-10-01

The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

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

Data.gov (United States)

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

Retrieving global aerosol sources from satellites using inverse modeling

Directory of Open Access Journals (Sweden)

O. Dubovik

2008-01-01

Full Text Available Understanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model.

The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators.

Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful

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

Science.gov (United States)

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

2015-03-01

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

Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

Science.gov (United States)

Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

2009-11-01

In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

Post-Disturbance Stability of Fish Assemblages Measured at Coarse Taxonomic Resolution Masks Change at Finer Scales.

Science.gov (United States)

Ceccarelli, Daniela M; Emslie, Michael J; Richards, Zoe T

2016-01-01

Quantifying changes to coral reef fish assemblages in the wake of cyclonic disturbances is challenging due to spatial variability of damage inherent in such events. Often, fish abundance appears stable at one spatial scale (e.g. reef-wide), but exhibits substantial change at finer scales (e.g. site-specific decline or increase). Taxonomic resolution also plays a role; overall stability at coarse taxonomic levels (e.g. family) may mask species-level turnover. Here we document changes to reef fish communities after severe Tropical Cyclone Ita crossed Lizard Island, Great Barrier Reef. Coral and reef fish surveys were conducted concurrently before and after the cyclone at four levels of exposure to the prevailing weather. Coral cover declined across all exposures except sheltered sites, with the largest decline at exposed sites. There was no significant overall reduction in the total density, biomass and species richness of reef fishes between 2011 and 2015, but individual fish taxa (families and species) changed in complex and unpredictable ways. For example, more families increased in density and biomass than decreased following Cyclone Ita, particularly at exposed sites whilst more fish families declined at lagoon sites even though coral cover did not decline. All sites lost biomass of several damselfish species, and at most sites there was an increase in macroinvertivores and grazers. Overall, these results suggest that the degree of change measured at coarse taxonomic levels masked high species-level turnover, although other potential explanations include that there was no impact of the storm, fish assemblages were impacted but underwent rapid recovery or that there is a time lag before the full impacts become apparent. This study confirms that in high-complexity, high diversity ecosystems such as coral reefs, species level analyses are essential to adequately capture the consequences of disturbance events.

GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

Energy Technology Data Exchange (ETDEWEB)

Cihlar, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Chen, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Toronto, Dept. of Geography, Toronto, Ontario (Canada); Li, Z. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Maryland, Dept of Meteorology, College Park, MD (United States)] [and others

2002-02-01

Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

International Nuclear Information System (INIS)

Cihlar, J.; Chen, J.; Li, Z.

2002-01-01

Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

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

OpenAIRE

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

2016-01-01

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

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

Science.gov (United States)

Vanhellemont, Q.

2016-02-01

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

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

OpenAIRE

Chandi Witharana; Heather J. Lynch

2016-01-01

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

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

International Nuclear Information System (INIS)

Yang Xu; Liu Dechang; Zhang Jielin

2008-01-01

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

Identifying grain-size dependent errors on global forest area estimates and carbon studies

Science.gov (United States)

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our...

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

Science.gov (United States)

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

2016-12-01

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

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

Data.gov (United States)

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

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

Science.gov (United States)

Kotsuki, S.; Tanaka, K.

2015-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Optimal Design of Experiments by Combining Coarse and Fine Measurements

Science.gov (United States)

Lee, Alpha A.; Brenner, Michael P.; Colwell, Lucy J.

2017-11-01

In many contexts, it is extremely costly to perform enough high-quality experimental measurements to accurately parametrize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that indicate whether each sample is above or below a given threshold. Can many such categorical or "coarse" measurements be combined with a much smaller number of high-resolution or "fine" measurements to yield accurate models? Here, we demonstrate an intuitive strategy, inspired by statistical physics, wherein the coarse measurements are used to identify the salient features of the data, while the fine measurements determine the relative importance of these features. A linear model is inferred from the fine measurements, augmented by a quadratic term that captures the correlation structure of the coarse data. We illustrate our strategy by considering the problems of predicting the antimalarial potency and aqueous solubility of small organic molecules from their 2D molecular structure.

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

Science.gov (United States)

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

2015-12-01

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

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

Science.gov (United States)

Benzouai, Siham; Smara, Youcef

2010-12-01

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

Adaptive resolution simulation of salt solutions

International Nuclear Information System (INIS)

Bevc, Staš; Praprotnik, Matej; Junghans, Christoph; Kremer, Kurt

2013-01-01

We present an adaptive resolution simulation of aqueous salt (NaCl) solutions at ambient conditions using the adaptive resolution scheme. Our multiscale approach concurrently couples the atomistic and coarse-grained models of the aqueous NaCl, where water molecules and ions change their resolution while moving from one resolution domain to the other. We employ standard extended simple point charge (SPC/E) and simple point charge (SPC) water models in combination with AMBER and GROMOS force fields for ion interactions in the atomistic domain. Electrostatics in our model are described by the generalized reaction field method. The effective interactions for water–water and water–ion interactions in the coarse-grained model are derived using structure-based coarse-graining approach while the Coulomb interactions between ions are appropriately screened. To ensure an even distribution of water molecules and ions across the simulation box we employ thermodynamic forces. We demonstrate that the equilibrium structural, e.g. radial distribution functions and density distributions of all the species, and dynamical properties are correctly reproduced by our adaptive resolution method. Our multiscale approach, which is general and can be used for any classical non-polarizable force-field and/or types of ions, will significantly speed up biomolecular simulation involving aqueous salt. (paper)

Predictive coarse-graining

Energy Technology Data Exchange (ETDEWEB)

Schöberl, Markus, E-mail: m.schoeberl@tum.de [Continuum Mechanics Group, Technical University of Munich, Boltzmannstraße 15, 85748 Garching (Germany); Zabaras, Nicholas [Institute for Advanced Study, Technical University of Munich, Lichtenbergstraße 2a, 85748 Garching (Germany); Department of Aerospace and Mechanical Engineering, University of Notre Dame, 365 Fitzpatrick Hall, Notre Dame, IN 46556 (United States); Koutsourelakis, Phaedon-Stelios [Continuum Mechanics Group, Technical University of Munich, Boltzmannstraße 15, 85748 Garching (Germany)

2017-03-15

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extended to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo – Expectation–Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Directory of Open Access Journals (Sweden)

Ghangho Kim

2015-04-01

Full Text Available A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO satellite using single-epoch measurements from a Global Positioning System (GPS receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS. Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state.

Coarse Initial Orbit Determination for a Geostationary Satellite Using Single-Epoch GPS Measurements

Science.gov (United States)

Kim, Ghangho; Kim, Chongwon; Kee, Changdon

2015-01-01

A practical algorithm is proposed for determining the orbit of a geostationary orbit (GEO) satellite using single-epoch measurements from a Global Positioning System (GPS) receiver under the sparse visibility of the GPS satellites. The algorithm uses three components of a state vector to determine the satellite’s state, even when it is impossible to apply the classical single-point solutions (SPS). Through consideration of the characteristics of the GEO orbital elements and GPS measurements, the components of the state vector are reduced to three. However, the algorithm remains sufficiently accurate for a GEO satellite. The developed algorithm was tested on simulated measurements from two or three GPS satellites, and the calculated maximum position error was found to be less than approximately 40 km or even several kilometers within the geometric range, even when the classical SPS solution was unattainable. In addition, extended Kalman filter (EKF) tests of a GEO satellite with the estimated initial state were performed to validate the algorithm. In the EKF, a reliable dynamic model was adapted to reduce the probability of divergence that can be caused by large errors in the initial state. PMID:25835299

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

Directory of Open Access Journals (Sweden)

Nahuel R. Peralta

2016-10-01

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

Multiresolution Modeling of Semidilute Polymer Solutions: Coarse-Graining Using Wavelet-Accelerated Monte Carlo

Directory of Open Access Journals (Sweden)

Animesh Agarwal

2017-09-01

Full Text Available We present a hierarchical coarse-graining framework for modeling semidilute polymer solutions, based on the wavelet-accelerated Monte Carlo (WAMC method. This framework forms a hierarchy of resolutions to model polymers at length scales that cannot be reached via atomistic or even standard coarse-grained simulations. Previously, it was applied to simulations examining the structure of individual polymer chains in solution using up to four levels of coarse-graining (Ismail et al., J. Chem. Phys., 2005, 122, 234901 and Ismail et al., J. Chem. Phys., 2005, 122, 234902, recovering the correct scaling behavior in the coarse-grained representation. In the present work, we extend this method to the study of polymer solutions, deriving the bonded and non-bonded potentials between coarse-grained superatoms from the single chain statistics. A universal scaling function is obtained, which does not require recalculation of the potentials as the scale of the system is changed. To model semi-dilute polymer solutions, we assume the intermolecular potential between the coarse-grained beads to be equal to the non-bonded potential, which is a reasonable approximation in the case of semidilute systems. Thus, a minimal input of microscopic data is required for simulating the systems at the mesoscopic scale. We show that coarse-grained polymer solutions can reproduce results obtained from the more detailed atomistic system without a significant loss of accuracy.

Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

Science.gov (United States)

Shen, Lin; Yang, Weitao

2016-04-12

We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

Hyper-Resolution Groundwater Modeling using MODFLOW 6

Science.gov (United States)

Hughes, J. D.; Langevin, C.

2017-12-01

MODFLOW 6 is the latest version of the U.S. Geological Survey's modular hydrologic model. MODFLOW 6 was developed to synthesize many of the recent versions of MODFLOW into a single program, improve the way different process models are coupled, and to provide an object-oriented framework for adding new types of models and packages. The object-oriented framework and underlying numerical solver make it possible to tightly couple any number of hyper-resolution models within coarser regional models. The hyper-resolution models can be used to evaluate local-scale groundwater issues that may be affected by regional-scale forcings. In MODFLOW 6, hyper-resolution meshes can be maintained as separate model datasets, similar to MODFLOW-LGR, which simplifies the development of a coarse regional model with imbedded hyper-resolution models from a coarse regional model. For example, the South Atlantic Coastal Plain regional water availability model was converted from a MODFLOW-2000 model to a MODFLOW 6 model. The horizontal discretization of the original model is approximately 3,218 m x 3,218 m. Hyper-resolution models of the Aiken and Sumter County water budget areas in South Carolina with a horizontal discretization of approximately 322 m x 322 m were developed and were tightly coupled to a modified version of the original coarse regional model that excluded these areas. Hydraulic property and aquifer geometry data from the coarse model were mapped to the hyper-resolution models. The discretization of the hyper-resolution models is fine enough to make detailed analyses of the effect that changes in groundwater withdrawals in the production aquifers have on the water table and surface-water/groundwater interactions. The approach used in this analysis could be applied to other regional water availability models that have been developed by the U.S. Geological Survey to evaluate local scale groundwater issues.

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

Science.gov (United States)

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

2015-09-01

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

Are satellite products good proxies for gauge precipitation over Singapore?

Science.gov (United States)

Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

2018-05-01

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate

Downscaling Satellite Land Surface Temperatures in Urban Regions for Surface Energy Balance Study and Heat Index Development

Science.gov (United States)

Norouzi, H.; Bah, A.; Prakash, S.; Nouri, N.; Blake, R.

2017-12-01

A great percentage of the world's population reside in urban areas that are exposed to the threats of global and regional climate changes and associated extreme weather events. Among them, urban heat islands have significant health and economic impacts due to higher thermal gradients of impermeable surfaces in urban regions compared to their surrounding rural areas. Therefore, accurate characterization of the surface energy balance in urban regions are required to predict these extreme events. High spatial resolution Land surface temperature (LST) in the scale of street level in the cities can provide wealth of information to study surface energy balance and eventually providing a reliable heat index. In this study, we estimate high-resolution LST maps using combination of LandSat 8 and infrared based satellite products such as Moderate Resolution Imaging Spectroradiometer (MODIS) and newly launched Geostationary Operational Environmental Satellite-R Series (GOES-R). Landsat 8 provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. However, MODIS and GOES-R have lower spatial resolution (1km and 4km respectively) with much higher temporal resolution. Several statistical downscaling methods were investigated to provide high spatiotemporal LST maps in urban regions. The results reveal that statistical methods such as Principal Component Analysis (PCA) can provide reliable estimations of LST downscaling with 2K accuracy. Other methods also were tried including aggregating (up-scaling) the high-resolution data to a coarse one to examine the limitations and to build the model. Additionally, we deployed flux towers over distinct materials such as concrete, asphalt, and rooftops in New York City to monitor the sensible and latent heat fluxes through eddy covariance method. To account for the incoming and outgoing radiation, a 4-component radiometer is used that can observe both incoming and outgoing longwave and shortwave radiation. This

Adaptive resolution simulation of an atomistic protein in MARTINI water

International Nuclear Information System (INIS)

Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J.; Praprotnik, Matej

2014-01-01

We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecular dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM).

Science.gov (United States)

Sinitskiy, Anton V; Voth, Gregory A

2018-01-07

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM)

Science.gov (United States)

Sinitskiy, Anton V.; Voth, Gregory A.

2018-01-01

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

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

Science.gov (United States)

Otrio, G.

1980-01-01

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

Automatic Blocked Roads Assessment after Earthquake Using High Resolution Satellite Imagery

Science.gov (United States)

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

2015-12-01

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

Integrating Landsat Data and High-Resolution Imagery for Applied Conservation Assessment of Forest Cover in Latin American Heterogenous Landscapes

Science.gov (United States)

Thomas, N.; Rueda, X.; Lambin, E.; Mendenhall, C. D.

2012-12-01

Large intact forested regions of the world are known to be critical to maintaining Earth's climate, ecosystem health, and human livelihoods. Remote sensing has been successfully implemented as a tool to monitor forest cover and landscape dynamics over broad regions. Much of this work has been done using coarse resolution sensors such as AVHRR and MODIS in combination with moderate resolution sensors, particularly Landsat. Finer scale analysis of heterogeneous and fragmented landscapes is commonly performed with medium resolution data and has had varying success depending on many factors including the level of fragmentation, variability of land cover types, patch size, and image availability. Fine scale tree cover in mixed agricultural areas can have a major impact on biodiversity and ecosystem sustainability but may often be inadequately captured with the global to regional (coarse resolution and moderate resolution) satellite sensors and processing techniques widely used to detect land use and land cover changes. This study investigates whether advanced remote sensing methods are able to assess and monitor percent tree canopy cover in spatially complex human-dominated agricultural landscapes that prove challenging for traditional mapping techniques. Our study areas are in high altitude, mixed agricultural coffee-growing regions in Costa Rica and the Colombian Andes. We applied Random Forests regression tree analysis to Landsat data along with additional spectral, environmental, and spatial variables to predict percent tree canopy cover at 30m resolution. Image object-based texture, shape, and neighborhood metrics were generated at the Landsat scale using eCognition and included in the variable suite. Training and validation data was generated using high resolution imagery from digital aerial photography at 1m to 2.5 m resolution. Our results are promising with Pearson's correlation coefficients between observed and predicted percent tree canopy cover of .86 (Costa

Review of surface particulate monitoring of dust events using geostationary satellite remote sensing

Science.gov (United States)

Sowden, M.; Mueller, U.; Blake, D.

2018-06-01

The accurate measurements of natural and anthropogenic aerosol particulate matter (PM) is important in managing both environmental and health risks; however, limited monitoring in regional areas hinders accurate quantification. This article provides an overview of the ability of recently launched geostationary earth orbit (GEO) satellites, such as GOES-R (North America) and HIMAWARI (Asia and Oceania), to provide near real-time ground-level PM concentrations (GLCs). The review examines the literature relating to the spatial and temporal resolution required by air quality studies, the removal of cloud and surface effects, the aerosol inversion problem, and the computation of ground-level concentrations rather than columnar aerosol optical depth (AOD). Determining surface PM concentrations using remote sensing is complicated by differentiating intrinsic aerosol properties (size, shape, composition, and quantity) from extrinsic signal intensities, particularly as the number of unknown intrinsic parameters exceeds the number of known extrinsic measurements. The review confirms that development of GEO satellite products has led to improvements in the use of coupled products such as GEOS-CHEM, aerosol types have consolidated on model species rather than prior descriptive classifications, and forward radiative transfer models have led to a better understanding of predictive spectra interdependencies across different aerosol types, despite fewer wavelength bands. However, it is apparent that the aerosol inversion problem remains challenging because there are limited wavelength bands for characterising localised mineralogy. The review finds that the frequency of GEO satellite data exceeds the temporal resolution required for air quality studies, but the spatial resolution is too coarse for localised air quality studies. Continual monitoring necessitates using the less sensitive thermal infra-red bands, which also reduce surface absorption effects. However, given the

Analysis of smear in high-resolution remote sensing satellites

Science.gov (United States)

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

2016-10-01

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

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

Directory of Open Access Journals (Sweden)

Biao Wang

2017-08-01

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

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

Science.gov (United States)

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

2016-10-01

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

Lectures on coarse geometry

CERN Document Server

Roe, John

2003-01-01

Coarse geometry is the study of spaces (particularly metric spaces) from a 'large scale' point of view, so that two spaces that look the same from a great distance are actually equivalent. This point of view is effective because it is often true that the relevant geometric properties of metric spaces are determined by their coarse geometry. Two examples of important uses of coarse geometry are Gromov's beautiful notion of a hyperbolic group and Mostow's proof of his famous rigidity theorem. The first few chapters of the book provide a general perspective on coarse structures. Even when only metric coarse structures are in view, the abstract framework brings the same simplification as does the passage from epsilons and deltas to open sets when speaking of continuity. The middle section reviews notions of negative curvature and rigidity. Modern interest in large scale geometry derives in large part from Mostow's rigidity theorem and from Gromov's subsequent 'large scale' rendition of the crucial properties of n...

Terrain aided navigation for autonomous underwater vehicles with coarse maps

International Nuclear Information System (INIS)

Zhou, Ling; Cheng, Xianghong; Zhu, Yixian

2016-01-01

Terrain aided navigation (TAN) is a form of geophysical localization technique for autonomous underwater vehicles (AUVs) operating in GPS-denied environments. TAN performance on sensor-rich AUVs has been evaluated in sea trials. However, many challenges remain before TAN can be successfully implemented on sensor-limited AUVs, especially with coarse maps. To improve TAN performance over coarse maps, a Gaussian process (GP) is proposed for the modeling of bathymetric terrain and integrated into the particle filter (GP-PF). GP is applied to provide not only the bathymetric value prediction through learning a set of bathymetric data from coarse maps but also the variance of the prediction. As a measurement update, calculated on bathymetric deviation is performed through the PF to obtain absolute and bounded positioning accuracy. Through the analysis of TAN performance on experimental data for two different terrains with map resolutions of 10–50 m, both the ability of the proposed model to represent the actual bathymetric terrain with accuracy and the effect of the GP-PF for TAN on sensor-limited systems in suited terrain are demonstrated. The experiment results further verify that there is an inverse relationship between the coarseness of the map and the overall TAN accuracy in rough terrains, but there is hardly any relationship between them in relatively flat terrains. (paper)

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

Directory of Open Access Journals (Sweden)

Byongjun Hwang

2017-07-01

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

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

Science.gov (United States)

Nikolakopoulos, Konstantinos G.

2013-10-01

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

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

Data.gov (United States)

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

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

Science.gov (United States)

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

2009-01-01

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

The relative entropy is fundamental to adaptive resolution simulations

Science.gov (United States)

Kreis, Karsten; Potestio, Raffaello

2016-07-01

Adaptive resolution techniques are powerful methods for the efficient simulation of soft matter systems in which they simultaneously employ atomistic and coarse-grained (CG) force fields. In such simulations, two regions with different resolutions are coupled with each other via a hybrid transition region, and particles change their description on the fly when crossing this boundary. Here we show that the relative entropy, which provides a fundamental basis for many approaches in systematic coarse-graining, is also an effective instrument for the understanding of adaptive resolution simulation methodologies. We demonstrate that the use of coarse-grained potentials which minimize the relative entropy with respect to the atomistic system can help achieve a smoother transition between the different regions within the adaptive setup. Furthermore, we derive a quantitative relation between the width of the hybrid region and the seamlessness of the coupling. Our results do not only shed light on the what and how of adaptive resolution techniques but will also help setting up such simulations in an optimal manner.

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

Science.gov (United States)

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

2018-04-01

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

U.S. Government Open Internet Access to Sub-meter Satellite Data

Science.gov (United States)

Neigh, Christopher S. R> Masek, Jeffery G.; Nickeson, Jaime E.

2012-01-01

The National Geospatial-Intelligence Agency (NGA) has contracted United States commercial remote sensing companies GeoEye and Digital Globe to provide very high resolution commercial quality satellite imagery to federal/state government agencies and those projects/people who support government interests. Under NextView contract terms, those engaged in official government programs/projects can gain online access to NGA's vast global archive. Additionally, data from vendor's archives of IKONOS-2 (IK-2), OrbView-3 (OB-3), GeoEye-1 (GE-1), QuickBird-1 (QB-1), WorldView-1 (WV-1), and WorldView-2 (WV-2), sensors can also be requested under these agreements. We report here the current extent of this archive, how to gain access, and the applications of these data by Earth science investigators to improve discoverability and community use of these data. Satellite commercial quality imagery (CQI) at very high resolution (source to U.S. federal, state, and local governments for many different purposes. The rapid growth of free global CQI data has been slow to disseminate to NASA Earth Science community and programs such as the Land-Cover Land-Use Change (LCLUC) program which sees potential benefit from unprecedented access. This article evolved from a workshop held on February 23rd, 2012 between representatives from NGA, NASA, and NASA LCLUC Scientists discussion on how to extend this resource to a broader license approved community. Many investigators are unaware of NGA's archive availability or find it difficult to access CQI data from NGA. Results of studies, both quality and breadth, could be improved with CQI data by combining them with other moderate to coarse resolution passive optical Earth observation remote sensing satellites, or with RADAR or LiDAR instruments to better understand Earth system dynamics at the scale of human activities. We provide the evolution of this effort, a guide for qualified user access, and describe current to potential use of these data in

Monitoring Snow and Land Ice Using Satellite data in the GMES Project CryoLand

Science.gov (United States)

Bippus, Gabriele; Nagler, Thomas

2013-04-01

The main objectives of the project "CryoLand - GMES Service Snow and Land Ice" are to develop, implement and validate services for snow, glaciers and lake and river ice products as a Downstream Service within the Global Monitoring for Environment and Security (GMES) program of the European Commission. CryoLand exploits Earth Observation data from current optical and microwave sensors and of the upcoming GMES Sentinel satellite family. The project prepares also the basis for the cryospheric component of the GMES Land Monitoring services. The CryoLand project team consists of 10 partner organisations from Austria, Finland, Norway, Sweden, Switzerland and Romania and is funded by the 7th Framework Program of the European Commission. The CryoLand baseline products for snow include fractional snow extent from optical satellite data, the extent of melting snow from SAR data, and coarse resolution snow water equivalent maps from passive microwave data. Experimental products include maps of snow surface wetness and temperature. The products range from large scale coverage at medium resolution to regional products with high resolution, in order to address a wide user community. Medium resolution optical data (e.g. MODIS, in the near future Sentinel-3) and SAR (ENVISAT ASAR, in the near future Sentinel-1) are the main sources of EO data for generating large scale products in near real time. For generation of regional products high resolution satellite data are used. Glacier products are based on high resolution optical (e.g. SPOT-5, in the near future Sentinel-2) and SAR (TerraSAR-X, in the near future Sentinel-1) data and include glacier outlines, mapping of glacier facies, glacier lakes and ice velocity. The glacier products are generated on users demand. Current test areas are located in the Alps, Norway, Greenland and the Himalayan Mountains. The lake and river ice products include ice extent and its temporal changes and snow extent on ice. The algorithms for these

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

Yeom, J. M.

2017-12-01

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

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

Science.gov (United States)

Rahmawati, Novi; Lubczynski, Maciek W.

2017-11-01

Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH25, CMORPH8, TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH25, CMORPH8, and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day-1 rain events. Lastly, the CMORPH25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH8.

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

Science.gov (United States)

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

2011-01-01

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

Attitude estimation from magnetometer and earth-albedo-corrected coarse sun sensor measurements

Science.gov (United States)

Appel, Pontus

2005-01-01

For full 3-axes attitude determination the magnetic field vector and the Sun vector can be used. A Coarse Sun Sensor consisting of six solar cells placed on each of the six outer surfaces of the satellite is used for Sun vector determination. This robust and low cost setup is sensitive to surrounding light sources as it sees the whole sky. To compensate for the largest error source, the Earth, an albedo model is developed. The total albedo light vector has contributions from the Earth surface which is illuminated by the Sun and visible from the satellite. Depending on the reflectivity of the Earth surface, the satellite's position and the Sun's position the albedo light changes. This cannot be calculated analytically and hence a numerical model is developed. For on-board computer use the Earth albedo model consisting of data tables is transferred into polynomial functions in order to save memory space. For an absolute worst case the attitude determination error can be held below 2∘. In a nominal case it is better than 1∘.

Super-resolution

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2014-01-01

Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...

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

Data.gov (United States)

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

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

Science.gov (United States)

Arellano-Baeza, Alonso A.

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

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

International Nuclear Information System (INIS)

Bauer, T.B.

2001-08-01

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

Detecting settlement expansion using hyper-temporal SAR time-series

CSIR Research Space (South Africa)

Kleynhans, W

2014-07-01

Full Text Available The detection of new informal settlements in South Africa using time-series data derived from coarse resolution satellite imagery has recently been an active area of research. Most of the previous methods presented using hyper-temporal satellite...

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

Science.gov (United States)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

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

Science.gov (United States)

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

2018-04-01

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

Shadow imaging of geosynchronous satellites

Science.gov (United States)

Douglas, Dennis Michael

Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2009-12-01

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Shaowei Ning

2016-10-01

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

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

Science.gov (United States)

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

2017-01-20

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

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models.

Science.gov (United States)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models

Science.gov (United States)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

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

Science.gov (United States)

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

2012-12-01

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

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

Directory of Open Access Journals (Sweden)

Elizabeth J. Botha

2016-05-01

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

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

DEFF Research Database (Denmark)

Schumacher, Paul; Mislimshoeva, Bunafsha; Brenning, Alexander

2016-01-01

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

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

Science.gov (United States)

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

2016-10-01

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

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

KAUST Repository

McCabe, Matthew

2016-10-25

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

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

Science.gov (United States)

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

2010-01-01

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

Monitoring Water Resources in Pastoral Areas of East Africa Using Satellite Data and Hydrologic Modeling

Science.gov (United States)

Alemu, H.; Senay, G. B.; Velpuri, N.; Asante, K. O.

2008-12-01

The nomadic pastoral communities in East Africa heavily depend on small water bodies and artificial lakes for domestic and livestock uses. The shortage of water in the region has made these water resources of great importance to them and sometimes even the reason for conflicts amongst rival communities in the region. Satellite-based data has significantly transformed the way we track and estimate hydrological processes such as precipitation and evapotranspiration. This approach has been particularly useful in remote places where conventional station-based weather networks are scarce. Tropical Rainfall Measuring Mission (TRMM) satellite data were extracted for the study region. National Oceanic and Atmospheric Administration's (NOAA) Global Data Assimilation System (GDAS) data were used to extract the climatic parameters needed to calculate reference evapotranspiration. The elevation data needed to delineate the watersheds were extracted from the Shuttle Radar Topography Mission (SRTM) with spatial resolution of 90m. The waterholes (most of which have average surface area less than a hectare) were identified using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images with a spatial resolution of 15 m. As part of National Aeronautics and Space Administration's (NASA) funded enhancement to a livestock early warning decision support system, a simple hydrologic water balance model was developed to estimate daily waterhole depth variations. The model was run for over 10 years from 1998 till 2008 for 10 representative waterholes in the region. Although there were no independent datasets to validate the results, the temporal patterns captured both the seasonal and inter-annual variations, depicting known drought and flood years. Future research includes the installation of staff-gauges for model calibration and validation. The simple modeling approach demonstrated the effectiveness of integrating dynamic coarse resolution datasets such as TRMM with

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

Science.gov (United States)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

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

Science.gov (United States)

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

2013-01-01

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

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

Science.gov (United States)

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Developing status of satellite remote sensing and its application

International Nuclear Information System (INIS)

Zhang Wanliang; Liu Dechang

2005-01-01

This paper has discussed the latest development of satellite remote sensing in sensor resolutions, satellite motion models, load forms, data processing and its application. The authors consider that sensor resolutions of satellite remote sensing have increased largely. Valid integration of multisensors is a new idea and technology of satellite remote sensing in the 21st century, and post-remote sensing application technology is the important part of deeply applying remote sensing information and has great practical significance. (authors)

Coarse mode aerosols in the High Arctic

Science.gov (United States)

Baibakov, K.; O'Neill, N. T.; Chaubey, J. P.; Saha, A.; Duck, T. J.; Eloranta, E. W.

2014-12-01

Fine mode (submicron) aerosols in the Arctic have received a fair amount of scientific attention in terms of smoke intrusions during the polar summer and Arctic haze pollution during the polar winter. Relatively little is known about coarse mode (supermicron) aerosols, notably dust, volcanic ash and sea salt. Asian dust is a regular springtime event whose optical and radiative forcing effects have been fairly well documented at the lower latitudes over North America but rarely reported for the Arctic. Volcanic ash, whose socio-economic importance has grown dramatically since the fear of its effects on aircraft engines resulted in the virtual shutdown of European civil aviation in the spring of 2010 has rarely been reported in the Arctic in spite of the likely probability that ash from Iceland and the Aleutian Islands makes its way into the Arctic and possibly the high Arctic. Little is known about Arctic sea salt aerosols and we are not aware of any literature on the optical measurement of these aerosols. In this work we present preliminary results of the combined sunphotometry-lidar analysis at two High Arctic stations in North America: PEARL (80°N, 86°W) for 2007-2011 and Barrow (71°N,156°W) for 2011-2014. The multi-years datasets were analyzed to single out potential coarse mode incursions and study their optical characteristics. In particular, CIMEL sunphotometers provided coarse mode optical depths as well as information on particle size and refractive index. Lidar measurements from High Spectral Resolution lidars (AHSRL at PEARL and NSHSRL at Barrow) yielded vertically resolved aerosol profiles and gave an indication of particle shape and size from the depolarization ratio and color ratio profiles. Additionally, we employed supplementary analyses of HYSPLIT backtrajectories, OMI aerosol index, and NAAPS (Navy Aerosol Analysis and Prediction System) outputs to study the spatial context of given events.

How coarse is too coarse for salmon spawning substrates?

Science.gov (United States)

Wooster, J. K.; Riebe, C. S.; Ligon, F. K.; Overstreet, B. T.

2009-12-01

Populations of Pacific salmon species have declined sharply in many rivers of the western US. Reversing these declines is a top priority and expense of many river restoration projects. To help restore salmon populations, managers often inject gravel into rivers, to supplement spawning habitat that has been depleted by gravel mining and the effects of dams—which block sediment and thus impair habitat downstream by coarsening the bed where salmon historically spawned. However, there is little quantitative understanding nor a methodology for determining when a river bed has become too coarse for salmon spawning. Hence there is little scientific basis for selecting sites that would optimize the restoration benefits of gravel injection (e.g., sites where flow velocities are suitable but bed materials are too coarse for spawning). To develop a quantitative understanding of what makes river beds too coarse for salmon spawning, we studied redds and spawning use in a series of California and Washington rivers where salmon spawning ability appears to be affected by coarse bed material. Our working hypothesis is that for a given flow condition, there is a maximum “threshold” particle size that a salmon of a given size is able to excavate and/or move as she builds her redd. A second, related hypothesis is that spawning use should decrease and eventually become impossible with increasing percent coverage by immovable particles. To test these hypotheses, we quantified the sizes and spatial distributions of immovably coarse particles in a series of salmon redds in each river during the peak of spawning. We also quantified spawning use and how it relates to percent coverage by immovable particles. Results from our studies of fall-run chinook salmon (Oncorhynchus tshawytsha) in the Feather River suggest that immovable particle size varies as a function of flow velocity over the redd, implying that faster water helps fish move bigger particles. Our Feather River study also

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

Science.gov (United States)

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

2008-07-01

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

Egypt satellite images for land surface characterization

DEFF Research Database (Denmark)

Hasager, Charlotte Bay

images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

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.

ASSIMILATION OF COARSE-SCALEDATAUSINGTHE ENSEMBLE KALMAN FILTER

KAUST Repository

Efendiev, Yalchin

2011-01-01

Reservoir data is usually scale dependent and exhibits multiscale features. In this paper we use the ensemble Kalman filter (EnKF) to integrate data at different spatial scales for estimating reservoir fine-scale characteristics. Relationships between the various scales is modeled via upscaling techniques. We propose two versions of the EnKF to assimilate the multiscale data, (i) where all the data are assimilated together and (ii) the data are assimilated sequentially in batches. Ensemble members obtained after assimilating one set of data are used as a prior to assimilate the next set of data. Both of these versions are easily implementable with any other upscaling which links the fine to the coarse scales. The numerical results with different methods are presented in a twin experiment setup using a two-dimensional, two-phase (oil and water) flow model. Results are shown with coarse-scale permeability and coarse-scale saturation data. They indicate that additional data provides better fine-scale estimates and fractional flow predictions. We observed that the two versions of the EnKF differed in their estimates when coarse-scale permeability is provided, whereas their results are similar when coarse-scale saturation is used. This behavior is thought to be due to the nonlinearity of the upscaling operator in the case of the former data. We also tested our procedures with various precisions of the coarse-scale data to account for the inexact relationship between the fine and coarse scale data. As expected, the results show that higher precision in the coarse-scale data yielded improved estimates. With better coarse-scale modeling and inversion techniques as more data at multiple coarse scales is made available, the proposed modification to the EnKF could be relevant in future studies.

A global, 30-m resolution land-surface water body dataset for 2000

Science.gov (United States)

Feng, M.; Sexton, J. O.; Huang, C.; Song, D. X.; Song, X. P.; Channan, S.; Townshend, J. R.

2014-12-01

Inland surface water is essential to terrestrial ecosystems and human civilization. The distribution of surface water in space and its change over time are related to many agricultural, environmental and ecological issues, and are important factors that must be considered in human socioeconomic development. Accurate mapping of surface water is essential for both scientific research and policy-driven applications. Satellite-based remote sensing provides snapshots of Earth's surface and can be used as the main input for water mapping, especially in large areas. Global water areas have been mapped with coarse resolution remotely sensed data (e.g., the Moderate Resolution Imaging Spectroradiometer (MODIS)). However, most inland rivers and water bodies, as well as their changes, are too small to map at such coarse resolutions. Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) imagery has a 30m spatial resolution and provides decades of records (~40 years). Since 2008, the opening of the Landsat archive, coupled with relatively lower costs associated with computing and data storage, has made comprehensive study of the dynamic changes of surface water over large even global areas more feasible. Although Landsat images have been used for regional and even global water mapping, the method can hardly be automated due to the difficulties on distinguishing inland surface water with variant degrees of impurities and mixing of soil background with only Landsat data. The spectral similarities to other land cover types, e.g., shadow and glacier remnants, also cause misidentification. We have developed a probabilistic based automatic approach for mapping inland surface water bodies. Landsat surface reflectance in multiple bands, derived water indices, and data from other sources are integrated to maximize the ability of identifying water without human interference. The approach has been implemented with open-source libraries to facilitate processing large

Review: advances in in situ and satellite phenological observations in Japan

Science.gov (United States)

Nagai, Shin; Nasahara, Kenlo Nishida; Inoue, Tomoharu; Saitoh, Taku M.; Suzuki, Rikie

2016-04-01

To accurately evaluate the responses of spatial and temporal variation of ecosystem functioning (evapotranspiration and photosynthesis) and services (regulating and cultural services) to the rapid changes caused by global warming, we depend on long-term, continuous, near-surface, and satellite remote sensing of phenology over wide areas. Here, we review such phenological studies in Japan and discuss our current knowledge, problems, and future developments. In contrast with North America and Europe, Japan has been able to evaluate plant phenology along vertical and horizontal gradients within a narrow area because of the country's high topographic relief. Phenological observation networks that support scientific studies and outreach activities have used near-surface tools such as digital cameras and spectral radiometers. Differences in phenology among ecosystems and tree species have been detected by analyzing the seasonal variation of red, green, and blue digital numbers (RGB values) extracted from phenological images, as well as spectral reflectance and vegetation indices. The relationships between seasonal variations in RGB-derived indices or spectral characteristics and the ecological and CO2 flux measurement data have been well validated. In contrast, insufficient satellite remote-sensing observations have been conducted because of the coarse spatial resolution of previous datasets, which could not detect the heterogeneous plant phenology that results from Japan's complex topography and vegetation. To improve Japanese phenological observations, multidisciplinary analysis and evaluation will be needed to link traditional phenological observations with "index trees," near-surface and satellite remote-sensing observations, "citizen science" (observations by citizens), and results published on the Internet.

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

Data.gov (United States)

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

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

Data.gov (United States)

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

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

Science.gov (United States)

2011-06-01

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

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.

Coarse graining for synchronization in directed networks

Science.gov (United States)

Zeng, An; Lü, Linyuan

2011-05-01

Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.

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

Science.gov (United States)

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

2003-01-01

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

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data.

Science.gov (United States)

Rogers, Brendan M; Solvik, Kylen; Hogg, Edward H; Ju, Junchang; Masek, Jeffrey G; Michaelian, Michael; Berner, Logan T; Goetz, Scott J

2018-02-26

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems. © 2018 John Wiley & Sons Ltd.

Comparison of atomic-level and coarse-grained models for liquid hydrocarbons from molecular dynamics configurational entropy estimates

NARCIS (Netherlands)

Baron, R; de Vries, AH; Hunenberger, PH; van Gunsteren, WF

2006-01-01

Molecular liquids can be modeled at different levels of spatial resolution. In atomic-level (AL) models, all (heavy) atoms can be explicitly simulated. In coarse-grained (CG) models, particles (beads) that represent groups of covalently bound atoms are used as elementary units. Ideally, a CG model

Adaptive Resolution Simulation of MARTINI Solvents

NARCIS (Netherlands)

Zavadlav, Julija; Melo, Manuel N.; Cunha, Ana V.; de Vries, Alex H.; Marrink, Siewert J.; Praprotnik, Matej

We present adaptive resolution dynamics simulations of aqueous and apolar solvents coarse-grained molecular models that are compatible with the MARTINI force field. As representatives of both classes solvents we have chosen liquid water and butane, respectively, at ambient temperature. The solvent

High-resolution mapping of forest carbon stocks in the Colombian Amazon

Directory of Open Access Journals (Sweden)

G. P. Asner

2012-07-01

Full Text Available High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40% of the Colombian Amazon – a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i employing a universal approach to airborne LiDAR-calibration with limited field data; (ii quantifying environmental controls over carbon densities; and (iii developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

Directory of Open Access Journals (Sweden)

Stovgaard Kasper

2010-08-01

Full Text Available Abstract Background Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. Results We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. Conclusion We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for

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

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

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

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

Science.gov (United States)

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

2017-12-01

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

Dual-resolution dose assessments for proton beamlet using MCNPX 2.6.0

Science.gov (United States)

Chao, T. C.; Wei, S. C.; Wu, S. W.; Tung, C. J.; Tu, S. J.; Cheng, H. W.; Lee, C. C.

2015-11-01

The purpose of this study is to access proton dose distribution in dual resolution phantoms using MCNPX 2.6.0. The dual resolution phantom uses higher resolution in Bragg peak, area near large dose gradient, or heterogeneous interface and lower resolution in the rest. MCNPX 2.6.0 was installed in Ubuntu 10.04 with MPI for parallel computing. FMesh1 tallies were utilized to record the energy deposition which is a special designed tally for voxel phantoms that converts dose deposition from fluence. 60 and 120 MeV narrow proton beam were incident into Coarse, Dual and Fine resolution phantoms with pure water, water-bone-water and water-air-water setups. The doses in coarse resolution phantoms are underestimated owing to partial volume effect. The dose distributions in dual or high resolution phantoms agreed well with each other and dual resolution phantoms were at least 10 times more efficient than fine resolution one. Because the secondary particle range is much longer in air than in water, the dose of low density region may be under-estimated if the resolution or calculation grid is not small enough.

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

Science.gov (United States)

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

2003-04-01

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

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

Science.gov (United States)

Arellano-Baeza, A. A.

2012-12-01

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

Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area

Directory of Open Access Journals (Sweden)

Stacy Jupiter

2011-03-01

Full Text Available The use of marine spatial planning for zoning multi-use areas is growing in both developed and developing countries. Comprehensive maps of marine resources, including those important for local fisheries management and biodiversity conservation, provide a crucial foundation of information for the planning process. Using a combination of field and high spatial resolution satellite data, we use an empirical procedure to create a bathymetric map (RMSE 1.76 m and object-based image analysis to produce accurate maps of geomorphic and benthic coral reef classes (Kappa values of 0.80 and 0.63; 9 and 33 classes, respectively covering a large (>260 km2 traditional fisheries management area in Fiji. From these maps, we derive per-pixel information on habitat richness, structural complexity, coral cover and the distance from land, and use these variables as input in models to predict fish species richness, diversity and biomass. We show that random forest models outperform five other model types, and that all three fish community variables can be satisfactorily predicted from the high spatial resolution satellite data. We also show geomorphic zone to be the most important predictor on average, with secondary contributions from a range of other variables including benthic class, depth, distance from land, and live coral cover mapped at coarse spatial scales, suggesting that data with lower spatial resolution and lower cost may be sufficient for spatial predictions of the three fish community variables.

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

Science.gov (United States)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

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.

Variability of wet troposphere delays over inland reservoirs as simulated by a high-resolution regional climate model

Science.gov (United States)

Clark, E.; Lettenmaier, D. P.

2014-12-01

Satellite radar altimetry is widely used for measuring global sea level variations and, increasingly, water height variations of inland water bodies. Existing satellite radar altimeters measure water surfaces directly below the spacecraft (approximately at nadir). Over the ocean, most of these satellites use radiometry to measure the delay of radar signals caused by water vapor in the atmosphere (also known as the wet troposphere delay (WTD)). However, radiometry can only be used to estimate this delay over the largest inland water bodies, such as the Great Lakes, due to spatial resolution issues. As a result, atmospheric models are typically used to simulate and correct for the WTD at the time of observations. The resolutions of these models are quite coarse, at best about 5000 km2 at 30˚N. The upcoming NASA- and CNES-led Surface Water and Ocean Topography (SWOT) mission, on the other hand, will use interferometric synthetic aperture radar (InSAR) techniques to measure a 120-km-wide swath of the Earth's surface. SWOT is expected to make useful measurements of water surface elevation and extent (and storage change) for inland water bodies at spatial scales as small as 250 m, which is much smaller than current altimetry targets and several orders of magnitude smaller than the models used for wet troposphere corrections. Here, we calculate WTD from very high-resolution (4/3-km to 4-km) simulations of the Weather Research and Forecasting (WRF) regional climate model, and use the results to evaluate spatial variations in WTD. We focus on six U.S. reservoirs: Lake Elwell (MT), Lake Pend Oreille (ID), Upper Klamath Lake (OR), Elephant Butte (NM), Ray Hubbard (TX), and Sam Rayburn (TX). The reservoirs vary in climate, shape, use, and size. Because evaporation from open water impacts local water vapor content, we compare time series of WTD over land and water in the vicinity of each reservoir. To account for resolution effects, we examine the difference in WRF

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

International Nuclear Information System (INIS)

Zhijian, Huang; Zhang, Jinfang; Xu, Fanjiang

2014-01-01

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

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

Science.gov (United States)

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

2018-06-01

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

Non-Galerkin Coarse Grids for Algebraic Multigrid

Energy Technology Data Exchange (ETDEWEB)

Falgout, Robert D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schroder, Jacob B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-06-26

Algebraic multigrid (AMG) is a popular and effective solver for systems of linear equations that arise from discretized partial differential equations. And while AMG has been effectively implemented on large scale parallel machines, challenges remain, especially when moving to exascale. Particularly, stencil sizes (the number of nonzeros in a row) tend to increase further down in the coarse grid hierarchy, and this growth leads to more communication. Therefore, as problem size increases and the number of levels in the hierarchy grows, the overall efficiency of the parallel AMG method decreases, sometimes dramatically. This growth in stencil size is due to the standard Galerkin coarse grid operator, $P^T A P$, where $P$ is the prolongation (i.e., interpolation) operator. For example, the coarse grid stencil size for a simple three-dimensional (3D) seven-point finite differencing approximation to diffusion can increase into the thousands on present day machines, causing an associated increase in communication costs. We therefore consider algebraically truncating coarse grid stencils to obtain a non-Galerkin coarse grid. First, the sparsity pattern of the non-Galerkin coarse grid is determined by employing a heuristic minimal “safe” pattern together with strength-of-connection ideas. Second, the nonzero entries are determined by collapsing the stencils in the Galerkin operator using traditional AMG techniques. The result is a reduction in coarse grid stencil size, overall operator complexity, and parallel AMG solve phase times.

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

Digital Repository Service at National Institute of Oceanography (India)

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

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

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)

HIRENASD coarse unstructured

Data.gov (United States)

National Aeronautics and Space Administration — Unstructured HIRENASD mesh: - coarse size (5.7 million nodes, 14.4 million elements) - for node centered solvers - 01.06.2011 - caution: dimensions in mm

Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-based Sensors and an Ensemble Kalman Filter

Science.gov (United States)

Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.

2015-12-01

Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an

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

DEFF Research Database (Denmark)

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

2011-01-01

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

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

Science.gov (United States)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

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

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

Science.gov (United States)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide

Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

Science.gov (United States)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Forman, Barton A.; Draper, Clara S.; Liu, Qing

2013-01-01

A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surface hydrological conditions, including soil moisture, snow, and terrestrial water storage (TWS), into a numerical model of land surface processes. In theory, the output from such a system is superior to estimates based on the observations or the model alone, thereby enhancing our ability to understand, monitor, and predict key elements of the terrestrial water cycle. In practice, however, satellite observations do not correspond directly to the water cycle variables of interest. The present paper addresses various aspects of this seeming mismatch using examples drawn from recent research with the ensemble-based NASA GEOS-5 LDAS. These aspects include (1) the assimilation of coarse-scale observations into higher-resolution land surface models, (2) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (3) the forward modeling of microwave brightness temperatures over land for radiance-based soil moisture and snow assimilation, and (4) the selection of the most relevant types of observations for the analysis of a specific water cycle variable that is not observed (such as root zone soil moisture). The solution to these challenges involves the careful construction of an observation operator that maps from the land surface model variables of interest to the space of the assimilated observations.

Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

Science.gov (United States)

Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

2013-12-01

Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this

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

Science.gov (United States)

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

2014-01-01

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

Generalized coarse-grained Becker-Doering equations

International Nuclear Information System (INIS)

Bolton, Colin D; Wattis, Jonathan A D

2003-01-01

We present and apply a generalized coarse-graining method of reducing the Becker-Doering model; originally formulated to describe the stepwise aggregation and fragmentation of clusters during nucleation. Previous formulations of the coarse-graining procedure have allowed a temporal rescaling of the coarse-grained reaction rates; this is generalized to allow the rescaling to depend on cluster size. The form of this factor is derived for general reaction rates and general mesh function so that the steady-state solution is preserved; in the case of an even mesh function the kinetics can also be accurately reproduced. With a size-dependent mesh function the equilibrium solution and the form of convergence to this state are matched for a specific example. Finally we consider reaction rates relevant to the classical nucleation theory of spherical cluster growth, and numerically compare solutions of the full system to the generalized coarse-grained system in both constant monomer and constant mass formulations, demonstrating the accuracy of the method

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

Science.gov (United States)

Ott, L.; Putman, B.; Collatz, J.; Gregg, W.

2012-01-01

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

Science.gov (United States)

Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

Science.gov (United States)

Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

The impact of spatial resolution on resolving spatial precipitation patterns in the Himalayas

NARCIS (Netherlands)

Bonekamp, P.N.J.; Collier, S.E.; Immerzeel, W.W.

2017-01-01

Frequently used gridded meteorological datasets poorly represent precipitation in the Himalaya due to their relatively low spatial resolution and the associated coarse representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy

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

Science.gov (United States)

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

2014-05-01

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

Coarse-mesh rebalancing acceleration for eigenvalue problems

International Nuclear Information System (INIS)

Asaoka, T.; Nakahara, Y.; Miyasaka, S.

1974-01-01

The coarse-mesh rebalance method is adopted for Monte Carlo schemes for aiming at accelerating the convergence of a source iteration process. At every completion of the Monte Carlo game for one batch of neutron histories, the scaling factor for the neutron flux is calculated to achieve the neutron balance in each coarse-mesh zone into which the total system is divided. This rebalance factor is multiplied to the weight of each fission source neutron in the coarse-mesh zone for playing the next Monte Carlo game. The numerical examples have shown that the coarse-mesh rebalance Monte Carlo calculation gives a good estimate of the eigenvalue already after several batches with a negligible extra computer time compared to the standard Monte Carlo. 5 references. (U.S.)

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

Directory of Open Access Journals (Sweden)

Mikhail Emelianov

2012-09-01

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

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

KAUST Repository

Altaf, Muhammad

2016-01-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model\\'s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

A new technique for online measurement of total and water-soluble copper (Cu) in coarse particulate matter (PM)

International Nuclear Information System (INIS)

Wang, Dongbin; Shafer, Martin M.; Schauer, James J.; Sioutas, Constantinos

2015-01-01

This study presents a novel system for online, field measurement of copper (Cu) in ambient coarse (2.5–10 μm) particulate matter (PM). This new system utilizes two virtual impactors combined with a modified liquid impinger (BioSampler) to collect coarse PM directly as concentrated slurry samples. The total and water-soluble Cu concentrations are subsequently measured by a copper Ion Selective Electrode (ISE). Laboratory evaluation results indicated excellent collection efficiency (over 85%) for particles in the coarse PM size ranges. In the field evaluations, very good agreements for both total and water-soluble Cu concentrations were obtained between online ISE-based monitor measurements and those analyzed by means of inductively coupled plasma mass spectrometry (ICP-MS). Moreover, the field tests indicated that the Cu monitor could achieve near-continuous operation for at least 6 consecutive days (a time resolution of 2–4 h) without obvious shortcomings. - Highlights: • A novel only PM sampling and Cu measuring technology is developed. • Very good particle collection efficiency for coarse PM is observed. • Excellent agreement is obtained between Cu ISE and offline ICP-MS measurements. • The new system can be continuously operated for at least 6 consecutive days. - A new technique for online measurements of Cu in coarse PM is described

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

Science.gov (United States)

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

2015-07-21

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

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

Science.gov (United States)

Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

2017-12-01

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

The Study of a Super Low Altitude Satellite

Science.gov (United States)

Noda, Atsushi; Homma, Masanori; Utashima, Masayoshi

This paper reports the result of a study for super low altitude satellite. The altitude of this satellite's orbit is lower than ever. The altitude of a conventional earth observing satellite is generally around from 600km to 900km. The lowest altitude of earth observing satellite launched in Japan was 350km; the Tropical Rainfall Measuring Mission (TRMM). By comparison, the satellite reported in this paper is much lower than that and it is planned to orbit below 200km. Furthermore, the duration of the flight planned is more than two years. Any satellite in the world has not achieved to keep such a low altitude that long term. The satellite in such a low orbit drops quickly because of the strong air drag. Our satellite will cancel the air drag effect by ion engine thrust. To realize this idea, a drag-free system will be applied. This usually leads a complicated and expensive satellite system. We, however, succeeded in finding a robust control law for a simple system even under the unpredictable change of air drag. When the altitude of the satellite is lowered successfully, the spatial resolution of an optical sensor can be highly improved. If a SAR is equipped with the satellite, it enables the drastic reduction of electric power consumption and the fabulous spatial resolution improvement at the same time.

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

Deriving temporally continuous soil moisture estimations at fine resolution by downscaling remotely sensed product

Science.gov (United States)

Jin, Yan; Ge, Yong; Wang, Jianghao; Heuvelink, Gerard B. M.

2018-06-01

Land surface soil moisture (SSM) has important roles in the energy balance of the land surface and in the water cycle. Downscaling of coarse-resolution SSM remote sensing products is an efficient way for producing fine-resolution data. However, the downscaling methods used most widely require full-coverage visible/infrared satellite data as ancillary information. These methods are restricted to cloud-free days, making them unsuitable for continuous monitoring. The purpose of this study is to overcome this limitation to obtain temporally continuous fine-resolution SSM estimations. The local spatial heterogeneities of SSM and multiscale ancillary variables were considered in the downscaling process both to solve the problem of the strong variability of SSM and to benefit from the fusion of ancillary information. The generation of continuous downscaled remote sensing data was achieved via two principal steps. For cloud-free days, a stepwise hybrid geostatistical downscaling approach, based on geographically weighted area-to-area regression kriging (GWATARK), was employed by combining multiscale ancillary variables with passive microwave remote sensing data. Then, the GWATARK-estimated SSM and China Soil Moisture Dataset from Microwave Data Assimilation SSM data were combined to estimate fine-resolution data for cloudy days. The developed methodology was validated by application to the 25-km resolution daily AMSR-E SSM product to produce continuous SSM estimations at 1-km resolution over the Tibetan Plateau. In comparison with ground-based observations, the downscaled estimations showed correlation (R ≥ 0.7) for both ascending and descending overpasses. The analysis indicated the high potential of the proposed approach for producing a temporally continuous SSM product at fine spatial resolution.

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

DEFF Research Database (Denmark)

Knudsen, Per

1999-01-01

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

Adaptive resolution simulation of supramolecular water : The concurrent making, breaking, and remaking of water bundles

NARCIS (Netherlands)

Zavadlav, Julija; Marrink, Siewert J; Praprotnik, Matej

The adaptive resolution scheme (AdResS) is a multiscale molecular dynamics simulation approach that can concurrently couple atomistic (AT) and coarse-grained (CG) resolution regions, i.e., the molecules can freely adapt their resolution according to their current position in the system. Coupling to

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-resolution

Unsupervised land cover change detection: meaningful sequential time series analysis

CSIR Research Space (South Africa)

Salmon, BP

2011-06-01

Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...

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

Science.gov (United States)

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

2014-11-01

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

More than the sum of its parts? A merged satellite product from MODIS and AMSR2 sea ice concentration

Science.gov (United States)

Ludwig, V. S.; Istomina, L.; Spreen, G.

2017-12-01

Arctic sea ice concentration (SIC), the fraction of a grid cell that is covered by sea ice, is relevant for a multitude of branches: physics (heat/momentum exchange), chemistry (gas exchange), biology (photosynthesis), navigation (location of pack ice) and others. It has been observed from passive microwave (PMW) radiometers on satellites continuously since 1979, providing an almost 40-year time series. However, the resolution is limited to typically 25 km which is good enough for climate studies but too coarse to properly resolve the ice edge or to show leads. The highest resolution from PMW sensors today is 5 km of the AMSR2 89 GHz channels. Thermal infrared (TIR) and visible (VIS) measurements provide much higher resolutions between 1 km (TIR) and 30 m (VIS, regional daily coverage). The higher resolutions come at the cost of depending on cloud-free fields of view (TIR and VIS) and daylight (VIS). We present a merged product of ASI-AMSR2 SIC (PMW) and MODIS SIC (TIR) at a nominal resolution of 1 km. This product benefits from both the independence of PMW towards cloud coverage and the high resolution of TIR data. An independent validation data set has been produced from manually selected, cloud-free Landsat VIS data at 30 m resolution. This dataset is used to evaluate the performance of the merged SIC dataset. Our results show that the merged product resolves features which are smeared out by the PMW data while benefitting from the PMW data in cloudy cases and is thus indeed more than the sum of its parts.

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

Science.gov (United States)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

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

Directory of Open Access Journals (Sweden)

Hassan Mohamed

2018-05-01

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

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

Science.gov (United States)

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

2015-04-01

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

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

Science.gov (United States)

Alvarez, Gabriel O.

2018-05-01

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

Prototyping global Earth System Models at high resolution: Representation of climate, ecosystems, and acidification in Eastern Boundary Currents

Science.gov (United States)

Dunne, J. P.; John, J. G.; Stock, C. A.

2013-12-01

The world's major Eastern Boundary Currents (EBC) such as the California Current Large Marine Ecosystem (CCLME) are critically important areas for global fisheries. Computational limitations have divided past EBC modeling into two types: high resolution regional approaches that resolve the strong meso-scale structures involved, and coarse global approaches that represent the large scale context for EBCs, but only crudely resolve only the largest scales of their manifestation. These latter global studies have illustrated the complex mechanisms involved in the climate change and acidification response in these regions, with the CCLME response dominated not by local adjustments but large scale reorganization of ocean circulation through remote forcing of water-mass supply pathways. While qualitatively illustrating the limitations of regional high resolution studies in long term projection, these studies lack the ability to robustly quantify change because of the inability of these models to represent the baseline meso-scale structures of EBCs. In the present work, we compare current generation coarse resolution (one degree) and a prototype next generation high resolution (1/10 degree) Earth System Models (ESMs) from NOAA's Geophysical Fluid Dynamics Laboratory in representing the four major EBCs. We review the long-known temperature biases that the coarse models suffer in being unable to represent the timing and intensity of upwelling-favorable winds, along with lack of representation of the observed high chlorophyll and biological productivity resulting from this upwelling. In promising contrast, we show that the high resolution prototype is capable of representing not only the overall meso-scale structure in physical and biogeochemical fields, but also the appropriate offshore extent of temperature anomalies and other EBC characteristics. Results for chlorophyll were mixed; while high resolution chlorophyll in EBCs were strongly enhanced over the coarse resolution

Learning to Play Efficient Coarse Correlated Equilibria

KAUST Repository

Borowski, Holly P.

2018-03-10

The majority of the distributed learning literature focuses on convergence to Nash equilibria. Coarse correlated equilibria, on the other hand, can often characterize more efficient collective behavior than even the best Nash equilibrium. However, there are no existing distributed learning algorithms that converge to specific coarse correlated equilibria. In this paper, we provide one such algorithm, which guarantees that the agents’ collective joint strategy will constitute an efficient coarse correlated equilibrium with high probability. The key to attaining efficient correlated behavior through distributed learning involves incorporating a common random signal into the learning environment.

A prototype method for diagnosing high ice water content probability using satellite imager data

Science.gov (United States)

Yost, Christopher R.; Bedka, Kristopher M.; Minnis, Patrick; Nguyen, Louis; Strapp, J. Walter; Palikonda, Rabindra; Khlopenkov, Konstantin; Spangenberg, Douglas; Smith, William L., Jr.; Protat, Alain; Delanoe, Julien

2018-03-01

Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

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

Directory of Open Access Journals (Sweden)

Hao Guo

2015-06-01

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

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

Science.gov (United States)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS

On the impacts of coarse-scale models of realistic roughness on a forward-facing step turbulent flow

International Nuclear Information System (INIS)

Wu, Yanhua; Ren, Huiying

2013-01-01

Highlights: ► Discrete wavelet transform was used to produce coarse-scale models of roughness. ► PIV were performed in a forward-facing step flow with roughness of different scales. ► Impacts of roughness scales on various turbulence statistics were studied. -- Abstract: The present work explores the impacts of the coarse-scale models of realistic roughness on the turbulent boundary layers over forward-facing steps. The surface topographies of different scale resolutions were obtained from a novel multi-resolution analysis using discrete wavelet transform. PIV measurements are performed in the streamwise–wall-normal (x–y) planes at two different spanwise positions in turbulent boundary layers at Re h = 3450 and δ/h = 8, where h is the mean step height and δ is the incoming boundary layer thickness. It was observed that large-scale but low-amplitude roughness scales had small effects on the forward-facing step turbulent flow. For the higher-resolution model of the roughness, the turbulence characteristics within 2h downstream of the steps are observed to be distinct from those over the original realistic rough step at a measurement position where the roughness profile possesses a positive slope immediately after the step’s front. On the other hand, much smaller differences exist in the flow characteristics at the other measurement position whose roughness profile possesses a negative slope following the step’s front

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

Science.gov (United States)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when

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

Science.gov (United States)

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

2012-12-01

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

Characterization of coarse particulate matter in school gyms

International Nuclear Information System (INIS)

Branis, Martin; Safranek, Jiri

2011-01-01

We investigated the mass concentration, mineral composition and morphology of particles resuspended by children during scheduled physical education in urban, suburban and rural elementary school gyms in Prague (Czech Republic). Cascade impactors were deployed to sample the particulate matter. Two fractions of coarse particulate matter (PM 10-2.5 and PM 2.5-1.0 ) were characterized by gravimetry, energy dispersive X-ray spectrometry and scanning electron microscopy. Two indicators of human activity, the number of exercising children and the number of physical education hours, were also recorded. Lower mass concentrations of coarse particulate matter were recorded outdoors (average PM 10-2.5 4.1-7.4 μg m -3 and PM 2.5-1.0 2.0-3.3 μg m -3 ) than indoors (average PM 10-2.5 13.6-26.7 μg m -3 and PM 2.5-1.0 3.7-7.4 μg m -3 ). The indoor concentrations of coarse aerosol were elevated during days with scheduled physical education with an average indoor-outdoor (I/O) ratio of 2.5-16.3 for the PM 10-2.5 and 1.4-4.8 for the PM 2.5-1.0 values. Under extreme conditions, the I/O ratios reached 180 (PM 10-2.5 ) and 19.1 (PM 2.5-1.0 ). The multiple regression analysis based on the number of students and outdoor coarse PM as independent variables showed that the main predictor of the indoor coarse PM concentrations is the number of students in the gym. The effect of outdoor coarse PM was weak and inconsistent. The regression models for the three schools explained 60-70% of the particular dataset variability. X-ray spectrometry revealed 6 main groups of minerals contributing to resuspended indoor dust. The most abundant particles were those of crustal origin composed of Si, Al, O and Ca. Scanning electron microscopy showed that, in addition to numerous inorganic particles, various types of fibers and particularly skin scales make up the main part of the resuspended dust in the gyms. In conclusion, school gyms were found to be indoor microenvironments with high concentrations of

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-09-01

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

Satellite imagery in safeguards: progress and prospects

International Nuclear Information System (INIS)

Niemeyer, I.; Listner, C.

2013-01-01

The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

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

Directory of Open Access Journals (Sweden)

Kun Hu

2016-09-01

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

Quantum theory of multiscale coarse-graining.

Science.gov (United States)

Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A

2018-03-14

Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.

Quantum theory of multiscale coarse-graining

Science.gov (United States)

Han, Yining; Jin, Jaehyeok; Wagner, Jacob W.; Voth, Gregory A.

2018-03-01

Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

KAUST Repository

Altaf, M. U.

2016-09-01

moisture fields conditioned on the radiometer-based, coarse resolution product from NASA’s SMAP satellite.

Effect of fly ash on the strength of porous concrete using recycled coarse aggregate to replace low-quality natural coarse aggregate

Science.gov (United States)

Arifi, Eva; Cahya, Evi Nur; Christin Remayanti, N.

2017-09-01

The performance of porous concrete made of recycled coarse aggregate was investigated. Fly ash was used as cement partial replacement. In this study, the strength of recycled aggregate was coMPared to low quality natural coarse aggregate which has high water absorption. Compression strength and tensile splitting strength test were conducted to evaluate the performance of porous concrete using fly ash as cement replacement. Results have shown that the utilization of recycled coarse aggregate up to 75% to replace low quality natural coarse aggregate with high water absorption increases compressive strength and splitting tensile strength of porous concrete. Using fly ash up to 25% as cement replacement improves compressive strength and splitting tensile strength of porous concrete.

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

Directory of Open Access Journals (Sweden)

M. Kopacz

2010-02-01

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

Remote diagnosis via a telecommunication satellite--ultrasonic tomographic image transmission experiments.

Science.gov (United States)

Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T

1985-04-01

An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.

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

Science.gov (United States)

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

2017-09-01

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

The Eccentric Satellites Problem: Comparing Milky Way Satellite Orbital Properties to Simulation Results

Science.gov (United States)

Haji, Umran; Pryor, Carlton; Applebaum, Elaad; Brooks, Alyson

2018-01-01

We compare the orbital properties of the satellite galaxies of the Milky Way to those of satellites found in simulated Milky Way-like systems as a means of testing cosmological simulations of galaxy formation. The particular problem that we are investigating is a discrepancy in the distribution of orbital eccentricities. Previous studies of Milky Way-mass systems analyzed in a semi-analytic ΛCDM cosmological model have found that the satellites tend to have significantly larger fractions of their kinetic energy invested in radial motion with respect to their central galaxy than do the real-world Milky Way satellites. We analyze several high-resolution ("zoom-in") hydrodynamical simulations of Milky Way-mass galaxies and their associated satellite systems to investigate why previous works found Milky Way-like systems to be rare. We find a possible relationship between a quiescent galactic assembly history and a distribution of satellite kinematics resembling that of the Milky Way. This project has been supported by funding from National Science Foundation grant PHY-1560077.

Spectroscopic Observations of Geo-Stationary Satellites Over the Korean Peninsula

OpenAIRE

D. K. Lee; S. J. Kim; W. Y. Han; J. S. Park; S. W. Min

2001-01-01

Low resolution spectroscopic observations of geo-stationary satellites over the Korean peninsula have been carried out at the KyungHee Optical Satellite Observing Facility (KOSOF) with a 40cm telescope. We have observed 9 telecommunication satellites and 1 weather satellite of 6 countries. The obtained spectral data showed that satellites could be classified and grouped with similar basic spectral feature. We divided the 10 satellites into 4 groups based on spectral slop and reflectance. It i...

Characterization of coarse particulate matter in school gyms

Energy Technology Data Exchange (ETDEWEB)

Branis, Martin, E-mail: branis@natur.cuni.cz [Charles University in Prague, Faculty of Science, Institute for Environmental Studies, Prague (Czech Republic); Safranek, Jiri [Charles University in Prague, Faculty of Physical Education, Department of Outdoor Sports, Prague (Czech Republic)

2011-05-15

We investigated the mass concentration, mineral composition and morphology of particles resuspended by children during scheduled physical education in urban, suburban and rural elementary school gyms in Prague (Czech Republic). Cascade impactors were deployed to sample the particulate matter. Two fractions of coarse particulate matter (PM{sub 10-2.5} and PM{sub 2.5-1.0}) were characterized by gravimetry, energy dispersive X-ray spectrometry and scanning electron microscopy. Two indicators of human activity, the number of exercising children and the number of physical education hours, were also recorded. Lower mass concentrations of coarse particulate matter were recorded outdoors (average PM{sub 10-2.5} 4.1-7.4 {mu}g m{sup -3} and PM{sub 2.5-1.0} 2.0-3.3 {mu}g m{sup -3}) than indoors (average PM{sub 10-2.5} 13.6-26.7 {mu}g m{sup -3} and PM{sub 2.5-1.0} 3.7-7.4 {mu}g m{sup -3}). The indoor concentrations of coarse aerosol were elevated during days with scheduled physical education with an average indoor-outdoor (I/O) ratio of 2.5-16.3 for the PM{sub 10-2.5} and 1.4-4.8 for the PM{sub 2.5-1.0} values. Under extreme conditions, the I/O ratios reached 180 (PM{sub 10-2.5}) and 19.1 (PM{sub 2.5-1.0}). The multiple regression analysis based on the number of students and outdoor coarse PM as independent variables showed that the main predictor of the indoor coarse PM concentrations is the number of students in the gym. The effect of outdoor coarse PM was weak and inconsistent. The regression models for the three schools explained 60-70% of the particular dataset variability. X-ray spectrometry revealed 6 main groups of minerals contributing to resuspended indoor dust. The most abundant particles were those of crustal origin composed of Si, Al, O and Ca. Scanning electron microscopy showed that, in addition to numerous inorganic particles, various types of fibers and particularly skin scales make up the main part of the resuspended dust in the gyms. In conclusion, school

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

Science.gov (United States)

Song, Huihui

-MODIS image pairs, we build the corresponding relationship between the difference images of MODIS and ETM+ by training a low- and high-resolution dictionary pair from the given prior image pairs. In the second scenario, i.e., only one Landsat- MODIS image pair being available, we directly correlate MODIS and ETM+ data through an image degradation model. Then, the fusion stage is achieved by super-resolving the MODIS image combining the high-pass modulation in a two-layer fusion framework. Remarkably, the proposed spatial-temporal fusion methods form a unified framework for blending remote sensing images with phenology change or land-cover-type change. Based on the proposed spatial-temporal fusion models, we propose to monitor the land use/land cover changes in Shenzhen, China. As a fast-growing city, Shenzhen faces the problem of detecting the rapid changes for both rational city planning and sustainable development. However, the cloudy and rainy weather in region Shenzhen located makes the capturing circle of high-quality satellite images longer than their normal revisit periods. Spatial-temporal fusion methods are capable to tackle this problem by improving the spatial resolution of images with coarse spatial resolution but frequent temporal coverage, thereby making the detection of rapid changes possible. On two Landsat-MODIS datasets with annual and monthly changes, respectively, we apply the proposed spatial-temporal fusion methods to the task of multiple change detection. Afterward, we propose a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning and sparse non-negative matrix factorization. By combining the spectral information from hyperspectral image, which is characterized by low spatial resolution but high spectral resolution and abbreviated as LSHS, and the spatial information from multispectral image, which is featured by high spatial resolution but low spectral

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

Science.gov (United States)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

All-weather Land Surface Temperature Estimation from Satellite Data

Science.gov (United States)

Zhou, J.; Zhang, X.

2017-12-01

Satellite remote sensing, including the thermal infrared (TIR) and passive microwave (MW), provides the possibility to observe LST at large scales. For better modeling the land surface processes with high temporal resolutions, all-weather LST from satellite data is desirable. However, estimation of all-weather LST faces great challenges. On the one hand, TIR remote sensing is limited to clear-sky situations; this drawback reduces its usefulness under cloudy conditions considerably, especially in regions with frequent and/or permanent clouds. On the other hand, MW remote sensing suffers from much greater thermal sampling depth (TSD) and coarser spatial resolution than TIR; thus, MW LST is generally lower than TIR LST, especially at daytime. Two case studies addressing the challenges mentioned previously are presented here. The first study is for the development of a novel thermal sampling depth correction method (TSDC) to estimate the MW LST over barren land; this second study is for the development of a feasible method to merge the TIR and MW LSTs by addressing the coarse resolution of the latter one. In the first study, the core of the TSDC method is a new formulation of the passive microwave radiation balance equation, which allows linking bulk MW radiation to the soil temperature at a specific depth, i.e. the representative temperature: this temperature is then converted to LST through an adapted soil heat conduction equation. The TSDC method is applied to the 6.9 GHz channel in vertical polarization of AMSR-E. Evaluation shows that LST estimated by the TSDC method agrees well with the MODIS LST. Validation is based on in-situ LSTs measured at the Gobabeb site in western Namibia. The results demonstrate the high accuracy of the TSDC method: it yields a root-mean squared error (RMSE) of 2 K and ignorable systematic error over barren land. In the second study, the method consists of two core processes: (1) estimation of MW LST from MW brightness temperature and (2

A coarse to fine minutiae-based latent palmprint matching.

Science.gov (United States)

Liu, Eryun; Jain, Anil K; Tian, Jie

2013-10-01

With the availability of live-scan palmprint technology, high resolution palmprint recognition has started to receive significant attention in forensics and law enforcement. In forensic applications, latent palmprints provide critical evidence as it is estimated that about 30 percent of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae in a rolled fingerprint) and large area of foreground region in full palmprints, novel strategies need to be developed for efficient and robust latent palmprint matching. In this paper, a coarse to fine matching strategy based on minutiae clustering and minutiae match propagation is designed specifically for palmprint matching. To deal with the large number of minutiae, a local feature-based minutiae clustering algorithm is designed to cluster minutiae into several groups such that minutiae belonging to the same group have similar local characteristics. The coarse matching is then performed within each cluster to establish initial minutiae correspondences between two palmprints. Starting with each initial correspondence, a minutiae match propagation algorithm searches for mated minutiae in the full palmprint. The proposed palmprint matching algorithm has been evaluated on a latent-to-full palmprint database consisting of 446 latents and 12,489 background full prints. The matching results show a rank-1 identification accuracy of 79.4 percent, which is significantly higher than the 60.8 percent identification accuracy of a state-of-the-art latent palmprint matching algorithm on the same latent database. The average computation time of our algorithm for a single latent-to-full match is about 141 ms for genuine match and 50 ms for impostor match, on a Windows XP desktop system with 2

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

Science.gov (United States)

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

2012-04-01

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

The impact of spatial resolution on resolving spatial precipitation patterns in the Himalayas

OpenAIRE

Bonekamp, P.N.J.; Collier, S.E.; Immerzeel, W.W.

2017-01-01

Frequently used gridded meteorological datasets poorly represent precipitation in the Himalaya due to their relatively low spatial resolution and the associated coarse representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields, as simulations at higher spatial resolution are more capable of resolving the interaction between the topography and the atmosphere. However, most physics par...

Homogenization-based topology optimization for high-resolution manufacturable micro-structures

DEFF Research Database (Denmark)

Groen, Jeroen Peter; Sigmund, Ole

2018-01-01

This paper presents a projection method to obtain high-resolution, manufacturable structures from efficient and coarse-scale, homogenization-based topology optimization results. The presented approach bridges coarse and fine scale, such that the complex periodic micro-structures can be represented...... by a smooth and continuous lattice on the fine mesh. A heuristic methodology allows control of the projected topology, such that a minimum length-scale on both solid and void features is ensured in the final result. Numerical examples show excellent behavior of the method, where performances of the projected...

Spatial scales of pollution from variable resolution satellite imaging

International Nuclear Information System (INIS)

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

2013-01-01

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

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...

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

Science.gov (United States)

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

2016-12-01

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

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

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

Directory of Open Access Journals (Sweden)

Shan-hu Jiang

2010-12-01

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

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

Science.gov (United States)

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

2015-01-01

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

Future Satellite Gravimetry and Earth Dynamics

CERN Document Server

Flury, Jakob

2005-01-01

Currently, a first generation of dedicated satellite missions for the precise mapping of the Earth’s gravity field is in orbit (CHAMP, GRACE, and soon GOCE). The gravity data from these satellite missions provide us with very new information on the dynamics of planet Earth. In particular, on the mass distribution in the Earth’s interior, the entire water cycle (ocean circulation, ice mass balance, continental water masses, and atmosphere), and on changes in the mass distribution. The results are fascinating, but still rough with respect to spatial and temporal resolution. Technical progress in satellite-to-satellite tracking and in gravity gradiometry will allow more detailed results in the future. In this special issue, Earth scientists develop visions of future applications based on follow-on high-precision satellite gravimetry missions.

Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

Dynamic coarse-graining fills the gap between atomistic simulations and experimental investigations of mechanical unfolding

Science.gov (United States)

Knoch, Fabian; Schäfer, Ken; Diezemann, Gregor; Speck, Thomas

2018-01-01

We present a dynamic coarse-graining technique that allows one to simulate the mechanical unfolding of biomolecules or molecular complexes on experimentally relevant time scales. It is based on Markov state models (MSMs), which we construct from molecular dynamics simulations using the pulling coordinate as an order parameter. We obtain a sequence of MSMs as a function of the discretized pulling coordinate, and the pulling process is modeled by switching among the MSMs according to the protocol applied to unfold the complex. This way we cover seven orders of magnitude in pulling speed. In the region of rapid pulling, we additionally perform steered molecular dynamics simulations and find excellent agreement between the results of the fully atomistic and the dynamically coarse-grained simulations. Our technique allows the determination of the rates of mechanical unfolding in a dynamical range from approximately 10-8/ns to 1/ns thus reaching experimentally accessible time regimes without abandoning atomistic resolution.

Coupling of convection and circulation at various resolutions

Directory of Open Access Journals (Sweden)

Cathy Hohenegger

2015-03-01

Full Text Available A correct representation of the coupling between convection and circulation constitutes a prerequisite for a correct representation of precipitation at all scales. In this study, the coupling between convection and a sea breeze is investigated across three main resolutions: large-eddy resolution where convection is fully explicit, convection-permitting resolution where convection is partly explicit and coarse resolution where convection is parameterised. The considered models are the UCLA-LES, COSMO and ICON. Despite the use of prescribed surface fluxes, comparison of the simulations reveals that typical biases associated with a misrepresentation of convection at convection-permitting and coarser resolutions significantly alter the characteristics of the sea breeze. The coarse-resolution simulations integrated without convective parameterisation and the convection-permitting simulations simulate a too slow propagation of the breeze front as compared to the large-eddy simulations. From the various factors affecting the propagation, a delayed onset and intensification of cold pools primarily explains the differences. This is a direct consequence of a delayed development of convection when the grid spacing is coarsened. Scaling the time the sea breeze reaches the centre of the land patch by the time precipitation exceeds 2 mm day−1, used as a measure for significant evaporation, yields a collapse of the simulations onto a simple linear relationship although subtle differences remain due to the use of different turbulence and microphysical schemes. Turning on the convection scheme significantly disrupts the propagation of the sea breeze due to a misrepresented timing (too early triggering and magnitude (too strong precipitation evaporation in one of the tested convection schemes of the convective processes.

Roads Data Conflation Using Update High Resolution Satellite Images

Science.gov (United States)

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

2017-11-01

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

A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

Science.gov (United States)

Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

2012-06-01

Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

Science.gov (United States)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

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

Directory of Open Access Journals (Sweden)

K. Leempoel

2013-08-01

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

TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

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G. Agugiaro

2012-07-01

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

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

Science.gov (United States)

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

2017-06-01

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

Satellite monitoring of cyanobacterial harmful algal bloom ...

Science.gov (United States)

Cyanobacterial harmful algal blooms (cyanoHABs) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern because of their dense biomass and the risk of exposure to toxins in both recreational waters and drinking source waters. Successful cyanoHAB assessment by satellites may provide a first-line of defense indicator for human and ecological health protection. In this study, assessment methods were developed to determine the utility of satellite technology for detecting cyanoHAB occurrence frequency at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent Sentinel-3 Ocean and Land Colour Imager (OLCI) launched in 2016. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, there were 275,897 lakes and reservoirs greater than 1 hectare in the 48 U.S. states. Results from this evaluation show that 5.6 % of waterbodies were resolvable by satellites with 300 m single pixel resolution and 0.7 % of waterbodies were resolvable when a 3x3 pixel array was applied based on minimum Euclidian distance from shore. Satellite data was also spatially joined to US public water surface intake (PWSI) locations, where single pixel resolution resolved 57% of PWSI and a 3x3 pixel array resolved 33% of

Palm Swamp Wetland Ecosystems of the Upper Amazon: Characterizing their Distribution and Inundation State Using Multiple Resolution Microwave Remote Sensing

Science.gov (United States)

Podest, E.; McDonald, K. C.; Schröder, R.; Pinto, N.; Zimmermann, R.; Horna, V.

2011-12-01

Palm swamp wetlands are prevalent in the Amazon basin, including extensive regions in northern Peru. These ecosystems are characterized by constant surface inundation and moderate seasonal water level variation. The combination of constantly saturated soils, giving rise to low oxygen conditions, and warm temperatures year-round can lead to considerable methane release to the atmosphere. Because of the widespread occurrence and expected sensitivity of these ecosystems to climate change, knowledge of their spatial extent and inundation state is crucial for assessing the associated land-atmosphere carbon exchange. Precise spatio-temporal information on palm swamps is difficult to gather because of their remoteness and difficult accessibility. Spaceborne microwave remote sensing is an effective tool for characterizing these ecosystems since it is sensitive to surface water and vegetation structure and allows monitoring large inaccessible areas on a temporal basis regardless of atmospheric conditions or solar illumination. We are developing a remote sensing methodology using multiple resolution microwave remote sensing data to determine palm swamp distribution and inundation state over focus regions in the Amazon basin in northern Peru. For this purpose, two types of multi-temporal microwave data are used: 1) high-resolution (100 m) data from the Advanced Land Observing Satellite (ALOS) Phased Array L-Band Synthetic Aperture Radar (PALSAR) to derive maps of palm swamp extent and inundation from dual-polarization fine-beam and multi-temporal HH-polarized ScanSAR, and 2) coarse resolution (25 km) combined active and passive microwave data from QuikSCAT and AMSR-E to derive inundated area fraction on a weekly basis. We compare information content and accuracy of the coarse resolution products to the PALSAR-based datasets to ensure information harmonization. The synergistic combination of high and low resolution datasets will allow for characterization of palm swamps and

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

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

Science.gov (United States)

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

2013-01-01

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

Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

2011-01-01

nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.

Spatial scales of pollution from variable resolution satellite imaging.

Science.gov (United States)

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

2013-01-01

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

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Rapid response flood detection using the MSG geostationary satellite

DEFF Research Database (Denmark)

Proud, Simon Richard; Fensholt, Rasmus; Rasmussen, Laura Vang

2011-01-01

A novel technique for the detection of flooded land using satellite data is presented. This new method takes advantage of the high temporal resolution of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) series of satellites to derive several p...... of data gathered during the 2009 flooding events in West Africa shows that the presented method can detect floods of comparable size to the SEVIRI pixel resolution on a short timescale, making it a valuable tool for large scale flood mapping....

Global tropospheric ozone modeling: Quantifying errors due to grid resolution

Science.gov (United States)

Wild, Oliver; Prather, Michael J.

2006-06-01

Ozone production in global chemical models is dependent on model resolution because ozone chemistry is inherently nonlinear, the timescales for chemical production are short, and precursors are artificially distributed over the spatial scale of the model grid. In this study we examine the sensitivity of ozone, its precursors, and its production to resolution by running a global chemical transport model at four different resolutions between T21 (5.6° × 5.6°) and T106 (1.1° × 1.1°) and by quantifying the errors in regional and global budgets. The sensitivity to vertical mixing through the parameterization of boundary layer turbulence is also examined. We find less ozone production in the boundary layer at higher resolution, consistent with slower chemical production in polluted emission regions and greater export of precursors. Agreement with ozonesonde and aircraft measurements made during the NASA TRACE-P campaign over the western Pacific in spring 2001 is consistently better at higher resolution. We demonstrate that the numerical errors in transport processes on a given resolution converge geometrically for a tracer at successively higher resolutions. The convergence in ozone production on progressing from T21 to T42, T63, and T106 resolution is likewise monotonic but indicates that there are still large errors at 120 km scales, suggesting that T106 resolution is too coarse to resolve regional ozone production. Diagnosing the ozone production and precursor transport that follow a short pulse of emissions over east Asia in springtime allows us to quantify the impacts of resolution on both regional and global ozone. Production close to continental emission regions is overestimated by 27% at T21 resolution, by 13% at T42 resolution, and by 5% at T106 resolution. However, subsequent ozone production in the free troposphere is not greatly affected. We find that the export of short-lived precursors such as NOx by convection is overestimated at coarse resolution.

Spectroscopic Observations of Geo-Stationary Satellites Over the Korean Peninsula

Directory of Open Access Journals (Sweden)

D. K. Lee

2001-11-01

Full Text Available Low resolution spectroscopic observations of geo-stationary satellites over the Korean peninsula have been carried out at the KyungHee Optical Satellite Observing Facility (KOSOF with a 40cm telescope. We have observed 9 telecommunication satellites and 1 weather satellite of 6 countries. The obtained spectral data showed that satellites could be classified and grouped with similar basic spectral feature. We divided the 10 satellites into 4 groups based on spectral slop and reflectance. It is suggested that the material types of the satellites can be determined through spectral comparisons with the ground laboratory data. We will continuously observe additional geo-stationary satellites for the accurate classification of spectral features.

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

Science.gov (United States)

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

2014-11-01

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

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

Satellite image time series simulation for environmental monitoring

Science.gov (United States)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

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

Satellite-Enhanced Dynamical Downscaling of Extreme Events

Science.gov (United States)

Nunes, A.

2015-12-01

Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.

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

Directory of Open Access Journals (Sweden)

Huai Yu

2016-03-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

Thompson, O. E.

1982-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

Directory of Open Access Journals (Sweden)

Timothy Shields

2016-05-01

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

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

Science.gov (United States)

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

2017-07-01

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

Coarse Thinking and Pricing a Financial Option

OpenAIRE

Siddiqi, Hammad

2009-01-01

Mullainathan et al [Quarterly Journal of Economics, May 2008] present a formalization of the concept of coarse thinking in the context of a model of persuasion. The essential idea behind coarse thinking is that people put situations into categories and the values assigned to attributes in a given situation are affected by the values of corresponding attributes in other co-categorized situations. We derive a new option pricing formula based on the assumption that the market consists of coars...

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

Science.gov (United States)

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

2014-12-01

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

Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

Directory of Open Access Journals (Sweden)

Qi Chen

2013-12-01

Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.

Multilevel coarse graining and nano-pattern discovery in many particle stochastic systems

International Nuclear Information System (INIS)

Kalligiannaki, Evangelia; Katsoulakis, Markos A.; Plecháč, Petr; Vlachos, Dionisios G.

2012-01-01

In this work we propose a hierarchy of Markov chain Monte Carlo methods for sampling equilibrium properties of stochastic lattice systems with competing short and long range interactions. Each Monte Carlo step is composed by two or more sub-steps efficiently coupling coarse and finer state spaces. The method can be designed to sample the exact or controlled-error approximations of the target distribution, providing information on levels of different resolutions, as well as at the microscopic level. In both strategies the method achieves significant reduction of the computational cost compared to conventional Markov chain Monte Carlo methods. Applications in phase transition and pattern formation problems confirm the efficiency of the proposed methods.

Top-down Estimates of Isoprene Emissions in Australia Inferred from OMI Satellite Data.

Science.gov (United States)

Greenslade, J.; Fisher, J. A.; Surl, L.; Palmer, P. I.

2017-12-01

Australia is a global hotspot for biogenic isoprene emission factors predicted by process-based models such as the Model of Emissions of Gases and Aerosols from Nature (MEGAN). It is also prone to increasingly frequent temperature extremes that can drive episodically high emissions. Estimates of biogenic isoprene emissions from Australia are poorly constrained, with the frequently used MEGAN model overestimating emissions by a factor of 4-6 in some areas. Evaluating MEGAN and other models in Australia is difficult due to sparse measurements of emissions and their ensuing chemical products. In this talk, we will describe efforts to better quantify Australian isoprene emissions using top-down estimates based on formaldehyde (HCHO) observations from the OMI satellite instrument, combined with modelled isoprene to HCHO yields obtained from the GEOS-Chem chemical transport model. The OMI-based estimates are evaluated using in situ observations from field campaigns conducted in southeast Australia. We also investigate the impact on the inferred emission of horizontal resolution used for the yield calculations, particularly in regions on the boundary between low- and high-NOx chemistry. The prevalence of fire smoke plumes roughly halves the available satellite dataset over Australia for much of the year; however, seasonal averages remain robust. Preliminary results show that the top-down isoprene emissions are lower than MEGAN estimates by up to 90% in summer. The overestimates are greatest along the eastern coast, including areas surrounding Australia's major population centres in Sydney, Melbourne, and Brisbane. The coarse horizontal resolution of the model significantly affects the emissions estimates, as many biogenic emitting regions lie along narrow coastal stretches. Our results confirm previous findings that the MEGAN biogenic emission model is poorly calibrated for the Australian environment and suggests that chemical transport models driven by MEGAN are likely

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.

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

Science.gov (United States)

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

2014-12-01

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

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Property A and Coarse Embedding for Locally Compact Groups

DEFF Research Database (Denmark)

Li, Kang

property A. In a joint work with Knudby, we characterize the connected simple Lie groups with the discrete topology that have different approximation properties (see Article B). Moreover, we give a contractive Schur multiplier characterization of locally compact groups coarsely embeddable into Hilbert......In the study of the Novikov conjecture, property A and coarse embedding of metric spaces were introduced by Yu and Gromov, respectively. The main topic of the thesis is property A and coarse embedding for locally compact second countable groups. We prove that many of the results that are known...... to hold in the discrete setting, hold also in the locally compact setting.In a joint work with Deprez, we show that property A is equivalent to amenability at infinity and the strong Novikov conjecture is true for every locally compact group that embeds coarsely into a Hilbert space (see Article A...

Two-level method with coarse space size independent convergence

Energy Technology Data Exchange (ETDEWEB)

Vanek, P.; Brezina, M. [Univ. of Colorado, Denver, CO (United States); Tezaur, R.; Krizkova, J. [UWB, Plzen (Czech Republic)

1996-12-31

The basic disadvantage of the standard two-level method is the strong dependence of its convergence rate on the size of the coarse-level problem. In order to obtain the optimal convergence result, one is limited to using a coarse space which is only a few times smaller than the size of the fine-level one. Consequently, the asymptotic cost of the resulting method is the same as in the case of using a coarse-level solver for the original problem. Today`s two-level domain decomposition methods typically offer an improvement by yielding a rate of convergence which depends on the ratio of fine and coarse level only polylogarithmically. However, these methods require the use of local subdomain solvers for which straightforward application of iterative methods is problematic, while the usual application of direct solvers is expensive. We suggest a method diminishing significantly these difficulties.

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

Science.gov (United States)

Brown, I.; Wennbom, M.

2013-12-01

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

Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China

Directory of Open Access Journals (Sweden)

Yangxiaoyue Liu

2017-12-01

Full Text Available Although numerous satellite-based soil moisture (SM products can provide spatiotemporally continuous worldwide datasets, they can hardly be employed in characterizing fine-grained regional land surface processes, owing to their coarse spatial resolution. In this study, we proposed a machine-learning-based method to enhance SM spatial accuracy and improve the availability of SM data. Four machine learning algorithms, including classification and regression trees (CART, K-nearest neighbors (KNN, Bayesian (BAYE, and random forests (RF, were implemented to downscale the monthly European Space Agency Climate Change Initiative (ESA CCI SM product from 25-km to 1-km spatial resolution. During the regression, the land surface temperature (including daytime temperature, nighttime temperature, and diurnal fluctuation temperature, normalized difference vegetation index, surface reflections (red band, blue band, NIR band and MIR band, and digital elevation model were taken as explanatory variables to produce fine spatial resolution SM. We chose Northeast China as the study area and acquired corresponding SM data from 2003 to 2012 in unfrozen seasons. The reconstructed SM datasets were validated against in-situ measurements. The results showed that the RF-downscaled results had superior matching performance to both ESA CCI SM and in-situ measurements, and can positively respond to precipitation variation. Additionally, the RF was less affected by parameters, which revealed its robustness. Both CART and KNN ranked second. Compared to KNN, CART had a relatively close correlation with the validation data, but KNN showed preferable precision. Moreover, BAYE ranked last with significantly abnormal regression values.

High-resolution inversion of OMI formaldehyde columns to quantify isoprene emission on ecosystem-relevant scales: application to the southeast US

Science.gov (United States)

Kaiser, Jennifer; Jacob, Daniel J.; Zhu, Lei; Travis, Katherine R.; Fisher, Jenny A.; González Abad, Gonzalo; Zhang, Lin; Zhang, Xuesong; Fried, Alan; Crounse, John D.; St. Clair, Jason M.; Wisthaler, Armin

2018-04-01

Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Bottom-up isoprene emission inventories used in atmospheric models are based on limited vegetation information and uncertain land cover data, leading to potentially large errors. Satellite observations of atmospheric formaldehyde (HCHO), a high-yield isoprene oxidation product, provide top-down information to evaluate isoprene emission inventories through inverse analyses. Past inverse analyses have however been hampered by uncertainty in the HCHO satellite data, uncertainty in the time- and NOx-dependent yield of HCHO from isoprene oxidation, and coarse resolution of the atmospheric models used for the inversion. Here we demonstrate the ability to use HCHO satellite data from OMI in a high-resolution inversion to constrain isoprene emissions on ecosystem-relevant scales. The inversion uses the adjoint of the GEOS-Chem chemical transport model at 0.25° × 0.3125° horizontal resolution to interpret observations over the southeast US in August-September 2013. It takes advantage of concurrent NASA SEAC4RS aircraft observations of isoprene and its oxidation products including HCHO to validate the OMI HCHO data over the region, test the GEOS-Chem isoprene oxidation mechanism and NOx environment, and independently evaluate the inversion. This evaluation shows in particular that local model errors in NOx concentrations propagate to biases in inferring isoprene emissions from HCHO data. It is thus essential to correct model NOx biases, which was done here using SEAC4RS observations but can be done more generally using satellite NO2 data concurrently with HCHO. We find in our inversion that isoprene emissions from the widely used MEGAN v2.1 inventory are biased high over the southeast US by 40 % on average, although the broad-scale distributions are correct including maximum emissions in Arkansas/Louisiana and high base emission factors in the oak-covered Ozarks of southeast

Nanosar-case study of synthetic aperture radar for nano-satellites

NARCIS (Netherlands)

Engelen, S.; Oever, M. van den; Mahapatra, P.; Sundaramoorthy, P.; Gill, E.; Meijer, R.J.; Verhoeven, C.

2012-01-01

Nano-satellites have a cost advantage due to their low mass and usage of commercial-off-the-shelf technologies. However, the low mass also restricts the functionality of a nano-satellite's payload. Typically, this would imply instruments with very low to low resolution and accuracy, essentially

Resolution enhancement of tri-stereo remote sensing images by super resolution methods

Science.gov (United States)

Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

2016-10-01

Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

Analysis of Specular Reflections Off Geostationary Satellites

Science.gov (United States)

Jolley, A.

2016-09-01

Many photometric studies of artificial satellites have attempted to define procedures that minimise the size of datasets required to infer information about satellites. However, it is unclear whether deliberately limiting the size of datasets significantly reduces the potential for information to be derived from them. In 2013 an experiment was conducted using a 14 inch Celestron CG-14 telescope to gain multiple night-long, high temporal resolution datasets of six geostationary satellites [1]. This experiment produced evidence of complex variations in the spectral energy distribution (SED) of reflections off satellite surface materials, particularly during specular reflections. Importantly, specific features relating to the SED variations could only be detected with high temporal resolution data. An update is provided regarding the nature of SED and colour variations during specular reflections, including how some of the variables involved contribute to these variations. Results show that care must be taken when comparing observed spectra to a spectral library for the purpose of material identification; a spectral library that uses wavelength as the only variable will be unable to capture changes that occur to a material's reflected spectra with changing illumination and observation geometry. Conversely, colour variations with changing illumination and observation geometry might provide an alternative means of determining material types.

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

Directory of Open Access Journals (Sweden)

Chandi Witharana

2016-04-01

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

Quantifying the Uncertainty in High Spatial and Temporal Resolution Synthetic Land Surface Reflectance at Pixel Level Using Ground-Based Measurements

Science.gov (United States)

Kong, J.; Ryu, Y.

2017-12-01

Algorithms for fusing high temporal frequency and high spatial resolution satellite images are widely used to develop dense time-series land surface observations. While many studies have revealed that the synthesized frequent high spatial resolution images could be successfully applied in vegetation mapping and monitoring, validation and correction of fused images have not been focused than its importance. To evaluate the precision of fused image in pixel level, in-situ reflectance measurements which could account for the pixel-level heterogeneity are necessary. In this study, the synthetic images of land surface reflectance were predicted by the coarse high-frequency images acquired from MODIS and high spatial resolution images from Landsat-8 OLI using the Flexible Spatiotemporal Data Fusion (FSDAF). Ground-based reflectance was measured by JAZ Spectrometer (Ocean Optics, Dunedin, FL, USA) on rice paddy during five main growth stages in Cheorwon-gun, Republic of Korea, where the landscape heterogeneity changes through the growing season. After analyzing the spatial heterogeneity and seasonal variation of land surface reflectance based on the ground measurements, the uncertainties of the fused images were quantified at pixel level. Finally, this relationship was applied to correct the fused reflectance images and build the seasonal time series of rice paddy surface reflectance. This dataset could be significant for rice planting area extraction, phenological stages detection, and variables estimation.

Coarse-graining stochastic biochemical networks: adiabaticity and fast simulations

Energy Technology Data Exchange (ETDEWEB)

Nemenman, Ilya [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Hengartner, Nick [Los Alamos National Laboratory

2008-01-01

We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscoplc, non-Poissonian fluctuations of the slow ones. Our approach, which is similar to the Born-Oppenhelmer approximation in quantum mechanics, follows from the stochastic path Integral representation of the cumulant generating function of reaction events. In applications with a small number of chemIcal reactions, It produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, Interpretable representation and can be used for coarse-grained numerical simulation schemes with a small computational complexity and yet high accuracy. As an example, we derive the coarse-grained description for a chain of biochemical reactions, and show that the coarse-grained and the microscopic simulations are in an agreement, but the coarse-gralned simulations are three orders of magnitude faster.

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Dynamics in coarse-grained models for oligomer-grafted silica nanoparticles

KAUST Repository

Hong, Bingbing

2012-01-01

Coarse-grained models of poly(ethylene oxide) oligomer-grafted nanoparticles are established by matching their structural distribution functions to atomistic simulation data. Coarse-grained force fields for bulk oligomer chains show excellent transferability with respect to chain lengths and temperature, but structure and dynamics of grafted nanoparticle systems exhibit a strong dependence on the core-core interactions. This leads to poor transferability of the core potential to conditions different from the state point at which the potential was optimized. Remarkably, coarse graining of grafted nanoparticles can either accelerate or slowdown the core motions, depending on the length of the grafted chains. This stands in sharp contrast to linear polymer systems, for which coarse graining always accelerates the dynamics. Diffusivity data suggest that the grafting topology is one cause of slower motions of the cores for short-chain oligomer-grafted nanoparticles; an estimation based on transition-state theory shows the coarse-grained core-core potential also has a slowing-down effect on the nanoparticle organic hybrid materials motions; both effects diminish as grafted chains become longer. © 2012 American Institute of Physics.

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

Directory of Open Access Journals (Sweden)

Charles R. Lane

2014-12-01

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

Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

OpenAIRE

Neumann, Mathias; Moreno, Adam; Thurnher, Christopher; Mues, Volker; Härkönen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Cardellini, Giuseppe; Thivolle-Cazat, Alain; Bronisz, Karol; Merganic, Jan; Alberdi, Iciar; Astrup, Rasmus; Mohren, Frits

2016-01-01

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily g...

Characterization of coarse particulate matter in school gyms.

Science.gov (United States)

Braniš, Martin; Šafránek, Jiří

2011-05-01

We investigated the mass concentration, mineral composition and morphology of particles resuspended by children during scheduled physical education in urban, suburban and rural elementary school gyms in Prague (Czech Republic). Cascade impactors were deployed to sample the particulate matter. Two fractions of coarse particulate matter (PM(10-2.5) and PM(2.5-1.0)) were characterized by gravimetry, energy dispersive X-ray spectrometry and scanning electron microscopy. Two indicators of human activity, the number of exercising children and the number of physical education hours, were also recorded. Lower mass concentrations of coarse particulate matter were recorded outdoors (average PM(10-2.5) 4.1-7.4 μg m(-3) and PM(2.5-1.0) 2.0-3.3 μg m(-3)) than indoors (average PM(10-2.5) 13.6-26.7 μg m(-3) and PM(2.5-1.0) 3.7-7.4 μg m(-3)). The indoor concentrations of coarse aerosol were elevated during days with scheduled physical education with an average indoor-outdoor (I/O) ratio of 2.5-16.3 for the PM(10-2.5) and 1.4-4.8 for the PM(2.5-1.0) values. Under extreme conditions, the I/O ratios reached 180 (PM(10-2.5)) and 19.1 (PM(2.5-1.0)). The multiple regression analysis based on the number of students and outdoor coarse PM as independent variables showed that the main predictor of the indoor coarse PM concentrations is the number of students in the gym. The effect of outdoor coarse PM was weak and inconsistent. The regression models for the three schools explained 60-70% of the particular dataset variability. X-ray spectrometry revealed 6 main groups of minerals contributing to resuspended indoor dust. The most abundant particles were those of crustal origin composed of Si, Al, O and Ca. Scanning electron microscopy showed that, in addition to numerous inorganic particles, various types of fibers and particularly skin scales make up the main part of the resuspended dust in the gyms. In conclusion, school gyms were found to be indoor microenvironments with high

Initial Assessment of Cyclone Global Navigation Satellite System (CYGNSS) Observations

Science.gov (United States)

McKague, D. S.; Ruf, C. S.

2017-12-01

The NASA Cyclone Global Navigation Satellite System (CYNSS) mission provides high temporal resolution observations of cyclones from a constellation of eight low-Earth orbiting satellites. Using the relatively new technique of Global Navigation Satellite System reflectometry (GNSS-R), all-weather observations are possible, penetrating even deep convection within hurricane eye walls. The compact nature of the GNSS-R receivers permits the use of small satellites, which in turn enables the launch of a constellation of satellites from a single launch vehicle. Launched in December of 2016, the eight CYGNSS satellites provide 25 km resolution observations of mean square slope (surface roughness) and surface winds with a 2.8 hour median revisit time from 38 S to 38 N degrees latitude. In addition to the calibration and validation of CYGNSS sea state observations, the CYGNSS science team is assessing the ability of the mission to provide estimates of cyclone size, intensity, and integrated kinetic energy. With its all-weather ability and high temporal resolution, the CYGNSS mission will add significantly to our ability to monitor cyclone genesis and intensification and will significantly reduce uncertainties in our ability to estimate cyclone intensity, a key variable in predicting its destructive potential. Members of the CYGNSS Science Team are also assessing the assimilation of CYGNSS data into hurricane forecast models to determine the impact of the data on forecast skill, using the data to study extra-tropical cyclones, and looking at connections between tropical cyclones and global scale weather, including the global hydrologic cycle. This presentation will focus on the assessment of early on-orbit observations of cyclones with respect to these various applications.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

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

Science.gov (United States)

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

2017-02-01

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

Non-periodic molecular dynamics simulations of coarse grained lipid bilayer in water

DEFF Research Database (Denmark)

Kotsalis, E. M.; Hanasaki, I.; Walther, Jens Honore

2010-01-01

We present a multiscale algorithm that couples coarse grained molecular dynamics (CGMD) with continuum solver. The coupling requires the imposition of non-periodic boundary conditions on the coarse grained Molecular Dynamics which, when not properly enforced, may result in spurious fluctuations o...... in simulating more complex systems by performing a non-periodic Molecular Dynamics simulation of a DPPC lipid in liquid coarse grained water.......We present a multiscale algorithm that couples coarse grained molecular dynamics (CGMD) with continuum solver. The coupling requires the imposition of non-periodic boundary conditions on the coarse grained Molecular Dynamics which, when not properly enforced, may result in spurious fluctuations...... of the material properties of the system represented by CGMD. In this paper we extend a control algorithm originally developed for atomistic simulations [3], to conduct simulations involving coarse grained water molecules without periodic boundary conditions. We demonstrate the applicability of our method...

Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

International Nuclear Information System (INIS)

Asner, Gregory P

2009-01-01

Large-scale carbon mapping is needed to support the UNFCCC program to reduce deforestation and forest degradation (REDD). Managers of forested land can potentially increase their carbon credits via detailed monitoring of forest cover, loss and gain (hectares), and periodic estimates of changes in forest carbon density (tons ha -1 ). Satellites provide an opportunity to monitor changes in forest carbon caused by deforestation and degradation, but only after initial carbon densities have been assessed. New airborne approaches, especially light detection and ranging (LiDAR), provide a means to estimate forest carbon density over large areas, which greatly assists in the development of practical baselines. Here I present an integrated satellite-airborne mapping approach that supports high-resolution carbon stock assessment and monitoring in tropical forest regions. The approach yields a spatially resolved, regional state-of-the-forest carbon baseline, followed by high-resolution monitoring of forest cover and disturbance to estimate carbon emissions. Rapid advances and decreasing costs in the satellite and airborne mapping sectors are already making high-resolution carbon stock and emissions assessments viable anywhere in the world.

Examination of aerosol distributions and radiative effects over the Bay of Bengal and the Arabian Sea region during ICARB using satellite data and a general circulation model

Directory of Open Access Journals (Sweden)

R. Cherian

2012-02-01

Full Text Available In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB and Arabian Sea (AS regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5 general circulation model extended by Hamburg Aerosol Module (HAM. By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement

High resolution radar satellite imagery analysis for safeguards applications

Energy Technology Data Exchange (ETDEWEB)

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

2011-12-15

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

FROM ATOMISTIC TO SYSTEMATIC COARSE-GRAINED MODELS FOR MOLECULAR SYSTEMS

KAUST Repository

Harmandaris, Vagelis; Kalligiannaki, Evangelia; Katsoulakis, Markos; Plechac, Petr

2017-01-01

The development of systematic (rigorous) coarse-grained mesoscopic models for complex molecular systems is an intense research area. Here we first give an overview of methods for obtaining optimal parametrized coarse-grained models, starting from

Thermodynamic forces in coarse-grained simulations

Science.gov (United States)

Noid, William

Atomically detailed molecular dynamics simulations have profoundly advanced our understanding of the structure and interactions in soft condensed phases. Nevertheless, despite dramatic advances in the methodology and resources for simulating atomically detailed models, low-resolution coarse-grained (CG) models play a central and rapidly growing role in science. CG models not only empower researchers to investigate phenomena beyond the scope of atomically detailed simulations, but also to precisely tailor models for specific phenomena. However, in contrast to atomically detailed simulations, which evolve on a potential energy surface, CG simulations should evolve on a free energy surface. Therefore, the forces in CG models should reflect the thermodynamic information that has been eliminated from the CG configuration space. As a consequence of these thermodynamic forces, CG models often demonstrate limited transferability and, moreover, rarely provide an accurate description of both structural and thermodynamic properties. In this talk, I will present a framework that clarifies the origin and impact of these thermodynamic forces. Additionally, I will present computational methods for quantifying these forces and incorporating their effects into CG MD simulations. As time allows, I will demonstrate applications of this framework for liquids, polymers, and interfaces. We gratefully acknowledge the support of the National Science Foundation via CHE 1565631.

Nigeria's Satellite Programme Development: Prospects and Challenges

Science.gov (United States)

Akinyede, Joseph

Nigeria's desire to maximize the benefits of space technology for its sustainable development, has become a reality with the establishment of the National Space Research and Development Agency (NASRDA) in May 1999 and the approval of the national Space Policy and Programmes in July 2001. In November, 2000, the Federal Government took a bold step with the signing of an agreement with the Surrey Satellite Technology Limited (SSTL) of United Kingdom (UK) for the design, construction and launch of a medium resolution micro-satellite - NigeriaSat-1 with a Ground Sampling Distance of thirty-two (32) meters. The agreement also covers the Know-How-Technology-Training (KHTT) to Nigerian Engineers and Scientists for a period of 18th months at SSTL‘s facility in the U.K.. NigeriaSat-1 was successfully launched into Leo Earth Orbit on 27th September, 2003. NigeriaSat- 1 is one of the five (5) satellites belonging to Nigeria, Algeria, Turkey, United Kingdom and China being operated in a Disaster Monitoring Constellation (DMC). The launch of NigeriaSat-1 has promoted access to information which has become a strategy for mass socio-economic development, as information underscores all developmental effort be it in education, provision of health services, marketing, construction industry, tourism, defense, etc. As a follow-up to the successful launch of NigeriaSat-1, the government of Nigeria started the implementation of a Nigerian communication satellite (NigcomSat-1) to address the problem of communication which is the greatest drawbacks to the socio-economic development of the country, particularly in the areas of rural telephone, tele-education, tele-medicine, egovernment, e-commerce and real-time monitoring services. NigcomSat-1, which carries 40- hybrid transponders in the C, KU, KA and L bands, has a 15 years life span and coverage of the African continent, Middle East and part of Europe was launched in May 2007. To satisfy geospatial data needs in sectors such as survey

Modelling airborne dispersion of coarse particulate material

International Nuclear Information System (INIS)

Apsley, D.D.

1989-03-01

Methods of modelling the airborne dispersion and deposition of coarse particulates are presented, with the emphasis on the heavy particles identified as possible constituents of releases from damaged AGR fuel. The first part of this report establishes the physical characteristics of the irradiated particulate in airborne emissions from AGR stations. The second part is less specific and describes procedures for extending current dispersion/deposition models to incorporate a coarse particulate component: the adjustment to plume spread parameters, dispersion from elevated sources and dispersion in conjunction with building effects and plume rise. (author)

Recycled Coarse Aggregate Produced by Pulsed Discharge in Water

Science.gov (United States)

Namihira, Takao; Shigeishi, Mitsuhiro; Nakashima, Kazuyuki; Murakami, Akira; Kuroki, Kaori; Kiyan, Tsuyoshi; Tomoda, Yuichi; Sakugawa, Takashi; Katsuki, Sunao; Akiyama, Hidenori; Ohtsu, Masayasu

In Japan, the recycling ratio of concrete scraps has been kept over 98 % after the Law for the Recycling of Construction Materials was enforced in 2000. In the present, most of concrete scraps were recycled as the Lower Subbase Course Material. On the other hand, it is predicted to be difficult to keep this higher recycling ratio in the near future because concrete scraps increase rapidly and would reach to over 3 times of present situation in 2010. In addition, the demand of concrete scraps as the Lower Subbase Course Material has been decreased. Therefore, new way to reuse concrete scraps must be developed. Concrete scraps normally consist of 70 % of coarse aggregate, 19 % of water and 11 % of cement. To obtain the higher recycling ratio, the higher recycling ratio of coarse aggregate is desired. In this paper, a new method for recycling coarse aggregate from concrete scraps has been developed and demonstrated. The system includes a Marx generator and a point to hemisphere mesh electrode immersed in water. In the demonstration, the test piece of concrete scrap was located between the electrodes and was treated by the pulsed discharge. After discharge treatment of test piece, the recycling coarse aggregates were evaluated under JIS and TS and had enough quality for utilization as the coarse aggregate.

Very high resolution satellite data: New challenges in image analysis

Digital Repository Service at National Institute of Oceanography (India)

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

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

High-Resolution Structural Monitoring of Ionospheric Absorption Events

Science.gov (United States)

2013-07-01

7 riometry. Incorporation of an outrigger site, to enable treatment of the unknown structure of the celestial background and the effects of...riometry. Incorporation of an outrigger site, to enable treatment of the unknown structure of the celestial background and the effects of confusion...event captured with this system . Note that, even at this fairly coarse resolution, there is discrete structure that changes in position and strength

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

Science.gov (United States)

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

2014-06-01

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

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.

Chemical-mineralogical characterisation of coarse recycled concrete aggregate

International Nuclear Information System (INIS)

Limbachiya, M.C.; Marrocchino, E.; Koulouris, A.

2007-01-01

The construction industry is now putting greater emphasis than ever before on increasing recycling and promoting more sustainable waste management practices. In keeping with this approach, many sectors of the industry have actively sought to encourage the use of recycled concrete aggregate (RCA) as an alternative to primary aggregates in concrete production. The results of a laboratory experimental programme aimed at establishing chemical and mineralogical characteristics of coarse RCA and its likely influence on concrete performance are reported in this paper. Commercially produced coarse RCA and natural aggregates (16-4 mm size fraction) were tested. Results of X-ray fluorescence (XRF) analyses showed that original source of RCA had a negligible effect on the major elements and a comparable chemical composition between recycled and natural aggregates. X-ray diffraction (XRD) analyses results indicated the presence of calcite, portlandite and minor peaks of muscovite/illite in recycled aggregates, although they were directly proportioned to their original composition. The influence of 30%, 50%, and 100% coarse RCA on the chemical composition of equal design strength concrete has been established, and its suitability for use in a concrete application has been assessed. In this work, coarse RCA was used as a direct replacement for natural gravel in concrete production. Test results indicated that up to 30% coarse RCA had no effect on the main three oxides (SiO 2 , Al 2 O 3 and CaO) of concrete, but thereafter there was a marginal decrease in SiO 2 and increase in Al 2 O 3 and CaO contents with increase in RCA content in the mix, reflecting the original constituent's composition

Chemical-mineralogical characterisation of coarse recycled concrete aggregate.

Science.gov (United States)

Limbachiya, M C; Marrocchino, E; Koulouris, A

2007-01-01

The construction industry is now putting greater emphasis than ever before on increasing recycling and promoting more sustainable waste management practices. In keeping with this approach, many sectors of the industry have actively sought to encourage the use of recycled concrete aggregate (RCA) as an alternative to primary aggregates in concrete production. The results of a laboratory experimental programme aimed at establishing chemical and mineralogical characteristics of coarse RCA and its likely influence on concrete performance are reported in this paper. Commercially produced coarse RCA and natural aggregates (16-4 mm size fraction) were tested. Results of X-ray fluorescence (XRF) analyses showed that original source of RCA had a negligible effect on the major elements and a comparable chemical composition between recycled and natural aggregates. X-ray diffraction (XRD) analyses results indicated the presence of calcite, portlandite and minor peaks of muscovite/illite in recycled aggregates, although they were directly proportioned to their original composition. The influence of 30%, 50%, and 100% coarse RCA on the chemical composition of equal design strength concrete has been established, and its suitability for use in a concrete application has been assessed. In this work, coarse RCA was used as a direct replacement for natural gravel in concrete production. Test results indicated that up to 30% coarse RCA had no effect on the main three oxides (SiO2, Al2O3 and CaO) of concrete, but thereafter there was a marginal decrease in SiO2 and increase in Al2O3 and CaO contents with increase in RCA content in the mix, reflecting the original constituent's composition.

Coarse graining of atactic polystyrene and its derivatives

Science.gov (United States)

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

2014-03-01

Capturing large length scales in polymers and soft matter while retaining atomistic properties is imperative to computational studies of dynamic systems. Here we present a new methodology developing coarse-grain model based on atomistic simulation of atactic polystyrene (PS). Similar to previous work by Fritz et al., each monomer is described by two coarse grained beads. In contrast to this earlier work where intramolecular potentials were based on Monte Carlo simulation of both isotactic and syndiotactic single PS molecule to capture stereochemistry, we obtained intramolecular interactions from a single molecular dynamics simulation of an all-atom atactic PS melts. The non-bonded interactions are obtained using the iterative Boltzmann inversion (IBI) scheme. This methodology has been extended to coarse graining of poly-(t-butyl-styrene) (PtBS). An additional coarse-grained bead is used to describe the t-butyl group. Similar to the process for PS, the intramolecular interactions are obtained from a single all atom atactic melt simulation. Starting from the non-bonded interactions for PS, we show that the IBI method for the non-bonded interactions of PtBS converges relatively fast. A generalized scheme for substituted PS is currently in development. We would like to acknowledge Prof. Kurt Kremer for helpful discussions during this work.

Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series

Directory of Open Access Journals (Sweden)

Claudia Kuenzer

2015-07-01

Full Text Available River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China, the Mekong Delta (Vietnam, the Irrawaddy Delta (Myanmar, and the Ganges-Brahmaputra (Bangladesh, India—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013. A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid

Coarse-graining free theories with gauge symmetries: the linearized case

International Nuclear Information System (INIS)

Bahr, Benjamin; Dittrich, Bianca; He Song

2011-01-01

Discretizations of continuum theories often do not preserve the gauge symmetry content. This occurs in particular for diffeomorphism symmetry in general relativity, which leads to severe difficulties in both canonical and covariant quantization approaches. We discuss here the method of perfect actions, which attempts to restore gauge symmetries by mirroring exactly continuum physics on a lattice via a coarse graining process. Analytical results can only be obtained via a perturbative approach, for which we consider the first step, namely the coarse graining of the linearized theory. The linearized gauge symmetries are exact also in the discretized theory; hence, we develop a formalism to deal with gauge systems. Finally, we provide a discretization of linearized gravity as well as a coarse graining map and show that with this choice the three-dimensional (3D) linearized gravity action is invariant under coarse graining.

Nonlinear Multigrid solver exploiting AMGe Coarse Spaces with Approximation Properties

DEFF Research Database (Denmark)

Christensen, Max la Cour; Villa, Umberto; Engsig-Karup, Allan Peter

The paper introduces a nonlinear multigrid solver for mixed finite element discretizations based on the Full Approximation Scheme (FAS) and element-based Algebraic Multigrid (AMGe). The main motivation to use FAS for unstructured problems is the guaranteed approximation property of the AMGe coarse...... properties of the coarse spaces. With coarse spaces with approximation properties, our FAS approach on unstructured meshes has the ability to be as powerful/successful as FAS on geometrically refined meshes. For comparison, Newton’s method and Picard iterations with an inner state-of-the-art linear solver...... are compared to FAS on a nonlinear saddle point problem with applications to porous media flow. It is demonstrated that FAS is faster than Newton’s method and Picard iterations for the experiments considered here. Due to the guaranteed approximation properties of our AMGe, the coarse spaces are very accurate...

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

Science.gov (United States)

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

2009-12-01

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

Technological possibilities for increasing coarse coal yield in the Staszic mine

Energy Technology Data Exchange (ETDEWEB)

Sikora, W; Major, M

1985-06-01

Experiments carried out in the Staszic underground black coal mine in Upper Silesia showed that there is a correlation of coarse coal yield and yield strength of shield supports used at longwall faces. The faces were equipped with Pioma 25-45, Fazos 15-31 and Fazos 19-32 shield supports, KWB 3RDU shearer loaders and Rybnik chain conveyors. Pressure of oil in water emulsion used in the Pioma 25/45 shield supports was reduced from the recommended 30 MPa to 15 MPa or to 10 MPa. Reducing emulsion pressure (and support yield strength) caused an increase in coarse coal yield. Coarse coal yield was also increased by use of Fazos 19/32 shield supports with reduced yield strength. During the tests coarse coal yield increased 1.68% and 2.65%. Test results are shown in 3 diagrams. Investigations carried out in the Staszic mine in 1983 showed that by optimizing yield strength of shield supports coarse coal yield could be increased 2 to 8%. 6 references.

Satellite Ocean Biology: Past, Present, Future

Science.gov (United States)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Earth mapping - aerial or satellite imagery comparative analysis

Science.gov (United States)

Fotev, Svetlin; Jordanov, Dimitar; Lukarski, Hristo

Nowadays, solving the tasks for revision of existing map products and creation of new maps requires making a choice of the land cover image source. The issue of the effectiveness and cost of the usage of aerial mapping systems versus the efficiency and cost of very-high resolution satellite imagery is topical [1, 2, 3, 4]. The price of any remotely sensed image depends on the product (panchromatic or multispectral), resolution, processing level, scale, urgency of task and on whether the needed image is available in the archive or has to be requested. The purpose of the present work is: to make a comparative analysis between the two approaches for mapping the Earth having in mind two parameters: quality and cost. To suggest an approach for selection of the map information sources - airplane-based or spacecraft-based imaging systems with very-high spatial resolution. Two cases are considered: area that equals approximately one satellite scene and area that equals approximately the territory of Bulgaria.

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

African Journals Online (AJOL)

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

Volume calculations of coarse woody debris; evaluation of coarse woody debris volume calculations and consequences for coarse woody debris volume estimates in forest reserves

NARCIS (Netherlands)

Wijdeven, S.M.J.; Vaessen, O.H.B.; Hees, van A.F.M.; Olsthoorn, A.F.M.

2005-01-01

Dead wood is recognized as one of the key indicators for sustainable forest management and biodiversity. Accurate assessments of dead wood volume are thus necessary. In this study New volume models were designed based on actual volume measurements of coarse woody debris. The New generic model

Spacetime coarse grainings in nonrelativistic quantum mechanics

International Nuclear Information System (INIS)

Hartle, J.B.

1991-01-01

Sum-over-histories generalizations of nonrelativistic quantum mechanics are explored in which probabilities are predicted, not just for alternatives defined on spacelike surfaces, but for alternatives defined by the behavior of spacetime histories with respect to spacetime regions. Closed, nonrelativistic systems are discussed whose histories are paths in a given configuration space. The action and the initial quantum state are assumed fixed and given. A formulation of quantum mechanics is used which assigns probabilities to members of sets of alternative coarse-grained histories of the system, that is, to the individual classes of a partition of its paths into exhaustive and exclusive classes. Probabilities are assigned to those sets which decohere, that is, whose probabilities are consistent with the sum rules of probability theory. Coarse graining by the behavior of paths with respect to regions of spacetime is described. For example, given a single region, the set of all paths may be partitioned into those which never pass through the region and those which pass through the region at least once. A sum-over-histories decoherence functional is defined for sets of alternative histories coarse-grained by spacetime regions. Techniques for the definition and effective computation of the relevant sums over histories by operator-product formulas are described and illustrated by examples. Methods based on Euclidean stochastic processes are also discussed and illustrated. Models of decoherence and measurement for spacetime coarse grainings are described. Issues of causality are investigated. Such spacetime generalizations of nonrelativistic quantum mechanics may be useful models for a generalized quantum mechanics of spacetime geometry

Resolution Enhancement of Multilook Imagery

Energy Technology Data Exchange (ETDEWEB)

Galbraith, Amy E. [Univ. of Arizona, Tucson, AZ (United States)

2004-07-01

This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The important topic of aliasing is examined in the context of the POCS resolution enhancement algorithm performance. In addition, the extension of the method to multispectral sensor images is discussed and an example is shown using multispectral confocal fluorescence imaging microscope data. Finally, the remote sensing issues of atmospheric path radiance and directional reflectance variations are explored to determine their effect on the resolution enhancement performance.

Constructing Optimal Coarse-Grained Sites of Huge Biomolecules by Fluctuation Maximization.

Science.gov (United States)

Li, Min; Zhang, John Zenghui; Xia, Fei

2016-04-12

Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10,000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems.

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

Science.gov (United States)

Pelta, Ran; Chudnovsky, Alexandra A

2017-02-01

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

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

Science.gov (United States)

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

2017-11-01

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

Entropies from Coarse-graining: Convex Polytopes vs. Ellipsoids

Directory of Open Access Journals (Sweden)

Nikos Kalogeropoulos

2015-09-01

Full Text Available We examine the Boltzmann/Gibbs/Shannon SBGS and the non-additive Havrda-Charvát/Daróczy/Cressie-Read/Tsallis Sq and the Kaniadakis κ-entropy Sκ from the viewpoint of coarse-graining, symplectic capacities and convexity. We argue that the functional form of such entropies can be ascribed to a discordance in phase-space coarse-graining between two generally different approaches: the Euclidean/Riemannian metric one that reflects independence and picks cubes as the fundamental cells in coarse-graining and the symplectic/canonical one that picks spheres/ellipsoids for this role. Our discussion is motivated by and confined to the behaviour of Hamiltonian systems of many degrees of freedom. We see that Dvoretzky’s theorem provides asymptotic estimates for the minimal dimension beyond which these two approaches are close to each other. We state and speculate about the role that dualities may play in this viewpoint.

Enhanced ionosphere-magnetosphere data from the DMSP satellites

International Nuclear Information System (INIS)

Rich, F.J.; Hardy, D.A.; Gussenhoven, M.S.

1985-01-01

The satellites of the Defense Meteorological Satellite Program (DMSP) represent a series of low-altitude (835 km) polar-orbiting satellites. Their primary objective is related to the observation of the tropospheric weather with a high-resolution white light and infrared imaging system. It is also possible to make images of auroras. On a daily basis, information about auroras is used to assist various communication systems which are affected by the ionospheric disturbances associated with auroras. In the past few years, there have been several improvements in the ionospheric monitoring instrumentation. Since the high-latitude ionosphere is connected to the magnetosphere, the DMSP data are used to monitor magnetospheric processes. The instrumentation of the DMSP satellites is discussed, taking into account the data provided by them. 7 references

Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data

Directory of Open Access Journals (Sweden)

G. Spreen

2017-07-01

Full Text Available A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous–plastic (VP sea-ice rheology are compared with synthetic aperture radar (SAR satellite observations (RGPS, RADARSAT Geophysical Processor System for the time period 1996–2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous–plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.

Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations

Science.gov (United States)

Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.

2011-09-01

Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.

Effects of model resolution and parameterizations on the simulations of clouds, precipitation, and their interactions with aerosols

Science.gov (United States)

Lee, Seoung Soo; Li, Zhanqing; Zhang, Yuwei; Yoo, Hyelim; Kim, Seungbum; Kim, Byung-Gon; Choi, Yong-Sang; Mok, Jungbin; Um, Junshik; Ock Choi, Kyoung; Dong, Danhong

2018-01-01

This study investigates the roles played by model resolution and microphysics parameterizations in the well-known uncertainties or errors in simulations of clouds, precipitation, and their interactions with aerosols by the numerical weather prediction (NWP) models. For this investigation, we used cloud-system-resolving model (CSRM) simulations as benchmark simulations that adopt high-resolution and full-fledged microphysical processes. These simulations were evaluated against observations, and this evaluation demonstrated that the CSRM simulations can function as benchmark simulations. Comparisons between the CSRM simulations and the simulations at the coarse resolutions that are generally adopted by current NWP models indicate that the use of coarse resolutions as in the NWP models can lower not only updrafts and other cloud variables (e.g., cloud mass, condensation, deposition, and evaporation) but also their sensitivity to increasing aerosol concentration. The parameterization of the saturation process plays an important role in the sensitivity of cloud variables to aerosol concentrations. while the parameterization of the sedimentation process has a substantial impact on how cloud variables are distributed vertically. The variation in cloud variables with resolution is much greater than what happens with varying microphysics parameterizations, which suggests that the uncertainties in the NWP simulations are associated with resolution much more than microphysics parameterizations.

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

Science.gov (United States)

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

2013-12-01

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

NONLINEAR MULTIGRID SOLVER EXPLOITING AMGe COARSE SPACES WITH APPROXIMATION PROPERTIES

Energy Technology Data Exchange (ETDEWEB)

Christensen, Max La Cour [Technical Univ. of Denmark, Lyngby (Denmark); Villa, Umberto E. [Univ. of Texas, Austin, TX (United States); Engsig-Karup, Allan P. [Technical Univ. of Denmark, Lyngby (Denmark); Vassilevski, Panayot S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-01-22

The paper introduces a nonlinear multigrid solver for mixed nite element discretizations based on the Full Approximation Scheme (FAS) and element-based Algebraic Multigrid (AMGe). The main motivation to use FAS for unstruc- tured problems is the guaranteed approximation property of the AMGe coarse spaces that were developed recently at Lawrence Livermore National Laboratory. These give the ability to derive stable and accurate coarse nonlinear discretization problems. The previous attempts (including ones with the original AMGe method, [5, 11]), were less successful due to lack of such good approximation properties of the coarse spaces. With coarse spaces with approximation properties, our FAS approach on un- structured meshes should be as powerful/successful as FAS on geometrically re ned meshes. For comparison, Newton's method and Picard iterations with an inner state-of-the-art linear solver is compared to FAS on a nonlinear saddle point problem with applications to porous media ow. It is demonstrated that FAS is faster than Newton's method and Picard iterations for the experiments considered here. Due to the guaranteed approximation properties of our AMGe, the coarse spaces are very accurate, providing a solver with the potential for mesh-independent convergence on general unstructured meshes.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

Science.gov (United States)

Davis, Philip A.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this

Spanish Earth Observation Satellite System

Science.gov (United States)

Borges, A.; Cerezo, F.; Fernandez, M.; Lomba, J.; Lopez, M.; Moreno, J.; Neira, A.; Quintana, C.; Torres, J.; Trigo, R.; Urena, J.; Vega, E.; Vez, E.

2010-12-01

The Spanish Ministry of Industry, Tourism and Trade (MITyC) and the Ministry of Defense (MoD) signed an agreement in 2007 for the development of a "Spanish Earth Observation Satellite System" based, in first instance, on two satellites: a high resolution optical satellite, called SEOSAT/Ingenio, and a radar satellite based on SAR technology, called SEOSAR/Paz. SEOSAT/Ingenio is managed by MITyC through the Centre for the Development of Industrial Technology (CDTI), with technical and contractual support from the European Space Agency (ESA). HISDESA T together with the Spanish Instituto Nacional de Técnica Aeroespacial (INTA, National Institute for Aerospace Technology) will be responsible for the in-orbit operation and the commercial operation of both satellites, and for the technical management of SEOSAR/Paz on behalf of the MoD. In both cases EADS CASA Espacio (ECE) is the prime contractor leading the industrial consortia. The ground segment development will be assigned to a Spanish consortium. This system is the most important contribution of Spain to the European Programme Global Monitoring for Environment and Security, GMES. This paper presents the Spanish Earth Observation Satellite System focusing on SEOSA T/Ingenio Programme and with special emphasis in the potential contribution to the ESA Third Party Missions Programme and to the Global Monitoring for Environment and Security initiative (GMES) Data Access.

Utilization of downscaled microwave satellite data and GRACE Total Water Storage anomalies for improving streamflow prediction in the Lower Mekong Basin

Science.gov (United States)

Lakshmi, V.; Gupta, M.; Bolten, J. D.

2016-12-01

The Mekong river is the world's eighth largest in discharge with draining an area of 795,000 km² from the Eastern watershed of the Tibetan Plateau to the Mekong Delta including, Myanmar, Laos PDR, Thailand, Cambodia, Vietnam and three provinces of China. The populations in these countries are highly dependent on the Mekong River and they are vulnerable to the availability and quality of the water resources within the Mekong River Basin. Soil moisture is one of the most important hydrological cycle variables and is available from passive microwave satellite sensors (such as AMSR-E, SMOS and SMAP), but their spatial resolution is frequently too coarse for effective use by land managers and decision makers. The merging of satellite observations with numerical models has led to improved land surface predictions. Although performance of the models have been continuously improving, the laboratory methods for determining key hydraulic parameters are time consuming and expensive. The present study assesses a method to determine the effective soil hydraulic parameters using a downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E). The soil moisture downscaling algorithm is based on a regression relationship between 1-km MODIS land surface temperature and 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) to produce an enhanced spatial resolution ASMR-E-based soil moisture product. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the land surface model. This work improves the hydrological fluxes and the state variables are optimized and the optimal parameter values are then transferred for retrieving hydrological fluxes. To evaluate the performance of the system in helping improve

Renormalization and Coarse-graining of Loop Quantum Gravity

OpenAIRE

Charles, Christoph

2017-01-01

The continuum limit of loop quantum gravity is still an open problem. Indeed, no proper dynamics in known to start with and we still lack the mathematical tools to study its would-be continuum limit. In the present PhD dissertation, we will investigate some coarse-graining methods that should become helpful in this enterprise. We concentrate on two aspects of the theory's coarse-graining: finding natural large scale observables on one hand and studying how the dynamics of varying graphs could...

Influence of uncoated and coated plastic waste coarse aggregates to concrete compressive strength

OpenAIRE

Purnomo Heru; Pamudji Gandjar; Satim Madsuri

2017-01-01

The use of plastic waste as coarse aggregates in concrete is part of efforts to reduce environmental pollution. In one hand the use of plastic as aggregates can provide lighter weight of the concrete than concrete using natural aggregates, but on the other hand bond between plastic coarse aggregates and hard matrix give low concrete compressive strength. Improvement of the bond between plastic coarse aggregate and hard matrix through a sand coating to plastic coarse aggregate whole surface is...

SAGA GIS based processing of spatial high resolution temperature data

International Nuclear Information System (INIS)

Gerlitz, Lars; Bechtel, Benjamin; Kawohl, Tobias; Boehner, Juergen; Zaksek, Klemen

2013-01-01

Many climate change impact studies require surface and near surface temperature data with high spatial and temporal resolution. The resolution of state of the art climate models and remote sensing data is often by far to coarse to represent the meso- and microscale distinctions of temperatures. This is particularly the case for regions with a huge variability of topoclimates, such as mountainous or urban areas. Statistical downscaling techniques are promising methods to refine gridded temperature data with limited spatial resolution, particularly due to their low demand for computer capacity. This paper presents two downscaling approaches - one for climate model output and one for remote sensing data. Both are methodically based on the FOSS-GIS platform SAGA. (orig.)

Compact design of a transmission electron microscope-scanning tunneling microscope holder with three-dimensional coarse motion

International Nuclear Information System (INIS)

Svensson, K.; Jompol, Y.; Olin, H.; Olsson, E.

2003-01-01

A scanning tunneling microscope (STM) with a compact, three-dimensional, inertial slider design is presented. Inertial sliding of the STM tip, in three dimensions, enables coarse motion and scanning using only one piezoelectric tube. Using the same electronics both for scanning and inertial sliding, step lengths of less than 5% of the piezo range were achieved. The compact design, less than 1 cm3 in volume, ensures a low mechanical noise level and enables us to fit the STM into the sample holder of a transmission electron microscope (TEM), while maintaining atomic scale resolution in both STM and TEM imaging

Use of Openly Available Satellite Images for Remote Sensing Education

Science.gov (United States)

Wang, C.-K.

2011-09-01

With the advent of Google Earth, Google Maps, and Microsoft Bing Maps, high resolution satellite imagery are becoming more easily accessible than ever. It have been the case that the college students may already have wealth experiences with the high resolution satellite imagery by using these software and web services prior to any formal remote sensing education. It is obvious that the remote sensing education should be adjusted to the fact that the audience are already the customers of remote sensing products (through the use of the above mentioned services). This paper reports the use of openly available satellite imagery in an introductory-level remote sensing course in the Department of Geomatics of National Cheng Kung University as a term project. From the experience learned from the fall of 2009 and 2010, it shows that this term project has effectively aroused the students' enthusiastic toward Remote Sensing.

A high-resolution open biomass burning emission inventory based on statistical data and MODIS observations in mainland China

Science.gov (United States)

Xu, Y.; Fan, M.; Huang, Z.; Zheng, J.; Chen, L.

2017-12-01

Open biomass burning which has adverse effects on air quality and human health is an important source of gas and particulate matter (PM) in China. Current emission estimations of open biomass burning are generally based on single source (alternative to statistical data and satellite-derived data) and thus contain large uncertainty due to the limitation of data. In this study, to quantify the 2015-based amount of open biomass burning, we established a new estimation method for open biomass burning activity levels by combining the bottom-up statistical data and top-down MODIS observations. And three sub-category sources which used different activity data were considered. For open crop residue burning, the "best estimate" of activity data was obtained by averaging the statistical data from China statistical yearbooks and satellite observations from MODIS burned area product MCD64A1 weighted by their uncertainties. For the forest and grassland fires, their activity levels were represented by the combination of statistical data and MODIS active fire product MCD14ML. Using the fire radiative power (FRP) which is considered as a better indicator of active fire level as the spatial allocation surrogate, coarse gridded emissions were reallocated into 3km ×3km grids to get a high-resolution emission inventory. Our results showed that emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC and OC in mainland China were 6607, 427, 84, 79, 1262, 1198, 1222, 159 and 686 Gg/yr, respectively. Among all provinces of China, Henan, Shandong and Heilongjiang were the top three contributors to the total emissions. In this study, the developed open biomass burning emission inventory with a high-resolution could support air quality modeling and policy-making for pollution control.

Resonant satellite transitions in argon

International Nuclear Information System (INIS)

Samson, J.A.R.; Lee Eunmee; Chung, Y.

1990-01-01

The production of specific Ar + satellite states has been studied with synchrotron radiation at wavelengths between 300 and 350 A with an effective energy resolution of 20 meV. The specific states studied were the ( 3 P)4p( 2 P 3/2 ), ( 1 D)4p( 2 F 7/2 ), and ( 1 D)4p( 2 P 1/2 ) states. The fluorescent radiation emitted from these excited ionic states was measured at 4766, 4611, and 4133 A by the use of narrow band interference filters. The variation of the fluorescence intensity was measured as a function of wavelength. This provided a measure of the relative cross section for production of the satellite states. Each satellite state was found to be completely dominated by autoionization of the neutral doubly excited states (3s 2 3p 4 )nl, n'l' found in this spectral region. (orig.)

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

Science.gov (United States)

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

2014-12-01

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

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

Science.gov (United States)

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

2015-01-01

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

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

The implementation of sea ice model on a regional high-resolution scale

Science.gov (United States)

Prasad, Siva; Zakharov, Igor; Bobby, Pradeep; McGuire, Peter

2015-09-01

The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional ice condition simulation. The paper describes the implementation of the Los Alamos sea ice model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea ice simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as ice concentration, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea ice behavior over 7 years was simulated to analyze ice formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated ice concentration correlated well with Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Ocean and Sea Ice Satellite Application Facility (OSI-SAF) data. Visual comparison of ice thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010-2011.

Adaptive resolution simulation of an atomistic DNA molecule in MARTINI salt solution

NARCIS (Netherlands)

Zavadlav, J.; Podgornik, R.; Melo, M.n.; Marrink, S.j.; Praprotnik, M.

2016-01-01

We present a dual-resolution model of a deoxyribonucleic acid (DNA) molecule in a bathing solution, where we concurrently couple atomistic bundled water and ions with the coarse-grained MAR- TINI model of the solvent. We use our fine-grained salt solution model as a solvent in the inner shell

Quantifying the clear-sky bias of satellite-derived infrared LST

Science.gov (United States)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

Resolving Properties of Polymers and Nanoparticle Assembly through Coarse-Grained Computational Studies.

Energy Technology Data Exchange (ETDEWEB)

Grest, Gary S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

Coupled length and time scales determine the dynamic behavior of polymers and polymer nanocomposites and underlie their unique properties. To resolve the properties over large time and length scales it is imperative to develop coarse grained models which retain the atomistic specificity. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details a nd access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using polyethylene as a model system, we probe how the coarse - graining scale affects the measured dynamics with different number methylene group s per coarse - grained beads. Using these models we simulate polyethylene melts for times over 500 ms to study the viscoelastic properties of well - entangled polymer melts and large nanoparticle assembly as the nanoparticles are driven close enough to form nanostructures.

Characteristics of thin and coarse particulates of urban and natural brazilian aerosols

International Nuclear Information System (INIS)

Orsini, C.Q.; Tabacnics, M.H.; Artaxo, P.; Andrade, M.F.; Kerr, A.S.

1994-01-01

Thin and coarse particulate were sampled during the period 1982-1985 in a natural coastal forest (Jureia), and five urban-industrial regions (Vitoria, Salvador, Porto Alegre, Sao Paulo and Belo Horizonte). The time variation of the concentration in the air, and the relative elementary composition of the thin and coarse particulate, sampled by thin and Coarse Particulate Sampler (AFG), were determined by gravimetric method and PIXE analysis respectively. The results demonstrated that the ground dust and salt from the sea are unequivocally one of the largest sources of coarse particulate, and also the ground is a significant thin particulate source. 25 refs, 22 figs, 28 tabs. (L.C.J.A.)

Importance of Coarse Woody Debris to Avian Communities in Loblolly Pine Forests

Energy Technology Data Exchange (ETDEWEB)

Lohr, S.M.; Gauthreaux, S.A.; Kilgo, J.C.

2001-06-14

Investigates the importance of standing and down coarse woody debris to bird communities in loblolly pine forests, researchers compared breeding and nonbreeding responses of birds among two coarse woody debris removal and control treatments. Quantification of vegetation layers to determine their effects on the experimental outcome coarse woody debris removal had no effect on the nonbreeding bird community. Most breeding and nonbreeding species used habitats with sparse midstory and well-developed understory, where as sparse canopy cover and dense midstory were important to some nonbreeding species. Snag and down coarse woody debris practices that maintain a dense understory, sparse midstory and canopy will create favorable breeding habitat.

Coarse-graining using the relative entropy and simplex-based optimization methods in VOTCA

Science.gov (United States)

Rühle, Victor; Jochum, Mara; Koschke, Konstantin; Aluru, N. R.; Kremer, Kurt; Mashayak, S. Y.; Junghans, Christoph

2014-03-01

Coarse-grained (CG) simulations are an important tool to investigate systems on larger time and length scales. Several methods for systematic coarse-graining were developed, varying in complexity and the property of interest. Thus, the question arises which method best suits a specific class of system and desired application. The Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) provides a uniform platform for coarse-graining methods and allows for their direct comparison. We present recent advances of VOTCA, namely the implementation of the relative entropy method and downhill simplex optimization for coarse-graining. The methods are illustrated by coarse-graining SPC/E bulk water and a water-methanol mixture. Both CG models reproduce the pair distributions accurately. SYM is supported by AFOSR under grant 11157642 and by NSF under grant 1264282. CJ was supported in part by the NSF PHY11-25915 at KITP. K. Koschke acknowledges funding by the Nestle Research Center.

Design of low-power coarse-grained reconfigurable architectures

CERN Document Server

Kim, Yoonjin

2010-01-01

Coarse-grained reconfigurable architecture (CGRA) has emerged as a solution for flexible, application-specific optimization of embedded systems. Helping you understand the issues involved in designing and constructing embedded systems, Design of Low-Power Coarse-Grained Reconfigurable Architectures offers new frameworks for optimizing the architecture of components in embedded systems in order to decrease area and save power. Real application benchmarks and gate-level simulations substantiate these frameworks.The first half of the book explains how to reduce power in the configuration cache. T

The precision of today's satellite laser ranging systems

Science.gov (United States)

Dunn, Peter J.; Torrence, Mark H.; Hussen, Van S.; Pearlman, Michael R.

1993-06-01

Recent improvements in the accuracy of modern satellite laser ranging (SLR) systems are strengthened by the new capability of many instruments to track an increasing number of geodetic satellite targets without significant scheduling conflict. This will allow the refinement of some geophysical parameters, such as solid Earth tidal effects and GM, and the improved temporal resolution of others, such as Earth orientation and station position. Better time resolution for the locations of fixed observatories will allow us to monitor more subtle motions at the stations, and transportable systems will be able to provide indicators of long term trends with shorter occupations. If we are to take advantage of these improvements, care must be taken to preserve the essential accuracy of an increasing volume of range observations at each stage of the data reduction process.

Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions

Directory of Open Access Journals (Sweden)

Xiaolin Zhu

2018-03-01

Full Text Available Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.

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.

Satellite observations of the northeast monsoon coastal current

Digital Repository Service at National Institute of Oceanography (India)

Shenoi, S.S.C.; Gouveia, A.D.; Shetye, S.R.; Rao, L.V.G.

Satellite Infrared observations, from Advanced Very High Resolution Radiometer (AVHRR), during November 1987-February 1988 and hydrographic data from the eastern Arabian Sea are used to describe the poleward flowing coastal current in the eastern...

Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations

NARCIS (Netherlands)

Lopez, Patricia Lopez; Wanders, Niko; Schellekens, Jaap; Renzullo, Luigi J.; Sutanudjaja, Edwin H.; Bierkens, Marc F. P.

2016-01-01

The coarse spatial resolution of global hydrological models (typically > 0.25◦ ) limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally tuned river models. A possible

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

Science.gov (United States)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

On the representability problem and the physical meaning of coarse-grained models

Energy Technology Data Exchange (ETDEWEB)

Wagner, Jacob W.; Dama, James F.; Durumeric, Aleksander E. P.; Voth, Gregory A., E-mail: gavoth@uchicago.edu [Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637 (United States)

2016-07-28

In coarse-grained (CG) models where certain fine-grained (FG, i.e., atomistic resolution) observables are not directly represented, one can nonetheless identify indirect the CG observables that capture the FG observable’s dependence on CG coordinates. Often, in these cases it appears that a CG observable can be defined by analogy to an all-atom or FG observable, but the similarity is misleading and significantly undermines the interpretation of both bottom-up and top-down CG models. Such problems emerge especially clearly in the framework of the systematic bottom-up CG modeling, where a direct and transparent correspondence between FG and CG variables establishes precise conditions for consistency between CG observables and underlying FG models. Here we present and investigate these representability challenges and illustrate them via the bottom-up conceptual framework for several simple analytically tractable polymer models. The examples provide special focus on the observables of configurational internal energy, entropy, and pressure, which have been at the root of controversy in the CG literature, as well as discuss observables that would seem to be entirely missing in the CG representation but can nonetheless be correlated with CG behavior. Though we investigate these problems in the framework of systematic coarse-graining, the lessons apply to top-down CG modeling also, with crucial implications for simulation at constant pressure and surface tension and for the interpretations of structural and thermodynamic correlations for comparison to experiment.

Satellite-generated radar images of the earth

International Nuclear Information System (INIS)

Schanda, E.

1980-01-01

The Synthetic Aperture Radar (SAR) on board of SEASAT was the first non-military satellite-borne radar producing high-resolution images of the earth. Several examples of European scenes are discussed to demonstrate the properties of presently available optically processes images. (orig.)

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

OpenAIRE

C. M. R. Mateo; C. M. R. Mateo; D. Yamazaki; D. Yamazaki; H. Kim; A. Champathong; J. Vaze; T. Oki; T. Oki

2017-01-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development...

BUILT-UP AREA AND LAND COVER EXTRACTION USING HIGH RESOLUTION PLEIADES SATELLITE IMAGERY FOR MIDRAND, IN GAUTENG PROVINCE, SOUTH AFRICA

Directory of Open Access Journals (Sweden)

E. Fundisi

2017-09-01

Full Text Available Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

Built-Up Area and Land Cover Extraction Using High Resolution Pleiades Satellite Imagery for Midrand, in Gauteng Province, South Africa

Science.gov (United States)

Fundisi, E.; Musakwa, W.

2017-09-01

Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

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

Science.gov (United States)

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

2011-12-01

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

Satellite studies of the stratospheric aerosol

International Nuclear Information System (INIS)

McCormick, M.P.; Hamill, P.; Pepin, T.J.; Chu, W.P.; Swissler, T.J.; McMaster, L.R.

1979-01-01

The potential climatological and environmental importance of the stratospheric aerosol layer has prompted great interest in measuring the properties of this aerosol. In this paper we report on two recently deployed NASA satellite systems (SAM II and SAGE) that are monitoring the stratospheric aerosol. The satellite orbits are such that nearly global coverage is obtained. The instruments mounted in the spacecraft are sun photometers that measure solar intensity at specific wavelengths as it is moderated by atmospheric particulates and gases during each sunrise and sunset encountered by the satellites. The data obtained are ''inverted'' to yield vertical aerosol and gaseous (primarily ozone) extinction profiles with 1 km vertical resolution. Thus, latitudinal, longitudinal, and temporal variations in the aerosol layer can be evaluated. The satellite systems are being validated by a series of ground truth experiments using airborne and ground lidar, balloon-borne dustsondes, aircraft-mounted impactors, and other correlative sensors. We describe the SAM II and SAGE satellite systems, instrument characteristics, and mode of operation; outline the methodology of the experiments; and describe the ground truth experiments. We present preliminary results from these measurements

A data mining approach for sharpening satellite thermal imagery over land

Science.gov (United States)

Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

GNSS, Satellite Altimetry and Formosat-3/COSMIC for Determination of Ionosphere Parameters

Science.gov (United States)

Mahdi Alizadeh Elizei, M.; Schuh, Harald; Schmidt, Michael; Todorova, Sonya

The dispersion of ionosphere with respect to the microwave signals allows gaining information about the parameters of this medium in terms of the electron density (Ne), or the Total Elec-tron Content (TEC). In the last decade space geodetic techniques, such as Global Navigation Satellite System (GNSS), satellite altimetry missions, and Low Earth Orbiting (LEO) satel-lites have turned into a promising tool for remote sensing the ionosphere. The dual-frequency GNSS observations provide the main input data for development of Global Ionosphere Maps (GIM). However, the GNSS stations are heterogeneously distributed, with large gaps particu-larly over the sea surface, which lowers the precision of the GIM over these areas. Conversely, dual-frequency satellite altimetry missions provide information about the ionosphere precisely above the sea surface. In addition, LEO satellites such as Formosat-3/COSMIC (F-3/C) pro-vide well-distributed information of ionosphere around the world. In this study we developed GIMs of VTEC from combination of GNSS, satellite altimetry and F-3/C data with temporal resolution of 2 hours and spatial resolution of 5 degree in longitude and 2.5 degree in latitude. The combined GIMs provide a more homogeneous global coverage and higher precision and reliability than results of each individual technique.

Recurrent Neural Networks to Correct Satellite Image Classification Maps

Science.gov (United States)

Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre

2017-09-01

While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

A novel capacitive absolute positioning sensor based on time grating with nanometer resolution

Science.gov (United States)

Pu, Hongji; Liu, Hongzhong; Liu, Xiaokang; Peng, Kai; Yu, Zhicheng

2018-05-01

The present work proposes a novel capacitive absolute positioning sensor based on time grating. The sensor includes a fine incremental-displacement measurement component combined with a coarse absolute-position measurement component to obtain high-resolution absolute positioning measurements. A single row type sensor was proposed to achieve fine displacement measurement, which combines the two electrode rows of a previously proposed double-row type capacitive displacement sensor based on time grating into a single row. To achieve absolute positioning measurement, the coarse measurement component is designed as a single-row type displacement sensor employing a single spatial period over the entire measurement range. In addition, this component employs a rectangular induction electrode and four groups of orthogonal discrete excitation electrodes with half-sinusoidal envelope shapes, which were formed by alternately extending the rectangular electrodes of the fine measurement component. The fine and coarse measurement components are tightly integrated to form a compact absolute positioning sensor. A prototype sensor was manufactured using printed circuit board technology for testing and optimization of the design in conjunction with simulations. Experimental results show that the prototype sensor achieves a ±300 nm measurement accuracy with a 1 nm resolution over a displacement range of 200 mm when employing error compensation. The proposed sensor is an excellent alternative to presently available long-range absolute nanometrology sensors owing to its low cost, simple structure, and ease of manufacturing.

Velocity estimation of an airplane through a single satellite image

Institute of Scientific and Technical Information of China (English)

Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

2012-01-01

The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

Classification of Clouds and Deep Convection from GEOS-5 Using Satellite Observations

Science.gov (United States)

Putman, William; Suarez, Max

2010-01-01

With the increased resolution of global atmospheric models and the push toward global cloud resolving models, the resemblance of model output to satellite observations has become strikingly similar. As we progress with our adaptation of the Goddard Earth Observing System Model, Version 5 (GEOS-5) as a high resolution cloud system resolving model, evaluation of cloud properties and deep convection require in-depth analysis beyond a visual comparison. Outgoing long-wave radiation (OLR) provides a sufficient comparison with infrared (IR) satellite imagery to isolate areas of deep convection. We have adopted a binning technique to generate a series of histograms for OLR which classify the presence and fraction of clear sky versus deep convection in the tropics that can be compared with a similar analyses of IR imagery from composite Geostationary Operational Environmental Satellite (GOES) observations. We will present initial results that have been used to evaluate the amount of deep convective parameterization required within the model as we move toward cloud system resolving resolutions of 10- to 1-km globally.

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.

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Science.gov (United States)

Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

2013-01-01

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg

Effects of Model Resolution and Ocean Mixing on Forced Ice-Ocean Physical and Biogeochemical Simulations Using Global and Regional System Models

Science.gov (United States)

Jin, Meibing; Deal, Clara; Maslowski, Wieslaw; Matrai, Patricia; Roberts, Andrew; Osinski, Robert; Lee, Younjoo J.; Frants, Marina; Elliott, Scott; Jeffery, Nicole; Hunke, Elizabeth; Wang, Shanlin

2018-01-01

The current coarse-resolution global Community Earth System Model (CESM) can reproduce major and large-scale patterns but is still missing some key biogeochemical features in the Arctic Ocean, e.g., low surface nutrients in the Canada Basin. We incorporated the CESM Version 1 ocean biogeochemical code into the Regional Arctic System Model (RASM) and coupled it with a sea-ice algal module to investigate model limitations. Four ice-ocean hindcast cases are compared with various observations: two in a global 1° (40˜60 km in the Arctic) grid: G1deg and G1deg-OLD with/without new sea-ice processes incorporated; two on RASM's 1/12° (˜9 km) grid R9km and R9km-NB with/without a subgrid scale brine rejection parameterization which improves ocean vertical mixing under sea ice. Higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice extent, ice thickness, and ice algae. In the Bering Sea shelf, only higher resolution contributed to lower model errors in salinity, nitrate (NO3), and chlorophyll-a (Chl-a). In the Arctic Basin, model errors in mixed layer depth (MLD) were reduced 36% by brine rejection parameterization, 20% by new sea-ice processes, and 6% by higher resolution. The NO3 concentration biases were caused by both MLD bias and coarse resolution, because of excessive horizontal mixing of high NO3 from the Chukchi Sea into the Canada Basin in coarse resolution models. R9km showed improvements over G1deg on NO3, but not on Chl-a, likely due to light limitation under snow and ice cover in the Arctic Basin.

Future development of IR thermovision weather satellite equipment