Spring green-up date derived from GIMMS3g and SPOT-VGT NDVI of winter wheat cropland in the North China Plain

NASA Astrophysics Data System (ADS)

Liu, Zhengjia; Wu, Chaoyang; Liu, Yansui; Wang, Xiaoyue; Fang, Bin; Yuan, Wenping; Ge, Quansheng

2017-08-01

Satellite temporal resolution affects the fitting accuracy of vegetation growth curves. However, there are few studies that evaluate the impact of different satellite data (including temporal resolution and time series change) on spring green-up date (GUD) extraction. In this study, four GUD algorithms and two different temporal resolution satellite data (GIMMS3g during 1982-2013 and SPOT-VGT during 1999-2013) were used to investigate winter wheat GUD in the North China Plain. Four GUD algorithms included logistic-NDVI (normalized difference vegetation index), logistic-cumNDVI (cumulative NDVI), polynomial-NDVI and polynomial-cumNDVI algorithms. All algorithms and data were first regrouped into eight controlled cases. At site scale, we evaluated the performance of each case using correlation coefficient (r), bias and root mean square error (RMSE). We further compared spatial patterns and inter-annual trends of GUD inferred from different algorithms, and then analyzed the difference between GIMMS3g-based GUD and SPOT-VGT-based GUD. Our results showed that all satellite-based GUD were correlated with observations with r ranging from 0.32 to 0.57 (p < 0.01). SPOT-VGT-based GUD generally had better correlations with observed GUD than those of GIMMS3g. Spatially, SPOT-VGT-based GUD performed more reasonable spatial distributions. Inter-annual regional averaged satellite-based GUD presented overall advanced trends during 1982-2013 (0.3-2.0 days/decade) while delayed trends were observed during 1999-2013 (1.7-7.4 days/decade for GIMMS3g and 3.8-7.4 days/decade for SPOT-VGT). However, their significance levels were highly dependent on the data and algorithms used. Our findings suggest cautions on previous results of inter-annual variability of phenology from a single data/method.

Object-based locust habitat mapping using high-resolution multispectral satellite data in the southern Aral Sea basin

NASA Astrophysics Data System (ADS)

Navratil, Peter; Wilps, Hans

2013-01-01

Three different object-based image classification techniques are applied to high-resolution satellite data for the mapping of the habitats of Asian migratory locust (Locusta migratoria migratoria) in the southern Aral Sea basin, Uzbekistan. A set of panchromatic and multispectral Système Pour l'Observation de la Terre-5 satellite images was spectrally enhanced by normalized difference vegetation index and tasseled cap transformation and segmented into image objects, which were then classified by three different classification approaches: a rule-based hierarchical fuzzy threshold (HFT) classification method was compared to a supervised nearest neighbor classifier and classification tree analysis by the quick, unbiased, efficient statistical trees algorithm. Special emphasis was laid on the discrimination of locust feeding and breeding habitats due to the significance of this discrimination for practical locust control. Field data on vegetation and land cover, collected at the time of satellite image acquisition, was used to evaluate classification accuracy. The results show that a robust HFT classifier outperformed the two automated procedures by 13% overall accuracy. The classification method allowed a reliable discrimination of locust feeding and breeding habitats, which is of significant importance for the application of the resulting data for an economically and environmentally sound control of locust pests because exact spatial knowledge on the habitat types allows a more effective surveying and use of pesticides.

Testing ecoregions in Kentucky and Tennessee with satellite imagery and Forest Inventory data

Treesearch

W. Henry McNab; F. Thomas Lloyd

2009-01-01

Ecoregions are large mapped areas of hypothesized ecological uniformity that are delineated subjectively based on multiple physical and biological components. Ecoregion maps are seldom evaluated because suitable data sets are often lacking. Landsat imagery is a readily available, low-cost source of archived data that can be used to calculate the normalized difference...

Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

NASA Astrophysics Data System (ADS)

Poon, P.; Kinoshita, A. M.

2017-12-01

Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa

PubMed Central

2012-01-01

Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. PMID:22443452

Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa.

PubMed

Dambach, Peter; Machault, Vanessa; Lacaux, Jean-Pierre; Vignolles, Cécile; Sié, Ali; Sauerborn, Rainer

2012-03-23

The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming. © 2012 Dambach et al; licensee BioMed Central Ltd.

Development of spectral indices for roofing material condition status detection using field spectroscopy and WorldView-3 data

NASA Astrophysics Data System (ADS)

Samsudin, Sarah Hanim; Shafri, Helmi Z. M.; Hamedianfar, Alireza

2016-04-01

Status observations of roofing material degradation are constantly evolving due to urban feature heterogeneities. Although advanced classification techniques have been introduced to improve within-class impervious surface classifications, these techniques involve complex processing and high computation times. This study integrates field spectroscopy and satellite multispectral remote sensing data to generate degradation status maps of concrete and metal roofing materials. Field spectroscopy data were used as bases for selecting suitable bands for spectral index development because of the limited number of multispectral bands. Mapping methods for roof degradation status were established for metal and concrete roofing materials by developing the normalized difference concrete condition index (NDCCI) and the normalized difference metal condition index (NDMCI). Results indicate that the accuracies achieved using the spectral indices are higher than those obtained using supervised pixel-based classification. The NDCCI generated an accuracy of 84.44%, whereas the support vector machine (SVM) approach yielded an accuracy of 73.06%. The NDMCI obtained an accuracy of 94.17% compared with 62.5% for the SVM approach. These findings support the suitability of the developed spectral index methods for determining roof degradation statuses from satellite observations in heterogeneous urban environments.

Vegetation monitoring and classification using NOAA/AVHRR satellite data

NASA Technical Reports Server (NTRS)

Greegor, D. H., Jr.; Norwine, J. R.

1983-01-01

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

DOE PAGES

Robinson, Nathaniel; Allred, Brady; Jones, Matthew; ...

2017-08-21

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Nathaniel; Allred, Brady; Jones, Matthew

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodologicalmore » challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.« less

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Comparison of simulation modeling and satellite techniques for monitoring ecological processes

NASA Technical Reports Server (NTRS)

Box, Elgene O.

1988-01-01

In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.

Research on anti - interference based on GNSS

NASA Astrophysics Data System (ADS)

Yu, Huanran; Liu, Yijun

2017-05-01

Satellite Navigation System has been widely used in military and civil fields. It has all-functional, all-weather, continuity and real-time characteristics, can provide the precise position, velocity and timing information's for the users. The environments where the receiver of satellite navigation system works become more and more complex, and the satellite signals are susceptible to intentional or unintentional interferences, anti-jamming capability has become a key problem of satellite navigation receiver's ability to work normal. In this paper, we study a DOA estimation algorithm based on linear symmetric matrix to improve the anti-jamming capability of the satellite navigation receiver, has great significance to improve the performance of satellite navigation system in complex electromagnetic environment and enhance its applicability in various environments.

Scintillation statistics measured in an earth-space-earth retroreflector link

NASA Technical Reports Server (NTRS)

Bufton, J. L.

1977-01-01

Scintillation was measured in a vertical path from a ground-based laser transmitter to the Geos 3 satellite and back to a ground-based receiver telescope and, the experimental results were compared with analytical results presented in a companion paper (Bufton, 1977). The normalized variance, the probability density function and the power spectral density of scintillation were all measured. Moments of the satellite scintillation data in terms of normalized variance were lower than expected. The power spectrum analysis suggests that there were scintillation components at frequencies higher than the 250 Hz bandwidth available in the experiment.

Web tools concerning performance analysis and planning support for solar energy plants starting from remotely sensed optical images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morelli, Marco, E-mail: marco.morelli1@unimi.it; Masini, Andrea, E-mail: andrea.masini@flyby.it; Ruffini, Fabrizio, E-mail: fabrizio.ruffini@i-em.eu

We present innovative web tools, developed also in the frame of the FP7 ENDORSE (ENergy DOwnstReam SErvices) project, for the performance analysis and the support in planning of solar energy plants (PV, CSP, CPV). These services are based on the combination between the detailed physical model of each part of the plants and the near real-time satellite remote sensing of incident solar irradiance. Starting from the solar Global Horizontal Irradiance (GHI) data provided by the Monitoring Atmospheric Composition and Climate (GMES-MACC) Core Service and based on the elaboration of Meteosat Second Generation (MSG) satellite optical imagery, the Global Tilted Irradiancemore » (GTI) or the Beam Normal Irradiance (BNI) incident on plant's solar PV panels (or solar receivers for CSP or CPV) is calculated. Combining these parameters with the model of the solar power plant, using also air temperature values, we can assess in near-real-time the daily evolution of the alternate current (AC) power produced by the plant. We are therefore able to compare this satellite-based AC power yield with the actually measured one and, consequently, to readily detect any possible malfunctions and to evaluate the performances of the plant (so-called “Controller” service). Besides, the same method can be applied to satellite-based averaged environmental data (solar irradiance and air temperature) in order to provide a Return on Investment analysis in support to the planning of new solar energy plants (so-called “Planner” service). This method has been successfully applied to three test solar plants (in North, Centre and South Italy respectively) and it has been validated by comparing satellite-based and in-situ measured hourly AC power data for several months in 2013 and 2014. The results show a good accuracy: the overall Normalized Bias (NB) is − 0.41%, the overall Normalized Mean Absolute Error (NMAE) is 4.90%, the Normalized Root Mean Square Error (NRMSE) is 7.66% and the overall Correlation Coefficient (CC) is 0.9538. The maximum value of the Normalized Absolute Error (NAE) is about 30% and occurs for time periods with highly variable meteorological conditions. - Highlights: • We developed an online service (Controller) dedicated to solar energy plants real-time monitoring • We developed an online service (Planner) that supports the planning of new solar energy plants • The services are based on the elaboration of satellite optical imagery in near real-time • The validation with respect to in-situ measured hourly AC power data for three test solar plants shows good accuracy • The maximum value of the Normalized Absolute Error is about 30% and occurs for highly variable meteorological conditions.« less

Vegetation Cover Change in Yosemite National Park (California) Detected using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Landsat image analysis over the past 20+ years showed that consistent increases in the satellite normalized difference vegetation index (NDVI) during relatively dry years were confined to large wildfire areas that burned in the late 1980s and 1990s.

Building a Consistent Long-Term SSS Data Record from Multi-Satellite Measurements: A Case Study in the Eastern Tropical Pacific (SPURS-2)

NASA Astrophysics Data System (ADS)

Melnichenko, O.; Hacker, P. W.; Wentz, F. J.; Meissner, T.; Maximenko, N. A.; Potemra, J. T.

2016-12-01

To address the need for a consistent, continuous, long-term, high-resolution sea surface salinity (SSS) dataset for ocean research and applications, a trial SSS analysis is produced in the eastern tropical Pacific from multi-satellite observations. The new SSS data record is a synergy of data from two satellite missions. The beginning segment, covering the period from September 2011 to June 2015, utilizes Aquarius SSS data and is based on the optimum interpolation analysis developed at the University of Hawaii. The analysis is produced on a 0.25-degree grid and uses a dedicated bias-correction algorithm to correct the satellite retrievals for large-scale biases with respect to in-situ data. The time series is continued with the Soil Moisture Active Passive (SMAP) satellite-based SSS data provided by Remote Sensing Systems (RSS). To ensure consistency and continuity in the data record, SMAP SSS fields are adjusted using a set of optimally designed spatial filters and in-situ, primarily Argo, data to: (i) remove large-scale satellite biases, and (ii) reduce small-scale noise, while preserving the high spatial and temporal resolution of the data set. The consistency between the two sub-sets of the data record is evaluated during their overlapping period in April-June 2015. Verification studies show that SMAP SSS has a very good agreement with the Aquarius SSS, noting that SMAP SSS can provide better spatial resolution. The 5-yr long time series of SSS in the SPURS-2 domain (125oW, 10oN) shows fresher than normal SSS during the last year's El Nino event. The year-mean difference is about 0.5 psu. The annual cycle during the El Nino year also appears to be much weaker than in a normal year.

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

PubMed

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

PubMed Central

Lange, Maximilian; Rebmann, Corinna; Cuntz, Matthias; Doktor, Daniel

2017-01-01

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure. PMID:28800065

Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

USGS Publications Warehouse

,

2005-01-01

The Advanced Very High Resolution Radiometer (AVHRR) is a broad-band scanner with four to six bands, depending on the model. The AVHRR senses in the visible, near-, middle-, and thermal- infrared portions of the electromagnetic spectrum. This sensor is carried on a series of National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES), beginning with the Television InfraRed Observation Satellite (TIROS-N) in 1978. Since 1989, the United States Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has been mapping the vegetation condition of the United States and Alaska using satellite information from the AVHRR sensor. The vegetation condition composites, more commonly called greenness maps, are produced every week using the latest information on the growth and condition of the vegetation. One of the most important aspects of USGS greenness mapping is the historical archive of information dating back to 1989. This historical stretch of information has allowed the USGS to determine a 'normal' vegetation condition. As a result, it is possible to compare the current week's vegetation condition with normal vegetation conditions. An above normal condition could indicate wetter or warmer than normal conditions, while a below normal condition could indicate colder or dryer than normal conditions. The interpretation of departure from normal will depend on the season and geography of a region.

Forecasting vegetation greenness with satellite and climate data

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R2 values range from 0.97-0.80 for 2-12 week forecasts, with higher R2 associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.

Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2015-01-01

Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

Thirty Years of Vegetation Change in the Coastal Santa Cruz Mountains of Northern California Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher

2015-01-01

Results from Landsat satellite image times series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90% of the (predominantly second-growth) evergreen forest locations sampled.

MODIS imagery as a tool for synoptic water quality assessments in the southern California coastal ocean

USGS Publications Warehouse

Nezlin, N.P.; DiGiacomo, P.M.; Jones, B.H.; Reifel, K.M.; Warrick, J.A.; Johnson, S.C.; Mengel, M.J.

2007-01-01

The dynamics of rainstorm plumes in the coastal waters of southern California was studied during the Bight'03 Regional Water Quality Program surveys. Measurements of surface salinity and bacterial counts collected from research vessels were compared to MODIS-Aqua satellite imagery. The spectra of normalized water-leaving radiation (nLw) were different in plumes and ambient ocean waters, enabling plumes discrimination and plume area size assessments from remotely-sensed data. The plume/ocean nLw differences (i.e., plume optical signatures) were most evident during first days after the rainstorm over the San Pedro shelf and in the San Diego region and less evident in Santa Monica Bay, where suspended sediments concentration in discharged water was lower than in other regions. In the Ventura area, plumes contained more suspended sediments than in other regions, but the grid of ship-based stations covered only a small part of the freshwater plume and was insufficient to reveal the differences between the plume and ocean optical signatures. The accuracy of plume area assessments from satellite imagery was not high (77% on average), seemingly because of inexactitude in satellite data processing. Nevertheless, satellite imagery is a useful tool for the estimation of the extent of polluted plumes, which is hardly achievable by contact methods.

Land mobile satellite demonstration system

NASA Technical Reports Server (NTRS)

Gooch, Guy M.; Nicholas, David C.

1988-01-01

A land mobile satellite demonstration system is described. It ulilizes the INMARSAT MARECS B2 satellite at 26 degrees W. The system provides data transmission using a poll-response protocol with error detection and retransmission at 200 b/s rate. For most tests a 1.8 inch monopole antenna was used, along with a satellite EIRP normally used for four voice channels. A brief summary of the results are given and the overall system consisting of three elements in addition to the satellite (the mobile unit, the base station, and the office terminal and map display) is described. Throughput statistics from one trip are summarized.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Extracting fields snow coverage information with HJ-1A/B satellites data

NASA Astrophysics Data System (ADS)

Dong, Wenquan; Meng, Jihua

2015-10-01

The distribution and change of snow coverage are sensitive factors of climate change. In northeast part of China, farmlands are still covered with snow in spring. Since sowing activity can only be done when the snow melted, fields snow coverage monitoring provides reference for the determination of sowing date. Because of the restriction of the sensors and application requirements, current researches on remote sensing of snow focus more on the study of musicale and large scale, rather than the study of small scale, and especially research on snow melting period is rarely reported.HJ-1A/B satellites are parts of little satellite constellation, focusing on environment and disaster monitoring and meteorological forecast. Compared to other data sources, HJ-1A/B satellites both have comparatively higher temporal and spatial resolution and are more conducive to monitor the variations of melting snow coverage at small watershed. This paper was based on HJ-1A/1B data, taking Hongxing farm of Bei'an, Heilongjiang Province, China as the study area. In this paper, we exploited the methods for extraction of snow cover information on farmland in two cases, both HJ-1A/1B CCD with HJ-1B IRS data and just HJ-1A/1B CCD data. The reason we chose the two cases is that, the two optical satellites HJ-1A/B are capable of providing a whole territory coverage period in visible light spectrum in two days, infrared spectrum in four days. So sometimes we can only obtain CCD image. In this case, the method of normalized snow index cannot be used to extract snow coverage information. Using HJ-1A/1B CCD with HJ-1B IRS data, combined with the theory of snow remote sensing monitoring, this paper analyzed spectral response characteristics of HJ-1A/1B satellites data, then the widely used Normalized Difference Snow Index(NDSI) and S3 Index were quoted to the HJ-1A/1B satellites data. The NDSI uses reflectance values of Red and SWIR spectral bands of HJ-1B, and S3 index uses reflectance values of NIR, Red and SWIR spectral bands. With multi-temporal HJ satellite data, the optimal threshold of normalized snow index was determined to divide the farmland into snow covering area, melting snow area and non-snow area. The results are quite similar to each other and of high accuracy, and the melting snow coverage can be well extracted by two types of normalized snow index. When we can only obtain CCD image, we use supervised classification method to extract melting snow coverage. With this method, the accuracy of fields snow coverage extraction is slightly lower than that using normalized snow index methods mentioned above. And in mountain area, the snow coverage area is slightly larger than that is extracted by normalized snow index methods, because the shadows make the color of snow in the valley darker, the supervised classification method divides it into non-snow coverage area, while the normalized snow index method well weakened the effect of shadow. This study shows that extraction accuracy in both cases is assessed, and both of them can meet the needs of practical applications. HJ-1A/1B satellites are conducive to monitor the variations of melting snow coverage over farmland, and they can provide reference for the determination of sowing date.

Digital image classification approach for estimating forest clearing and regrowth rates and trends

NASA Technical Reports Server (NTRS)

Sader, Steven A.

1987-01-01

A technique is presented to monitor vegetation changes for a selected study area in Costa Rica. A normalized difference vegetation index was computed for three dates of Landsat satellite data and a modified parallelipiped classifier was employed to generate a multitemporal greenness image representing all three dates. A second-generation image was created by partitioning the intensity levels at each date into high, medium, and low and thereby reducing the number of classes to 21. A sampling technique was applied to describe forest and other land cover change occurring between time periods based on interpretation of aerial photography that closely matched the dates of satellite acquisition. Comparison of the Landsat-derived classes with the photo-interpreted sample areas can provide a basis for evaluating the satellite monitoring technique and the accuracy of estimating forest clearing and regrowth rates and trends.

Exact Delaunay normalization of the perturbed Keplerian Hamiltonian with tesseral harmonics

NASA Astrophysics Data System (ADS)

Mahajan, Bharat; Vadali, Srinivas R.; Alfriend, Kyle T.

2018-03-01

A novel approach for the exact Delaunay normalization of the perturbed Keplerian Hamiltonian with tesseral and sectorial spherical harmonics is presented in this work. It is shown that the exact solution for the Delaunay normalization can be reduced to quadratures by the application of Deprit's Lie-transform-based perturbation method. Two different series representations of the quadratures, one in powers of the eccentricity and the other in powers of the ratio of the Earth's angular velocity to the satellite's mean motion, are derived. The latter series representation produces expressions for the short-period variations that are similar to those obtained from the conventional method of relegation. Alternatively, the quadratures can be evaluated numerically, resulting in more compact expressions for the short-period variations that are valid for an elliptic orbit with an arbitrary value of the eccentricity. Using the proposed methodology for the Delaunay normalization, generalized expressions for the short-period variations of the equinoctial orbital elements, valid for an arbitrary tesseral or sectorial harmonic, are derived. The result is a compact unified artificial satellite theory for the sub-synchronous and super-synchronous orbit regimes, which is nonsingular for the resonant orbits, and is closed-form in the eccentricity as well. The accuracy of the proposed theory is validated by comparison with numerical orbit propagations.

Development of fog detection algorithm using Himawari-8/AHI data at daytime

NASA Astrophysics Data System (ADS)

Han, Ji-Hye; Kim, So-Hyeong; suh, Myoung-Seok

2017-04-01

Fog is defined that small cloud water drops or ice particles float in the air and visibility is less than 1 km. In general, fog affects ecological system, radiation budget and human activities such as airplane, ship, and car. In this study, we developed a fog detection algorithm (FDA) consisted of four threshold tests of optical and textual properties of fog using satellite and ground observation data at daytime. For the detection of fog, we used satellite data (Himawari-8/AHI data) and other ancillary data such as air temperature from NWP data (over land), SST from OSTIA (over sea). And for validation, ground observed visibility data from KMA. The optical and textual properties of fog are normalized albedo (NAlb) and normalized local standard deviation (NLSD), respectively. In addition, differences between air temperature (SST) and fog top temperature (FTa(S)) are applied to discriminate the fog from low clouds. And post-processing is performed to detect the fog edge based on spatial continuity of fog. Threshold values for each test are determined by optimization processes based on the ROC analysis for the selected fog cases. Fog detection is performed according to solar zenith angle (SZA) because of the difference of available satellite data. In this study, we defined daytime when SZA is less than 85˚ . Result of FDA is presented by probability (0 ˜ 100 %) of fog through the weighted sum of each test result. The validation results with ground observed visibility data showed that POD and FAR are 0.63 ˜ 0.89 and 0.29 ˜ 0.46 according to the fog intensity and type, respectively. In general, the detection skills are better in the cases of intense and without high clouds than localized and weak fog. We are plan to transfer this algorithm to the National Meteorological Satellite Center of KMA for the operational detection of fog using GK-2A/AMI data which will be launched in 2018.

Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

NASA Astrophysics Data System (ADS)

Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

2016-04-01

Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map CC based on seasonal features with possibility to integrate medium resolution satellite observation from several sensors (e.g. Landsat and Sentinel-2) in the future.

Monitoring vegetation greenness with satellite data

Treesearch

Robert E. Burgan; Roberta A. Hartford

1993-01-01

Vegetation greenness can be monitored at 1-km resolution for the conterminous United States through data obtained from the Advanced Very High Resolution Radiometer on the NOAA-11 weather satellites. The data are used to calculate biweekly composites of the Normalized Difference Vegetation Index. The resulting composite images are updated weekly and made available to...

Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

NASA Astrophysics Data System (ADS)

Akay, S. S.; Sertel, E.

2016-06-01

Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.

Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

NASA Astrophysics Data System (ADS)

Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

2016-12-01

Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (<1 m) and land cover features such as substrate exposure that may affect estimates of vegetation structure in satellite data. Yet it is unclear how differences in spatial and spectral resolution between UAS and satellite data affect their relationships to each other, and to common field measurements of leaf area (e.g. LiCOR photosensors) and land cover. Constraining these relationships is important for leveraging UAS data to improve scaling of field data on leaf area and biomass to satellite data from Landsat, Sentinel-2, and increasing numbers of commercial sensors. Here, we quantify relationships among field, UAS and satellite estimates of vegetation leaf area and biomass in three case study landscapes spanning semi-arid Mediterranean (Matera, Southern Italy and Mallorca, Spain) and North American temperate ecosystems (New Jersey, USA). We assess how land cover and sensor spectral characteristics affect UAS and satellite-derived NDVI, leaf-area and biomass estimates. Then, we assess the fidelity of UAS, WorldView-2, and Landsat leaf-area and biomass estimates to field-measured landscape changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Wave optics-based LEO-LEO radio occultation retrieval

NASA Astrophysics Data System (ADS)

Benzon, Hans-Henrik; Høeg, Per

2016-06-01

This paper describes the theory for performing retrieval of radio occultations that use probing frequencies in the XK and KM band. Normally, radio occultations use frequencies in the L band, and GPS satellites are used as the transmitting source, and the occultation signals are received by a GPS receiver on board a Low Earth Orbit (LEO) satellite. The technique is based on the Doppler shift imposed, by the atmosphere, on the signal emitted from the GPS satellite. Two LEO satellites are assumed in the occultations discussed in this paper, and the retrieval is also dependent on the decrease in the signal amplitude caused by atmospheric absorption. The radio wave transmitter is placed on one of these satellites, while the receiver is placed on the other LEO satellite. One of the drawbacks of normal GPS-based radio occultations is that external information is needed to calculate some of the atmospheric products such as the correct water vapor content in the atmosphere. These limitations can be overcome when a proper selected range of high-frequency waves are used to probe the atmosphere. Probing frequencies close to the absorption line of water vapor have been included, thus allowing the retrieval of the water vapor content. Selecting the correct probing frequencies would make it possible to retrieve other information such as the content of ozone. The retrieval is performed through a number of processing steps which are based on the Full Spectrum Inversion (FSI) technique. The retrieval chain is therefore a wave optics-based retrieval chain, and it is therefore possible to process measurements that include multipath. In this paper simulated LEO to LEO radio occultations based on five different frequencies are used. The five frequencies are placed in the XK or KM frequency band. This new wave optics-based retrieval chain is used on a number of examples, and the retrieved atmospheric parameters are compared to the parameters from a global European Centre for Medium-Range Weather Forecasts analysis model. This model is used in a forward propagator that simulates the electromagnetic field amplitudes and phases at the receiver on board the LEO satellite. LEO-LEO cross-link radio occultations using high frequencies are a relatively new technique, and the possibilities and advantages of the technique still need to be investigated. The retrieval of this type of radio occultations is considerably more complicated than standard GPS to LEO radio occultations, because the attenuation of the probing radio waves is used in the retrieval and the atmospheric parameters are found using a least squares solver. The best algorithms and the number of probing frequencies that is economically viable must also be determined. This paper intends to answer some of these questions using end-to-end simulations.

Global Gravity Field Determination by Combination of terrestrial and Satellite Gravity Data

NASA Astrophysics Data System (ADS)

Fecher, T.; Pail, R.; Gruber, T.

2011-12-01

A multitude of impressive results document the success of the satellite gravity field mission GOCE with a wide field of applications in geodesy, geophysics and oceanography. The high performance of GOCE gravity field models can be further improved by combination with GRACE data, which is contributing the long wavelength signal content of the gravity field with very high accuracy. An example for such a consistent combination of satellite gravity data are the satellite-only models GOCO01S and GOCO02S. However, only the further combination with terrestrial and altimetric gravity data enables to expand gravity field models up to very high spherical harmonic degrees and thus to achieve a spatial resolution down to 20-30 km. First numerical studies for high-resolution global gravity field models combining GOCE, GRACE and terrestrial/altimetric data on basis of the DTU10 model have already been presented. Computations up to degree/order 600 based on full normal equations systems to preserve the full variance-covariance information, which results mainly from different weights of individual terrestrial/altimetric data sets, have been successfully performed. We could show that such large normal equations systems (degree/order 600 corresponds to a memory demand of almost 1TByte), representing an immense computational challenge as computation time and memory requirements put high demand on computational resources, can be handled. The DTU10 model includes gravity anomalies computed from the global model EGM08 in continental areas. Therefore, the main focus of this presentation lies on the computation of high-resolution combined gravity field models based on real terrestrial gravity anomaly data sets. This is a challenge due to the inconsistency of these data sets, including also systematic error components, but a further step to a real independent gravity field model. This contribution will present our recent developments and progress by using independent data sets at certain land areas, which are combined with DTU10 in the ocean areas, as well as satellite gravity data. Investigations have been made concerning the preparation and optimum weighting of the different data sources. The results, which should be a major step towards a GOCO-C model, will be validated using external gravity field data and by applying different validation methods.

Using the remote sensing vegetation condition to assess the drought stress

NASA Astrophysics Data System (ADS)

Semerádová, Daniela; Trnka, Miroslav; Hlavinka, Petr; Balek, Jan; Bohovic, Roman; Tadesse, Tsegaye; Hayes, Michael; Wardlow, Brian; Žalud, Zdeněk

2015-04-01

The occurrence of the meteorological and soil drought is one of the major hydrometeorological extremes with significant impacts on agriculture, horticulture and forestry. The drought monitor system for the Czech Republic was released in 2012. It is based on a daily step calculations of soil moisture for the whole area of the Czech Republic divided into regular grids with a spatial resolution of 500 m. The results are published on the weekly operated webpage (www.intersucho.cz). Using freely available data from the MODIS (Moderate Resolution Imaging Spectroradiometer instrument onboard Terra satellite) the vegetation state condition is taken into account as support tool for vegetation drought impact assessment. Based on the surface reflectance bands the Normalized Difference Vegetation Index (NDVI) is calculated. Consequently, weekly NDVI anomaly is expressed as Percent of Average Actual Greenness (PAAG) in relation to the average for the period of 2000-2014. The system contains filter algorithms that eliminate the noise in the satellite NDVI data mainly due to cloud effects. The following operation allows for changing crop patterns between seasons and aggregates filtered values to the 5x5 km resolution with regard to the main land use categories. The aim of this study was to compare the satellite based vegetation condition to the results of soil moisture calculation in order to detect the impacts of drought on vegetation during seasons with low and normal precipitation sums. This contribution was supported by COST CZ program, project No. LD14121 and the Operational Program of the Czech Republic, project No. CZ.1.07/2.3.00/20.0248.

Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

NASA Astrophysics Data System (ADS)

Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

2014-05-01

The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF showed a bimodal distribution, which could be related to the different cultivation schemes of crops. We suggest to divide croplands according their distinctly different temporal dynamics of the GVF into "early covering - maturing" crops (winter rape, winter wheat, spring barley) and "late covering - non-maturing" crops (sugar beet, silage maize). Based on the achieved results we recommend that simulations with LSM should take into account this differentiation of croplands since it is to be expected that these two crop groups have pronounced differences with regard to energy partitioning at the land surface.

Satellite-Based EMI Detection, Identification, and Mitigation

NASA Astrophysics Data System (ADS)

Stottler, R.; Bowman, C.

2016-09-01

Commanding, controlling, and maintaining the health of satellites requires a clear operating spectrum for communications. Electro Magnetic Interference (EMI) from other satellites can interfere with these communications. Determining which satellite is at fault improves space situational awareness and can be used to avoid the problem in the future. The Rfi detection And Prediction Tool, Optimizing Resources (RAPTOR) monitors the satellite communication antenna signals to detect EMI (also called RFI for Radio Frequency Interference) using a neural network trained on past cases of both normal communications and EMI events. RAPTOR maintains a database of satellites that have violated the reserved spectrum in the past. When satellite-based EMI is detected, RAPTOR first checks this list to determine if any are angularly close to the satellite being communicated with. Additionally, RAPTOR checks the Space Catalog to see if any of its active satellites are angularly close. RAPTOR also consults on-line databases to determine if the described operating frequencies of the satellites match the detected EMI and recommends candidates to be added to the known offenders database, accordingly. Based on detected EMI and predicted orbits and frequencies, RAPTOR automatically reschedules satellite communications to avoid current and future satellite-based EMI. It also includes an intuitive display for a global network of satellite communications antennas and their statuses including the status of their EM spectrum. RAPTOR has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication signals and is currently undergoing full-scale development. This paper describes the RAPTOR technologies and results of testing.

BRE facilitates skeletal muscle regeneration by promoting satellite cell motility and differentiation

PubMed Central

Xiao, Lihai; Lee, Kenneth Ka Ho

2016-01-01

ABSTRACT The function of the Bre gene in satellite cells was investigated during skeletal muscle regeneration. The tibialis anterior leg muscle was experimentally injured in Bre knockout mutant (BRE-KO) mice. It was established that the accompanying muscle regeneration was impaired as compared with their normal wild-type counterparts (BRE-WT). There were significantly fewer pax7+ satellite cells and smaller newly formed myofibers present in the injury sites of BRE-KO mice. Bre was required for satellite cell fusion and myofiber formation. The cell fusion index and average length of newly-formed BRE-KO myofibers were found to be significantly reduced as compared with BRE-WT myofibers. It is well established that satellite cells are highly invasive which confers on them the homing ability to reach the muscle injury sites. Hence, we tracked the migratory behavior of these cells using time-lapse microscopy. Image analysis revealed no difference in directionality of movement between BRE-KO and BRE-WT satellite cells but there was a significant decrease in the velocity of BRE-KO cell movement. Moreover, chemotactic migration assays indicated that BRE-KO satellite cells were significantly less responsive to chemoattractant SDF-1α than BRE-WT satellite cells. We also established that BRE normally protects CXCR4 from SDF-1α-induced degradation. In sum, BRE facilitates skeletal muscle regeneration by enhancing satellite cell motility, homing and fusion. PMID:26740569

Power attenuation characteristics as switch-over criterion in personal satellite mobile communications

NASA Technical Reports Server (NTRS)

Castro, Jonathan P.

1993-01-01

A third generation mobile system intends to support communications in all environments (i.e., outdoors, indoors at home or office and when moving). This system will integrate services that are now available in architectures such as cellular, cordless, mobile data networks, paging, including satellite services to rural areas. One way through which service integration will be made possible is by supporting a hierarchical cellular structure based on umbrella cells, macro cells, micro and pico cells. In this type of structure, satellites are part of the giant umbrella cells allowing continuous global coverage, the other cells belong to cities, neighborhoods, and buildings respectively. This does not necessarily imply that network operation of terrestrial and satellite segments interconnect to enable roaming and spectrum sharing. However, the cell concept does imply hand-off between different cell types, which may involve change of frequency. Within this propsective, the present work uses power attenuation characteristics to determine a dynamic criterion that allows smooth transition from space to terrestrial networks. The analysis includes a hybrid channel that combines Rician, Raleigh and Log Normal fading characteristics.

Observations of Typhoon Center by Using Satellite-derived Normalized Difference Convection Index

NASA Astrophysics Data System (ADS)

Liu, Chung-Chih; Chen, Chun-Hsu

2015-04-01

A technique involving differencing water vapor and infrared window channel brightness temperature values to identify and quantify intense convection in tropical cyclones using bispectral geostationary satellite imagery was proposed by Olander and Velden (2009). Rouse et al. (1974) calculated a normalized ratio of the near infrared and red bands and proposed an index called the normalized difference vegetation index. It was then used in many fields such as estimations of vegetation biomass, leaf area, the proportion of absorbed photosynthetically active radiation, etc. The present study used the spectral features of the IR1 and WV channels of the satellite to define a new index, the brightness temperature of the infrared window channel minus the brightness temperature of the water vapor channel divided by the brightness temperature of the infrared window channel plus the brightness temperature of the water vapor channel. The values obtained by this formula are called the Normalized Difference Convection Index (NDCI) values. The NDCI value is between -1 and 1. The NDCI value at WV = 0K is the highest, 1; while that at IR1 = 0K is the lowest, -1. In cases of a clear sky or atmosphere with thin cloud and dry air, NDCI values should be larger than 0. In cases of a convective cloud system, NDCI values should be lower than 0. In addition, the newly defined NDCI does show significant difference from simple difference of IR1-WV. For example, the NDCI value is -0.0017 at IR1=299K and WV=300K, while the NDCI value is -0.0033 at IR1=149K and WV=150K. The two times difference of NDCI values shows the features of clouds with NDCI value -0.0017 are quite different from those with NDCI value -0.0033. The former may be low level clouds, but the latter may be deep convections. However, the simple difference of IR1-WV cannot be used to distinguish the difference. The NDCI was applied to determine the centers of Typhoon Longwang (2005). The results showed that the two-dimensional NDCI analysis helped to identify positions of overshooting areas. In addition, because the NDCI values near a typhoon eye were rather significant, if a typhoon eye was formed, the NDCI cross-section analysis could help to confirm its position. When the center of a typhoon was covered by the high Anvils and Cirrus Layers, it could still be found qualitatively through the two-dimensional analysis. Keywords:Typhoon, Satellite imagery, Normalized Difference Convection Index

Arctic tundra greening and browning (2007-2013) based on satellite-observed solar-induced fluorescence data

NASA Astrophysics Data System (ADS)

Fu, D.; Su, F.; Wang, J.

2017-12-01

More accurate evaluation of the state of Arctic tundra vegetation is important for our understanding of Arctic and global systems. Arctic tundra greening has been reported, increasing vegetation cover and productivity in many regions, but browning has been also reported, based on satellite-observed Normalized Difference Vegetation Index (NDVI) from 2011 until recently. Here we demonstrate a satellite-based method of estimating tundra greenness trend. A more direct indicator of greenness (spatially downscaling solar-induced fluorescence, SIF) was used to analyze the spatial and temporal patterns of Arctic tundra greenness trends based on ordinary least square regression (2007-2013). Meanwhile, two other greenness indices were used for the comparison, which were two NDVI products: GIMMS NDVI3g, and MOD13Q1 Collection 6. Generally, the Arctic tundra was not consistently greening, browning also existed. For the spatial trends, the results showed that most parts of the Arctic tundra below 75ºN was browning (-0.0098 mW/m2/sr/nm/year) using SIF, whereas spatially heterogeneous trends (greening or browning) were obtained based on the two NDVI products. For the temporal trends, the greenness value of Eurasia Arctic tundra is higher than Northern America and the whole Arctic tundra for the three greenness indices. From 2010, the Arctic tundra was greening based on MOD13Q1, whereas is browning using GIMMS NDVI3g. However, the Arctic tundra was obviously browning using SIF data. This study demonstrates a way of investigating the variation of Arctic tundra vegetation via new satellite-observed data.

Robust Satellite Techniques analysis of ten years (2004-2013) of MSG/SEVIRI TIR radiances over Greece region

NASA Astrophysics Data System (ADS)

Genzano, N.; Eleftheriou, A.; Filizzola, C.; Paciello, R.; Pergola, N.; Vallianatos, F.; Tramutoli, V.

2014-12-01

Space-time fluctuations of Earth's emitted Thermal InfraRed (TIR) radiation have been observed from satellite months to weeks before earthquakes occurrence. Among the different approach proposed to discern transient anomalous signals possibly associated to seismic activity from normal TIR signal fluctuations (i.e. related to the change of natural factor and/or observation conditions), since 2001 the Robust Satellite Techniques (RST) were used to investigate tens of earthquakes with a wide range of magnitudes (from 4.0 to 7.9) occurred in different continents and in various geo-tectonic setting (e.g. Athens earthquake, 7 September 1999; Abruzzo earthquake, 6 April 2009, etc.).The RST approach gives a statistically - based definition of "TIR anomalies" and offers a suitable method for their identification even in very different local (e.g. related to atmosphere and/or surface) and observational (e.g. related to time/season, but also to solar and satellite zenithal angles) conditions. It has been always carried out by using a validation/confutation approach, to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity.In this paper, the RST approach is extensively implemented on 10 years of TIR satellite records collected by the geostationary satellite sensor MSG/SEVIRI over the Greece region. The results of the analysis performed to investigate possible correlations (within predefined space-time windows) of anomalous TIR transients with time and place of occurrence of earthquakes with M>4 will be discussed in terms of reliability and effectiveness also in the perspective of a time-Dependent Assessment of Seismic Hazard (t-DASH) system.

Covariance analyses of satellite-derived mesoscale wind fields

NASA Technical Reports Server (NTRS)

Maddox, R. A.; Vonder Haar, T. H.

1979-01-01

Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.

A new comprehensive index for drought monitoring with TM data

NASA Astrophysics Data System (ADS)

Wang, Yuanyuan

2017-10-01

Drought is one of the most important and frequent natural hazards to agriculture production in North China Plain. To improve agriculture water management, accurate drought monitoring information is needed. This study proposed a method for comprehensive drought monitoring by combining a meteorological index and three satellite drought indices of TM data together. SPI (Standard Precipitation Index), the meteorological drought index, is used to measure precipitation deficiency. Three satellite drought indices (Temperature Vegetation Drought Index, Land Surface Water Index, Modified Perpendicular Drought Index) are used to evaluate agricultural drought risk by exploring data from various channels (VIS, NIR, SWIR, TIR). Considering disparities in data ranges of different drought indices, normalization is implemented before combination. First, SPI is normalized to 0 — 100 given that its normal range is -4 - +4. Then, the three satellite drought indices are normalized to 0 - 100 according to the maximum and minimum values in the image, and aggregated using weighted average method (the result is denoted as ADI, Aggregated drought index). Finally, weighed geometric mean of SPI and ADI are calculated (the result is denoted as DIcombined). A case study in North China plain using three TM images acquired during April-May 2007 show that the method proposed in this study is effective. In spatial domain, DIcombined demonstrates dramatically more details than SPI; in temporal domain, DIcombined shows more reasonable drought development trajectory than satellite indices that are derived from independent TM images.

Normal and Tangential Momentum Accommodation for Earth Satellite Conditions

NASA Technical Reports Server (NTRS)

Knechtel, Earl D.; Pitts, William C.

1973-01-01

Momentum accommodation was determined experimentally for gas-surface interactions simulating in a practical way those of near-earth satellites. Throughout the ranges of gas energies and incidence angles of interest for earth-conditions, two components of force were measured by means of a vacuum microbalance to determine the normal and tangential momentum-accommodation coefficients for nitrogen ions on technical-quality aluminum surfaces. For these experimental conditions, the electrodynamics of ion neutralization near the surface indicate that results for nitrogen ions should differ relatively little from those for nitrogen molecules, which comprise the largest component of momentum flux for near-earth satellites. The experimental results indicated that both normal and tangential momentum-accommodation coefficients varied widely with energy, tending to be relatively well accommodated at the higher energies, but becoming progressively less accommodated as the energy was reduced to and below that for earth-satellite speeds. Both coefficients also varied greatly with incidence angle, the normal momentum becoming less accommodated as the incidence angle became more glancing, whereas the tangential momentum generally became more fully accommodated. For each momentum coefficient, an empirical correlation function was obtained which closely approximated the experimental results over the ranges of energy and incidence angle. Most of the observed variations of momentum accommodation with energy and incidence angle were qualitatively indicated by a calculation using a three-dimensional model that simulated the target surface by a one-dimensional attractive potential and hard sphere reflectors.

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface air temperature difference that used to calculate these lapse rate, which are ~3K difference between surface-observed and the satellite derived during the daytime and 5.1 K during nighttime. Further studies of the cause of the temperature inversions that may help the cloud heights retrievals by satellite. The preliminary comparisons in MBL microphysical properties have shown that the averaged CERES-MODIS derived MBL cloud-droplet effective radius is only 1.5 μm larger than ARM retrieval (13.2 μm), and LWP values are also very close to each other (112 vs. 124 gm-2) with a relative large difference in optical depth (10.6 vs. 14.4).

The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

NASA Astrophysics Data System (ADS)

Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

2017-11-01

Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

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

PubMed

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

2014-11-01

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

The Microscope Space Mission and the In-Orbit Calibration Plan for its Instrument

NASA Astrophysics Data System (ADS)

Levy, Agnès Touboul, Pierre; Rodrigues, Manuel; Onera, Émilie Hardy; Métris, Gilles; Robert, Alain

2015-01-01

The MICROSCOPE space mission aims at testing the Equivalence Principle (EP) with an accuracy of 10-15. This principle is one of the basis of the General Relativity theory; it states the equivalence between gravitational and inertial mass. The test is based on the precise measurement of a gravitational signal by a differential electrostatic accelerometer which includes two cylindrical test masses made of different materials. The accelerometers constitute the payload accommodated on board a drag-free micro-satellite which is controlled inertial or rotating about the normal to the orbital plane. The acceleration estimates used for the EP test are disturbed by the instruments physical parameters and by the instrument environment conditions on-board the satellite. These parameters are partially measured with ground tests or during the integration of the instrument in the satellite (alignment). Nevertheless, the ground evaluations are not sufficient with respect to the EP test accuracy objectives. An in-orbit calibration is therefore needed to characterize them finely. The calibration process for each parameter has been defined.

Quaternion normalization in additive EKF for spacecraft attitude determination. [Extended Kalman Filters

NASA Technical Reports Server (NTRS)

Bar-Itzhack, I. Y.; Deutschmann, J.; Markley, F. L.

1991-01-01

This work introduces, examines and compares several quaternion normalization algorithms, which are shown to be an effective stage in the application of the additive extended Kalman filter to spacecraft attitude determination, which is based on vector measurements. Three new normalization schemes are introduced. They are compared with one another and with the known brute force normalization scheme, and their efficiency is examined. Simulated satellite data are used to demonstate the performance of all four schemes.

Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

NASA Astrophysics Data System (ADS)

Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

2017-12-01

Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

Integrated approach to estimate the ocean's time variable dynamic topography including its covariance matrix

NASA Astrophysics Data System (ADS)

Müller, Silvia; Brockmann, Jan Martin; Schuh, Wolf-Dieter

2015-04-01

The ocean's dynamic topography as the difference between the sea surface and the geoid reflects many characteristics of the general ocean circulation. Consequently, it provides valuable information for evaluating or tuning ocean circulation models. The sea surface is directly observed by satellite radar altimetry while the geoid cannot be observed directly. The satellite-based gravity field determination requires different measurement principles (satellite-to-satellite tracking (e.g. GRACE), satellite-gravity-gradiometry (GOCE)). In addition, hydrographic measurements (salinity, temperature and pressure; near-surface velocities) provide information on the dynamic topography. The observation types have different representations and spatial as well as temporal resolutions. Therefore, the determination of the dynamic topography is not straightforward. Furthermore, the integration of the dynamic topography into ocean circulation models requires not only the dynamic topography itself but also its inverse covariance matrix on the ocean model grid. We developed a rigorous combination method in which the dynamic topography is parameterized in space as well as in time. The altimetric sea surface heights are expressed as a sum of geoid heights represented in terms of spherical harmonics and the dynamic topography parameterized by a finite element method which can be directly related to the particular ocean model grid. Besides the difficult task of combining altimetry data with a gravity field model, a major aspect is the consistent combination of satellite data and in-situ observations. The particular characteristics and the signal content of the different observations must be adequately considered requiring the introduction of auxiliary parameters. Within our model the individual observation groups are combined in terms of normal equations considering their full covariance information; i.e. a rigorous variance/covariance propagation from the original measurements to the final product is accomplished. In conclusion, the developed integrated approach allows for estimating the dynamic topography and its inverse covariance matrix on arbitrary grids in space and time. The inverse covariance matrix contains the appropriate weights for model-data misfits in least-squares ocean model inversions. The focus of this study is on the North Atlantic Ocean. We will present the conceptual design and dynamic topography estimates based on time variable data from seven satellite altimeter missions (Jason-1, Jason-2, Topex/Poseidon, Envisat, ERS-2, GFO, Cryosat2) in combination with the latest GOCE gravity field model and in-situ data from the Argo floats and near-surface drifting buoys.

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Analysis of dynamic thresholds for the normalized difference water index

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Wylie, Bruce K.

2009-01-01

The normalized difference water index (NDWI) has been successfully used to delineate surface water features. However, two major problems have been often encountered: (a) NDWIs calculated from different band combinations [visible, nearinfrared, or shortwave-infrared (SWIR)] can generate different results, and (b) NDWI thresholds vary depending on the proportions of subpixel water/non-water components. We need to evaluate all the NDWIS for determining the best performing index and to establish appropriate thresholds for clearly identifying water features. We used the spectral data obtained from a spectral library to simulate the satellite sensors Landsat ETM+, SPOT-5, ASTER, and MODIS, and calculated the simulated NDWI in different forms. We found that the NDWI calculated from (green - swm)/(green + SWIR), where SWIR is the shorter wavelength region (1.2 to 1.8 ??m), has the most stable threshold. We recommend this NDWI be employed for mapping water, but adjustment of the threshold based on actual situations is necessary. ?? 2009 American Society for Photogrammetry and Remote Sensing.

In-depth Analysis of Land Surface Emissivity using Microwave Polarization Difference Index to Improve Satellite QPE

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P. E.; Hong, Y.; Wen, Y.; Turk, J.; Gourley, J. J.

2015-12-01

One of primary uncertainties in satellite overland quantitative precipitation estimates (QPE) from passive sensors such as radiometers is the impact on the brightness temperatures by the surface land emissivity. The complexity of surface land emissivity is linked to its temporal variations (diurnal and seasonal) and spatial variations (subsurface vertical profiles of soil moisture, vegetation structure and surface temperature) translating into sub-pixel heterogeneity within the satellite field of view (FOV). To better extract the useful signal from hydrometeors, surface land emissivity needs to be determined and filtered from the satellite-measured brightness temperatures. Based on the dielectric properties of surface land cover constitutes, Microwave Polarization Differential index (MPDI) is expected to carry the composite effect of surface land properties on land surface emissivity, with a higher MPDI indicating a lower emissivity. This study analyses the dependence of MPDI to soil moisture, vegetation and surface skin temperature over 9 different land surface types. Such analysis is performed using the normalized difference vegetation index (NDVI) from MODIS, the near surface air temperature from the RAP model and ante-precedent precipitation accumulation from the Multi-Radar Multi-Sensor as surrogates for the vegetation, surface skin temperature and shallow layer soil moisture, respectively. This paper provides 1) evaluations of brightness temperature-based MPDI from the TRMM and GPM Microwave Imagers in both raining and non-raining conditions to test the dependence of MPDI to precipitation; 2) comparisons of MPDI categorized into instantly before, during and immediately after selected precipitation events to examine the impact of modest-to-heavy precipitation on the spatial pattern of MPDI; 3) inspections of relationship between MPDI versus rain fraction and rain rate within the satellite sensors FOV to investigate the behaviors of MPDI in varying precipitation conditions; 4) analysis of discrepancies of MPDI over 10.65, 19.35, 37 and 85.8 GHz to identify the sensitivity of MPDS to microwave wavelengths.

Co-culture of Adult Mesenchymal Stem Cells and Nucleus Pulposus Cells in Bilaminar Pellets for Intervertebral Disc Regeneration.

PubMed

Allon, Aliza A; Schneider, Richard A; Lotz, Jeffrey C

2009-01-01

Our goal is to optimize stem cell-based tissue engineering strategies in the context of the intervertebral disc environment. We explored the benefits of co-culturing nucleus pulposus cells (NPC) and adult mesenchymal stem cells (MSC) using a novel spherical bilaminar pellet culture system where one cell type is enclosed in a sphere of the other cell type. Our 3D system provides a structure that exploits embryonic processes such as tissue induction and condensation. We observed a unique phenomenon: the budding of co-culture pellets and the formation of satellite pellets that separate from the main pellet. MSC and NPC co-culture pellets were formed with three different structural organizations. The first had random organization. The other two had bilaminar organization with either MSC inside and NPC outside or NPC inside and MSC outside. By 14 days, all co-culture pellets exhibited budding and spontaneously generated satellite pellets. The satellite pellets were composed of both cell types and, surprisingly, all had the same bilaminar organization with MSC on the inside and NPC on the outside. This organization was independent of the structure of the main pellet that the satellites stemmed from. The main pellets generated satellite pellets that spontaneously organized into a bilaminar structure. This implies that structural organization occurs naturally in this cell culture system and may be inherently favorable for cell-based tissue engineering strategies. The occurrence of budding and the organization of satellite pellets may have important implications for the use of co-culture pellets in cell-based therapies for disc regeneration. From a therapeutic point of view, the generation of satellite pellets may be a beneficial feature that would serve to spread donor cells throughout the host matrix and restore normal matrix composition in a sustainable way, ultimately renewing tissue function.

Satellite Images Analysis of Temporal Change (1979-2000) of the Mangrove Covertures that Surround the Mandinga Coastal Lagoon, Mexico.

NASA Astrophysics Data System (ADS)

Aldeco-Ramírez, J.; Cervantes-Candelas, A.

2007-05-01

Knowledge about the historical condition of the resources and the risk of natural hazards is an urgent necessity in developing countries. Satellite images analysis was applied in this study in order to evaluate coverture changes between 1979 and 2000. Mangroves cover large areas of coastal lagoon shoreline in the tropics and subtropics where they are important components in the productivity and integrity of their ecosystems. Visual and digital analysis of satellite images have been applied since the seventies when the first Land sat satellite was put in orbit. The digital analysis technique is mainly based on the reflectance or spectral response of the different objects laid on the earth surface as captured by the satellite. The results are useful for the environmental assessment of natural resources as forest and crops, and the quantification of hazards as fires, plagues, deforestation and urban expansion. This research surveys satellite images from the Mandinga Lagoon System, a coastal lagoon located to the south of the main port of Veracruz (19.1N, 96.1W), during three periods: 1989 1999 and 2000. The mangrove foliar cover was analyzed throughout the time. The reflectance signal of the mangrove that encircles the lagoon was taken as a base line for reference. The normalized difference vegetation index (NDVI) was computed in order to classify the vegetal coverage along the time. From our analysis we obtained that from 1979 to 1990 and from 1990 to 2000 areas of 122 hectares (approx. 305 acres) and 202 hectares (approx. 505 acres) were lost, respectively. The rates of mangrove trimming of 11.1 and 20.2 hectares yr-1 are high compared with other coastal lagoons of Mexico. The main causes of this deforestation are also discussed along with other factors as, the change of use of land and the fishery declination.

High-resolution near real-time drought monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

NASA Astrophysics Data System (ADS)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

New-Generation BeiDou (BDS-3) Experimental Satellite Precise Orbit Determination with an Improved Cycle-Slip Detection and Repair Algorithm

PubMed Central

Hu, Chao; Wang, Qianxin; Wang, Zhongyuan; Hernández Moraleda, Alberto

2018-01-01

Currently, five new-generation BeiDou (BDS-3) experimental satellites are working in orbit and broadcast B1I, B3I, and other new signals. Precise satellite orbit determination of the BDS-3 is essential for the future global services of the BeiDou system. However, BDS-3 experimental satellites are mainly tracked by the international GNSS Monitoring and Assessment Service (iGMAS) network. Under the current constraints of the limited data sources and poor data quality of iGMAS, this study proposes an improved cycle-slip detection and repair algorithm, which is based on a polynomial prediction of ionospheric delays. The improved algorithm takes the correlation of ionospheric delays into consideration to accurately estimate and repair cycle slips in the iGMAS data. Moreover, two methods of BDS-3 experimental satellite orbit determination, namely, normal equation stacking (NES) and step-by-step (SS), are designed to strengthen orbit estimations and to make full use of the BeiDou observations in different tracking networks. In addition, a method to improve computational efficiency based on a matrix eigenvalue decomposition algorithm is derived in the NES. Then, one-year of BDS-3 experimental satellite precise orbit determinations were conducted based on iGMAS and Multi-GNSS Experiment (MGEX) networks. Furthermore, the orbit accuracies were analyzed from the discrepancy of overlapping arcs and satellite laser range (SLR) residuals. The results showed that the average three-dimensional root-mean-square error (3D RMS) of one-day overlapping arcs for BDS-3 experimental satellites (C31, C32, C33, and C34) acquired by NES and SS are 31.0, 36.0, 40.3, and 50.1 cm, and 34.6, 39.4, 43.4, and 55.5 cm, respectively; the RMS of SLR residuals are 55.1, 49.6, 61.5, and 70.9 cm and 60.5, 53.6, 65.8, and 73.9 cm, respectively. Finally, one month of observations were used in four schemes of BDS-3 experimental satellite orbit determination to further investigate the reliability and advantages of the improved methods. It was suggested that the scheme with improved cycle-slip detection and repair algorithm based on NES was optimal, which improved the accuracy of BDS-3 experimental satellite orbits by 34.07%, 41.05%, 72.29%, and 74.33%, respectively, compared with the widely-used strategy. Therefore, improved methods for the BDS-3 experimental satellites proposed in this study are very beneficial for the determination of new-generation BeiDou satellite precise orbits. PMID:29724062

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Callie

2005-01-01

Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970s. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is employed in this study, due to its abundance of coastal habitats and its vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated from multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

Techniques for Producing Coastal Land Water Masks from Landsat and Other Multispectral Satellite Data

NASA Technical Reports Server (NTRS)

Spruce, Joe; Hall, Callie

2005-01-01

Coastal erosion and land loss continue to threaten many areas in the United States. Landsat data has been used to monitor regional coastal change since the 1970's. Many techniques can be used to produce coastal land water masks, including image classification and density slicing of individual bands or of band ratios. Band ratios used in land water detection include several variations of the Normalized Difference Water Index (NDWI). This poster discusses a study that compares land water masks computed from unsupervised Landsat image classification with masks from density-sliced band ratios and from the Landsat TM band 5. The greater New Orleans area is imployed in this study, due to its abundance of coastal habitats and ist vulnerability to coastal land loss. Image classification produced the best results based on visual comparison to higher resolution satellite and aerial image displays. However, density-sliced NDWI imagery from either near infrared (NIR) and blue bands or from NIR and green bands also produced more effective land water masks than imagery from the density-sliced Landsat TM band 5. NDWI based on NIR and green bands is noteworthy because it allows land water masks to be generated form multispectral satellite sensors without a blue band (e.g., ASTER and Landsat MSS). NDWI techniques also have potential for producing land water masks from coarser scaled satellite data, such as MODIS.

Skeletal Myogenic Progenitors Originating from Embryonic Dorsal Aorta Coexpress Endothelial and Myogenic Markers and Contribute to Postnatal Muscle Growth and Regeneration

PubMed Central

De Angelis, Luciana; Berghella, Libera; Coletta, Marcello; Lattanzi, Laura; Zanchi, Malvina; Gabriella, M.; Ponzetto, Carola; Cossu, Giulio

1999-01-01

Skeletal muscle in vertebrates is derived from somites, epithelial structures of the paraxial mesoderm, yet many unrelated reports describe the occasional appearance of myogenic cells from tissues of nonsomite origin, suggesting either transdifferentiation or the persistence of a multipotent progenitor. Here, we show that clonable skeletal myogenic cells are present in the embryonic dorsal aorta of mouse embryos. This finding is based on a detailed clonal analysis of different tissue anlagen at various developmental stages. In vitro, these myogenic cells show the same morphology as satellite cells derived from adult skeletal muscle, and express a number of myogenic and endothelial markers. Surprisingly, the latter are also expressed by adult satellite cells. Furthermore, it is possible to clone myogenic cells from limbs of mutant c-Met−/− embryos, which lack appendicular muscles, but have a normal vascular system. Upon transplantation, aorta-derived myogenic cells participate in postnatal muscle growth and regeneration, and fuse with resident satellite cells. The potential of the vascular system to generate skeletal muscle cells may explain observations of nonsomite skeletal myogenesis and raises the possibility that a subset of satellite cells may derive from the vascular system. PMID:10562287

Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

NASA Astrophysics Data System (ADS)

Liu, Z.; Shie, C. L.; Meyer, D. J.

2017-12-01

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

Describing the spatio-temporal variability of vines and soil by satellite-based spectral indices: A case study in Apulia (South Italy)

NASA Astrophysics Data System (ADS)

Borgogno-Mondino, E.; Novello, V.; Lessio, A.; de Palma, L.

2018-06-01

A time series of Landsat 8 OLI (L8 OLI) multispectral images acquired between May 2013 and February 2016 were used to investigate vigour, vine and soil water content in a vineyard of Moscato Reale (syn. Moscato Bianco) sited in the Castel del Monte DOCG area. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated and compared with vine midday stem water potential (ΨMDstem) and soil volume water content (VWC), to calibrate estimation models. Estimation models were calibrated using already existing ground observation datasets from previous ordinary vineyard management operations: ΨMDstem was measured at two different locations in vineyard at 6 different dates in summer 2014; VWC was continuously measured from June to October 2014 and from January to September 2015. Results showed that: a) vine stem water potential can be locally estimated with an accuracy ranging from ±0.046 (high vigour vines) to ±0.127 (low vigour vines) MPa; b) soil volume water content can be locally estimated with an accuracy of about ±1.7%. Medium resolution satellite imagery proved, therefore, to be effective, at vineyard level, to describe vigour, vine and soil water status and their seasonality. This is an important issue to focus on since, as Landsat 8 images are free, the entire process is economic enough to be consistent with cost and incoming of the farming system.

Estimating Net Primary Productivity Using Satellite and Ancillary Data

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Houser, Paul (Technical Monitor)

2001-01-01

The net primary productivity (C) or annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of the rate of gross photosynthesis (A(sub g)) and autotrophic respiration (R) per unit ground area. Although available observations show that R is a large and variable fraction of A(sub g), viz., 0.3 to 0.7, it is generally recognized that much uncertainties exist in this fraction due to difficulties associated with the needed measurements. Additional uncertainties arise when these measurements are extrapolated to regional or global land surface using empirical equations, for example, using regression equations relating C to mean annual precipitation and air temperature. Here, a process-based approach has been taken to calculate A(sub g) and R using satellite and ancillary data. A(sub g) has been expressed as a product of radiation use efficiency, magnitude of intercepted photosynthetically active radiation (PAR), and normalized by stresses due to soil water shortage and air temperature away from the optimum range. A biophysical model has been used to determine the radiation use efficiency from the maximum rate of carbon assimilation by a leaf, foliage temperature, and the fraction of diffuse PAR incident on a canopy. All meteorological data (PAR, air temperature, precipitation, etc.) needed for the calculation are derived from satellite observations, while a land use, land cover data (based on satellite and ground measurements) have been used to assess the maximum rate of carbon assimilation by a leaf of varied cover type based on field measurements. R has been calculated as the sum of maintenance and growth components. The maintenance respiration of foliage and live fine roots at a standard temperature of different land cover has been determined from their nitrogen content using field and satellite measurements, while that of living fraction of woody stem (viz., sapwood) from the seasonal maximum leaf area index as determined from satellite observations. These maintenance respiration values were then adjusted to that corresponding to air temperature according to a prescribed non-linear variation of respiration with temperature. The growth respiration has been calculated from the difference of Ag and maintenance respiration, according to the two-compartment model. The results of calculations will be reported for 36 consecutive months (1987-1989) over large contiguous areas (ca. 10(exp 5) sq km) Of agricultural land and tropical humid evergreen forests, and compared with available field data.

Robust and brilliant Raman tags based on core-satellite assemblies for brain tumor cell imaging

NASA Astrophysics Data System (ADS)

Chang, Yung-Ching; Huang, Li-Ching; Sun, Wei-Lun; Chuang, Shih Yi; Lin, Tien-Hsin; Wu, Yi-Syuan; Sze, Chun-I.; Chen, Shiuan-Yeh

2018-02-01

GBM (Glioblastoma Multiforme), a fatal brain tumor, is highly infiltrative and difficult to be completely removed by the surgery. In this work, the Raman tags based on the plasmonic core-satellite assemblies with 1 nm internal gap accompanied by extremely high gap field have been fabricated and applied to GBM cell labeling. The brightness of the Raman tags is comparable to the fluorophores. The GBM cells with overexpression of EGFR are labeled with these Raman tags and can be distinguished from the normal cells through Raman imaging.

Edge Response and NIIRS Estimates for Commercial Remote Sensing Satellites

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Ryan, Robert E.; Pagnutti, mary; Stanley, Thomas

2006-01-01

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Basic research and data analysis for the National Geodetic Satellite program and for the Earth Surveys program

NASA Technical Reports Server (NTRS)

1972-01-01

Current research is reported on precise and accurate descriptions of the earth's surface and gravitational field and on time variations of geophysical parameters. A new computer program was written in connection with the adjustment of the BC-4 worldwide geometric satellite triangulation net. The possibility that an increment to accuracy could be transferred from a super-control net to the basic geodetic (first-order triangulation) was investigated. Coordinates of the NA9 solution were computed and were transformed to the NAD datum, based on GEOS 1 observations. Normal equations from observational data of several different systems and constraint equations were added and a single solution was obtained for the combined systems. Transformation parameters with constraints were determined, and the impact of computers on surveying and mapping is discussed.

Reconciling Satellite-Derived Atmospheric Properties with Fine-Resolution Land Imagery: Insights for Atmospheric Correction

NASA Technical Reports Server (NTRS)

Zelazowski, Przemyslaw; Sayer, Andrew M.; Thomas, Gareth E; Grainger, Roy G.

2011-01-01

This paper investigates to what extent satellite measurements of atmospheric properties can be reconciled with fine-resolution land imagery, in order to improve the estimates of surface reflectance through physically based atmospheric correction. The analysis deals with mountainous area (Landsat scene of Peruvian Amazon/Andes, 72 E and 13 S), where the atmosphere is highly variable. Data from satellite sensors were used for characterization of the key atmospheric constituents: total water vapor (TWV), aerosol optical depth (AOD), and total ozone. Constituent time series revealed the season-dependent mean state of the atmosphere and its variability. Discrepancies between AOD from the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS) highlighted substantial uncertainty of atmospheric aerosol properties. The distribution of TWV and AOD over a Landsat scene was found to be exponentially related to ground elevation (mean R(sup 2) of 0.82 and 0.29, respectively). In consequence, the atmosphere-induced and seasonally varying bias of the top-of-atmosphere signal was also elevation dependent (e.g., mean Normalized Difference Vegetation Index bias at 500 m was 0.06 and at 4000 m was 0.01). We demonstrate that satellite measurements of key atmospheric constituents can be downscaled and gap filled with the proposed "background + anomalies" approach, to allow for a better compatibility with fine-resolution land surface imagery. Older images (i.e., predating the MODIS/ATSR era), without coincident atmospheric data, can be corrected using climatologies derived from time series of satellite retrievals. Averaging such climatologies over space compromises the quality of correction result to a much greater degree than averaging them over time. We conclude that the quality of both recent and older fine-resolution land surface imagery can be improved with satellite-based atmospheric data acquired to date.

The relationship between wind vector and normalized radar cross section used to derive Seasat-A Satellite Scatterometer winds

NASA Technical Reports Server (NTRS)

Schroeder, L. C.; Jones, W. L.; Boggs, D. H.; Halberstam, I. M.; Dome, G.; Pierson, W. J.; Wentz, F. J.

1982-01-01

The Seasat-A Satellite Scatterometer (SASS) ocean normalized radar cross section (NRCS) dependence on the 19.5-m neutral stability wind vector may be specified as a function of radar incidence angle, the angle between wind direction and radar azimuth, and the neutral stability wind speed expressed in m/sec at a height of 19.5 m. An account is given of the development of models both expressing this relationship and providing the basis of inversion of NRCS to SASS winds, from initially aircraft scatterometer measurement-based forms to three Seasat field-validation experiments which furnish model NRCS versus surface windspeed data for comparison with SASS data.

Estimation of chlorophyll-a concentration on an inland lake by using satellite data.

NASA Astrophysics Data System (ADS)

Iwata, T.

2017-12-01

Chlorophyll concentration is common as an index of water quality and phytoplankton activity in coastal areas and lake water. In this research, we propose a method to estimate chlorophyll-a distribution of lake surface by using satellite data. The satellite data used is the sea surface reflectance of 3 channels of band-9, -10, and -12 by MODIS/Aqua MYDOCGA data provided by NASA/EOSDIS, and its data resolution is spatially 1 km and temporally 1 day. As index for estimating chlorophyll-a from reflection intensity, four indices of two types are proposed and comparatively analyzed. One of the two types is the ratio of the reflectance of the visible green light band (Gr) to the one of the visible blue light band (Bl), and the other index is obtained by normalizing difference of the reflectance between two bands. The two types of indices are expressed as follows. * Band ratio (BR) = Gr / Bl * Normalized difference (ND) = (Gr-Bl) / (Gr+Bl) As the visible blue light band, band-9 (438-448 nm) and band-10 (483-493 nm) were used. The four indices are represented as BR9, BR10, ND9, and ND10. The Lake Biwa in Japan is selected as the test area to be analyzed. At the Lake, temperature and the chlorophyll-a concentration around the lake center are periodically measured every month, and data is published. From April 2011 to December 2015, correlation analysis was done using 29 data on which the water measurement date and the valid satellite data acquisition date coincided ( Fig.1 and 2 ). Based on the analysis, the following two formulas were shown as models that can successfully express surface chlorophyll-a concentration. * Chl-a [μg/L] = 6.11×BR10 - 2.61 * Chl-a [μg/L] = 32.6×ND102 + 10.2×ND10 + 3.24

Estimation of the rice-planting field in Bangladesh by satellite remote sensing

NASA Astrophysics Data System (ADS)

Furuta, E.; Suzuki, G.; Yamassaki, M.; Teraoka, T.; Fujiwara, H.; Ogino, Y.; Akashi, M.; Lahrita, L.; Naruse, N.; Takahashi, Y.

2016-12-01

In Bangladesh, price of rice has been unstable due to a large increase in production. To control the price can become a political issue, because rice agriculture is one of the most important industries in Bangladesh, whereas the total area of the paddy field is accurately unknown, owing to unsustainable and on-site surveys for the area (1). Satellite remote sensing is an effective solution to research the all area of domestic paddy field. Microwave satellite imaging has a large merit to be observable regardless of the weather conditions, however, research institutions have been limited to observing continuously since the cost is high for developing countries, such as Bangladesh. This study aims to establish the way to grasp the paddy field using optical satellite images for free of charge (Landsat-8). We have focused on seasonal changes in the water and the vegetation indices obtained from paddy fields. We have performed image calculations of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) of the well-known paddy field in Bangladesh Rice Research Institute. We found that there are seasonal changes of NDVI and NDWI calculated from paddy field. The characteristics are as follows; the NDVI and the NDWI values varies by 0.17-0.25 up and 0.11-0.19 down, respectively, at the transition from the dry to the rainy season, on the other hand, the NDVI and the NDWI changes by 0.21-0.29 down and 0.09-0.17 up from the rainy to the dry season. These features make us to distinguish the paddy field from the other cultivated area. The decrease of NDVI means that rice bares, The increase of NDWI can be interpreted that the paddy field is covered with water for the preparation for planting it. Our estimated area of paddy field in Bangladesh (85,900km ) corresponds well with the previous reported value of 117,700km (1). We have established the way to grasp the paddy field using optical satellite images for free of charge, on the bases of the seasonal changes of NDVI and NDWI. Ref: 1.FAOSTAT 2013

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2012-01-01

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2011-01-01

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, we evaluated the impact of sensor degradation on trend detection using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004/yr decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends MODIS NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.

Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

NASA Astrophysics Data System (ADS)

Pan, Xin; Cao, Chen; Yang, Yingbao; Li, Xiaolong; Shan, Liangliang; Zhu, Xi

2018-04-01

The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of +/-0.02 predictor perturbances, respectively.

Quasistationary areas of NDVI trend dynamics is a powerful research tool for studying spatial patterns of land vegetation

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Larko, Aleksandr

The most important task for humankind is to study and understand global processes on Earth. Large factual material on the dynamics of the optical spectral characteristics of the land surface has been accumulated in recent decades. This has been only made possible due to the use of satellite information. The development of satellite measurement technologies and new methods for pre-processing and interpretation of satellite data allowed the research adequate to the scale of the Earth. This adequacy includes the compliance of scale terrestrial objects to the scale of satellite measurements. Research is not limited by any latitude or longitude of the objects studied. The second most important quality is the adequacy of the technologies used to velocities of processes on Earth. This is enabled by long-term continuous satellite measurements at almost all latitudes. Effectiveness of this approach to the study of natural systems has been shown by the authors in ASR publications (AP Shevyrnogov, GS Vysotskaya, JI Gitelson, Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996), which reported a method for determining the ocean surface quasistationary zones. This approach allowed us to identify different types of phytopigment dynamics and the hydrological structure of the ocean. We proposed a similar approach for the study of land vegetation. In some aspects, it is similar to the previously published approach, despite the different nature of terrestrial and aquatic ecosystems. The results are based on the processing of satellite data from 1981 to 2006. Dynamics is the most interesting and important parameter of ecosystems, especially their trends. Therefore, it has been chosen for the analysis of spatial patterns of plant biota. The first results showed great heterogeneity of variances in nonlinear trends of the study areas of the Earth's surface. They corresponded to different natural systems. Various scales of temporal and spatial windows highlight different features of land vegetation. Methods for normalization of the initial information are also effective for highlighting the features of the spatial structure of vegetation. Thus, we have a powerful tool to analyze the spatial distribution and dynamics of terrestrial vegetation based on satellite data. This approach provides a great opportunity to get fundamental knowledge on the functioning of the biosphere. This is global warming, shifts in permafrost boundaries, global gas exchange, etc. It can be used for practical applications in various fields of human activity: forestry, environmental protection, agriculture, etc. We show the illustration of this method: the global maps of land surface dynamics of trends with different parameters of data processing.

Recovery of atmospheric refractivity profiles from simulated satellite-to-satellite tracking data

NASA Technical Reports Server (NTRS)

Murray, C. W., Jr.; Rangaswamy, S.

1975-01-01

Techniques for recovering atmospheric refractivity profiles from simulated satellite-to-satellite tracking data are documented. Examples are given using the geometric configuration of the ATS-6/NIMBUS-6 Tracking Experiment. The underlying refractivity model for the lower atmosphere has the spherically symmetric form N = exp P(s) where P(s) is a polynomial in the normalized height s. For the simulation used, the Herglotz-Wiechert technique recovered values which were 0.4% and 40% different from the input values at the surface and at a height of 33 kilometers, respectively. Using the same input data, the model fitting technique recovered refractivity values 0.05% and 1% different from the input values at the surface and at a height of 50 kilometers, respectively. It is also shown that if ionospheric and water vapor effects can be properly modelled or effectively removed from the data, pressure and temperature distributions can be obtained.

Investigation the Behavior of Modis Ocean Color Products Under the 2008 Red Tide in the Eastern Persian Gulf

NASA Astrophysics Data System (ADS)

Ghanea, M.; Moradi, M.; Kabiri, K.

2015-12-01

Biophysical properties of water undergo serious variations under red tide (RT) outbreak. During RT conditions, algal blooms spread out in the estuarine, marine and fresh waters due to different triggering factors such as nutrient loading, marine currents, and monsoonal winds. The Persian Gulf (PG) was a talent region subjected to different RTs in recent decade. A massive RT started from the Strait of Hormuz in October 2008 and extended towards the northern parts of the PG covering more than 1200 km of coastlines. The bloom of microorganism C. Polykrikoides was the main specie that generated large fish mortalities, and hampered marine industries, and water desalination appliances. Ocean color satellite data have many advantages to monitor and alarm RT occurrences, such as wide and continuous extent, short time of imagery, high accessibility, and appropriate estimation of ocean color parameters. Since 1999, MODerate Resolution Imaging Spectroradiometer (MODIS) satellite sensor has estimated satellite derived chlorophyll-a (Chl-a), normalized fluorescence line height (nFLH), and diffuse attenuation coefficient at 490nm (kd490). It provides a capability to study the behavior of these parameters during RT and normal conditions. This study monitors variations in satellite derived Chl-a, nFLH, and kd490 under both RT and normal conditions of the PG between 2002 and 2008. Up to now, daily and monthly variations in these products were no synchronously investigated under RT conditions in the PG. In doing so, the MODIS L1B products were provided from NASA data archive. They were corrected for Rayleigh scattering and gaseous absorption, and atmospheric interference in turbid coastal waters, and then converted to level 2 data. In addition, Enhanced Red Green Blue (ERGB) image was used to illustrate better water variations. ERGB image was built with three normalized leaving water radiance between 443 to 560nm. All the above data processes were applied by SeaDAS 7 software package. The Strait of Hormuz was selected as the study area in the eastern part of the PG. Images including high cloud coverage (>50%) over the study area were filtered out. The classification maps of the above products were shown during RT and normal periods. Monthly variations of mentioned products were calculated for the dates before, during, and after RT appearance. The results were demonstrated as time-series diagrams. All the above calculations and presentations were performed in Matlab 7 software package. The results show that MODIS Chl-a, nFLH, and kd490 increased during the 2008 RT. Based on the feedback of these parameters under RT conditions, hybrid ocean color index (HOCI) is defined. HOCI is able to display better water variations during RT outbreak. High values of HOCI show RT affected areas.

Cross Correlation versus Normalized Mutual Information on Image Registration

NASA Technical Reports Server (NTRS)

Tan, Bin; Tilton, James C.; Lin, Guoqing

2016-01-01

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

IMS/Satellite Situation Center report: Orbit plots and bar charts for Prognoz 4, days 1-91 1976

NASA Technical Reports Server (NTRS)

1976-01-01

Orbit plots for the Prognoz 4 satellite for the time period January to March 1976 are given. This satellite was identified as a possible important contributor to the International Magnetospheric Study project. The orbits were based on an element epoch of December 26, 1975, 3h 8min and 17s. In view of the low perigee of this satellite, the Satellite Situation Center (SSC) considered that the effect of atmospheric drag precludes orbit predictions for the length of time normally used by the SSC for high-altitude satellites. Consequently, orbit data are shown for the first 3 months of 1976 only. The orbit generated for this report was based on the earlier epoch, and it positions the satellite within 30s of the ascending node at the later epoch. Therefore, within the accuracy of the plots shown in this report, the orbit used was regarded as an achieved orbit. The orbit information is displayed graphically in four ways: bar charts, geocentric solar ecliptic plots, boundary plots, and solar magnetic latitude versus local time plots. The most concise presentation is the bar charts. The bar charts give the crude three-dimensional position of the satellite for each magnetospheric region.

Exploratory normalized difference water indices for semi-automated extraction of Antarctic lake features

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Luis, Alvarinho J.

2016-05-01

This work presents various normalized difference water indices (NDWI) to delineate lakes from Schirmacher Oasis, East Antarctica, by using a very high resolution WorldView-2 (WV-2) satellite imagery. Schirmacher oasis region hosts a number of fresh as well as saline water lakes, such as epishelf lakes, ice-free or landlocked lakes, which are completely frozen or semi-frozen and in a ice-free state. Hence, detecting all these types of lakes distinctly on satellite imagery was the major challenge, as the spectral characteristics of various types of lakes were identical to the other land cover targets. Multiband spectral index pixel-based approach is most experimented and recently growing technique because of its unbeatable advantages such as its simplicity and comparatively lesser amount of processing-time. In present study, semiautomatic extraction of lakes in cryospheric region was carried out by designing specific spectral indices. The study utilized number of existing spectral indices to extract lakes but none could deliver satisfactory results and hence we modified NDWI. The potentials of newly added bands in WV-2 satellite imagery was explored by developing spectral indices comprising of Yellow (585 - 625 nm) band, in combination with Blue (450 - 510 nm), Coastal (400 - 450 nm) and Green (510 - 580 nm) bands. For extraction of frozen lakes, use of Yellow (585 - 625 nm) and near-infrared 2 (NIR2) band pair, and Yellow and Green band pair worked well, whereas for ice-free lakes extraction, a combination of Blue and Coastal band yielded appreciable results, when compared with manually digitized data. The results suggest that the modified NDWI approach rendered bias error varying from 1 to 34 m2.

Investigation and Comparison between New Satellite Impact Test Results and NASA Standard Breakup Model

NASA Technical Reports Server (NTRS)

Sakuraba, K.; Tsuruda, Y.; Hanada, T.; Liou, J.-C.; Akahoshi, Y.

2007-01-01

This paper summarizes two new satellite impact tests conducted in order to investigate on the outcome of low- and hyper-velocity impacts on two identical target satellites. The first experiment was performed at a low velocity of 1.5 km/s using a 40-gram aluminum alloy sphere, whereas the second experiment was performed at a hyper-velocity of 4.4 km/s using a 4-gram aluminum alloy sphere by two-stage light gas gun in Kyushu Institute of Technology. To date, approximately 1,500 fragments from each impact test have been collected for detailed analysis. Each piece was analyzed based on the method used in the NASA Standard Breakup Model 2000 revision. The detailed analysis will conclude: 1) the similarity in mass distribution of fragments between low and hyper-velocity impacts encourages the development of a general-purpose distribution model applicable for a wide impact velocity range, and 2) the difference in area-to-mass ratio distribution between the impact experiments and the NASA standard breakup model suggests to describe the area-to-mass ratio by a bi-normal distribution.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods

NASA Astrophysics Data System (ADS)

Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.

2017-12-01

Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).

Development of a nitric oxide-releasing analogue of the muscle relaxant guaifenesin for skeletal muscle satellite cell myogenesis.

PubMed

Wang, Guqi; Burczynski, Frank J; Hasinoff, Brian B; Zhang, Kaidong; Lu, Qilong; Anderson, Judy E

2009-01-01

Nitric oxide (NO) mediates activation of satellite precursor cells to enter the cell cycle. This provides new precursor cells for skeletal muscle growth and muscle repair from injury or disease. Targeting a new drug that specifically delivers NO to muscle has the potential to promote normal function and treat neuromuscular disease, and would also help to avoid side effects of NO from other treatment modalities. In this research, we examined the effectiveness of the NO donor, iosorbide dinitrate (ISDN), and a muscle relaxant, methocarbamol, in promoting satellite cell activation assayed by muscle cell DNA synthesis in normal adult mice. The work led to the development of guaifenesin dinitrate (GDN) as a new NO donor for delivering nitric oxide to muscle. The results revealed that there was a strong increase in muscle satellite cell activation and proliferation, demonstrated by a significant 38% rise in DNA synthesis after a single transdermal treatment with the new compound for 24 h. Western blot and immunohistochemistry analyses showed that the markers of satellite cell myogenesis, expression of myf5, myogenin, and follistatin, were increased after 24 h oral administration of the compound in adult mice. This research extends our understanding of the outcomes of NO-based treatments aimed at promoting muscle regeneration in normal tissue. The potential use of such treatment for conditions such as muscle atrophy in disuse and aging, and for the promotion of muscle tissue repair as required after injury or in neuromuscular diseases such as muscular dystrophy, is highlighted.

Development of monitoring method of coffee leaf rust fungus (Hemileia vastatrix) infected area using satellite remote sensing

NASA Astrophysics Data System (ADS)

Katsuhama, N.; Ikeda, K.; Imai, M.; Watanabe, K.; Marpaung, F.; Yoshii, T.; Naruse, N.; Takahashi, Y.

2016-12-01

Since 2008, coffee leaf rust fungus (Hemileia vastatrix) has expanded its infection in Latin America, and early trimming and burning infected trees have been only effective countermeasures to prevent spreading infection. Although some researchers reported a case about the monitoring of coffee leaf rust using satellite remote sensing in 1970s, the spatial resolution was unsatisfied, and therefore, further technological development has been required. The purpose of this research is to develop effective method of discovering coffee leaf rust infected areas using satellite remote sensing. Annual changes of vegetation indices, i.e. Normalized Difference Vegetation Index (NDVI) and Modified Structure Insensitive Pigment Index (MSIPI), around Cuchumatanes Mountains, Republic of Guatemala, were analyzed by Landsat 7 images. Study fields in the research were limited by the coffee farm areas based on a previous paper about on site surveys in different damage areas. As the result of the analysis, the annual change of NDVI at the coffee farm areas with damages tended to be lower than those without damages. Moreover, the decline of NDVI appear from 2008 before the damage was reported. On the other hand, the change of MSIPI had no significant difference. NDVI and MSIPI are mainly related to the amount of chlorophyll and carotenoid in the leaves respectively. This means that the infected coffee leaves turned yellow without defoliation. This situation well matches the symptom of coffee leaf rust. The research concluded that the property of infected leaves turning yellow is effective to monitoring of infection areas by satellite remote sensing.

From Order to Chaos in Earth Satellite Orbits

NASA Astrophysics Data System (ADS)

Gkolias, Ioannis; Daquin, Jérôme; Gachet, Fabien; Rosengren, Aaron J.

2016-11-01

We consider Earth satellite orbits in the range of semimajor axes where the perturbing effects of Earth’s oblateness and lunisolar gravity are of comparable order. This range covers the medium-Earth orbits (MEO) of the Global Navigation Satellite Systems and the geosynchronous orbits (GEO) of the communication satellites. We recall a secular and quadrupolar model, based on the Milankovitch vector formulation of perturbation theory, which governs the long-term orbital evolution subject to the predominant gravitational interactions. We study the global dynamics of this two-and-a-half degrees-of-freedom Hamiltonian system by means of the fast Lyapunov indicator (FLI), used in a statistical sense. Specifically, we characterize the degree of chaoticity of the action space using angle-averaged normalized FLI maps, thereby overcoming the angle dependencies of the conventional stability maps. Emphasis is placed upon the phase-space structures near secular resonances, which are of primary importance to the space debris community. We confirm and quantify the transition from order to chaos in MEO, stemming from the critical inclinations and find that highly inclined GEO orbits are particularly unstable. Despite their reputed normality, Earth satellite orbits can possess an extraordinarily rich spectrum of dynamical behaviors and, from a mathematical perspective, have all the complications that make them very interesting candidates for testing the modern tools of chaos theory.

High-Resolution Near Real-Time Drought Monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

Assessment of Ionospheric Gradient Impacts on Ground-Based Augmentation System (GBAS) Data in Guangdong Province, China

PubMed Central

Wang, Zhipeng; Wang, Shujing; Zhu, Yanbo; Xin, Pumin

2017-01-01

Ionospheric delay is one of the largest and most variable sources of error for Ground-Based Augmentation System (GBAS) users because inospheric activity is unpredictable. Under normal conditions, GBAS eliminates ionospheric delays, but during extreme ionospheric storms, GBAS users and GBAS ground facilities may experience different ionospheric delays, leading to considerable differential errors and threatening the safety of users. Therefore, ionospheric monitoring and assessment are important parts of GBAS integrity monitoring. To study the effects of the ionosphere on the GBAS of Guangdong Province, China, GPS data collected from 65 reference stations were processed using the improved “Simple Truth” algorithm. In addition, the ionospheric characteristics of Guangdong Province were calculated and an ionospheric threat model was established. Finally, we evaluated the influence of the standard deviation and maximum ionospheric gradient on GBAS. The results show that, under normal ionospheric conditions, the vertical protection level of GBAS was increased by 0.8 m for the largest over bound σvig (sigma of vertical ionospheric gradient), and in the case of the maximum ionospheric gradient conditions, the differential correction error may reach 5 m. From an airworthiness perspective, when the satellite is at a low elevation, this interference does not cause airworthiness risks, but when the satellite is at a high elevation, this interference can cause airworthiness risks. PMID:29019953

Assessment of Ionospheric Gradient Impacts on Ground-Based Augmentation System (GBAS) Data in Guangdong Province, China.

PubMed

Wang, Zhipeng; Wang, Shujing; Zhu, Yanbo; Xin, Pumin

2017-10-11

Ionospheric delay is one of the largest and most variable sources of error for Ground-Based Augmentation System (GBAS) users because inospheric activity is unpredictable. Under normal conditions, GBAS eliminates ionospheric delays, but during extreme ionospheric storms, GBAS users and GBAS ground facilities may experience different ionospheric delays, leading to considerable differential errors and threatening the safety of users. Therefore, ionospheric monitoring and assessment are important parts of GBAS integrity monitoring. To study the effects of the ionosphere on the GBAS of Guangdong Province, China, GPS data collected from 65 reference stations were processed using the improved "Simple Truth" algorithm. In addition, the ionospheric characteristics of Guangdong Province were calculated and an ionospheric threat model was established. Finally, we evaluated the influence of the standard deviation and maximum ionospheric gradient on GBAS. The results show that, under normal ionospheric conditions, the vertical protection level of GBAS was increased by 0.8 m for the largest over bound σ v i g (sigma of vertical ionospheric gradient), and in the case of the maximum ionospheric gradient conditions, the differential correction error may reach 5 m. From an airworthiness perspective, when the satellite is at a low elevation, this interference does not cause airworthiness risks, but when the satellite is at a high elevation, this interference can cause airworthiness risks.

Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

NASA Astrophysics Data System (ADS)

Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

Estimation of Subpixel Snow-Covered Area by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Kuter, S.; Akyürek, Z.; Weber, G.-W.

2016-10-01

Measurement of the areal extent of snow cover with high accuracy plays an important role in hydrological and climate modeling. Remotely-sensed data acquired by earth-observing satellites offer great advantages for timely monitoring of snow cover. However, the main obstacle is the tradeoff between temporal and spatial resolution of satellite imageries. Soft or subpixel classification of low or moderate resolution satellite images is a preferred technique to overcome this problem. The most frequently employed snow cover fraction methods applied on Moderate Resolution Imaging Spectroradiometer (MODIS) data have evolved from spectral unmixing and empirical Normalized Difference Snow Index (NDSI) methods to latest machine learning-based artificial neural networks (ANNs). This study demonstrates the implementation of subpixel snow-covered area estimation based on the state-of-the-art nonparametric spline regression method, namely, Multivariate Adaptive Regression Splines (MARS). MARS models were trained by using MODIS top of atmospheric reflectance values of bands 1-7 as predictor variables. Reference percentage snow cover maps were generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also employed to estimate the percentage snow-covered area on the same data set. The results indicated that the developed MARS model performed better than th

Electrophysiological evidence of doubly innervated branched muscle fibers in the human brachioradialis muscle.

PubMed

Lateva, Zoia C; McGill, Kevin C

2007-12-01

Motor-unit action potentials (MUAPs) with unstable satellite (late-latency) components are found in EMG signals from the brachioradialis muscles of normal subjects. We analyzed the morphology and blocking behavior of these MUAPs to determine their anatomical origin. EMG signals were recorded from the brachioradialis muscles of 5 normal subjects during moderate-level isometric contractions. MUAP waveforms, discharge patterns, and blocking were determined using computer-aided EMG decomposition. Twelve MUAPs with unstable satellite potentials were detected, always two together in the same signal. Each MUAP also had a second unstable component associated with its main spike. The blocking behavior of the unstable components depended on how close together the two MUAPs were when they discharged. The latencies and blocking behavior indicate that the unstable components came from branched muscle fibers innervated by two different motoneurons. The satellite potentials were due to action potentials that traveled to the branching point along one branch and back along the other. The blockings were due to action-potential collisions when both motoneurons discharged close together in time. Animal studies suggest that branched muscle fibers may be a normal characteristic of series-fibered muscles. This study adds to our understanding of these muscles in humans.

Remotely-sensed detection of effects of extreme droughts on gross primary production.

PubMed

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-06-15

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

NASA Technical Reports Server (NTRS)

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

Aerosol-Cloud Interaction Determined by Both in Situ and Satellite Data Over a Northern High-Latitude Site

NASA Technical Reports Server (NTRS)

Lihavainen, H.; Kerminen, V.-M.; Remer, L. A.

2009-01-01

The first aerosol indirect effect over a clean, northern high-latitude site was investigated by determining the aerosol cloud interaction (ACI) using three different approaches; ground-based in situ measurements, combined ground-based in situ measurements 5 and satellite retrievals and using only satellite retrievals. The obtained values of ACI were highest for in situ ground-based data, clearly lower for combined ground-based and satellite data, and lowest for data relying solely on satellite retrievals. One of the key findings of this study was the high sensitivity of ACI to the definition of the aerosol burden. We showed that at least a part of the variability in ACI can be explained by 10 how different investigators have related dierent cloud properties to "aerosol burden".

APPLYING SATELLITE IMAGERY TO TRIAGE ASSESSMENT OF ECOSYSTEM HEALTH

EPA Science Inventory

Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR)imagery to develop calibration patterns of change in the Normalized Difference Vegetation Ind...

Improving the RST Approach for Earthquake Prone Areas Monitoring: Results of Correlation Analysis among Significant Sequences of TIR Anomalies and Earthquakes (M>4) occurred in Italy during 2004-2014

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Coviello, I.; Filizzola, C.; Genzano, N.; Lisi, M.; Paciello, R.; Pergola, N.

2015-12-01

Looking toward the assessment of a multi-parametric system for dynamically updating seismic hazard estimates and earthquake short term (from days to weeks) forecast, a preliminary step is to identify those parameters (chemical, physical, biological, etc.) whose anomalous variations can be, to some extent, associated to the complex process of preparation of a big earthquake. Among the different parameters, the fluctuations of Earth's thermally emitted radiation, as measured by sensors on board of satellite system operating in the Thermal Infra-Red (TIR) spectral range, have been proposed since long time as potential earthquake precursors. Since 2001, a general approach called Robust Satellite Techniques (RST) has been used to discriminate anomalous thermal signals, possibly associated to seismic activity from normal fluctuations of Earth's thermal emission related to other causes (e.g. meteorological) independent on the earthquake occurrence. Thanks to its full exportability on different satellite packages, RST has been implemented on TIR images acquired by polar (e.g. NOAA-AVHRR, EOS-MODIS) and geostationary (e.g. MSG-SEVIRI, NOAA-GOES/W, GMS-5/VISSR) satellite sensors, in order to verify the presence (or absence) of TIR anomalies in presence (absence) of earthquakes (with M>4) in different seismogenic areas around the world (e.g. Italy, Turkey, Greece, California, Taiwan, etc.).In this paper, a refined RST (Robust Satellite Techniques) data analysis approach and RETIRA (Robust Estimator of TIR Anomalies) index were used to identify Significant Sequences of TIR Anomalies (SSTAs) during eleven years (from May 2004 to December 2014) of TIR satellite records, collected over Italy by the geostationary satellite sensor MSG-SEVIRI. On the basis of specific validation rules (mainly based on physical models and results obtained by applying RST approach to several earthquakes all around the world) the level of space-time correlation among SSTAs and earthquakes (with M≥4) occurrence has been evaluated. Achieved results will be discussed, also in the framework of a multi-parametric approach to time-Dependent Assessment of Seismic Hazard (t-DASH).

Model improvements and validation of TerraSAR-X precise orbit determination

NASA Astrophysics Data System (ADS)

Hackel, S.; Montenbruck, O.; Steigenberger, P.; Balss, U.; Gisinger, C.; Eineder, M.

2017-05-01

The radar imaging satellite mission TerraSAR-X requires precisely determined satellite orbits for validating geodetic remote sensing techniques. Since the achieved quality of the operationally derived, reduced-dynamic (RD) orbit solutions limits the capabilities of the synthetic aperture radar (SAR) validation, an effort is made to improve the estimated orbit solutions. This paper discusses the benefits of refined dynamical models on orbit accuracy as well as estimated empirical accelerations and compares different dynamic models in a RD orbit determination. Modeling aspects discussed in the paper include the use of a macro-model for drag and radiation pressure computation, the use of high-quality atmospheric density and wind models as well as the benefit of high-fidelity gravity and ocean tide models. The Sun-synchronous dusk-dawn orbit geometry of TerraSAR-X results in a particular high correlation of solar radiation pressure modeling and estimated normal-direction positions. Furthermore, this mission offers a unique suite of independent sensors for orbit validation. Several parameters serve as quality indicators for the estimated satellite orbit solutions. These include the magnitude of the estimated empirical accelerations, satellite laser ranging (SLR) residuals, and SLR-based orbit corrections. Moreover, the radargrammetric distance measurements of the SAR instrument are selected for assessing the quality of the orbit solutions and compared to the SLR analysis. The use of high-fidelity satellite dynamics models in the RD approach is shown to clearly improve the orbit quality compared to simplified models and loosely constrained empirical accelerations. The estimated empirical accelerations are substantially reduced by 30% in tangential direction when working with the refined dynamical models. Likewise the SLR residuals are reduced from -3 ± 17 to 2 ± 13 mm, and the SLR-derived normal-direction position corrections are reduced from 15 to 6 mm, obtained from the 2012-2014 period. The radar range bias is reduced from -10.3 to -6.1 mm with the updated orbit solutions, which coincides with the reduced standard deviation of the SLR residuals. The improvements are mainly driven by the satellite macro-model for the purpose of solar radiation pressure modeling, improved atmospheric density models, and the use of state-of-the-art gravity field models.

Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between MODIS and 30 Other Satellite Sensors Using Rice Canopy Spectra

PubMed Central

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-01-01

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red reflectance, −8.52% to −0.23% for the NIR reflectance, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors. PMID:24287529

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

PubMed

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-11-26

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors.

Satellite Image-based Estimates of Snow Water Equivalence in Restored Ponderosa Pine Forests in Northern Arizona

NASA Astrophysics Data System (ADS)

Sankey, T.; Springer, A. E.; O'Donnell, F. C.; Donald, J.; McVay, J.; Masek Lopez, S.

2014-12-01

The U.S. Forest Service plans to conduct forest restoration treatments through the Four Forest Restoration Initiative (4FRI) on hundreds of thousands of acres of ponderosa pine forest in northern Arizona over the next 20 years with the goals of reducing wildfire hazard and improving forest health. The 4FRI's key objective is to thin and burn the forests to create within-stand openings that "promote snowpack accumulation and retention which benefit groundwater recharge and watershed processes at the fine (1 to 10 acres) scale". However, little is known about how these openings created by restoration treatments affect snow water equivalence (SWE) and soil moisture, which are key parts of the water balance that greatly influence water availability for healthy trees and for downstream water users in the Sonoran Desert. We have examined forest canopy cover by calculating a Normalized Difference Vegetation Index (NDVI), a key indicator of green vegetation cover, using Landsat satellite data. We have then compared NDVI between treatments at our study sites in northern Arizona and have found statistically significant differences in tree canopy cover between treatments. The control units have significantly greater forest canopy cover than the treated units. The thinned units also have significantly greater tree canopy cover than the thin-and-burn units. Winter season Landsat images have also been analyzed to calculate Normalized Difference Snow Index (NDSI), a key indicator of snow water equivalence and snow accumulation at the treated and untreated forests. The NDSI values from these dates are examined to determine if snow accumulation and snow water equivalence vary between treatments at our study sites. NDSI is significantly greater at the treated units than the control units. In particular, the thinned forest units have significantly greater snow cover than the control units. Our results indicate that forest restoration treatments result in increased snow pack accumulation and this increase can be efficiently estimated at a landscape scale using satellite data.

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

Quaternion normalization in additive EKF for spacecraft attitude determination

NASA Technical Reports Server (NTRS)

Bar-Itzhack, I. Y.; Deutschmann, J.; Markley, F. L.

1991-01-01

This work introduces, examines, and compares several quaternion normalization algorithms, which are shown to be an effective stage in the application of the additive extended Kalman filter (EKF) to spacecraft attitude determination, which is based on vector measurements. Two new normalization schemes are introduced. They are compared with one another and with the known brute force normalization scheme, and their efficiency is examined. Simulated satellite data are used to demonstrate the performance of all three schemes. A fourth scheme is suggested for future research. Although the schemes were tested for spacecraft attitude determination, the conclusions are general and hold for attitude determination of any three dimensional body when based on vector measurements, and use an additive EKF for estimation, and the quaternion for specifying the attitude.

The use of lidar for stratospheric measurements

NASA Technical Reports Server (NTRS)

Mccormick, M. P.

1977-01-01

Stratospheric measurements possible with ground-based, airborne, and satellite-borne lidar systems are reviewed. The instruments, basic equations, and formats normally used for various scattering and absorption phenomena measurements are presented including a discussion of elastic, resonance, Raman, and fluorescence scattering techniques.

3D-information fusion from very high resolution satellite sensors

NASA Astrophysics Data System (ADS)

Krauss, T.; d'Angelo, P.; Kuschk, G.; Tian, J.; Partovi, T.

2015-04-01

In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl'eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.

Global validation of empirically corrected EP-Total Ozone Mapping Spectrometer (TOMS) total ozone columns using Brewer and Dobson ground-based measurements

NASA Astrophysics Data System (ADS)

Antón, M.; Koukouli, M. E.; Kroon, M.; McPeters, R. D.; Labow, G. J.; Balis, D.; Serrano, A.

2010-10-01

This article focuses on the global-scale validation of the empirically corrected Version 8 total ozone column data set acquired by the NASA Total Ozone Mapping Spectrometer (TOMS) during the period 1996-2004 when this instrument was flying aboard the Earth Probe (EP) satellite platform. This analysis is based on the use of spatially co-located, ground-based measurements from Dobson and Brewer spectrophotometers. The original EP-TOMS V8 total ozone column data set was also validated with these ground-based measurements to quantify the improvements made by the empirical correction that was necessary as a result of instrumental degradation issues occurring from the year 2000 onward that were uncorrectable by normal calibration techniques. EP-TOMS V8-corrected total ozone data present a remarkable improvement concerning the significant negative bias of around ˜3% detected in the original EP-TOMS V8 observations after the year 2000. Neither the original nor the corrected EP-TOMS satellite total ozone data sets show a significant dependence on latitude. In addition, both EP-TOMS satellite data sets overestimate the Brewer measurements for small solar zenith angles (SZA) and underestimate for large SZA, explaining a significant seasonality (˜1.5%) for cloud-free and cloudy conditions. Conversely, relative differences between EP-TOMS and Dobson present almost no dependence on SZA for cloud-free conditions and a strong dependence for cloudy conditions (from +2% for small SZA to -1% for high SZA). The dependence of the satellite ground-based relative differences on total ozone shows good agreement for column values above 250 Dobson units. Our main conclusion is that the upgrade to TOMS V8-corrected total ozone data presents a remarkable improvement. Nevertheless, despite its quality, the EP-TOMS data for the period 2000-2004 should not be used as a source for trend analysis since EP-TOMS ozone trends are empirically corrected using NOAA-16 and NOAA-17 solar backscatter ultraviolet/2 data as external references, and therefore, they are no longer considered as independent observations.

Satellite Vegetation Index Data as a Tool to Forecast Population Dynamics of Medically Important Mosquitoes at Military Installations in the Continental United States

DTIC Science & Technology

2008-07-01

for the two installations. We obtained monthly North American normalized differ- ence vegetation index ( NDVI ) satellite climate data sets for 1981-2005...from the Goddard Space Flight Center."*-" The NDVI measures the greenness of the earth, capturing in one index the combined effects of temperature...humidity, insola- tion, elevation, soils, land use. and precipitation on vegeta- tion. There is an almost-linear relationship between NDVI values and

Cross Calibration of TOMS, SBUV/2 and SCIAMACHY Radiances from Ground Observations

NASA Technical Reports Server (NTRS)

Hilsenrath, Ernest; Bhartia, P. K.; Bojkov, B.; Kowaleski, M.; Labow, G.; Ahmad, Z.

2002-01-01

We have shown that validation of radiances is a very effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called 'Skyrad', employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS, SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOMEZ, OMI, and OMPS. Additional information is included in the original extended abstract.

FROM ORDER TO CHAOS IN EARTH SATELLITE ORBITS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gkolias, Ioannis; Gachet, Fabien; Daquin, Jérôme

We consider Earth satellite orbits in the range of semimajor axes where the perturbing effects of Earth’s oblateness and lunisolar gravity are of comparable order. This range covers the medium-Earth orbits (MEO) of the Global Navigation Satellite Systems and the geosynchronous orbits (GEO) of the communication satellites. We recall a secular and quadrupolar model, based on the Milankovitch vector formulation of perturbation theory, which governs the long-term orbital evolution subject to the predominant gravitational interactions. We study the global dynamics of this two-and-a-half degrees-of-freedom Hamiltonian system by means of the fast Lyapunov indicator (FLI), used in a statistical sense. Specifically,more » we characterize the degree of chaoticity of the action space using angle-averaged normalized FLI maps, thereby overcoming the angle dependencies of the conventional stability maps. Emphasis is placed upon the phase-space structures near secular resonances, which are of primary importance to the space debris community. We confirm and quantify the transition from order to chaos in MEO, stemming from the critical inclinations and find that highly inclined GEO orbits are particularly unstable. Despite their reputed normality, Earth satellite orbits can possess an extraordinarily rich spectrum of dynamical behaviors and, from a mathematical perspective, have all the complications that make them very interesting candidates for testing the modern tools of chaos theory.« less

Validating an operational physical method to compute surface radiation from geostationary satellites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Manajit; Dhere, Neelkanth G.; Wohlgemuth, John H.

We developed models to compute global horizontal irradiance (GHI) and direct normal irradiance (DNI) over the last three decades. These models can be classified as empirical or physical based on the approach. Empirical models relate ground-based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the physics behind the radiation received at the satellite and create retrievals to estimate surface radiation. Furthermore, while empirical methods have been traditionally used for computing surface radiation for the solar energy industry, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Projectmore » (GSIP) is a physical model that computes DNI and GHI using the visible and infrared channel measurements from a weather satellite. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate GHI and DNI. Developed for polar orbiting satellites, GSIP has been adapted to NOAA's Geostationary Operation Environmental Satellite series and can run operationally at high spatial resolutions. Our method holds the possibility of creating high quality datasets of GHI and DNI for use by the solar energy industry. We present an outline of the methodology and results from running the model as well as a validation study using ground-based instruments.« less

Comparison and Analysis of Accuracy of Elevation Extraction Based on the ZY-3 01 and 02 Satellites Stereoscopic Images

NASA Astrophysics Data System (ADS)

Zhao, L.; Fu, X.; Dou, X.; Liu, H.; Fang, Z.

2018-04-01

The ZY-3 is the civil high-resolution optical stereoscopic mapping satellite independently developed by China. The ZY-3 constellation of the twin satellites operates in a sun-synchronous, near-polar, circular 505 km orbit, with a descending location time of 10:30 AM and a 29-day revisiting period. The panchromatic triplet sensors, pointing forward, nadir, and backward with an angle of 22°, have excellent base-to-height ratio, which is beneficial to the extraction of DEM. In order to extract more detailed and highprecision DEM, the ZY-3 (02) satellite has been upgraded based on the ZY-3 (01), and the GSD of the stereo camera has been optimized from 3.5 to 2.5 meters. In the paper case studies using the ZY-3 01 and the 02 satellite data for block adjustment and DEM extraction have been carried out in Liaoning Province of China. The results show that the planimetric and altimetric accuracy can reach 3 meters, which meet the mapping requirements of 1 : 50,000 national topographic map and the design performance of the satellites. The normalized elevation accuracy index (NEAI) is adopted to evaluate the twin satellite stereoscopic performance, and the NEAIs of the twin ZY-3 satellites are good and the index of the ZY-3(02) is slightly better. The comparison of the overlapping DEMs from the twin ZY-3 satellites and SRTM is analysed. The bias and the standard deviation of all the DEMs are better than 5 meters. In addition, in the process of accuracy comparison, some gross errors of the DEM can be identified, and some elevation changes of the DEM can also be found. The differential DEM becomes a new tool and application.

USE OF REMOTELY SENSED DATA FOR PARAMETERIZING AND VALIDATING LAND-USE HYDROLOGIC MODELS

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA satellites. NDVI variability was compared with regi...

Petrologic model of the northern Mississippi Embayment based on satellite magnetic and ground-based geophysical data

NASA Technical Reports Server (NTRS)

Thomas, H. H.

1984-01-01

A petrologic model of the northern Mississippi Embayment, derived from gravity, seismic and rift data, is evaluated by converting the model to a magnetization model which is compared with satellite magnetic anomaly models. A magnetization contrast of approximately -0.54 A/m, determined from the petrologic model of the embayment compares favorably to values of -0.62 A/m and -0.45 A/m from a Magsat United States Apparent Magnetization Contrast Map and a published POGO magnetization contrast model, respectively. The petrologic model suggests that the magnetic anomaly low associated with the Mississippi Embayment may be largely due to the intrusion under non-oxidizing conditions of low Curie temperature gabbroic material at the base of the crust of the embayment. Near-surface mafic plutons, bordering the Mississippi Valley Graben, appear from aeromagnetic data to have higher magnetizations than the deeper gabbroic material; however, it is impossible to ascertain if this is due to compositional differences or similar material at shallower (lower temperature) depths. These results indicate that variations in the Curie temperatures of intrusions accompanying rifting may account for a large part of the wide range of magnetic anomalies associated with presently inactive rifts with normal heat flow.

Interactive visualization of vegetation dynamics

USGS Publications Warehouse

Reed, B.C.; Swets, D.; Bard, L.; Brown, J.; Rowland, James

2001-01-01

Satellite imagery provides a mechanism for observing seasonal dynamics of the landscape that have implications for near real-time monitoring of agriculture, forest, and range resources. This study illustrates a technique for visualizing timely information on key events during the growing season (e.g., onset, peak, duration, and end of growing season), as well as the status of the current growing season with respect to the recent historical average. Using time-series analysis of normalized difference vegetation index (NDVI) data from the advanced very high resolution radiometer (AVHRR) satellite sensor, seasonal dynamics can be derived. We have developed a set of Java-based visualization and analysis tools to make comparisons between the seasonal dynamics of the current year with those from the past twelve years. In addition, the visualization tools allow the user to query underlying databases such as land cover or administrative boundaries to analyze the seasonal dynamics of areas of their own interest. The Java-based tools (data exploration and visualization analysis or DEVA) use a Web-based client-server model for processing the data. The resulting visualization and analysis, available via the Internet, is of value to those responsible for land management decisions, resource allocation, and at-risk population targeting.

A spectral water index based on visual bands

NASA Astrophysics Data System (ADS)

Basaeed, Essa; Bhaskar, Harish; Al-Mualla, Mohammed

2013-10-01

Land-water segmentation is an important preprocessing step in a number of remote sensing applications such as target detection, environmental monitoring, and map updating. A Normalized Optical Water Index (NOWI) is proposed to accurately discriminate between land and water regions in multi-spectral satellite imagery data from DubaiSat-1. NOWI exploits the spectral characteristics of water content (using visible bands) and uses a non-linear normalization procedure that renders strong emphasize on small changes in lower brightness values whilst guaranteeing that the segmentation process remains image-independent. The NOWI representation is validated through systematic experiments, evaluated using robust metrics, and compared against various supervised classification algorithms. Analysis has indicated that NOWI has the advantages that it: a) is a pixel-based method that requires no global knowledge of the scene under investigation, b) can be easily implemented in parallel processing, c) is image-independent and requires no training, d) works in different environmental conditions, e) provides high accuracy and efficiency, and f) works directly on the input image without any form of pre-processing.

The impact of customer-contractor interactions on spacecraft innovation: Insights from communication satellite history

NASA Astrophysics Data System (ADS)

Szajnfarber, Zoe; Stringfellow, Margaret V.; Weigel, Annalisa L.

2010-11-01

This paper captures a first detailed attempt to quantitatively analyze the innovation history of the space sector. Building on a communication satellite innovation metric and a spacecraft innovation framework developed as part of an ongoing project, this paper presents a preliminary model of global communication satellite innovation. In addition to innovation being a function of the rate of performance normalized by price, innovation was found to be strongly influenced by characteristics of the customer-contractor contractual relationship. Specifically, Department of Defense contracts tend to result in a lower level of innovation on average as compared to other customers. Also, particular customer-contractor pairs perform differently and exhibit a second order relationship in time.

An Accurate Absorption-Based Net Primary Production Model for the Global Ocean

NASA Astrophysics Data System (ADS)

Silsbe, G.; Westberry, T. K.; Behrenfeld, M. J.; Halsey, K.; Milligan, A.

2016-02-01

As a vital living link in the global carbon cycle, understanding how net primary production (NPP) varies through space, time, and across climatic oscillations (e.g. ENSO) is a key objective in oceanographic research. The continual improvement of ocean observing satellites and data analytics now present greater opportunities for advanced understanding and characterization of the factors regulating NPP. In particular, the emergence of spectral inversion algorithms now permits accurate retrievals of the phytoplankton absorption coefficient (aΦ) from space. As NPP is the efficiency in which absorbed energy is converted into carbon biomass, aΦ measurements circumvents chlorophyll-based empirical approaches by permitting direct and accurate measurements of phytoplankton energy absorption. It has long been recognized, and perhaps underappreciated, that NPP and phytoplankton growth rates display muted variability when normalized to aΦ rather than chlorophyll. Here we present a novel absorption-based NPP model that parameterizes the underlying physiological mechanisms behind this muted variability, and apply this physiological model to the global ocean. Through a comparison against field data from the Hawaii and Bermuda Ocean Time Series, we demonstrate how this approach yields more accurate NPP measurements than other published NPP models. By normalizing NPP to satellite estimates of phytoplankton carbon biomass, this presentation also explores the seasonality of phytoplankton growth rates across several oceanic regions. Finally, we discuss how future advances in remote-sensing (e.g. hyperspectral satellites, LIDAR, autonomous profilers) can be exploited to further improve absorption-based NPP models.

Remotely-sensed detection of effects of extreme droughts on gross primary production

PubMed Central

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-01-01

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671

Normal Faulting at the Western Margin of the Altiplano Plateau, Southern Peru

NASA Astrophysics Data System (ADS)

Schildgen, T. F.; Hodges, K. V.; Whipple, K. X.; Perignon, M.; Smith, T. M.

2004-12-01

Although the western margin of the Altiplano Plateau is commonly used to illustrate the marked differences in the evolution of a mountain range with strong latitudinal and longitudinal precipitation gradients, the nature of tectonism in this semi-arid region is poorly understood and much debated. The western margin of the Altiplano in southern Peru and northern Chile marks an abrupt transition from the forearc region of the Andes to the high topography of the Cordillera Occidental. This transition has been interpreted by most workers as a monocline, with modifications due to thrust faulting, normal faulting, and gravity slides. Based on recent fieldwork and satellite image analysis, we suggest that, at least in the semi-arid climate of southern Peru, this transition has been the locus of significant high-angle normal faulting related to the block uplift of the Cordillera Occidental. We have focused our initial work in the vicinity of 15\\deg S latitude, 71\\deg W longitude, where the range front crosses Colca Canyon, a major antecedent drainage northwest of Arequipa. In that area, Oligocene to Miocene sediments of the Moquegua Formation, which were eroded from uplifted terrain to the northeast, presently dip to the northeast at angles between 2 and 10º. Field observations of a normal fault contact between the Moquegua sedimentary rocks and Jurassic basement rocks, as well as 15-m resolution 3-D images generated from ASTER satellite imagery, show that the Moquegua units are down-dropped to the west across a steeply SW-dipping normal fault of regional significance. Morphology of the range front throughout southern Peru suggests that normal faulting along the range front has characterized the recent tectonic history of the region. We present geochronological data to constrain the timing of movement both directly from the fault zone as well as indirectly from canyon incision that likely responded to fault movement.

Probabilistic drought intensification forecasts using temporal patterns of satellite-derived drought indicators

NASA Astrophysics Data System (ADS)

Park, Sumin; Im, Jungho; Park, Seonyeong

2016-04-01

A drought occurs when the condition of below-average precipitation in a region continues, resulting in prolonged water deficiency. A drought can last for weeks, months or even years, so can have a great influence on various ecosystems including human society. In order to effectively reduce agricultural and economic damage caused by droughts, drought monitoring and forecasts are crucial. Drought forecast research is typically conducted using in situ observations (or derived indices such as Standardized Precipitation Index (SPI)) and physical models. Recently, satellite remote sensing has been used for short term drought forecasts in combination with physical models. In this research, drought intensification was predicted using satellite-derived drought indices such as Normalized Difference Drought Index (NDDI), Normalized Multi-band Drought Index (NMDI), and Scaled Drought Condition Index (SDCI) generated from Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) products over the Korean Peninsula. Time series of each drought index at the 8 day interval was investigated to identify drought intensification patterns. Drought condition at the previous time step (i.e., 8 days before) and change in drought conditions between two previous time steps (e.g., between 16 days and 8 days before the time step to forecast) Results show that among three drought indices, SDCI provided the best performance to predict drought intensification compared to NDDI and NMDI through qualitative assessment. When quantitatively compared with SPI, SDCI showed a potential to be used for forecasting short term drought intensification. Finally this research provided a SDCI-based equation to predict short term drought intensification optimized over the Korean Peninsula.

Object-based landslide mapping on satellite images from different sensors

NASA Astrophysics Data System (ADS)

Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

2015-04-01

Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be transferred to the different satellite images. The presence of bare ground was assumed to be an evidence for the occurrence of landslides. For separating vegetated from non-vegetated areas the Normalized Difference Vegetation Index (NDVI) was primarily used. Each image was divided into two respective parts based on an automatically calculated NDVI threshold value in eCognition (Trimble) software by combining the homogeneity criterion of multiresolution segmentation and histogram-based methods, so that heterogeneity is increased to a maximum. Expert knowledge models, which depict features and thresholds that are usually used by experts for digital landslide mapping, were considered for refining the classification. The results were compared to the respective results from visual image interpretation (i.e. manually digitized reference polygons for each image), which were produced by an independent local expert. By that, the spatial overlaps as well as under- and over-estimated areas were identified and the performance of the approach in relation to each sensor was evaluated. The presented method can complement traditional manual mapping efforts. Moreover, it contributes to current developments for increasing the transferability of semi-automated OBIA approaches and for improving the efficiency of change detection approaches across multi-sensor imagery.

Satellite-derived land covers for runoff estimation using SCS-CN method in Chen-You-Lan Watershed, Taiwan

NASA Astrophysics Data System (ADS)

Zhang, Wen-Yan; Lin, Chao-Yuan

2017-04-01

The Soil Conservation Service Curve Number (SCS-CN) method, which was originally developed by the USDA Natural Resources Conservation Service, is widely used to estimate direct runoff volume from rainfall. The runoff Curve Number (CN) parameter is based on the hydrologic soil group and land use factors. In Taiwan, the national land use maps were interpreted from aerial photos in 1995 and 2008. Rapid updating of post-disaster land use map is limited due to the high cost of production, so the classification of satellite images is the alternative method to obtain the land use map. In this study, Normalized Difference Vegetation Index (NDVI) in Chen-You-Lan Watershed was derived from dry and wet season of Landsat imageries during 2003 - 2008. Land covers were interpreted from mean value and standard deviation of NDVI and were categorized into 4 groups i.e. forest, grassland, agriculture and bare land. Then, the runoff volume of typhoon events during 2005 - 2009 were estimated using SCS-CN method and verified with the measured runoff data. The result showed that the model efficiency coefficient is 90.77%. Therefore, estimating runoff by using the land cover map classified from satellite images is practicable.

Coastline detection with time series of SAR images

NASA Astrophysics Data System (ADS)

Ao, Dongyang; Dumitru, Octavian; Schwarz, Gottfried; Datcu, Mihai

2017-10-01

For maritime remote sensing, coastline detection is a vital task. With continuous coastline detection results from satellite image time series, the actual shoreline, the sea level, and environmental parameters can be observed to support coastal management and disaster warning. Established coastline detection methods are often based on SAR images and wellknown image processing approaches. These methods involve a lot of complicated data processing, which is a big challenge for remote sensing time series. Additionally, a number of SAR satellites operating with polarimetric capabilities have been launched in recent years, and many investigations of target characteristics in radar polarization have been performed. In this paper, a fast and efficient coastline detection method is proposed which comprises three steps. First, we calculate a modified correlation coefficient of two SAR images of different polarization. This coefficient differs from the traditional computation where normalization is needed. Through this modified approach, the separation between sea and land becomes more prominent. Second, we set a histogram-based threshold to distinguish between sea and land within the given image. The histogram is derived from the statistical distribution of the polarized SAR image pixel amplitudes. Third, we extract continuous coastlines using a Canny image edge detector that is rather immune to speckle noise. Finally, the individual coastlines derived from time series of .SAR images can be checked for changes.

A Five-Year Analysis of MODIS NDVI and NDWI for Rangeland Drought Assessment: Preliminary Results

NASA Astrophysics Data System (ADS)

Gu, Y.; Brown, J. F.; Verdin, J. P.; Wardlow, B.

2006-12-01

Drought is one of the most costly natural disasters in the United States. Traditionally, drought monitoring has been based on weather station observations, which lack the continuous spatial coverage needed to adequately characterize and monitor detailed spatial patterns of drought conditions. Satellite remote sensing observations can provide a synoptic view of the land and provide a spatial context for measuring drought. A common satellite-based index, the normalized difference vegetation index (NDVI) has a 30-year history of use for vegetation condition monitoring. NDVI is calculated from the visible red and near infrared channels and measures the changes in chlorophyll absorption and reflection in the spongy mesophyll of the vegetation canopy that are reflected in these respective bands. The normalized difference water index (NDWI) is another index, derived from the near-infrared and short wave infrared channels, and reflects changes in both the water content and spongy mesophyll in the vegetation canopy. As a result, the NDWI is influenced by both desiccation and wilting in the vegetation canopy and may be a more sensitive indicator than the NDVI for large- area drought monitoring. The objective of this study was to process and evaluate a 5-year history of 500-meter NDVI and NDWI data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument and to investigate methods for measuring and monitoring drought in rangeland over the southern plains of the United States. This initial study included: (1) the development of a climatological database for MODIS NDVI and NDWI, (2) a study of the relationship between the NDVI, NDWI, and drought condition over rangeland, (3) the development of a method to provide threshold NDVI/NDWI values under drought conditions based on the 5-year NDVI/NDWI/drought condition analysis, and (4) the investigation of additional vegetation drought information provided by the NDWI versus the NDVI in a 5-year comparison of the two indices. The MODIS data were obtained from the Land Processes Distributed Active Archive System. Results show strong relationships among NDVI, NDWI, and drought analyzed over grasslands in the Flint Hills region of Kansas and Oklahoma. During the summer months, the average NDVI and NDWI values were consistently lower (NDVI<0.5 and NDWI<0.3) for the tallgrass prairie under drought conditions than under normal climate conditions (NDVI>0.6 and NDWI>0.4). The distinctions between drought conditions and normal climate conditions are based on the historic U.S. Drought Monitor maps and the historic Palmer index data. To take advantage of information contained in both indices, we calculated the difference between NDVI and NDWI (NDVI-NDWI). The difference between NDVI and NDWI slightly increases during the summer drought condition. Based on these analyses, the NDWI appears to be more sensitive than NDVI to drought conditions. The results of statistical analysis of the relationships among these indices will be presented in the poster.

Crop classification using temporal stacks of multispectral satellite imagery

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Brumby, Steven P.; Chartrand, Rick; Keisler, Ryan; Longbotham, Nathan; Mertes, Carly; Skillman, Samuel W.; Warren, Michael S.

2017-05-01

The increase in performance, availability, and coverage of multispectral satellite sensor constellations has led to a drastic increase in data volume and data rate. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. The data analysis capability, however, has lagged behind storage and compute developments, and has traditionally focused on individual scene processing. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and can scale with the high-rate and dimensionality of imagery being collected. We investigate and compare the performance of pixel-level crop identification using tree-based classifiers and its dependence on both temporal and spectral features. Classification performance is assessed using as ground-truth Cropland Data Layer (CDL) crop masks generated by the US Department of Agriculture (USDA). The CDL maps contain 30m spatial resolution, pixel-level labels for around 200 categories of land cover, but are however only available post-growing season. The analysis focuses on McCook county in South Dakota and shows crop classification using a temporal stack of Landsat 8 (L8) imagery over the growing season, from April through October. Specifically, we consider the temporal L8 stack depth, as well as different normalized band difference indices, and evaluate their contribution to crop identification. We also show an extension of our algorithm to map corn and soy crops in the state of Mato Grosso, Brazil.

Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi

2016-03-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.

Land surface temperature distribution and development for green open space in Medan city using imagery-based satellite Landsat 8

NASA Astrophysics Data System (ADS)

Sulistiyono, N.; Basyuni, M.; Slamet, B.

2018-03-01

Green open space (GOS) is one of the requirements where a city is comfortable to stay. GOS might reduce land surface temperature (LST) and air pollution. Medan is one of the biggest towns in Indonesia that experienced rapid development. However, the early development tends to neglect the GOS existence for the city. The objective of the study is to determine the distribution of land surface temperature and the relationship between the normalized difference vegetation index (NDVI) and the priority of GOS development in Medan City using imagery-based satellite Landsat 8. The method approached to correlate the distribution of land surface temperature derived from the value of digital number band 10 with the NDVI which was from the ratio of groups five and four on satellite images of Landsat 8. The results showed that the distribution of land surface temperature in the Medan City in 2016 ranged 20.57 - 33.83 °C. The relationship between the distribution of LST distribution with NDVI was reversed with a negative correlation of -0.543 (sig 0,000). The direction of GOS in Medan City is therefore developed on the allocation of LST and divided into three priority classes namely first priority class had 5,119.71 ha, the second priority consisted of 16,935.76 ha, and third priority of 6,118.50 ha.

The celestial mechanics approach: application to data of the GRACE mission

NASA Astrophysics Data System (ADS)

Beutler, Gerhard; Jäggi, Adrian; Mervart, Leoš; Meyer, Ulrich

2010-11-01

The celestial mechanics approach (CMA) has its roots in the Bernese GPS software and was extensively used for determining the orbits of high-orbiting satellites. The CMA was extended to determine the orbits of Low Earth Orbiting satellites (LEOs) equipped with GPS receivers and of constellations of LEOs equipped in addition with inter-satellite links. In recent years the CMA was further developed and used for gravity field determination. The CMA was developed by the Astronomical Institute of the University of Bern (AIUB). The CMA is presented from the theoretical perspective in (Beutler et al. 2010). The key elements of the CMA are illustrated here using data from 50 days of GPS, K-Band, and accelerometer observations gathered by the Gravity Recovery And Climate Experiment (GRACE) mission in 2007. We study in particular the impact of (1) analyzing different observables [Global Positioning System (GPS) observations only, inter-satellite measurements only], (2) analyzing a combination of observations of different types on the level of the normal equation systems (NEQs), (3) using accelerometer data, (4) different orbit parametrizations (short-arc, reduced-dynamic) by imposing different constraints on the stochastic orbit parameters, and (5) using either the inter-satellite ranges or their time derivatives. The so-called GRACE baseline, i.e., the achievable accuracy of the GRACE gravity field for a particular solution strategy, is established for the CMA.

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

One-dimensional nonlinear instability study of a slightly viscoelastic, perfectly conducting liquid jet under a radial electric field

NASA Astrophysics Data System (ADS)

Li, Fang; Yin, Xie-Yuan; Yin, Xie-Zhen

2016-05-01

A one-dimensional electrified viscoelastic model is built to study the nonlinear behavior of a slightly viscoelastic, perfectly conducting liquid jet under a radial electric field. The equations are solved numerically using an implicit finite difference scheme together with a boundary element method. The electrified viscoelastic jet is found to evolve into a beads-on-string structure in the presence of the radial electric field. Although the radial electric field greatly enhances the linear instability of the jet, its influence on the decay of the filament thickness is limited during the nonlinear evolution of the jet. On the other hand, the radial electric field induces axial non-uniformity of the first normal stress difference within the filament. The first normal stress difference in the center region of the filament may be greatly decreased by the radial electric field. The regions with/without satellite droplets are illuminated on the χ (the electrical Bond number)-k (the dimensionless wave number) plane. Satellite droplets may be formed for larger wave numbers at larger radial electric fields.

Normalized GNSS Interference Pattern Technique for Altimetry

PubMed Central

Ribot, Miguel Angel; Kucwaj, Jean-Christophe; Botteron, Cyril; Reboul, Serge; Stienne, Georges; Leclère, Jérôme; Choquel, Jean-Bernard; Farine, Pierre-André; Benjelloun, Mohammed

2014-01-01

It is well known that reflected signals from Global Navigation Satellite Systems (GNSS) can be used for altimetry applications, such as monitoring of water levels and determining snow height. Due to the interference of these reflected signals and the motion of satellites in space, the signal-to-noise ratio (SNR) measured at the receiver slowly oscillates. The oscillation rate is proportional to the change in the propagation path difference between the direct and reflected signals, which depends on the satellite elevation angle. Assuming a known receiver position, it is possible to compute the distance between the antenna and the surface of reflection from the measured oscillation rate. This technique is usually known as the interference pattern technique (IPT). In this paper, we propose to normalize the measurements in order to derive an alternative model of the SNR variations. From this model, we define a maximum likelihood estimate of the antenna height that reduces the estimation time to a fraction of one period of the SNR variation. We also derive the Cramér–Rao lower bound for the IPT and use it to assess the sensitivity of different parameters to the estimation of the antenna height. Finally, we propose an experimental framework, and we use it to assess our approach with real GPS L1 C/A signals. PMID:24922453

Angular motion equations for a satellite with hinged flexible solar panel

NASA Astrophysics Data System (ADS)

Ovchinnikov, M. Yu.; Tkachev, S. S.; Roldugin, D. S.; Nuralieva, A. B.; Mashtakov, Y. V.

2016-11-01

Non-linear mathematical model for the satellite with hinged flexible solar panel is presented. Normal modes of flexible elements are used for motion description. Motion equations are derived using virtual work principle. A comparison of normal modes calculation between finite element method and developed model is presented.

Ocean Heat Content Reveals Secrets of Fish Migrations

PubMed Central

Luo, Jiangang; Ault, Jerald S.; Shay, Lynn K.; Hoolihan, John P.; Prince, Eric D.; Brown, Craig A.; Rooker, Jay R.

2015-01-01

For centuries, the mechanisms surrounding spatially complex animal migrations have intrigued scientists and the public. We present a new methodology using ocean heat content (OHC), a habitat metric that is normally a fundamental part of hurricane intensity forecasting, to estimate movements and migration of satellite-tagged marine fishes. Previous satellite-tagging research of fishes using archival depth, temperature and light data for geolocations have been too coarse to resolve detailed ocean habitat utilization. We combined tag data with OHC estimated from ocean circulation and transport models in an optimization framework that substantially improved geolocation accuracy over SST-based tracks. The OHC-based movement track provided the first quantitative evidence that many of the tagged highly migratory fishes displayed affinities for ocean fronts and eddies. The OHC method provides a new quantitative tool for studying dynamic use of ocean habitats, migration processes and responses to environmental changes by fishes, and further, improves ocean animal tracking and extends satellite-based animal tracking data for other potential physical, ecological, and fisheries applications. PMID:26484541

Interannual growth dynamics of vegetation in the Kuparuk River watershed, Alaska based on the Normalized Difference Vegetation Index

USGS Publications Warehouse

Hope, A.S.; Boynton, W.L.; Stow, D.A.; Douglas, David C.

2003-01-01

Interannual above-ground production patterns are characterized for three tundra ecosystems in the Kuparuk River watershed of Alaska using NOAA-AVHRR Normalized Difference Vegetation Index (NDVI) data. NDVI values integrated over each growing season (SINDVI) were used to represent seasonal production patterns between 1989 and 1996. Spatial differences in ecosystem production were expected to follow north-south climatic and soil gradients, while interannual differences in production were expected to vary with variations in seasonal precipitation and temperature. It was hypothesized that the increased vegetation growth in high latitudes between 1981 and 1991 previously reported would continue through the period of investigation for the study watershed. Zonal differences in vegetation production were confirmed but interannual variations did not covary with seasonal precipitation or temperature totals. A sharp reduction in the SINDVI in 1992 followed by a consistent increase up to 1996 led to a further hypothesis that the interannual variations in SINDVI were associated with variations in stratospheric optical depth. Using published stratospheric optical depth values derived from the SAGE and SAGE-II satellites, it is demonstrated that variations in these depths are likely the primary cause of SINDVI interannual variability.

Spatiotemporal Path-Matching for Comparisons Between Ground- Based and Satellite Lidar Measurements

NASA Technical Reports Server (NTRS)

Berkoff, Timothy A.; Valencia, Sandra; Welton, Ellsworth J.; Spinhirne, James D.

2005-01-01

The spatiotemporal sampling differences between ground-based and satellite lidar data can contribute to significant errors for direct measurement comparisons. Improvement in sample correspondence is examined by the use of radiosonde wind velocity to vary the time average in ground-based lidar data to spatially match coincident satellite lidar measurements. Results are shown for the 26 February 2004 GLAS/ICESat overflight of a ground-based lidar stationed at NASA GSFC. Statistical analysis indicates that improvement in signal correlation is expected under certain conditions, even when a ground-based observation is mismatched in directional orientation to the satellite track.

(How) Can We Use Satellite Data to Estimate Effects of Extreme Drought on Photosynthesis?

NASA Astrophysics Data System (ADS)

Vicca, S.; Balzarolo, M.; Filella, I.; Granier, A.; Herbst, M.; Knohl, A.; Longdoz, B.; Mund, M.; Nagy, Z.; Pintér, K.; Rambal, S.; Verbesselt, J.; Verger, A.; Zeileis, A.; Zhang, C.; Penuelas, J.

2017-12-01

Severe droughts can strongly impact photosynthesis (GPP), but the tool best suited for large-scale and long-term monitoring, satellite imagery, has yet to prove its ability to detect drought effects on GPP. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect effect of a strong drought (that started during the European heatwave of 2003) on GPP in a beech forest in France (Hesse). While vegetation state remained largely unaffected by the drought, Eddy Covariance data revealed a substantial decrease in GPP and GPP recovered only after about three years. This three-year reduction in GPP was, however not detected by severaly commonly used reflectance indices (like NDVI and FAPAR) or by MODIS GPP product. Only he Enhanced Vegetation Index (EVI) and the Photochemical Reflectance Index (PRI) detected the drought effect, but the PRI only after normalization for absorbed light. These results were compared to a two other forests where a severe drought event had affected GPP and these data confirmed that especially the PRI normalized for absorbed light provides useful information about vegetation functioning that is not captured by other remote sensing indicators under test.

Post-hurricane forest damage assessment using satellite remote sensing

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu; J.A. Stanturf

2010-01-01

This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was...

NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Imbernon, J.; Dedieu, G.; Hautecoeur, O.; Lagouarde, J. P.

1989-01-01

NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRPT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2018-01-01

The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

Satellite-Based Solar Resource Data Sets for India 2002-2012

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, M.; Perez, R.; Gueymard, C.

A new 10-km hourly solar resource product was created for India. This product was created using satellite radiances from the Meteosat series of satellites. The product contains global horizontal irradiances (GHI) and direct normal irradiances (DNI) for the period from 2002 to 2011. An additional solar resource data set covering the period from January 2012 to June 2012 was created solely for validation because this period overlaps ground measurements that were made available from the Indian Ministry of New and Renewable Energy's (MNRE's) National Institute for Solar Energy for five stations that are part of MNRE's solar resource network. Thesemore » measurements were quality checked using the SERI QC software and used to validate the satellite product. A comparison of the satellite product to the ground measurements for the five stations shows good agreement. This report also presents a comparison of the new version of solar resource data to the previous version, which covered the period from 2002 to 2008.« less

Multi-temporal RADARSAT-1 and ERS backscattering signatures of coastal wetlands in southeastern Louisiana

USGS Publications Warehouse

Kwoun, Oh-Ig; Lu, Z.

2009-01-01

Using multi-temporal European Remote-sensing Satellites (ERS-1/-2) and Canadian Radar Satellite (RADARSAT-1) synthetic aperture radar (SAR) data over the Louisiana coastal zone, we characterize seasonal variations of radar backscat-tering according to vegetation type. Our main findings are as follows. First, ERS-1/-2 and RADARSAT-1 require careful radiometric calibration to perform multi-temporal backscattering analysis for wetland mapping. We use SAR backscattering signals from cities for the relative calibration. Second, using seasonally averaged backscattering coefficients from ERS-1/-2 and RADARSAT-1, we can differentiate most forests (bottomland and swamp forests) and marshes (freshwater, intermediate, brackish, and saline marshes) in coastal wetlands. The student t-test results support the usefulness of season-averaged backscatter data for classification. Third, combining SAR backscattering coefficients and an optical-sensor-based normalized difference vegetation index can provide further insight into vegetation type and enhance the separation between forests and marshes. Our study demonstrates that SAR can provide necessary information to characterize coastal wetlands and monitor their changes.

Characteristics of monsoon inversions over the Arabian Sea observed by satellite sounder and reanalysis data sets

NASA Astrophysics Data System (ADS)

Dwivedi, Sanjeev; Narayanan, M. S.; Venkat Ratnam, M.; Narayana Rao, D.

2016-04-01

Monsoon inversion (MI) over the Arabian Sea (AS) is one of the important characteristics associated with the monsoon activity over Indian region during summer monsoon season. In the present study, we have used 5 years (2009-2013) of temperature and water vapour measurement data obtained from satellite sounder instrument, an Infrared Atmospheric Sounding Interferometer (IASI) onboard MetOp satellite, in addition to ERA-Interim data, to study their characteristics. The lower atmospheric data over the AS have been examined first to identify the areas where MIs are predominant and occur with higher strength. Based on this information, a detailed study has been made to investigate their characteristics separately in the eastern AS (EAS) and western AS (WAS) to examine their contrasting features. The initiation and dissipation times of MIs, their percentage occurrence, strength, etc., has been examined using the huge database. The relation with monsoon activity (rainfall) over Indian region during normal and poor monsoon years is also studied. WAS ΔT values are ˜ 2 K less than those over the EAS, ΔT being the temperature difference between 950 and 850 hPa. A much larger contrast between the WAS and EAS in ΔT is noticed in ERA-Interim data set vis-à-vis those observed by satellites. The possibility of detecting MI from another parameter, refractivity N, obtained directly from another satellite constellation of GPS Radio Occultation (RO) (COSMIC), has also been examined. MI detected from IASI and Atmospheric Infrared Sounder (AIRS) onboard the NOAA satellite have been compared to see how far the two data sets can be combined to study the MI characteristics. We suggest MI could also be included as one of the semipermanent features of southwest monsoon along with the presently accepted six parameters.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China

NASA Astrophysics Data System (ADS)

Wu, Hao; Ye, Lu-Ping; Shi, Wen-Zhong; Clarke, Keith C.

2014-10-01

Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less

Incidence angle normalization of radar backscatter data

USDA-ARS?s Scientific Manuscript database

NASA’s Soil Moisture Passive Active (SMAP) satellite (~2014) will include a radar system that will provide L-band multi-polarization backscatter at a constant incidence angle of 40º. During the pre-launch phase of the project there is a need for observations that will support the radar-based soil mo...

Monitoring Lake and Reservoir Level: Satellite Observations, Modeling and Prediction

NASA Astrophysics Data System (ADS)

Ricko, M.; Birkett, C. M.; Adler, R. F.; Carton, J.

2013-12-01

Satellite measurements of lake and reservoir water levels complement in situ observations by providing stage information for un-gauged basins and by filling data gaps in gauge records. However, different satellite radar altimeter-derived continental water level products may differ significantly owing to choice of satellites and data processing methods. To explore the impacts of these differences, a direct comparison between three different altimeter-based surface water level estimates (USDA/NASA GRLM, LEGOS and ESA-DMU) will be presented and products validated with lake level gauge time series for lakes and reservoirs of a variety of sizes and conditions. The availability of satellite-based rainfall (i.e., TRMM and GPCP) and satellite-based lake/reservoir levels offers exciting opportunities to estimate and monitor the hydrologic properties of the lake systems. Here, a simple water balance model is utilized to relate net freshwater flux on a catchment basin to lake/reservoir level. Focused on tropical lakes and reservoirs it allows a comparison of the flux to altimetric lake level estimates. The combined use of model, satellite-based rainfall, evaporation information and reanalysis products, can be used to output water-level hindcasts and seasonal future forecasts. Such a tool is fundamental for understanding present-day and future variations in lake/reservoir levels and enabling a better understand of climatic variations on inter-annual to inter-decadal time-scales. New model-derived water level estimates of lakes and reservoirs, on regional to global scales, would assist communities with interests in climate studies focusing on extreme events, such as floods and droughts, and be important for water resources management.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.

Understanding and Reconciling Differences in Surface and Satellite-Based Lower Troposphere Temperatures

NASA Astrophysics Data System (ADS)

Hausfather, Z.; Thorne, P.; Mears, C. A.

2017-12-01

One of the main remaining uncertainties in global temperatures over the past few decades is the disagreement between surface and microwave sounding unit (MSU) satellite-based observations of the lower troposphere. Reconciling these will prove an important step in improving our understanding of modern climate change, and help resolve an issue that has been frequently brought to the attention of policymakers and highlighted as a reason to distrust climate observations. To assess differences between surface and satellite records, we examine data from radiosondes, from atmospheric reanalysis, from numerous different satellites, from surface observations over the land and ocean, and from global climate models. Controlling for spatial coverage, we determine where these datasets agree and disagree, isolate the differences, and identify for common factors to explain the divergences. We find large systemic differences between surface and lower troposphere warming in MSU/AMSU records compared to radiosondes, reanalysis products, and climate models that suggest possible residual inhomogeneities in satellite records. We further show that no reasonable subset of surface temperature records exhibits as little warming over the last two decades as satellite observations, suggesting that inhomogeneities in the surface record are very likely not responsible for the divergence.

Extravehicular Crewman Work System (ECWS) study program. Volume 3: Satellite service

NASA Technical Reports Server (NTRS)

Wilde, R. C.

1980-01-01

The satellite service portion of the Extravehicular Crewman Work System Study defines requirements and service equipment concepts for performing satellite service from the space shuttle orbiter. Both normal and contingency orbital satellite service is required. Service oriented satellite design practices are required to provide on orbit satellite service capability for the wide variety of satellites at the subsystem level. Development of additional satellite service equipment is required. The existing space transportation system provides a limited capability for performing satellite service tasks in the shuttle payload bay area.

Normalization and calibration of geostationary satellite radiances for the International Satellite Cloud Climatology Project

NASA Technical Reports Server (NTRS)

Desormeaux, Yves; Rossow, William B.; Brest, Christopher L.; Campbell, G. G.

1993-01-01

Procedures are described for normalizing the radiometric calibration of image radiances obtained from geostationary weather satellites that contributed data to the International Satellite Cloud Climatology Project. The key step is comparison of coincident and collocated measurements made by each satellite and the concurrent AVHRR on the 'afternoon' NOAA polar-orbiting weather satellite at the same viewing geometry. The results of this comparison allow transfer of the AVHRR absolute calibration, which has been established over the whole series, to the radiometers on the geostationary satellites. Results are given for Meteosat-2, 3, and 4, for GOES-5, 6, and 7, for GMS-2, 3, and 4 and for Insat-1B. The relative stability of the calibrations of these radiance data is estimated to be within +/- 3 percent; the uncertainty of the absolute calibrations is estimated to be less than 10 percent. The remaining uncertainties are at least two times smaller than for the original radiance data.

A Classification of Mediterranean Cyclones Based on Global Analyses

NASA Technical Reports Server (NTRS)

Reale, Oreste; Atlas, Robert

2003-01-01

The Mediterranean Sea region is dominated by baroclinic and orographic cyclogenesis. However, previous work has demonstrated the existence of rare but intense subsynoptic-scale cyclones displaying remarkable similarities to tropical cyclones and polar lows, including, but not limited to, an eye-like feature in the satellite imagery. The terms polar low and tropical cyclone have been often used interchangeably when referring to small-scale, convective Mediterranean vortices and no definitive statement has been made so far on their nature, be it sub-tropical or polar. Moreover, most of the classifications of Mediterranean cyclones have neglected the small-scale convective vortices, focusing only on the larger-scale and far more common baroclinic cyclones. A classification of all Mediterranean cyclones based on operational global analyses is proposed The classification is based on normalized horizontal shear, vertical shear, scale, low versus mid-level vorticity, low-level temperature gradients, and sea surface temperatures. In the classification system there is a continuum of possible events, according to the increasing role of barotropic instability and decreasing role of baroclinic instability. One of the main results is that the Mediterranean tropical cyclone-like vortices and the Mediterranean polar lows appear to be different types of events, in spite of the apparent similarity of their satellite imagery. A consistent terminology is adopted, stating that tropical cyclone- like vortices are the less baroclinic of all, followed by polar lows, cold small-scale cyclones and finally baroclinic lee cyclones. This classification is based on all the cyclones which occurred in a four-year period (between 1996 and 1999). Four cyclones, selected among all the ones which developed during this time-frame, are analyzed. Particularly, the classification allows to discriminate between two cyclones (occurred in October 1996 and in March 1999) which both display a very well-defined eye-like feature in the satellite imagery. According to our classification system, the two events are dynamically different and can be categorized as being respectively a tropical cyclone-like vortex and well-developed polar low.

SDI satellite autonomy using AI and Ada

NASA Technical Reports Server (NTRS)

Fiala, Harvey E.

1990-01-01

The use of Artificial Intelligence (AI) and the programming language Ada to help a satellite recover from selected failures that could lead to mission failure are described. An unmanned satellite will have a separate AI subsystem running in parallel with the normal satellite subsystems. A satellite monitoring subsystem (SMS), under the control of a blackboard system, will continuously monitor selected satellite subsystems to become alert to any actual or potential problems. In the case of loss of communications with the earth or the home base, the satellite will go into a survival mode to reestablish communications with the earth. The use of an AI subsystem in this manner would have avoided the tragic loss of the two recent Soviet probes that were sent to investigate the planet Mars and its moons. The blackboard system works in conjunction with an SMS and a reconfiguration control subsystem (RCS). It can be shown to be an effective way for one central control subsystem to monitor and coordinate the activities and loads of many interacting subsystems that may or may not contain redundant and/or fault-tolerant elements. The blackboard system will be coded in Ada using tools such as the ABLE development system and the Ada Production system.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

NASA Astrophysics Data System (ADS)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

CO-ORBITING PLANES OF SUB-HALOS ARE SIMILARLY UNLIKELY AROUND PAIRED AND ISOLATED HOSTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pawlowski, Marcel S.; McGaugh, Stacy S., E-mail: marcel.pawlowski@case.edu

2014-07-01

Sub-halos in dark-matter-based cosmological simulations tend to be distributed approximately isotropically around their host. The existence of highly flattened, co-orbiting planes of satellite galaxies has therefore been identified as a possible problem for these cosmological models, but so far studies have not considered the hosts' environments. That satellite planes are now known around both major galaxies in the Local Group raises the question whether they are more likely to be found around paired hosts. In a first attempt to investigate this possibility, we focus on the flattening and orbital coherence of the 11 brightest satellite galaxies of the vast polarmore » structure (VPOS) around the Milky Way (MW). We search for VPOS analogs in the ''Exploring the Local Volume in Simulations'' suite of cosmological simulations, which consist of 24 paired and 24 isolated host halos. We do not find significant differences between the properties of sub-halo distributions around paired and isolated hosts. The observed flattening and the observed orbital alignment are each reproduced by only 0.2%-2% of paired and isolated systems incorporating the obscuration of satellites by randomly oriented galactic disks. Only 1 of all 4800 analyzed realizations (0.02%) reproduces both parameters simultaneously, but the average orbital pole of this sub-halo system does not align as well with the normal to the plane fit as observed. That the MW is part of a galaxy pair thus does not help to explain the existence of the VPOS if the satellite galaxies are identified with sub-halos found in dissipationless simulations.« less

The 3D Radiation Dose Analysis For Satellite

NASA Astrophysics Data System (ADS)

Cai, Zhenbo; Lin, Guocheng; Chen, Guozhen; Liu, Xia

2002-01-01

the earth. These particles come from the Van Allen Belt, Solar Cosmic Ray and Galaxy Cosmic Ray. They have different energy and flux, varying with time and space, and correlating with solar activity tightly. These particles interact with electrical components and materials used on satellites, producing various space radiation effects, which will damage satellite to some extent, or even affect its safety. orbit. Space energy particles inject into components and materials used on satellites, and generate radiation dose by depositing partial or entire energy in them through ionization, which causes their characteristic degradation or even failure. As a consequence, the analysis and protection for radiation dose has been paid more attention during satellite design and manufacture. Designers of satellites need to analyze accurately the space radiation dose while satellites are on orbit, and use the results as the basis for radiation protection designs and ground experiments for satellites. can be calculated, using the model of the trapped proton and the trapped electron in the Van Allen Belt (AE8 and AP8). This is the 1D radiation dose analysis for satellites. Obviously, the mass shielding from the outside space to the computed point in all directions is regarded as a simple sphere shell. The actual structure of satellites, however, is very complex. When energy particles are injecting into a given equipment inside satellite from outside space, they will travel across satellite structure, other equipment, the shell of the given equipment, and so on, which depends greatly on actual layout of satellite. This complex radiation shielding has two characteristics. One is that the shielding masses for the computed point are different in different injecting directions. The other is that for different computed points, the shielding conditions vary in all space directions. Therefore, it is very difficult to tell the differences described above using the 1D radiation analysis, and hence, it is too simple to guide satellite radiation protection and ground experiments only based on the 1D radiation analysis results. To comprehend the radiation dose status of satellite adequately, it's essential to perform 3D radiation analysis for satellites. using computer software. From this 3D layout, the satellite model can be simplified appropriately. First select the point to be analyzed in the simplified satellite model, and extend many lines to the outside space, which divides the 4 space into many corresponding small areas with a certain solid angle. Then the shielding masses through the satellite equipment and structures along each direction are calculated, resulting in the shielding mass distribution in all space directions based on the satellite layout. Finally, using the relationship between radiation dose and shielding thickness from the 1D analysis, calculate the radiation dose in each area represented by each line. After we obtain the radiation dose and its space distribution for the point of interest, the 3D satellite radiation analysis is completed. radiation analysis based on satellite 3D CAD layout has larger benefit for engineering applications than the 1D analysis based on the solid sphere shielding model. With the 3D model, the analysis of space environment and its effect is combined closely with actual satellite engineering. The 3D radiation analysis not only provides valuable engineering data for satellite radiation design and protection, but also provides possibility to apply new radiation protection approaches, which expands technology horizon and broadens ways for technology development.

An Unsupervised Anomalous Event Detection and Interactive Analysis Framework for Large-scale Satellite Data

NASA Astrophysics Data System (ADS)

LIU, Q.; Lv, Q.; Klucik, R.; Chen, C.; Gallaher, D. W.; Grant, G.; Shang, L.

2016-12-01

Due to the high volume and complexity of satellite data, computer-aided tools for fast quality assessments and scientific discovery are indispensable for scientists in the era of Big Data. In this work, we have developed a framework for automated anomalous event detection in massive satellite data. The framework consists of a clustering-based anomaly detection algorithm and a cloud-based tool for interactive analysis of detected anomalies. The algorithm is unsupervised and requires no prior knowledge of the data (e.g., expected normal pattern or known anomalies). As such, it works for diverse data sets, and performs well even in the presence of missing and noisy data. The cloud-based tool provides an intuitive mapping interface that allows users to interactively analyze anomalies using multiple features. As a whole, our framework can (1) identify outliers in a spatio-temporal context, (2) recognize and distinguish meaningful anomalous events from individual outliers, (3) rank those events based on "interestingness" (e.g., rareness or total number of outliers) defined by users, and (4) enable interactively query, exploration, and analysis of those anomalous events. In this presentation, we will demonstrate the effectiveness and efficiency of our framework in the application of detecting data quality issues and unusual natural events using two satellite datasets. The techniques and tools developed in this project are applicable for a diverse set of satellite data and will be made publicly available for scientists in early 2017.

Estimation of the Earth's gravity field by combining normal equation matrices from GRACE and SLR

NASA Astrophysics Data System (ADS)

Haberkorn, Christoph; Bloßfeld, Mathis; Bouman, Johannes

2014-05-01

Since 2002, GRACE observes the Earth's gravity field with a spatial resolution up to 150 km. The main goal of this mission is the determination of temporal variations in the Earth's gravity field to detect mass displacements. The GRACE mission consists of two identical satellites, which observe the range along the line of sight of both satellites. GRACE observations can be linked with the Earth's gravitational potential, which is expressed in terms of spherical harmonics for global solutions. However, the estimation of low degree coefficients is difficult with GRACE. In contrast to gravity field missions, which observe the gravity field with high spectral resolution, SLR data allow to estimate the lower degree coefficients. Therefore, the coefficient C20 is often replaced by a value derived from Satellite Laser Ranging (SLR). Instead of replacing C20, it can be determined consistently by a combined estimation using GRACE and SLR data. We compute monthly normal equation (NEQ) matrices for GRACE and SLR. Coefficients from monthly GRACE gravity field models of different institutions (Center for Space Research (CSR), USA, Geoforschungszentrum Potsdam (GFZ), Germany and Jet Propulsion Laboratory (JPL), USA) and coefficients from monthly gravity field models of our SLR processing are then combined using the NEQ matrices from both techniques. We will evaluate several test scenarios with gravity field models from different institutions and with different set ups for the SLR NEQ matrices. The effect of the combination on the estimated gravity field will be analysed and presented.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA

Treesearch

Jay D. Miller; Eric E. Knapp; Carl H. Key; Carl N. Skinner; Clint J. Isbell; R. Max Creasy; Joseph W. Sherlock

2009-01-01

Multispectral satellite data have become a common tool used in the mapping of wildland fire effects. Fire severity, defined as the degree to which a site has been altered, is often the variable mapped. The Normalized Burn Ratio (NBR) used in an absolute difference change detection protocol (dNBR), has become the remote sensing method of choice for US Federal land...

The comparison between a ground based and a space based probabilistic landslide susceptibility assessment

NASA Astrophysics Data System (ADS)

Reichenbach, P.; Mondini, A.; Guzzetti, F.; Rossi, M.; Ardizzone, F.; Cardinali, M.

2009-04-01

Probabilistic landslide susceptibility assessments attempt to predict the location and threat posed by known landslides. Under the assumption that landslides will occur in the future because of the same conditions that produced them in the past, geomorphologists use susceptibility assessments to predict the location of future landslides. We present an attempt to exploit satellite data to prepare a landslide susceptibility zonation for a the Collazzone area that extends for 79 sq km in the Umbria region, Central Italy. For the study area we have prepared a map of the Normalized Difference Vegetation Index (NDVI) obtained by processing raw NIR and RED channels (b2 and b3 bands) at 15 m x 15 m resolution of an image acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), on board the TERRA satellite, and a map of Land Surface Temperature (LST) obtained by processing raw TIR channels (b11 to b15 bands) at 90 m × 90 m resolution from the same image. Both maps, in general proxy for soil moisture maps, were obtained through standard algorithms. As expected, there is a strong correspondence between NDVI and LST, but, when the NDVI does not change, elevation effects and others are predominant in LST. For the Collazzone area we prepared two different susceptibility models. The first was prepared through multivariate analysis of thematic data (including morphometry, lithology, structure and land use) obtained through traditional methods, primarily the interpretation of aerial photographs and field work. The second susceptibility model was prepared using terrain morphology and information obtained processing satellite data. The two models were compared in term of model fit and model performance and were validated exploiting landslide inventories not used to build the models. The two susceptibility models are very similar from a geographic and a classification point of view. This is good news, as it tells us that for landslide susceptibility, thematic maps obtained processing satellite data can be an effective alternative to maps prepared using more traditional, ground based methods.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object-oriented segmentation data, and finally get the rice extent map. At last, by using the time series analysis, the peak count was obtained for each rice area to ensure the crop intensity. In this work, the rice ground point from a GVG crowdsourcing smartphone and rice area statistical results from National Bureau of Statistics were used to validate and evaluate our result.

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson

USGS Publications Warehouse

Wallace, Cynthia S.A.; Advised by Marsh, Stuart E.

2002-01-01

The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Caballero, Isabel; Silva, Gustavo; Parra, Pedro-Cecilio; Vázquez, Águeda; Caldeira, Rui

2017-06-01

A forest fire started on August 8th, 2016 in several places on Madeira Island causing damage and casualties. As of August 10th the local media had reported the death of three people, over 200 people injured, over 950 habitants evacuated, and 50 houses damaged. This study presents the preliminary results of the assessment of several spectral indices to evaluate the burn severity of Madeira fires during August 2016. These spectral indices were calculated using the new European satellite Sentinel-2A launched in June 2015. The study confirmed the advantages of several spectral indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVIreXn) using red-edge spectral bands to assess the post-fire conditions. Results showed high correlation between NDVI, GNDVI, NBR and NDVIre1n spectral indices and the analysis performed by Copernicus Emergency Management Service (EMSR175), considered as the reference truth. Regarding the red-edge spectral indices, the NDVIre1n (using band B5, 705 nm) presented better results compared with B6 (740 nm) and B7 (783 nm) bands. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for post-fire monitoring. In the future, the two twin Sentinel-2 satellites will offer global coverage of the Madeira Archipelago every five days, therefore allowing the simultaneous study of the evolution of the burnt area and reforestation information with high spatial (up to 10 m) and temporal resolution (5 days).

Arase: mission overview and initial results

NASA Astrophysics Data System (ADS)

Miyoshi, Y.; Shinohara, I.; Takashima, T.; Asamura, K.; Wang, S. Y.; Kazama, Y.; Kasahara, S.; Yokota, S.; Mitani, T.; Higashio, N.; Kasahara, Y.; Kasaba, Y.; Yagitani, S.; Matsuoka, A.; Kojima, H.; Kazuo, S.; Seki, K.; Hori, T.; Shoji, M.; Teramoto, M.; Chang, T. F.; Kurita, S.; Matsuda, S.; Keika, K.; Miyashita, Y.; Hosokawa, K.; Ogawa, Y.; Kadokura, A.; Kataoka, R.; Ono, T.

2017-12-01

Geospace Exploation Project; ERG addresses what mechanisms cause acceleration, transportation and loss of MeV electrons of the radiation belts and evolutions of space storms. Cross-energy and cross-regional couplings are key concepts for the project. In order to address questions, the project has been organized by three research teams; satellite observations, ground-based observations, and modeling/data-analysis studies, and interdisciplinary research are realized for comprehensive understanding of geospace. The Arase (ERG) satellite had been developed and 9 science instruments are developed and provided from JAXA, universities and instituted in Japan and Taiwan. The Arase satellite was successfully launched on December 20, 2016. After the initial operation including maneuvers, Arase has started normal observations since March, 2017. Until now, Arase has observed several geomagnetic storms driven by coronal hole streams and CMEs, and several interesting features are observed associated with geomagnetic disturbances. The six particle instruments; LEP-e/LEP-i/MEP-e/MEP-i/HEP/XEP have shown large enhancement as well as loss of wide energy electrons and ions and variations as well as changes of pitch angle and energy spectrum. The two field/wave instruments: PWE and MGF observed several kinds of plasma waves such as chorus, hiss, EMIC as well as large scale electric and magnetic field variations. And newly developed S-WPIA has been operated to identify micro-process of wave-particle interactions. Since conjugate observations between Arase and ground-based observations are essential for comprehensive understanding of geospace, we organized several campaign observations that include both satellite and ground-based observations. The project has collaborated with the international projects, EISCAT, SuperDARN and other ground-based observations, and various data are obtained from such international collaborations. Moreover, multi-point satellite observations by collaboration with other satellites; Van Allen Probes, THEMIS and MMS are realized. In this presentation, we will report overview and initial highlights for the first year and discuss importance of synergies of multi-satellites and ground-based observations that are realized by international collaborations.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

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

PubMed

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

2018-06-01

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.

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

Spreading vs. Rifting as modes of extensional tectonics on the globally expanded Ganymede

NASA Astrophysics Data System (ADS)

Pizzi, Alberto; Domenica, Alessandra Di; Komatsu, Goro; Cofano, Alessandra; Mitri, Giuseppe; Bruzzone, Lorenzo

2017-05-01

The formation of Ganymede's sulci is likely related to extensional tectonics that affected this largest icy satellite of Jupiter. Through geometric and structural analyses we reconstructed the pre-deformed terrains and we recognized two different modes of extension associated with sulci. In the first mode, smooth sulci constitute spreading centers between two dark terrain plates, similar to the fast oceanic spreading centers on Earth. Here extension is primarily accommodated by crustal accretion of newly formed icy crust. In the second mode, dark terrain extension is mainly accommodated by swaths of normal fault systems analogous to Earth's continental crustal rifts. A comparison with terrestrial extensional analogues, based on the fault displacement/length (Dmax/L) ratio, spacing and morphology, showed that magmato-tectonic spreading centers and continental crustal rifts on Earth follow the same relative patterns observed on Ganymede. Our results suggest that the amount of extensional strain may have previously been underestimated since the occurrence of spreading centers may have played a major role in the tectonic evolution of the globally expanded Ganymede. We also discuss a possible model for the origin of the different modes of extension in the context of the global expansion of the satellite.

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

NASA Astrophysics Data System (ADS)

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 governmental entities and municipalities.

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

New Microwave-Based Missions Applications for Rainfed Crops Characterization

NASA Astrophysics Data System (ADS)

Sánchez, N.; Lopez-Sanchez, J. M.; Arias-Pérez, B.; Valcarce-Diñeiro, R.; Martínez-Fernández, J.; Calvo-Heras, J. M.; Camps, A.; González-Zamora, A.; Vicente-Guijalba, F.

2016-06-01

A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.

Analysis of orbit determination from Earth-based tracking for relay satellites in a perturbed areostationary orbit

NASA Astrophysics Data System (ADS)

Romero, P.; Pablos, B.; Barderas, G.

2017-07-01

Areostationary satellites are considered a high interest group of satellites to satisfy the telecommunications needs of the foreseen missions to Mars. An areostationary satellite, in an areoequatorial circular orbit with a period of 1 Martian sidereal day, would orbit Mars remaining at a fixed location over the Martian surface, analogous to a geostationary satellite around the Earth. This work addresses an analysis of the perturbed orbital motion of an areostationary satellite as well as a preliminary analysis of the aerostationary orbit estimation accuracy based on Earth tracking observations. First, the models for the perturbations due to the Mars gravitational field, the gravitational attraction of the Sun and the Martian moons, Phobos and Deimos, and solar radiation pressure are described. Then, the observability from Earth including possible occultations by Mars of an areostationary satellite in a perturbed areosynchronous motion is analyzed. The results show that continuous Earth-based tracking is achievable using observations from the three NASA Deep Space Network Complexes in Madrid, Goldstone and Canberra in an occultation-free scenario. Finally, an analysis of the orbit determination accuracy is addressed considering several scenarios including discontinuous tracking schedules for different epochs and different areoestationary satellites. Simulations also allow to quantify the aerostationary orbit estimation accuracy for various tracking series durations and observed orbit arc-lengths.

Isolated Galaxies and Isolated Satellite Systems

NASA Astrophysics Data System (ADS)

Ann, H. B.; Park, C.; Choi, Y. Y.

2010-10-01

We search for isolated galaxies using a volume-limited sample of galaxies with 0.02 < z < 0.04742 from SDSS DR7 supplemented by bright galaxies. We devise a diagnostic tool to select isolated galaxies in different environments using the projected separation (rp) normalized by the virial radius of the nearest neighbor (rvir,nei) and the local background density. We find that the isolation condition of rp > rvir,nei and ρ < ρbar well segregates the CIG galaxies. We confirm the morphology conformity between the host and their satellites, which suggests the importance to galaxy evolution of hydrodynamic interactions among galaxies within their virial radii.

Drone based estimation of actual evapotranspiration over different forest types

NASA Astrophysics Data System (ADS)

Marzahn, Philip; Gampe, David; Castro, Saulo; Vega-Araya, Mauricio; Sanchez-Azofeifa, Arturo; Ludwig, Ralf

2017-04-01

Actual evapotranspiration (Eta) plays an important role in surface-atmosphere interactions. Traditionally, Eta is measured by means of lysimeters, eddy-covariance systems or fiber optics, providing estimates which are spatially restricted to a footprint from a few square meters up to several hectares . In the past, several methods have been developed to derive Eta by means of multi-spectral remote sensing data using thermal and VIS/NIR satellite imagery of the land surface. As such approaches do have their justification on coarser scales, they do not provide Eta information on the fine resolution plant level over large areas which is mandatory for the detection of water stress or tree mortality. In this study, we present a comparison of a drone based assessment of Eta with eddy-covariance measurements over two different forest types - a deciduous forest in Alberta, Canada and a tropical dry forest in Costa Rica. Drone based estimates of Eta were calculated applying the Triangle-Method proposed by Jiang and Islam (1999). The Triangle-Method estimates actual evapotranspiration (Eta) by means of the Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) provided by two camera systems (MicaSense RedEdge, FLIR TAU2 640) flown simultaneously on an octocopter. . Results indicate a high transferability of the original approach from Jiang and Islam (1999) developed for coarse to medium resolution satellite imagery tothe high resolution drone data, leading to a deviation in Eta estimates of 10% compared to the eddy-covariance measurements. In addition, the spatial footprint of the eddy-covariance measurement can be detected with this approach, by showing the spatial heterogeneities of Eta due to the spatial distribution of different trees and understory vegetation.

A model of ocean basin crustal magnetization appropriate for satellite elevation anomalies

NASA Technical Reports Server (NTRS)

Thomas, Herman H.

1987-01-01

A model of ocean basin crustal magnetization measured at satellite altitudes is developed which will serve both as background to which anomalous magnetizations can be contrasted and as a beginning point for studies of tectonic modification of normal ocean crust. The model is based on published data concerned with the petrology and magnetization of the ocean crust and consists of viscous magnetization and induced magnetization estimated for individual crustal layers. Thermal remanent magnetization and chemical remanent magnetization are excluded from the model because seafloor spreading anomalies are too short in wavelength to be resolved at satellite altitudes. The exception to this generalization is found at the oceanic magnetic quiet zones where thermal remanent magnetization and chemical remanent magnetization must be considered along with viscous magnetization and induced magnetization.

Detection of Unknown LEO Satellite Using Radar Measurements

NASA Astrophysics Data System (ADS)

Kamensky, S.; Samotokhin, A.; Khutorovsky, Z.; Alfriend, T.

While processing of the radar information aimed at satellite catalog maintenance some measurements do not correlate with cataloged and tracked satellites. These non-correlated measurements participate in the detection (primary orbit determination) of new (not cataloged) satellites. The satellite is considered newly detected when it is missing in the catalog and the primary orbit determination on the basis of the non-correlated measurements provides the accuracy sufficient for reliable correlation of future measurements. We will call this the detection condition. One non-correlated measurement in real conditions does not have enough accuracy and thus does not satisfy the detection condition. Two measurements separated by a revolution or more normally provides orbit determination with accuracy sufficient for selection of other measurements. However, it is not always possible to say with high probability (close to 1) that two measurements belong to one satellite. Three measurements for different revolutions, which are included into one orbit, have significantly higher chances to belong to one satellite. Thus the suggested detection (primary orbit determination) algorithm looks for three uncorrelated measurements in different revolutions for which we can determine the orbit inscribing them. The detection procedure based on search for the triplets is rather laborious. Thus only relatively high efficiency can be the reason for its practical implementation. The work presents the detailed description of the suggested detection procedure based on the search for triplets of uncorrelated measurements (for radar measurements). The break-ups of the tracked satellites provide the most difficult conditions for the operation of the detection algorithm and reveal explicitly its characteristics. The characteristics of time efficiency and reliability of the detected orbits are of maximum interest. Within this work we suggest to determine these characteristics using simulation of break-ups with further acquisition of measurements generated by the fragments. In particular, using simulation we can not only evaluate the characteristics of the algorithm but adjust its parameters for certain conditions: the orbit of the fragmented satellite, the features of the break-up, capabilities of detection radars etc. We describe the algorithm performing the simulation of radar measurements produced by the fragments of the parent satellite. This algorithm accounts of the basic factors affecting the characteristics of time efficiency and reliability of the detection. The catalog maintenance algorithm includes two major components detection and tracking. These are two processes permanently interacting with each other. This is actually in place for the processing of real radar data. The simulation must take this into account since one cannot obtain reliable characteristics of detection procedure simulating only this process. Thus we simulated both processes in their interaction. The work presents the results of simulation for the simplest case of a break-up in near-circular orbit with insignificant atmospheric drag. The simulations show rather high efficiency. We demonstrate as well that the characteristics of time efficiency and reliability of determined orbits essentially depend on the density of the observed break-up fragments.

Climate-disease connections: Rift Valley Fever in Kenya

NASA Technical Reports Server (NTRS)

Anyamba, A.; Linthicum, K. J.; Tucker, C. J.

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Nino/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

Climate-disease connections: Rift Valley Fever in Kenya.

PubMed

Anyamba, A; Linthicum, K J; Tucker, C J

2001-01-01

All known Rift Valley fever(RVF) outbreaks in Kenya from 1950 to 1998 followed periods of abnormally high rainfall. On an interannual scale, periods of above normal rainfall in East Africa are associated with the warm phase of the El Niño/Southern Oscillation (ENSO) phenomenon. Anomalous rainfall floods mosquito-breeding habitats called dambos, which contain transovarially infected mosquito eggs. The eggs hatch Aedes mosquitoes that transmit the RVF virus preferentially to livestock and to humans as well. Analysis of historical data on RVF outbreaks and indicators of ENSO (including Pacific and Indian Ocean sea surface temperatures and the Southern Oscillation Index) indicates that more than three quarters of the RVF outbreaks have occurred during warm ENSO event periods. Mapping of ecological conditions using satellite normalized difference vegetation index (NDVI) data show that areas where outbreaks have occurred during the satellite recording period (1981-1998) show anomalous positive departures in vegetation greenness, an indicator of above-normal precipitation. This is particularly observed in arid areas of East Africa, which are predominantly impacted by this disease. These results indicate a close association between interannual climate variability and RVF outbreaks in Kenya.

Space Based Satellite Tracking and Characterization Utilizing Non-Imaging Passive Sensors

DTIC Science & Technology

2008-03-01

vary from only slightly here. The classical orbital elements are: a - The Semimajor Axis e - Eccentricity i - Inclination Ω - Right Ascension of the...Eccentricity . . . . . . . . . . . . . . . . . . . . . . . . . . 7 ~h Axis normal to orbital plane . . . . . . . . . . . . . . . . . 7 Ω Right ascension of...transistion matrix . . . . . . . . . . . . . . . . . . . 27 i Orbital inclination . . . . . . . . . . . . . . . . . . . . . . 28 Ẑ Unit vector in ECI frame

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Ying; Fu, Rong; Dickinson, Robert

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events

DOE PAGES

Sun, Ying; Fu, Rong; Dickinson, Robert; ...

2015-11-02

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite-observed solar-induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME-2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought-induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below-normal precipitation. Inmore » contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME-2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. Here, we conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.« less

Statistical Evaluation of VIIRS Ocean Color Products

NASA Astrophysics Data System (ADS)

Mikelsons, K.; Wang, M.; Jiang, L.

2016-02-01

Evaluation and validation of satellite-derived ocean color products is a complicated task, which often relies on precise in-situ measurements for satellite data quality assessment. However, in-situ measurements are only available in comparatively few locations, expensive, and not for all times. In the open ocean, the variability in spatial and temporal scales is longer, and the water conditions are generally more stable. We use this fact to perform extensive statistical evaluations of consistency for ocean color retrievals based on comparison of retrieved data at different times, and corresponding to various retrieval parameters. We have used the NOAA Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system for ocean color product data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS). We show the results for statistical dependence of normalized water-leaving radiance spectra with respect to various parameters of retrieval geometry, such as solar- and sensor-zenith angles, as well as physical variables, such as wind speed, air pressure, ozone amount, water vapor, etc. In most cases, the results show consistent retrievals within the relevant range of retrieval parameters, showing a good performance with the MSL12 in the open ocean. The results also yield the upper bounds of solar- and sensor-zenith angles for reliable ocean color retrievals, and also show a slight increase of VIIRS-derived normalized water-leaving radiances with wind speed and water vapor concentration.

Integrating proximal and satellite optical data for the analysis of ecosystem carbon uptake and plant phenology at the European larch Specnet site

NASA Astrophysics Data System (ADS)

Galvagno, Marta; Gamon, John; Cremonese, Edoardo; Garrity, Steven; Huemmrich, K. Fred; Filippa, Gianluca; Morra di Cella, Umberto; Rossini, Micol

2017-04-01

Automated canopy-level optical sampling in tandem with ecosystem-atmosphere flux observations is continuously carried on at a variety of ecosystems through the Specnet network (http://specnet.info/). Specifically, 9 sites within US and Europe were selected since 2015, to investigate the use of novel NDVI and PRI low-cost sensors for the analysis of ecosystem functioning and phenology. Different plant functional types, such as grasslands, deciduous, and evergreen forests belong to the network, here we present specific data from the larch (Larix decidua Mill.) forest Italian site. Three automated NDVI and three automated PRI spectral reflectance sensors (Decagon Devices Inc.) were installed in 2015 on the top of the 20-meters eddy covariance tower, pointing toward the west, north, and east orientations. An additional system, composed by one NDVI and PRI system was installed to monitor the understory component. The objective of this analysis is the comparison between these in-situ inexpensive sensors, independent NDVI and PRI sensors (Skye Instruments) previously installed on the 20-meters tower and satellite-derived NDVI. Both MODIS and Sentinel NDVI data were used for the comparison. Moreover, the newly derived chlorophyll/carotenoid index (CCI, Gamon et al. 2016), computed as the normalized difference between the NDVI red band and PRI 532 nm band, was tested to estimate the seasonal pattern of daily Gross Primary Productivity (GPP) of the larch forest. Results showed that the seasonality of NDVI was comparable among in-situ sensors and satellite data, though orientation-specific differences were observed. Both NDVI and CCI tracked daily GPP, but with different sensitivity to its seasonality. Future analysis will be directed toward a comparison between this site-based results with the other sites within the Specnet network.

Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

Treesearch

Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

2009-01-01

Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

On the estimation of physical height changes using GRACE satellite mission data - A case study of Central Europe

NASA Astrophysics Data System (ADS)

Godah, Walyeldeen; Szelachowska, Małgorzata; Krynski, Jan

2017-12-01

The dedicated gravity satellite missions, in particular the GRACE (Gravity Recovery and Climate Experiment) mission launched in 2002, provide unique data for studying temporal variations of mass distribution in the Earth's system, and thereby, the geometry and the gravity fi eld changes of the Earth. The main objective of this contribution is to estimate physical height (e.g. the orthometric/normal height) changes over Central Europe using GRACE satellite mission data as well as to analyse them and model over the selected study area. Physical height changes were estimated from temporal variations of height anomalies and vertical displacements of the Earth surface being determined over the investigated area. The release 5 (RL05) GRACE-based global geopotential models as well as load Love numbers from the Preliminary Reference Earth Model (PREM) were used as input data. Analysis of the estimated physical height changes and their modelling were performed using two methods: the seasonal decomposition method and the PCA/ EOF (Principal Component Analysis/Empirical Orthogonal Function) method and the differences obtained were discussed. The main fi ndings reveal that physical height changes over the selected study area reach up to 22.8 mm. The obtained physical height changes can be modelled with an accuracy of 1.4 mm using the seasonal decomposition method.

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

NASA Astrophysics Data System (ADS)

Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

2017-12-01

Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

Investigations of possible contributions NDVI's have to misclassification in AVHRR data analysis

Treesearch

David L. Evans; Raymond L. Czaplewski

1996-01-01

Numerous subcontinental-scale projects have placed significant emphasis on the use of Normalized Difference Vegetation Indices (NDVI's) derived from Advanced Very High Resolution Radiometer (AVHRR) satellite data for vegetation type recognition. In multi-season AVHRR data, overlap of NDVI ranges for vegetation classes may degrade overall classification performance...

A remote sensing protocol for identifying rangelands with degraded productive capacity

Treesearch

Matthew C. Reeves; L. Scott Bagget

2014-01-01

Rangeland degradation is a growing problem throughout the world. An assessment process for com-paring the trend and state of vegetation productivity to objectively derived reference conditions wasdeveloped. Vegetation productivity was estimated from 2000 to 2012 using annual maximum Normalized Difference Vegetation Index (NDVI) from the MODIS satellite platform. Each...

Combining points and lines in rectifying satellite images

NASA Astrophysics Data System (ADS)

Elaksher, Ahmed F.

2017-09-01

The quick advance in remote sensing technologies established the potential to gather accurate and reliable information about the Earth surface using high resolution satellite images. Remote sensing satellite images of less than one-meter pixel size are currently used in large-scale mapping. Rigorous photogrammetric equations are usually used to describe the relationship between the image coordinates and ground coordinates. These equations require the knowledge of the exterior and interior orientation parameters of the image that might not be available. On the other hand, the parallel projection transformation could be used to represent the mathematical relationship between the image-space and objectspace coordinate systems and provides the required accuracy for large-scale mapping using fewer ground control features. This article investigates the differences between point-based and line-based parallel projection transformation models in rectifying satellite images with different resolutions. The point-based parallel projection transformation model and its extended form are presented and the corresponding line-based forms are developed. Results showed that the RMS computed using the point- or line-based transformation models are equivalent and satisfy the requirement for large-scale mapping. The differences between the transformation parameters computed using the point- and line-based transformation models are insignificant. The results showed high correlation between the differences in the ground elevation and the RMS.

Latitudinal dependence on the frequency of Pi2 pulsations near the plasmapause using THEMIS satellites and Asian-Oceanian SuperDARN radars

NASA Astrophysics Data System (ADS)

Teramoto, Mariko; Nishitani, Nozomu; Nishimura, Yukitoshi; Nagatsuma, Tsutomu

2016-02-01

We herein describe a harmonic Pi2 wave that started at 09:12 UT on August 19, 2010, with data that were obtained simultaneously at 19:00-20:00 MLT by three mid-latitude Asian-Oceanian Super Dual Auroral Radar Network (SuperDARN) radars (Unwin, Tiger, and Hokkaido radars), three Time History of Events and Macroscale Interactions during Substorms (THEMIS) satellites (THEMIS A, THEMIS D, and THEMIS E), and ground-based magnetometers at low and high latitudes. All THEMIS satellites, which were located in the plasmasphere, observed Pi2 pulsations dominantly in the magnetic compressional ( B //) and electric azimuthal ( E A) components, i.e., the fast-mode component. The spectrum of Pi2 pulsations in the B // and E A components contained two spectral peaks at approximately 12 to 14 mHz ( f 1, fundamental) and 23 to 25 mHz ( f 2, second harmonic). The Poynting flux derived from the electric and magnetic fields indicated that these pulsations were waves propagating earthward and duskward. Doppler variations ( V) from the 6-s or 8-s resolution camping beams of the Tiger and Unwin SuperDARN radars, which are associated with Pi2 pulsations in the eastward electric field component in the ionosphere, observed Pi2 pulsations within and near the footprint of the plasmapause, whose location was estimated by the THEMIS satellites. The latitudinal profile of f 2 power normalized by f 1 power for Doppler velocities indicated that the enhancement of the normalized f 2 power was the largest near the plasmapause at an altitude-adjusted corrected geomagnetic (AACGM) latitude of 60° to 65°. Based on these features, we suggest that compressional waves propagate duskward away from the midnight sector, where the harmonic cavity mode is generated.

Total ozone column derived from GOME and SCIAMACHY using KNMI retrieval algorithms: Validation against Brewer measurements at the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Antón, M.; Kroon, M.; López, M.; Vilaplana, J. M.; Bañón, M.; van der A, R.; Veefkind, J. P.; Stammes, P.; Alados-Arboledas, L.

2011-11-01

This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.

Analysis of urban regions using AVHRR thermal infrared data

USGS Publications Warehouse

Wright, Bruce

1993-01-01

Using 1-km AVHRR satellite data, relative temperature difference caused by conductivity and inertia were used to distinguish urban and non urban land covers. AVHRR data that were composited on a biweekly basis and distributed by the EROS Data Center in Sioux Falls, South Dakota, were used for the classification process. These composited images are based on the maximum normalized different vegetation index (NDVI) of each pixel during the 2-week period using channels 1 and 2. The resultant images are nearly cloud-free and reduce the need for extensive reclassification processing. Because of the physiographic differences between the Eastern and Western United States, the initial study was limited to the eastern half of the United States. In the East, the time of maximum difference between the urban surfaces and the vegetated non urban areas is the peak greenness period in late summer. A composite image of the Eastern United States for the 2-weel time period from August 30-Septmeber 16, 1991, was used for the extraction of the urban areas. Two channels of thermal data (channels 3 and 4) normalized for regional temperature differences and a composited NDVI image were classified using conventional image processing techniques. The results compare favorably with other large-scale urban area delineations.

Drought in the Rockies

NASA Technical Reports Server (NTRS)

2002-01-01

This image shows the difference between the amount of vegetation in July 2000 and the average July vegetation for North America. Of particular interest are the dry conditions in the western United States. This spring and summer the Rocky Mountains have been relatively dry, and the brown regions stretching from the Canadian to the Mexican border, indicate the effect on the regions' forests. Western Montana and eastern Idaho are particularly parched, and appear darker brown. The dry conditions have contributed to this year's devastating fire season, during which millions of acres have burned in the west. Scientists find that during the growing season, land plants can be used to measure drought. Healthy, thriving plants reflect and absorb visible and near-infrared light differently than plants under stress. These variations in reflectance and absorption can be measured by satellites to produce maps of healthy and stressed vegetation. This image shows Normalized Difference Vegetation Index (NDVI) anomaly, which indicates where vegetation growth was above average (green pixels), below average (brown pixels), or normal (white pixels). For more images and information about measuring vegetation and drought from space visit: Drought and Vegetation Monitoring. Image courtesy NASA Goddard Space Flight Center Biospheric Sciences Branch, based on data from NOAA.

Estimating the spin axis orientation of the Echostar-2 box-wing geosynchronous satellite

NASA Astrophysics Data System (ADS)

Earl, Michael A.; Somers, Philip W.; Kabin, Konstantin; Bédard, Donald; Wade, Gregg A.

2018-04-01

For the first time, the spin axis orientation of an inactive box-wing geosynchronous satellite has been estimated from ground-based optical photometric observations of Echostar-2's specular reflections. Recent photometric light curves obtained of Echostar-2 over four years suggest that unusually bright and brief specular reflections were occurring twice within an observed spin period. These bright and brief specular reflections suggested two satellite surfaces with surface normals separated by approximately 180°. The geometry between the satellite, the Sun, and the observing location at the time of each of the brightest observed reflections, was used to estimate Echostar-2's equatorial spin axis orientation coordinates. When considering prograde and retrograde rotation, Echostar-2's spin axis orientation was estimated to have been located within 30° of either equatorial coordinate pole. Echostar-2's spin axis was observed to have moved approximately 180° in right ascension, within a time span of six months, suggesting a roughly one year spin axis precession period about the satellite's angular momentum vector.

Validation of SCIAMACHY and TOMS UV Radiances Using Ground and Space Observations

NASA Technical Reports Server (NTRS)

Hilsenrath, E.; Bhartia, P. K.; Bojkov, B. R.; Kowalewski, M.; Labow, G.; Ahmad, Z.

2004-01-01

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify its recovery. We show that validation of satellite radiances from space and from the ground can be a very effective means for correcting long term drifts of backscatter type satellite measurements and can be used to cross calibrate all B W instruments in orbit (TOMS, SBW/2, GOME, SCIAMACHY, OM, GOME-2, OMPS). This method bypasses the retrieval algorithms used for both satellite and ground based measurements that are normally used to validate and correct the satellite data. Radiance comparisons employ forward models and are inherently more accurate than inverse (retrieval) algorithms. This approach however requires well calibrated instruments and an accurate radiative transfer model that accounts for aerosols. TOMS and SCIAMACHY calibrations are checked to demonstrate this method and to demonstrate applicability for long term trends.

Spectroradiometric calibration of the Thematic Mapper and Multispectral Scanner system. [White Sands, New Mexico

NASA Technical Reports Server (NTRS)

Palmer, J. M. (Principal Investigator); Slater, P. N.

1984-01-01

The newly built Caste spectropolarimeters gave satisfactory performance during tests in the solar radiometer and helicopter modes. A bandwidth normalization technique based on analysis of the moments of the spectral responsivity curves was used to analyze the spectral bands of the MSS and TM subsystems of LANDSAT 4 and 5 satellites. Results include the effective wavelength, the bandpass, the wavelength limits, and the normalized responsivity for each spectral channel. Temperature coefficients for TM PF channel 6 were also derived. The moments normalization method used yields sensor parameters whose derivation is independent of source characteristics (i.e., incident solar spectral irradiance, atmospheric transmittance, or ground reflectance). The errors expected using these parameters are lower than those expected using other normalization methods.

On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales

NASA Astrophysics Data System (ADS)

Härer, Stefan; Bernhardt, Matthias; Siebers, Matthias; Schulz, Karsten

2018-05-01

Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.

Galileo satellite antenna modeling

NASA Astrophysics Data System (ADS)

Steigenberger, Peter; Dach, Rolf; Prange, Lars; Montenbruck, Oliver

2015-04-01

The space segment of the European satellite navigation system Galileo currently consists of six satellites. Four of them belong to the first generation of In-Orbit Validation (IOV) satellites whereas the other two are Full Operational Capability (FOC) satellites. High-precision geodetic applications require detailed knowledge about the actual phase center of the satellite and receiver antenna. The deviation of this actual phase center from a well-defined reference point is described by phase center offsets (PCOs) and phase center variations (PCVs). Unfortunately, no public information is available about the Galileo satellite antenna PCOs and PCVs, neither for the IOV, nor the FOC satellites. Therefore, conventional values for the IOV satellite antenna PCOs have been adopted for the Multi-GNSS experiment (MGEX) of the International GNSS Service (IGS). The effect of the PCVs is currently neglected and no PCOs for the FOC satellites are available yet. To overcome this deficiency in GNSS observation modeling, satellite antenna PCOs and PCVs are estimated for the Galileo IOV satellites based on global GNSS tracking data of the MGEX network and additional stations of the legacy IGS network. Two completely independent solutions are computed with the Bernese and Napeos software packages. The PCO and PCV values of the individual satellites are analyzed and the availability of two different solutions allows for an accuracy assessment. The FOC satellites are built by a different manufacturer and are also equipped with another type of antenna panel compared to the IOV satellites. Signal transmission of the first FOC satellite has started in December 2014 and activation of the second satellite is expected for early 2015. Based on the available observations PCO estimates and, optionally PCVs of the FOC satellites will be presented as well. Finally, the impact of the new antenna model on the precision and accuracy of the Galileo orbit determination is analyzed.

Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

NASA Astrophysics Data System (ADS)

Lasaponara, R.; Masini, n.

2012-04-01

The paper focus on the setting up of a methodology for analyzing cultural landscapes to extract information about ancient civilization settlements, land-use variations, stratified anthropogenic environment, human impacts on landscape, as well as climate driven changes over short, medium, and long periods of time. The analysis of cultural landscape along with its protection and preservation strategies requires the contribution of integrated disciplines and data source, and, above all, the fusion of multi-temporal and multi dimensional data available from different sources. In this contest satellite time series may help us in improve knowledge content of cultural landscape and heritage . The methodology approach we devised is focused on multitemporal/multisource/multiscale data analysis as a support for extracting (i) archaeological settlements and (ii) potential ancient land-use patterning. To these aims, DTM from SRTM and ASTER along multispectral data from TM, ASTER and Quikbird have been used. In order to make the satellite data more meaningful and more exploitable for investigations, reliable data processing have been carried out. Over the years a great variety of digital image enhancement techniques have been devised for specific application fields according to data availability. Nevertheless, only recently these methods have captured great attention also in the field of archaeology for an easier extraction of quantitative information using effective and reliable semiautomatic data processing. The setting up of fully-automatic methodologies is a big challenge to be strategically addressed by research communities in the next years. Multitemporal, multiscale and multisensor satellite data sets can provide useful tool for extracting information and traces related both to modern and ancient civilizations still fossilized in the modern landscape. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1): 53-60.

Estimating Soil Moisture from Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

1998-01-01

Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data and used to derive the one-way canopy transmissivity. Using a simple radiative transfer model, this information was combined with horizontally polarized 6.6 GHz SMMR observations to derive a 9-year time series of soil moisture for all of Spain at a one quarter degree spatial scale. Both day and night SMMR observations were used independently, in order to check the consistency of the results. A first order Fourier Transform was performed on the mean monthly soil moisture values to identify major characteristics of time series such as trend, amplitude, and phase shift.

Validation of OMPS Ozone Profile Data with Expanded Dataset from Brewer and Automated Dobson Network.

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I.; Weatherhead, E.; Cede, A.; Oltmans, S. J.; Kireev, S.; Maillard, E.; Bhartia, P. K.; Flynn, L. E.

2005-12-01

The first NPOESS satellite is scheduled to be launched in 2010 and will carry the Ozone Mapping and Profiler Suite (OMPS) instruments for ozone monitoring. Prior this, the OMPS instruments and algorithms will be tested by flight on the NPOESS/NPP satellite, scheduled for launch in 2008. Pre-launch planning for validation, post launch data validation and verification of the nadir and limb profile algorithm are key components for insuring that the NPOESS will produce a high quality, reliable ozone profile data set. The heritage of satellite instrument validation (TOMS, SBUV, GOME, SCIAMACHY, SAGE, HALOE, ATMOS, etc) has always relied upon surface-based observations. While the global coverage of satellite observations is appealing for validating another satellite, there is no substitute for the hard reference point of a ground-based system such as the Dobson or Brewer network, whose instruments are routinely calibrated and intercompared to standard references. The standard solar occultation instruments, SAGE II and HALOE are well beyond their planned lifetimes and might be inoperative during the OMPS period. The Umkehr network has been one of the key data sets for stratospheric ozone trend calculations and has earned its place as a benchmark network for stratospheric ozone profile observations. The normalization of measurements at different solar zenith angle (SZAs) to the measurement at the smallest SZA cancels out many calibration parameters, including the extra-terrestrial solar flux and instrumental constant, thus providing a "self-calibrating" technique in the same manner relied upon by the occultation sensors on satellites. Moreover, the ground-based Umkehr measurement is the only technique that provides data with the same altitude resolution and in the same units (DU) as do the UV-nadir instruments (SBUV-2, GOME-2, OMPS-nadir), i.e., as ozone amount in pressure layers, whereas, occultation instruments measure ozone density with height. A new Umkehr algorithm will enhance the information content of the retrieved profiles and extend the applicability of the technique. Automated Dobson and Brewer instruments offer the potential for greatly expanded network of Umkehr observations once the new algorithm is applied. We will discuss the new algorithm development and present results of its performance in comparisons of retrievals between co-located Brewer and Dobson ozone profiles measured at Arosa station in Switzerland.

Inter-Satellite Calibration Linkages for the Visible and Near-Infrared Channels of the Advanced Very High Resolution Radiometer on the NOAA-7, -9, and -11 Spacecraft. Revised

NASA Technical Reports Server (NTRS)

NagarajaRao, C. R.; Chen, J.

1996-01-01

The post-launch degradation of the visible (channel 1: 0.58- 068 microns) and near-infrared (channel 2: approx. 0.72 - l.l microns) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-7, -9, and -11 Polar-orbiting Operational Environmental Satellites (POES) was estimated using the south-eastern part of the Libyan Desert as a radiometrically stable calibration target. The relative annual degradation rates, in per cent, for the two channels are, respectively: 3.6 and 4.3 (NOAA-7); 5.9 and 3.5 (NOAA-9); and 1.2 and 2.0 (NOAA-11). Using the relative degradation rates thus determined, in conjunction with absolute calibrations based on congruent path aircraft/satellite radiance measurements over White Sands, New Mexico (USA), the variation in time of the absolute gain or slope of the AVHRR on NOAA-9 was evaluated. Inter-satellite calibration linkages were established, using the AVHRR on NOAA-9 as a normalization standard. Formulae for the calculation of calibrated radiances and albedos (AVHRR usage), based on these interlinkages, are given for the three AVHRRs.

A laboratory system for the investigation of rain fade compensation techniques for Ka-band satellites

NASA Technical Reports Server (NTRS)

Svoboda, James S.; Kachmar, Brian A.

1993-01-01

The design and performance of a rain fade simulation/counteraction system on a laboratory simulated 30/20 GHz, time division multiple access (TDMA) satellite communications testbed is evaluated. Severe rain attenuation of electromagnetic radiation at 30/20 GHz occurs due to the carrier wavelength approaching the water droplet size. Rain in the downlink path lowers the signal power present at the receiver, resulting in a higher number of bit errors induced in the digital ground terminal. The laboratory simulation performed at NASA Lewis Research Center uses a programmable PIN diode attenuator to simulate 20 GHz satellite downlink geographic rain fade profiles. A computer based network control system monitors the downlink power and informs the network of any power threshold violations, which then prompts the network to issue commands that temporarily increase the gain of the satellite based traveling wave tube (TWT) amplifier. After the rain subsides, the network returns the TWT to the normal energy conserving power mode. Bit error rate (BER) data taken at the receiving ground terminal serves as a measure of the severity of rain degradation, and also evaluates the extent to which the network can improve the faded channel.

Determination of Spring Onset and Growing Season Duration using Satellite Measurements

NASA Technical Reports Server (NTRS)

Min, Q.; Lin, Bing

2006-01-01

An integrated approach to retrieve microwave emissivity difference vegetation index (EDVI) over land regions has been developed from combined multi-platform/multi-sensor satellite measurements, including SSM/I measurements. A possible relationship of the remotely sensed EDVI and the leaf physiology of canopy is exploited at the Harvard Forest site for two growing seasons. This study finds that the EDVI is sensitive to leaf development through vegetation water content of the crown layer of the forest canopy, and has demonstrated that the spring onset and growing season duration can be determined accurately from the time series of satellite estimated EDVI within uncertainties about 3 and 7 days for spring onsets and growing season duration, respectively, compared to in-situ observations. The leaf growing stage may also be quantitatively monitored by a normalized EDVI. Since EDVI retrievals from satellite are generally possible during both daytime and nighttime under non-rain conditions, the EDVI technique studied here may provide higher temporal resolution observations for monitoring the onset of spring and the duration of growing season compared to currently operational satellite methods.

Hemispheric differences in PMC altitudes observed by the AIM satellite for the 2007/2008 seasons

NASA Astrophysics Data System (ADS)

Russell, J. M.; Bailey, S. M.; Gordley, L. L.; Hervig, M. E.; Stevens, M. H.; Thomas, G. E.; Rong, P.

2008-05-01

The Aeronomy of Ice in the Mesosphere (AIM) mission was launched from Vandenberg Air Force Base in California at 1:26:03 PDT on April 25, 2007 becoming the first satellite mission dedicated to the study of noctilucent clouds. A Pegasus XL rocket launched the satellite into a near perfect 600 km sun synchronous circular orbit providing an ideal injection for conducting AIM science studies. This paper focuses on hemispheric differences in polar mesospheric cloud (PMC) altitudes observed by the Solar Occultation For Ice Experiment (SOFIE) for the 2007 northern hemisphere season and the 2007/2008 southern hemisphere season. Results show PMC peak altitude differences of 1 km to 3 km depending on time in the season which is larger than previous ground-based and satellite results (~1 km). SOFIE data show that altitude differences are dependent on time within the season and that the differences are correlated with mesopause height. Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature data measured from the TIMED satellite over the 2003 to 2007 period show that hemispheric differences in the summer mesopause height were unusually large for part of the 2007 PMC season, consistent with the 3 km height difference in PMCs during that time.

Comparison of Ground-Based and Satellite-Derived Solar UV Index Levels at Six South African Sites.

PubMed

Cadet, Jean-Maurice; Bencherif, Hassan; Portafaix, Thierry; Lamy, Kévin; Ncongwane, Katlego; Coetzee, Gerrie J R; Wright, Caradee Y

2017-11-14

South Africa has been measuring the ground-based solar UV index for more than two decades at six sites to raise awareness about the impacts of the solar UV index on human health. This paper is an exploratory study based on comparison with satellite UV index measurements from the OMI/AURA experiment. Relative UV index differences between ground-based and satellite-derived data ranged from 0 to 45% depending on the site and year. Most of time, these differences appear in winter. Some ground-based stations' data had closer agreement with satellite-derived data. While the ground-based instruments are not intended for long-term trend analysis, they provide UV index information for public awareness instead, with some weak signs suggesting such long-term trends may exist in the ground-based data. The annual cycle, altitude, and latitude effects clearly appear in the UV index data measured in South Africa. This variability must be taken into account for the development of an excess solar UV exposure prevention strategy.

Comparison of Ground-Based and Satellite-Derived Solar UV Index Levels at Six South African Sites

PubMed Central

Cadet, Jean-Maurice; Bencherif, Hassan; Portafaix, Thierry; Lamy, Kévin; Ncongwane, Katlego; Coetzee, Gerrie J. R.; Wright, Caradee Y.

2017-01-01

South Africa has been measuring the ground-based solar UV index for more than two decades at six sites to raise awareness about the impacts of the solar UV index on human health. This paper is an exploratory study based on comparison with satellite UV index measurements from the OMI/AURA experiment. Relative UV index differences between ground-based and satellite-derived data ranged from 0 to 45% depending on the site and year. Most of time, these differences appear in winter. Some ground-based stations’ data had closer agreement with satellite-derived data. While the ground-based instruments are not intended for long-term trend analysis, they provide UV index information for public awareness instead, with some weak signs suggesting such long-term trends may exist in the ground-based data. The annual cycle, altitude, and latitude effects clearly appear in the UV index data measured in South Africa. This variability must be taken into account for the development of an excess solar UV exposure prevention strategy. PMID:29135965

Comparisons of Radiative Flux Distributions from Satellite Observations and Global Models

NASA Astrophysics Data System (ADS)

Raschke, Ehrhard; Kinne, Stefan; Wild, Martin; Stackhouse, Paul; Rossow, Bill

2014-05-01

Radiative flux distributions at the top of the atmosphere (TOA) and at the surface are compared between typical data from satellite observations and from global modeling. Averages of CERES, ISCCP and SRB data-products (for the same 4-year period) represent satellite observations. Central values of IPCC-4AR output (over a 12-year period) represent global modeling. At TOA, differences are dominated by differences for cloud-effects, which are extracted from the differences between all-sky and clear-sky radiative flux products. As satellite data are considered as TOA reference, these differences document the poor representation of clouds in global modeling, especially for low altitude clouds over oceans. At the surface the differences, caused by the different cloud treatment are overlaid by a general offset. Satellite products suggest a ca 15Wm-2 stronger surface net-imbalance (and with it stronger precipitation). Since surface products of satellite and modeling are based on simulations and many assumptions, this difference has remained an open issue. BSRN surface monitoring is too short and too sparsely distributed for clear answers to provide a reliable basis for validation.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms

NASA Technical Reports Server (NTRS)

Balch, William; Evans, Robert; Brown, Jim; Feldman, Gene; Mcclain, Charles; Esaias, Wayne

1992-01-01

Global pigment and primary productivity algorithms based on a new data compilation of over 12,000 stations occupied mostly in the Northern Hemisphere, from the late 1950s to 1988, were tested. The results showed high variability of the fraction of total pigment contributed by chlorophyll, which is required for subsequent predictions of primary productivity. Two models, which predict pigment concentration normalized to an attenuation length of euphotic depth, were checked against 2,800 vertical profiles of pigments. Phaeopigments consistently showed maxima at about one optical depth below the chlorophyll maxima. CZCS data coincident with the sea truth data were also checked. A regression of satellite-derived pigment vs ship-derived pigment had a coefficient of determination. The satellite underestimated the true pigment concentration in mesotrophic and oligotrophic waters and overestimated the pigment concentration in eutrophic waters. The error in the satellite estimate showed no trends with time between 1978 and 1986.

Search for Best Astronomical Observatory Sites in the MENA Region using Satellite Measurements

NASA Astrophysics Data System (ADS)

Abdelaziz, G.; Guebsi, R.; Guessoum, N.; Flamant, C.

2017-06-01

We perform a systematic search for astronomical observatory sites in the MENA (Middle-East and North Africa) region using space-based data for all the relevant factors, i.e. altitude (DEM), cloud fraction (CF), light pollution (NTL), precipitable water vapor (PWV), aerosol optical depth (AOD), relative humidity (RH), wind speed (WS), Richardson Number (RN), and diurnal temperature range (DTR). We look for the best locations overall even where altitudes are low (the threshold that we normally consider being 1,500 m) or where the combination of the afore-mentioned determining factors had previously excluded all locations in a given country. In this aim, we use the rich data that Earth-observing satellites provide, e.g. the Terra and Aqua multi-national NASA research satellites, with their MODIS (Moderate Resolution Imaging Spectroradiometer) and AIRS (Atmospheric Infrared Sounder) instruments, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS), and other products from climate diagnostics archives (e.g. MERRA). We present preliminary results on the best locations for the region.

Robust Satellite Techniques for monitoring earth emitted radiation in the Japanese seismic area by using MTSAT observations in the TIR spectral range

NASA Astrophysics Data System (ADS)

Genzano, Nicola; Filizzola, Carolina; Hattori, Katsumi; Lisi, Mariano; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2016-04-01

Since eighties, the fluctuations of Earth's thermally emitted radiation, measured by satellite sensors operating in the thermal infrared (TIR) spectral range, have been associated with the complex process of preparation for major earthquakes. But, like other claimed earthquake precursors (seismological, physical, chemical, biological, etc.) they have been for long-time considered with some caution by scientific community. The lack of a rigorous definition of anomalous TIR signal fluctuations and the scarce attention paid to the possibility that other causes (e.g. meteorological) different from seismic activity could be responsible for the observed TIR variations were the main causes of such skepticism. Compared with previously proposed approaches the general change detection approach, named Robust Satellite Techniques (RST), showed good ability to discriminate anomalous TIR signals possibly associated to seismic activity, from the normal variability of TIR signal due to other causes. Thanks to its full exportability on different satellite packages, since 2001 RST has been implemented on TIR images acquired by polar (e.g. NOAA-AVHRR, EOS -MODIS) and geostationary (e.g. MSG-SEVIRI, NOAA-GOES/W, GMS-5/VISSR) satellite sensors, in order to verify the presence (or absence) of TIR anomalies in presence (absence) of earthquakes (with M>4) in different seismogenic areas around the world (e.g. Italy, Greece, Turkey, India, Taiwan, etc.). In this paper, the RST data analysis approach has been implemented on TIR satellite records collected over Japan by the geostationary satellite sensor MTSAT (Multifunctional Transport SATellites) and RETIRA (Robust Estimator of TIR Anomalies) index was used to identify Significant Sequences of TIR Anomalies (SSTAs) in a possible space-time relations with seismic events. Achieved results will be discussed in the perspective of a multi-parametric approach for a time-Dependent Assessment of Seismic Hazard (t-DASH).

The initial conceptualization and design of a meteorological satellite

NASA Technical Reports Server (NTRS)

Greenfield, S. M.

1982-01-01

The meteorological satellite had its substantive origin in the analytical process that helped initiate America's military satellite program. Its impetus lay in the desire to acquire current meteorological information in large areas for which normal meteorological observational data were not available on a day-to-day basis. Serious consideration was given to the feasibility of reconnaissance from meteorological satellites. The conceptualization of a meteorological satellite is discussed along with the early research which gave substance to that concept.

A review of spatial downscaling of satellite remotely sensed soil moisture

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Merlin, Olivier; Verhoest, Niko E. C.

2017-06-01

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.

Coordinates of features on the Galilean satellites

NASA Technical Reports Server (NTRS)

Davies, M. E.; Katayama, F. Y.

1980-01-01

The coordinate systems of each of the Galilean satellites are defined and coordinates of features seen in the Voyager pictures of these satellites are presented. The control nets of the satellites were computed by means of single block analytical triangulations. The normal equations were solved by the conjugate iterative method which is convenient and which converges rapidly as the initial estimates of the parameters are very good.

S-NPP CrIS Full Resolution Sensor Data Record Processing and Evaluations

NASA Astrophysics Data System (ADS)

Chen, Y.; Han, Y.; Wang, L.; Tremblay, D. A.; Jin, X.; Weng, F.

2014-12-01

The Cross-track Infrared Sounder (CrIS) on Suomi National Polar-orbiting Partnership Satellite (S-NPP) is a Fourier transform spectrometer. It provides a total of 1305 channels in the normal mode for sounding the atmosphere. CrIS can also be operated in the full spectral resolution (FSR) mode, in which the MWIR and SWIR band interferograms are recorded with the same maximum path difference as the LWIR band and with spectral resolution of 0.625 cm-1 for all three bands (total 2211 channels). NOAA will operate CrIS in FSR mode in December 2014 and the Joint Polar Satellite System (JPSS). Up to date, the FSR mode has been commanded three times in-orbit (02/23/2012, 03/12/2013, and 08/27/2013). Based on CrIS Algorithm Development Library (ADL), CrIS full resolution Processing System (CRPS) has developed to generate the FSR Sensor Data Record (SDR). This code can also be run for normal mode and truncation mode SDRs with recompiling. Different calibration approaches are implemented in the code in order to study the ringing effect observed in CrIS normal mode SDR and to support to select the best calibration algorithm for J1. We develop the CrIS FSR SDR Validation System to quantify the CrIS radiometric and spectral accuracy, since they are crucial for improving its data assimilation in the numerical weather prediction, and for retrieving atmospheric trace gases. In this study, CrIS full resolution SDRs are generated from CRPS using the data collected from FSR mode of S-NPP, and the radiometric and spectral accuracy are assessed by using the Community Radiative Transfer Model (CRTM) and European Centre for Medium-Range Weather Forecasts (ECMWF) forecast fields. The biases between observation and simulations are evaluated to estimate the FOV-2-FOV variability and bias under clear sky over ocean. Double difference method and Simultaneous Nadir Overpass (SNO) method are also used to assess the CrIS radiance consistency with well-validated IASI. Two basic frequency validation methods (absolute and relative spectral validations) are used to assess the CrIS spectral accuracy. Results show that CrIS SDRs from FSR have similar radiometric and spectral accuracy as those from normal mode.

A COMPARISON OF THE SALINITY REGIME ALONG THE TEXAS COAST WITH TERRESTRIAL VEGETATION GREENNESS AND WATER USE IN THE GALVESTON BAY WATERSHED USING REMOTING SENSING

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (A VHRR) flown on NOAA satellites. NDVI variability was compared with reg...

TERRESTRIAL VEGETATION GREENNESS OF THE LOWER GALVESTON BAY WATERSHED FROM SATELLITE REMOTE SENSING AND ITS RELATION TO WATER AND THE SALINITY REGIME OF THE GALVESTON BAY ESTUARY

EPA Science Inventory

Spatial and temporal variability of vegetation greenness have been determined for coastal Texas using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR). Results are presented on relationships between grou...

Detecting channel riparian vegetation response to best-management-practices implementation in ephemeral streams with the use of spot high-resolution visible imagery

USGS Publications Warehouse

Kamp, Kendall Vande; Rigge, Matthew B.; Troelstrup, Nels H.; Smart, Alexander J.; Wylie, Bruce

2013-01-01

Heavily grazed riparian areas are commonly subject to channel incision, a lower water table, and reduced vegetation, resulting in sediment delivery above normal regimes. Riparian and in-channel vegetation functions as a roughness element and dissipates flow energy, maintaining stable channel geometry. Ash Creek, a tributary of the Bad River in western South Dakota contains a high proportion of incised channels, remnants of historically high grazing pressure. Best management practices (BMP), including off-stream watering sources and cross fencing, were implemented throughout the Bad River watershed during an Environmental Protection Agency (EPA) 319 effort to address high sediment loads. We monitored prairie cordgrass (Spartina pectinata Link) establishment within stream channels for 16 yr following BMP implementation. Photos were used to group stream reaches (n = 103) subjectively into three classes; absent (estimated  40% cover; n = 16) based on the relative amount of prairie cordgrass during 2010 assessments of ephemeral channels. Reaches containing drainage areas of 0.54 to 692 ha were delineated with the use of 2010 National Agriculture Imagery Program (NAIP) imagery. Normalized difference vegetation index (NDVI) values were extracted from 5 to 39 sample points proportional to reach length using a series of Satellite Pour l'Observation de la Terre (SPOT) satellite imagery. Normalized NDVI (nNDVI) of 2 152 sample points were determined from pre- and post-BMP images. Mean nNDVI values for each reach ranged from 0.33 to 1.77. ANOVA revealed significant increase in nNDVI in locations classified as present prairie cordgrass cover following BMP implementation. Establishment of prairie cordgrass following BMP implementation was successfully detected remotely. Riparian vegetation such as prairie cordgrass adds channel roughness that reduces the flow energy responsible for channel degradation.

Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.

PubMed

Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

2013-05-01

Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.

SASS measurements of the Ku-band radar signature of the ocean

NASA Technical Reports Server (NTRS)

Schroeder, L. C.; Grantham, W. L.; Mitchell, J. L.; Sweet, J. L.

1982-01-01

SeaSat-A Satellite Scatterometer (SASS) measurements of normalized radar cross section (NRCS) have been merged with high quality surface-wind fields based on in situ, to create a large data base of NRCS-wind signature data. These data are compared to the existing NRCS-wind model used by the SASS to infer winds. Falso-color maps of SASS NRCS and ocean winds from multiple orbits show important synoptic trends.

The Application of Jason-Measurements to Estimate the Global Near Surface Ocean Circulation for Climate Research

NASA Technical Reports Server (NTRS)

Niiler, Pearn P.

2004-01-01

The scientific objective of this research program were to utilize drifter and satellite sea level data for the determination of time mean and time variable surface currents of the global ocean. To accomplish these tasks has required the processing of drifter data to include a wide variety of different configurations of drifters into a uniform format and to process the along track satellite altimeter data for computing the geostrophic current components normal to the track. These tasks were accomplished, which resulted in an increase of drifter data by about 40% and the development of new algorithms for obtaining satellite derived geostrophic velocity data that was consistent with the drifter observations of geostrophic time-variable currents. The methodologies and the research results using these methodologies were reported in the publications listed in this paper.

The use of NOAA AVHRR data for assessment of the urban heat sland effect

USGS Publications Warehouse

Gallo, K.P.; McNab, A. L.; Karl, Thomas R.; Brown, Jesslyn F.; Hood, J. J.; Tarpley, J.D.

1993-01-01

A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.

Design Concepts for a Small Space-Based GEO Relay Satellite for Missions Between Low Earth and near Earth Orbits

NASA Technical Reports Server (NTRS)

Bhasin, Kul B.; Warner, Joseph D.; Oleson, Steven; Schier, James

2014-01-01

The main purpose of the Small Space-Based Geosynchronous Earth orbiting (GEO) satellite is to provide a space link to the user mission spacecraft for relaying data through ground networks to user Mission Control Centers. The Small Space Based Satellite (SSBS) will provide services comparable to those of a NASA Tracking Data Relay Satellite (TDRS) for the same type of links. The SSBS services will keep the user burden the same or lower than for TDRS and will support the same or higher data rates than those currently supported by TDRS. At present, TDRSS provides links and coverage below GEO; however, SSBS links and coverage capability to above GEO missions are being considered for the future, especially for Human Space Flight Missions (HSF). There is also a rising need for the capability to support high data rate links (exceeding 1 Gbps) for imaging applications. The communication payload on the SSBS will provide S/Ka-band single access links to the mission and a Ku-band link to the ground, with an optical communication payload as an option. To design the communication payload, various link budgets were analyzed and many possible operational scenarios examined. To reduce user burden, using a larger-sized antenna than is currently in use by TDRS was considered. Because of the SSBS design size, it was found that a SpaceX Falcon 9 rocket could deliver three SSBSs to GEO. This will greatly reduce the launch costs per satellite. Using electric propulsion was also evaluated versus using chemical propulsion; the power system size and time to orbit for various power systems were also considered. This paper will describe how the SSBS will meet future service requirements, concept of operations, and the design to meet NASA users' needs for below and above GEO missions. These users' needs not only address the observational mission requirements but also possible HSF missions to the year 2030. We will provide the trade-off analysis of the communication payload design in terms of the number of links looking above and below GEO; the detailed design of a GEO SSBS spacecraft bus and its accommodation of the communication payload, and a summary of the trade study that resulted in the selection of the Falcon 9 launch vehicle to deploy the SSBS and its impact on cost reductions per satellite. ======================================================================== Several initiatives have taken place within NASA1 and international space agencies2 to create a human exploration strategy for expanding human presence into the solar system; these initiatives have been driven by multiple factors to benefit Earth. Of the many elements in the strategy one stands out: to send robotic and human missions to destinations beyond Low Earth Orbit (LEO), including cis-lunar space, Near-Earth Asteroids (NEAs), the Moon, and Mars and its moons.3, 4 The time frame for human exploration to various destinations, based on the public information available,1,4 is shown in Figure 1. Advance planning is needed to define how future space communications services will be provided in the new budget environment to meet future space communications needs. The spacecraft for these missions can be dispersed anywhere from below LEO to beyond GEO, and to various destinations within the solar system. NASA's Space Communications and Navigation (SCaN) program office provides communication and tracking services to space missions during launch, in-orbit testing, and operation phases. Currently, SCaN's space networking relay satellites mainly provide services to users below GEO, at Near Earth Orbit (NEO), below LEO, and in deep space. The potential exists for using a space-based relay satellite, located in the vicinity of various solar system destinations, to provide communication space links to missions both below and above its orbit. Such relays can meet the needs of human exploration missions for maximum connectivity to Earth locations and for reduced latency. In the past, several studies assessed the ability of satellite-based relays working above GEO in conjunction with Earth ground stations. Many of these focused on the trade between space relay and direct-to-Earth station links5,6,7. Several others focused on top-level architecture based on relays at various destinations8,9,10,11,12. Much has changed in terms of microwave and optical technology since the publication of the referenced papers; Ka-band communication systems are being deployed, optical communication is being demonstrated, and spacecraft buses are becoming increasingly more functional and operational. A design concept study was undertaken to access the potential for deploying a Small Space-Based Satellite (SSBS) relay capable of serving missions between LEO and NEO. The needs of future human exploration missions were analyzed, and a notional relay-based architecture concept was generated as shown in Fig. 1. Relay satellites in Earth through cis-Lunar orbits are normally located in stable orbits requiring low fuel consumption. Relay satellites for Mars orbit are normally selected based on the mission requirement and projected fuel consumption. Relay satellites have extreme commonalities of functions between them, differing only in the redundancy and frequencies used; therefore, the relay satellite in GEO was selected for further analysis since it will be the first step in achieving a relay-based architecture for human exploration missions (see Fig.Figure 2). The mission design methodology developed by the Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team13 was used to produce the satellite relay design and to perform various design trades. At the start of the activity, the team was provided with the detailed concept of the notional architecture and the system and communication payload drivers.

Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

USGS Publications Warehouse

Wallace, Cynthia S.A.; Villarreal, Miguel; van Riper, Charles

2013-01-01

We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using Fourier harmonic analysis to analyze the waveform of the annual NDVI profile at each pixel. We modeled the spatial distribution of Yellow-billed Cuckoo habitat by coupling the field data of Cuckoo presence or absence and point-based samples of riparian and cottonwood-willow vegetation types with satellite phenometrics for 1998. Models were validated using field and satellite data collected in 1999. The results indicate that Yellow-billed Cuckoo occupy locations within their preferred habitat that exhibit peak greenness after the start of the summer monsoon and are greener and more dynamic than “average” habitat. Identification of preferred phenotypes within recognized habitat areas can be used to refine habitat models, inform predictions of habitat response to climate change, and suggest adaptation strategies.

A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom

NASA Astrophysics Data System (ADS)

Page, Benjamin P.; Kumar, Abhishek; Mishra, Deepak R.

2018-04-01

As the frequency of cyanobacterial harmful algal blooms (CyanoHABs) become more common in recreational lakes and water supply reservoirs, demand for rapid detection and temporal monitoring will be imminent for effective management. The goal of this study was to demonstrate a novel and potentially operational cross-satellite based protocol for synoptic monitoring of rapidly evolving and increasingly common CyanoHABs in inland waters. The analysis involved a novel way to cross-calibrate a chlorophyll-a (Chl-a) detection model for the Landsat-8 OLI sensor from the relationship between the normalized difference chlorophyll index and the floating algal index derived from Sentinel-2A on a coinciding overpass date during the summer CyanoHAB bloom in Utah Lake. This aided in the construction of a time-series phenology of the Utah Lake CyanoHAB event. Spatio-temporal cyanobacterial density maps from both Sentinel-2A and Landsat-8 sensors revealed that the bloom started in the first week of July 2016 (July 3rd, mean cell count: 9163 cells/mL), reached peak in mid-July (July 15th, mean cell count: 108176 cells/mL), and reduced in August (August 24th, mean cell count: 9145 cells/mL). Analysis of physical and meteorological factors suggested a complex interaction between landscape processes (high surface runoff), climatic conditions (high temperature, high rainfall followed by negligible rainfall, stable wind), and water quality (low water level, high Chl-a) which created a supportive environment for triggering these blooms in Utah Lake. This cross satellite-based monitoring methods can be a great tool for regular monitoring and will reduce the budget cost for monitoring and predicting CyanoHABs in large lakes.

Spatial and decadal variations in satellite-based terrestrial evapotranspiration and drought over Inner Mongolia Autonomous Region of China during 1982-2009

NASA Astrophysics Data System (ADS)

Zhang, Zhaolu; Kang, Hui; Yao, Yunjun; Fadhil, Ayad M.; Zhang, Yuhu; Jia, Kun

2017-12-01

Evapotranspiration ( ET) plays an important role in exchange of water budget and carbon cycles over the Inner Mongolia autonomous region of China (IMARC). However, the spatial and decadal variations in terrestrial ET and drought over the IMARC in the past was calculated by only using sparse meteorological point-based data which remain quite uncertain. In this study, by combining satellite and meteorology datasets, a satellite-based semi-empirical Penman ET (SEMI-PM) algorithm is used to estimate regional ET and evaporative wet index (EWI) calculated by the ratio of ET and potential ET ( PET) over the IMARC. Validation result shows that the square of the correlation coefficients (R2) for the four sites varies from 0.45 to 0.84 and the root-mean-square error (RMSE) is 0.78 mm. We found that the ET has decreased on an average of 4.8 mm per decade (p=0.10) over the entire IMARC during 1982-2009 and the EWI has decreased on an average of 1.1% per decade (p=0.08) during the study period. Importantly, the patterns of monthly EWI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from 1982 to 2009, indicating EWI can be used to monitor regional surface drought with high spatial resolution. In high-latitude ecosystems of northeast region of the IMARC, both air temperature (Ta) and incident solar radiation (Rs) are the most important parameters in determining ET. However, in semiarid and arid areas of the central and southwest regions of the IMARC, both relative humidity (RH) and normalized difference vegetation index (NDVI) are the most important factors controlling annual variation of ET.

Grazed grass was estimated via satellite images better then mowed grass

NASA Astrophysics Data System (ADS)

Koncz, Péter; Gubányi, András; Gecse, Bernadett; Tolnai, Márton; Pintér, Krisztina; Kertész, Péter; Fóti, Szilvia; Balogh, János; Nagy, Zoltán

2017-04-01

Precise livestock management requires objective alert system about the potential threats of overgrazing and intensive mowing. This kind of system could be based on the estimation of the amount of grazed and mowed biomass by remote sensing of vegetation indices. In our study we used the Normalized Difference Vegetation Index (NDVI) derived from Landsat 7 and 8 satellites to establish a regression between the vegetation index and the biomass (cut from ten, 40× 40 cm plots, during 52 measurement campaigns, 2011-2013) in a semi-arid grassland of Hungary, Bugac. Based on the regression time series of NDVI data were converted into biomass data in case of grazed and mowed areas (2011?2016). Biomass changes, inferred from NDVI data, were compared to the estimated grazed (based on daily dry matter uptake of cattle) and measured mowed (weighted) biomass. We found significant correlation between the NDVI and the total biomass (r2=0.6, p<0.05, n=52, RMSE=52.8 g m-2) and a stronger one between the NDVI and the green biomass (r2=0.75, p<0.05, n=52, RMSE=36.8 g m-2). We found that the amount of grazed biomass based on dry matter uptake was in close agreement with the biomass changes inferred from NDVI data (r2=0.42, p=0.11, n=7, RMSE=25.2 g m-2). However, there was no correlation between the biomass of the measured hay and the biomass inferred from NDVI data (r2=0.16, p=0.49, n=5, RMSE=67.4 g m-2). This was most probably due to the fact that mowing is a sudden, while grazing is a prolonged event, hence satellite data are less likely to be available before and after the mowing events (i.e. within days) compared to the grazing periods which usually lasts for months (only 12±2 satellite images were suitable per year). Therefore, NDVI changes are more accurately captured when grazing is observed than when mowing. We concluded that NDVI data from satellite images could be used to estimate the amount of grazed biomass, however to estimate the amount of mowed hay more frequent data coverage would be needed.

Monitoring global vegetation using Nimbus-7 37 GHz data - Some empirical relations

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Tucker, C. J.

1987-01-01

The difference of the vertically and horizontally polarized brightness temperatures observed by the 37 GHz channel of the SMMR on board the Nimbus-7 satellite are correlated temporally with three indicators of vegetation density, namely the temporal variation of the atmospheric CO2 concentration at Mauna Loa (Hawaii), rainfall over the Sahel and the normalized difference vegetation index derived from the AVHRR on board the NOAA-7 satellite. SMMR 37 GHz and AVHRR provide complementary data sets for monitoring global vegetation, the 37 GHz data being more suitable for arid and semiarid regions as these data are more sensitive to changes in sparse vegetation. The 37-GHz data might be useful for understanding desertification and indexing Co2 exchange between the biosphere and the atmosphere.

Defunct Satellites, Rotation Rates and the YORP Effect

NASA Astrophysics Data System (ADS)

Albuja, A.; Scheeres, D.

2013-09-01

With the increasing number of defunct satellites and associated space debris found in orbit, it is important to understand the dynamics governing the motion of these bodies. Orbit perturbations are coupled with the body's attitude dynamics; therefore it is necessary to have an understanding of attitude dynamics for accurate predictions of debris orbits. Additionally, it is important to have a clear idea of the rotational dynamics of such objects for removal and mitigation purposes. The Yarkovsky-O'Keefe-Raszvieskii-Paddack (YORP) effect has been well studied and credited for the observed secular change in angular velocity of various asteroids. The YORP effect arises due to sunlight being either absorbed and re-emitted as energy or being directly reflected, creating a net downward force on the body's surface. As a result of both of these factors, an overall torque is created on the body yielding a change in the rotational dynamics. While YORP has been extensively studied for asteroids, it has yet to be systematically applied to objects in Earth orbit such as space debris. This paper analyzes the effects of YORP on the obliquity and angular velocity of defunct satellites and other pieces of debris found in Earth orbit. The rotational dynamics are first averaged over the rotational period and next over the orbital period of the Earth, about which the debris is assumed to be orbiting. Using these averaged dynamics, long-term predictions of the evolution of both angular velocity and obliquity are made. In the analysis simulation results are compared to published observational data for defunct satellites. The observed rotation periods of the satellites are used to compute how much torque would be required to obtain such a period only due to YORP. These required torques are compared to the torques that we predict to be acting on these satellites. As an example of what we will present, consider the GEO satellite Gorizont-11. The normalized inferred coefficient for the satellite Gorizont-11 is compared to the computed normalized coefficient for the same satellite. The computed normalized coefficient for Gorizont-11 is 6e-3, while the inferred normalized coefficient for the same satellite is 9e-3. We note that these are of the same order of magnitude, although the real number will be a function of the optical reflectance properties of the bodies, their geometry, etc. The results of this work show that YORP could be the sole cause for the anomalous and rapid rotation of some defunct satellites that has been seen through observations.

Robust satellite techniques for oil spill detection and monitoring

NASA Astrophysics Data System (ADS)

Casciello, D.; Pergola, N.; Tramutoli, V.

Discharge of oil into the sea is one of the most dangerous, among technological hazards, for the maritime environment. In the last years maritime transport and exploitation of marine resources continued to increase; as a result, tanker accidents are nowadays increasingly frequent, continuously menacing the maritime security and safety. Satellite remote sensing could contribute in multiple ways, in particular for what concerns early warning and real-time (or near real-time) monitoring. Several satellite techniques exist, mainly based on the use of SAR (Synthetic Aperture Radar) technology, which are able to recognise, with sufficient accuracy, oil spills discharged into the sea. Unfortunately, such methods cannot be profitably used for real-time detection, because of the low observational frequency assured by present satellite platforms carrying SAR sensors (the mean repetition rate is something like 30 days). On the other hand, potential of optical sensors aboard meteorological satellites, was not yet fully exploited and no reliable techniques have been developed until now for this purpose. Main limit of proposed techniques can be found in the ``fixed threshold'' approach which makes such techniques difficult to implement without operator supervision and, generally, without an independent information on the oil spill presence that could drive the choice of the best threshold. A different methodological approach (RAT, Robust AVHRR Techniques) proposed by Tramutoli (1998) and already successfully applied to several natural and environmental emergencies related to volcanic eruptions, forest fires and seismic activity. In this paper its extension to near real-time detection and monitoring of oil spills by means of NOAA-AVHRR (Advanced Very High Resolution Radiometer) records will be described. Briefly, RAT approach is an automatic change-detection scheme that considers a satellite image as a space-time process, described at each place (x,y) and time t, by the value of the satellite derived measurements V(x,y,t). Generally speaking an Absolute Local Index of Change of the Environment (ALICE) is computed and this index permits to identify signal anomalies, in the space-time domain, as deviations from a normal state preliminarily defined, for each image pixel, (e.g. in terms of time average and standard deviation) on the base only of satellite observations collected during several year in the past, in similar observational conditions (same time of the day, same month of the year). By this way local (i.e. specific for the place and the time of observation) instead than fixed thresholds are automatically set by RAT which permit to discriminate signal anomalies from those variations due to natural or observational condition variability. Using AVHRR observations in the Thermal (TIR) and Middle (MIR) Infrared region, such an approach has been applied to the extended oil spill event, occurred at the end of January 1991 in the Persian Gulf. Preliminary results will be analysed that confirm as the suggested technique is able to detect and monitoring oil spills also in the most difficult observational conditions. Automatic implementation, intrinsic exportability on whatever geographic zone and/or satellite package, high sensitivity also to low intensity signals (i.e. small or thin spills), no need for ancillary information (different form satellite data at hand), seem the most promising merits of the proposed technique. Although these results should be confirmed by further analyses on different events and extended also to other AVHRR spectral bands (VIS, NIR), this work surely encourages to continue the research in this field. Moreover, the complete independence of the RAT approach on the specific sensor and/or satellite system, will ensure its full exportability on the new generation of Earth observation satellite sensors (e.g. SEVIRI-Spinning Enhanced Visible and Infrared Imager onboard Meteosat Second generation satellite, with a repetition rate of 15 minutes and 12 spectral bands) which, thanks to their improved capabilities, could actually guarantee timely, reliable and accurate information.

A Method for Assessing the Quality of Model-Based Estimates of Ground Temperature and Atmospheric Moisture Using Satellite Data

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, Siegfried; Lin, Ching I.; Stajner, Ivanka; Einaudi, Franco (Technical Monitor)

2000-01-01

A method is developed for validating model-based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear-sky longwave fluxes at the top of the Earth-atmosphere system to errors in geophysical parameters. The fluxes include clear-sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 microns (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four-dimensional data assimilation (4-DDA) products. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic clear-sky longwave fluxes from two different 4-DDA data sets. Simple linear regression is used to relate the clear-sky longwave flux discrepancies to discrepancies in ground temperature ((delta)T(sub g)) and broad-layer integrated atmospheric precipitable water ((delta)pw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model-based estimates of clear-sky longwave fluxes. For illustration we analyze the discrepancies in the clear-sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium-Range Weather Forecasts data assimilation system. The analysis of the synthetic clear-sky flux data shows that simple linear regression employing (delta)T(sub g)) and broad layer (delta)pw provides a good approximation to the full radiative transfer calculations, typically explaining more thin 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters, Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (delta)T(sub g) to approx. 20% for the lower tropospheric moisture between 500 hPa and surface. The regression relationships developed from the synthetic flux data, together with CLR and RadWn observed with the Clouds and Earth Radiant Energy System instrument, ire used to assess the quality of the GEOS2 T(sub g) and pw. Results showed that the GEOS2 T(sub g) is too cold over land, and pw in upper layers is too high over the tropical oceans and too low in the lower atmosphere.

Normalized-Difference Snow Index (NDSI)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.

2010-01-01

The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

NASA Astrophysics Data System (ADS)

Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

2010-09-01

In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross-calibration and co-registration. In order to avoid such problems and to generate spatially distributed values of Kc capturing field-specific crop development, the employment of vegetation indices derived from medium resolution MODIS data having a higher temporal sampling has been investigated. The spatial and temporal correlation between NDVI (Normalized Difference Vegetation Index) and crop coefficients for different herbaceous and arboreal cultivations has been investigated to define their relationships. Through this approach site-specific crop coefficients were derived taking into account the effective ground coverage and status. The analysis has been applied on the 2005-2008 time series for the Basilicata region, Southern Italy.

Research on the impact factors of GRACE precise orbit determination by dynamic method

NASA Astrophysics Data System (ADS)

Guo, Nan-nan; Zhou, Xu-hua; Li, Kai; Wu, Bin

2018-07-01

With the successful use of GPS-only-based POD (precise orbit determination), more and more satellites carry onboard GPS receivers to support their orbit accuracy requirements. It provides continuous GPS observations in high precision, and becomes an indispensable way to obtain the orbit of LEO satellites. Precise orbit determination of LEO satellites plays an important role for the application of LEO satellites. Numerous factors should be considered in the POD processing. In this paper, several factors that impact precise orbit determination are analyzed, namely the satellite altitude, the time-variable earth's gravity field, the GPS satellite clock error and accelerometer observation. The GRACE satellites provide ideal platform to study the performance of factors for precise orbit determination using zero-difference GPS data. These factors are quantitatively analyzed on affecting the accuracy of dynamic orbit using GRACE observations from 2005 to 2011 by SHORDE software. The study indicates that: (1) with the altitude of the GRACE satellite is lowered from 480 km to 460 km in seven years, the 3D (three-dimension) position accuracy of GRACE satellite orbit is about 3˜4 cm based on long spans data; (2) the accelerometer data improves the 3D position accuracy of GRACE in about 1 cm; (3) the accuracy of zero-difference dynamic orbit is about 6 cm with the GPS satellite clock error products in 5 min sampling interval and can be raised to 4 cm, if the GPS satellite clock error products with 30 s sampling interval can be adopted. (4) the time-variable part of earth gravity field model improves the 3D position accuracy of GRACE in about 0.5˜1.5 cm. Based on this study, we quantitatively analyze the factors that affect precise orbit determination of LEO satellites. This study plays an important role to improve the accuracy of LEO satellites orbit determination.

Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

NASA Astrophysics Data System (ADS)

Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

2005-10-01

Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

Parallel satellite orbital situational problems solver for space missions design and control

NASA Astrophysics Data System (ADS)

Atanassov, Atanas Marinov

2016-11-01

Solving different scientific problems for space applications demands implementation of observations, measurements or realization of active experiments during time intervals in which specific geometric and physical conditions are fulfilled. The solving of situational problems for determination of these time intervals when the satellite instruments work optimally is a very important part of all activities on every stage of preparation and realization of space missions. The elaboration of universal, flexible and robust approach for situation analysis, which is easily portable toward new satellite missions, is significant for reduction of missions' preparation times and costs. Every situation problem could be based on one or more situation conditions. Simultaneously solving different kinds of situation problems based on different number and types of situational conditions, each one of them satisfied on different segments of satellite orbit requires irregular calculations. Three formal approaches are presented. First one is related to situation problems description that allows achieving flexibility in situation problem assembling and presentation in computer memory. The second formal approach is connected with developing of situation problem solver organized as processor that executes specific code for every particular situational condition. The third formal approach is related to solver parallelization utilizing threads and dynamic scheduling based on "pool of threads" abstraction and ensures a good load balance. The developed situation problems solver is intended for incorporation in the frames of multi-physics multi-satellite space mission's design and simulation tools.

On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2012-04-01

The great amount of multispectral VHR satellite images, even available free of charge in Google earth has opened new strategic challenges in the field of remote sensing for archaeological studies. These challenges substantially deal with: (i) the strategic exploitation of satellite data as much as possible, (ii) the setting up of effective and reliable automatic and/or semiautomatic data processing strategies and (iii) the integration with other data sources from documentary resources to the traditional ground survey, historical documentation, geophysical prospection, etc. VHR satellites provide high resolution data which can improve knowledge on past human activities providing precious qualitative and quantitative information developed to such an extent that currently they share many of the physical characteristics of aerial imagery. This makes them ideal for investigations ranging from a local to a regional scale (see. for example, Lasaponara and Masini 2006a,b, 2007a, 2011; Masini and Lasaponara 2006, 2007, Sparavigna, 2010). Moreover, satellite data are still the only data source for research performed in areas where aerial photography is restricted because of military or political reasons. Among the main advantages of using satellite remote sensing compared to traditional field archaeology herein we briefly focalize on the use of wavelet data processing for enhancing google earth satellite data with particular reference to multitemporal datasets. Study areas selected from Southern Italy, Middle East and South America are presented and discussed. Results obtained point out the use of automatic image enhancement can successfully applied as first step of supervised classification and intelligent data analysis for semiautomatic identification of features of archaeological interest. Reference Lasaponara R, Masini N (2006a) On the potential of panchromatic and multispectral Quickbird data for archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1): 53-60. Sparavigna Enhancing the Google imagery using a wavelet filter, A.C. Sparavigna,http://arxiv.org/abs/1009.1590

Semi-supervised classification tool for DubaiSat-2 multispectral imagery

NASA Astrophysics Data System (ADS)

Al-Mansoori, Saeed

2015-10-01

This paper addresses a semi-supervised classification tool based on a pixel-based approach of the multi-spectral satellite imagery. There are not many studies demonstrating such algorithm for the multispectral images, especially when the image consists of 4 bands (Red, Green, Blue and Near Infrared) as in DubaiSat-2 satellite images. The proposed approach utilizes both unsupervised and supervised classification schemes sequentially to identify four classes in the image, namely, water bodies, vegetation, land (developed and undeveloped areas) and paved areas (i.e. roads). The unsupervised classification concept is applied to identify two classes; water bodies and vegetation, based on a well-known index that uses the distinct wavelengths of visible and near-infrared sunlight that is absorbed and reflected by the plants to identify the classes; this index parameter is called "Normalized Difference Vegetation Index (NDVI)". Afterward, the supervised classification is performed by selecting training homogenous samples for roads and land areas. Here, a precise selection of training samples plays a vital role in the classification accuracy. Post classification is finally performed to enhance the classification accuracy, where the classified image is sieved, clumped and filtered before producing final output. Overall, the supervised classification approach produced higher accuracy than the unsupervised method. This paper shows some current preliminary research results which point out the effectiveness of the proposed technique in a virtual perspective.

Design of satellite flexibility experiments

NASA Technical Reports Server (NTRS)

Kaplan, M. H.; Hillard, S. E.

1977-01-01

A preliminary study has been completed to begin development of a flight experiment to measure spacecraft control/flexible structure interaction. The work reported consists of two phases: identification of appropriate structural parameters which can be associated with flexibility phenomena, and suggestions for the development of an experiment for a satellite configuration typical of near-future vehicles which are sensitive to such effects. Recommendations are made with respect to the type of data to be collected and instrumentation associated with these data. The approach consists of developing the equations of motion for a vehicle possessing a flexible solar array, then linearizing about some nominal motion of the craft. A set of solutions are assumed for array deflection using a continuous normal mode method and important parameters are exposed. Inflight and ground based measurements are distinguished. Interrelationships between these parameters, measurement techniques, and input requirements are discussed which assure minimization of special vehicle maneuvers and optimization of data to be obtained during the normal flight sequence.

Point- and line-based transformation models for high resolution satellite image rectification

NASA Astrophysics Data System (ADS)

Abd Elrahman, Ahmed Mohamed Shaker

Rigorous mathematical models with the aid of satellite ephemeris data can present the relationship between the satellite image space and the object space. With government funded satellites, access to calibration and ephemeris data has allowed the development and use of these models. However, for commercial high-resolution satellites, which have been recently launched, these data are withheld from users, and therefore alternative empirical models should be used. In general, the existing empirical models are based on the use of control points and involve linking points in the image space and the corresponding points in the object space. But the lack of control points in some remote areas and the questionable accuracy of the identified discrete conjugate points provide a catalyst for the development of algorithms based on features other than control points. This research, concerned with image rectification and 3D geo-positioning determination using High-Resolution Satellite Imagery (HRSI), has two major objectives. First, the effects of satellite sensor characteristics, number of ground control points (GCPs), and terrain elevation variations on the performance of several point based empirical models are studied. Second, a new mathematical model, using only linear features as control features, or linear features with a minimum number of GCPs, is developed. To meet the first objective, several experiments for different satellites such as Ikonos, QuickBird, and IRS-1D have been conducted using different point based empirical models. Various data sets covering different terrain types are presented and results from representative sets of the experiments are shown and analyzed. The results demonstrate the effectiveness and the superiority of these models under certain conditions. From the results obtained, several alternatives to circumvent the effects of the satellite sensor characteristics, the number of GCPs, and the terrain elevation variations are introduced. To meet the second objective, a new model named the Line Based Transformation Model (LBTM) is developed for HRSI rectification. The model has the flexibility to either solely use linear features or use linear features and a number of control points to define the image transformation parameters. Unlike point features, which must be explicitly defined, linear features have the advantage that they can be implicitly defined by any segment along the line. (Abstract shortened by UMI.)

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The utility of satellite precipitation products for hydrologic prediction in topographically complex regions: The Chehalis River Basin, WA as a case study

NASA Astrophysics Data System (ADS)

Cao, Q.; Mehran, A.; Lettenmaier, D. P.; Mass, C.; Johnson, N.

2015-12-01

Accurate measurements of precipitation are of great importance in hydrologic predictions especially for floods, which are a pervasive natural hazard. One of the primary objectives of Global Precipitation Measurement (GPM) mission is to provide a basis for hydrologic predictions using satellite sensors. A major advance in GPM relative to the Tropical Rainfall Measuring Mission (TRMM) is that it observes atmospheric river (AR) events, most of which have landfall too far north to be tracked by TRMM. These events are responsible for most major floods along the U.S. West Coast. We address the question of whether, for hydrologic modeling purposes, it is better to use precipitation products derived directly from GPM and/or other precipitation fields from weather models that have assimilated satellite data. Our overall strategy is to compare different methods for prediction of flood and/or high flow events by different forcings on the hydrologic model. We examine four different configurations of the Distroibute Hydrology Soil Vegetation Model (DHSVM) over the Chehalis River Basin that use a) precipitation forcings based on gridded station data; b) precipitation forcings based on NWS WSR-88D data, c) forcings based from short-term precipitation forecasts using the Weather Research and Forecasting (WRF) mesoscale atmospheric model, and d) satellite-based precipitation estimates (TMPA and IMERG). We find that in general, biases in the radar and satellite products result in much larger errors than with either gridded station data or WRF forcings, but if these biases are removed, comparable performance in flood predictions can be achieved by Satellite-based precipitation estimates (TMPA and IMERG).

Reconstruction of F-Region Electric Current Densities from more than 2 Years of Swarm Satellite Magnetic data

NASA Astrophysics Data System (ADS)

Tozzi, R.; Pezzopane, M.; De Michelis, P.; Pignalberi, A.; Siciliano, F.

2016-12-01

The constellation geometry adopted by ESA for Swarm satellites has opened the way to new investigations based on magnetic data. An example is the curl-B technique that allows reconstructing F-region electric current density in terms of its radial, meridional, and zonal components based on data from two satellites of Swarm constellation (Swarm A and B) which fly at different altitudes. Here, we apply this technique to more than 2 years of Swarm magnetic vector data and investigate the average large scale behaviour of F-region current densities as a function of local time, season and different interplanetary conditions (different strength and direction of the three IMF components and/or geomagnetic activity levels).

Response of vegetation NDVI to climatic extremes in the arid region of Central Asia: a case study in Xinjiang, China

NASA Astrophysics Data System (ADS)

Yao, Junqiang; Chen, Yaning; Zhao, Yong; Mao, Weiyi; Xu, Xinbing; Liu, Yang; Yang, Qing

2018-02-01

Observed data showed the climatic transition from warm-dry to warm-wet in Xinjiang during the past 30 years and will probably affect vegetation dynamics. Here, we analyze the interannual change of vegetation index based on the satellite-derived normalized difference vegetation index (NDVI) with temperature and precipitation extreme over the Xinjiang, using the 8-km NDVI third-generation (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) from 1982 to 2010. Few previous studies analyzed the link between climate extremes and vegetation response. From the satellite-based results, annual NDVI significantly increased in the first two decades (1981-1998) and then decreased after 1998. We show that the NDVI decrease over the past decade may conjointly be triggered by the increases of temperature and precipitation extremes. The correlation analyses demonstrated that the trends of NDVI was close to the trend of extreme precipitation; that is, consecutive dry days (CDD) and torrential rainfall days (R24) positively correlated with NDVI during 1998-2010. For the temperature extreme, while the decreases of NDVI correlate positively with warmer mean minimum temperature ( Tnav), it correlates negatively with the number of warmest night days ( Rwn). The results suggest that the climatic extremes have possible negative effects on the ecosystem.

Observations of low-energy ions in the wake of a magnetospheric satellite

NASA Technical Reports Server (NTRS)

Samir, U.; Comfort, R. H.; Chappell, C. R.; Stone, N. H.

1986-01-01

Measurements of low-energy ions made by the retarding ion mass spectrometer (RIMS) onboard the Dynamics Explorer 1 (DE 1) satellite are used to study some aspects of 'body-plasma interactions' in the terrestrial plasmasphere. Preliminary results are presented, yielding the degree of H+ and He+ ion depletion in the wake of the satellite in terms of specific and average ion Mach numbers, average ion mass, body size normalized to ionic Debye length, and body potential normalized to ion thermal energy. Some results from the RIMS measurements are compared with relevant results from the Explorer 31 and the Atmosphere Explorer C ionospheric satellites. Wake depletion is found to vary approximately linearly for small bodies (R-sub-Di less than about 12) and exponentially for large bodies (R-sub-Di greater than 50).

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

NASA Technical Reports Server (NTRS)

Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.;

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

NASA Astrophysics Data System (ADS)

Langheinrich, M.; Fischer, P.; Probeck, M.; Ramminger, G.; Wagner, T.; Krauß, T.

2017-05-01

The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth's surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO) High-Resolution Layer (HRL) mapping of the HRL Forest for 20 Western, Central and (South)Eastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for.

Triple crossings of a string of magnetic islands at duskside magnetopause encountered by AMPTE/IRM satellite on 8 August 1985

NASA Astrophysics Data System (ADS)

Teh, W.-L.; Hau, L.-N.

2007-08-01

There have been a number of reports on the existence of pearl-like magnetic island structures at the magnetopause current layer based on the analyses of single spacecraft data and two-dimensional reconstruction method of solving the Grad-Shafranov equation as a spatial initial value problem. This paper presents an unusual event of multiple magnetopause crossings encountered by AMPTE/IRM satellite at the duskside equatorial plane on 8 August, 1985. In a total of 11 magnetopause crossings spanning for nearly 2 hours, crossing 3, 4, and 9 display similar features of a string of magnetic islands imbedded within the overall tangential discontinuity-like current layers. In these crossings, the deHoffmann-Teller velocities form approximately 90° from the magnetopause normal that the in-and-out magnetopause motion becomes subsiding for the satellite to pick up the pearl-like plasmoids with island width of about 6-12 ion inertial length. In particular, crossing 3 and 9 are 1 hour apart but have almost the same magnetopause normal and deHoffmann-Teller velocity as well as similar invariant axis. A region of cold plasma adjacent to the magnetopause within the magnetosphere, the low-latitude boundary layer, is seen in all three crossings.

COMS normal operation for Earth Observation mission

NASA Astrophysics Data System (ADS)

Cho, Young-Min

2012-09-01

Communication Ocean Meteorological Satellite (COMS) for the hybrid mission of meteorological observation, ocean monitoring, and telecommunication service was launched onto Geostationary Earth Orbit on June 27, 2010 and it is currently under normal operation service since April 2011. The COMS is located on 128.2° East of the geostationary orbit. In order to perform the three missions, the COMS has 3 separate payloads, the meteorological imager (MI), the Geostationary Ocean Color Imager (GOCI), and the Ka-band antenna. Each payload is dedicated to one of the three missions, respectively. The MI and GOCI perform the Earth observation mission of meteorological observation and ocean monitoring, respectively. For this Earth observation mission the COMS requires daily mission commands from the satellite control ground station and daily mission is affected by the satellite control activities. For this reason daily mission planning is required. The Earth observation mission operation of COMS is described in aspects of mission operation characteristics and mission planning for the normal operation services of meteorological observation and ocean monitoring. And the first year normal operation results after the In-Orbit-Test (IOT) are investigated through statistical approach to provide the achieved COMS normal operation status for the Earth observation mission.

Lunar occultation of Saturn. II - The normal reflectance of Rhea, Titan, and Iapetus

NASA Technical Reports Server (NTRS)

Elliot, J. L.; Dunham, E. W.; Veverka, J.; Goguen, J.

1978-01-01

An inversion procedure to obtain the reflectance of the central region of a satellite's disk from lunar occultation data is presented. The scheme assumes that the limb darkening of the satellite depends only on the radial distance from the center of the disk. Given this assumption, normal reflectances can be derived that are essentially independent of the limb darkening and the diameter of the satellite. The procedure has been applied to our observations of the March 1974 lunar occultation of Tethys, Dione, Rhea, Titan, and Iapetus. In the V passband we derive the following normal reflectances: Rhea (0.97 plus or minus 0.20), Titan (0.24 plus or minus 0.03), Iapetus, bright face (0.60 plus or minus 0.14). For Tethys and Dione the values derived have large uncertainties, but are consistent with our result for Rhea.

Global long-term ozone trends derived from different observed and modelled data sets

NASA Astrophysics Data System (ADS)

Coldewey-Egbers, M.; Loyola, D.; Zimmer, W.; van Roozendael, M.; Lerot, C.; Dameris, M.; Garny, H.; Braesicke, P.; Koukouli, M.; Balis, D.

2012-04-01

The long-term behaviour of stratospheric ozone amounts during the past three decades is investigated on a global scale using different observed and modelled data sets. Three European satellite sensors GOME/ERS-2, SCIAMACHY/ENVISAT, and GOME-2/METOP are combined and a merged global monthly mean total ozone product has been prepared using an inter-satellite calibration approach. The data set covers the 16-years period from June 1995 to June 2011 and it exhibits an excellent long-term stability, which is required for such trend studies. A multiple linear least-squares regression algorithm using different explanatory variables is applied to the time series and statistically significant positive trends are detected in the northern mid latitudes and subtropics. Global trends are also estimated using a second satellite-based Merged Ozone Data set (MOD) provided by NASA. For few selected geographical regions ozone trends are additionally calculated using well-maintained measurements of individual Dobson/Brewer ground-based instruments. A reasonable agreement in the spatial patterns of the trends is found amongst the European satellite, the NASA satellite, and the ground-based observations. Furthermore, two long-term simulations obtained with the Chemistry-Climate Models E39C-A provided by German Aerospace Center and UMUKCA-UCAM provided by University of Cambridge are analysed.

A Prototype Knowledge-Based System for Satellite Mission Planning.

DTIC Science & Technology

1986-12-01

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

Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska

USGS Publications Warehouse

Hogrefe, Kyle R.; Patil, Vijay; Ruthrauff, Daniel R.; Meixell, Brandt W.; Budde, Michael E.; Hupp, Jerry W.; Ward, David H.

2017-01-01

Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator (R2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI (R2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study demonstrates the importance of matching the scale of NDVI measurements to the vegetation properties of biomass and nitrogen phenology.

Atmospheric correction using near-infrared bands for satellite ocean color data processing in the turbid western Pacific region.

PubMed

Wang, Menghua; Shi, Wei; Jiang, Lide

2012-01-16

A regional near-infrared (NIR) ocean normalized water-leaving radiance (nL(w)(λ)) model is proposed for atmospheric correction for ocean color data processing in the western Pacific region, including the Bohai Sea, Yellow Sea, and East China Sea. Our motivation for this work is to derive ocean color products in the highly turbid western Pacific region using the Geostationary Ocean Color Imager (GOCI) onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS). GOCI has eight spectral bands from 412 to 865 nm but does not have shortwave infrared (SWIR) bands that are needed for satellite ocean color remote sensing in the turbid ocean region. Based on a regional empirical relationship between the NIR nL(w)(λ) and diffuse attenuation coefficient at 490 nm (K(d)(490)), which is derived from the long-term measurements with the Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, an iterative scheme with the NIR-based atmospheric correction algorithm has been developed. Results from MODIS-Aqua measurements show that ocean color products in the region derived from the new proposed NIR-corrected atmospheric correction algorithm match well with those from the SWIR atmospheric correction algorithm. Thus, the proposed new atmospheric correction method provides an alternative for ocean color data processing for GOCI (and other ocean color satellite sensors without SWIR bands) in the turbid ocean regions of the Bohai Sea, Yellow Sea, and East China Sea, although the SWIR-based atmospheric correction approach is still much preferred. The proposed atmospheric correction methodology can also be applied to other turbid coastal regions.

Satellite constraints on surface concentrations of particulate matter

NASA Astrophysics Data System (ADS)

Ford Hotmann, Bonne

Because of the increasing evidence of the widespread adverse effects on human health from exposure to poor air quality and the recommendations of the World Health Organization to significantly reduce PM2.5 in order to reduce these risks, better estimates of surface air quality globally are required. However, surface measurements useful for monitoring particulate exposure are scarce, especially in developing countries which often experience the worst air pollution. Therefore, other methods are necessary to augment estimates in regions with limited surface observations. The prospect of using satellite observations to infer surface air quality is attractive; however, it requires knowledge of the complicated relationship between satellite-observed aerosol optical depth (AOD) and surface concentrations. This dissertation explores how satellite observations can be used in conjunction with a chemical transport model (GEOS-Chem) to better understand this relationship. First, we investigate the seasonality in aerosols over the Southeastern United States using observations from several satellite instruments (MODIS, MISR, CALIOP) and surface network sites (IMPROVE, SEARCH, AERONET). We find that the strong summertime enhancement in satellite-observed aerosol optical depth (factor 2-3 enhancement over wintertime AOD) is not present in surface mass concentrations (25-55% summertime enhancement). Goldstein et al. [2009] previously attributed this seasonality in AOD to biogenic organic aerosol; however, surface observations show that organic aerosol only accounts for ~35% of PM2.5 mass and exhibits similar seasonality to total surface PM2.5. The GEOS-Chem model generally reproduces these surface aerosol measurements, but under represents the AOD seasonality observed by satellites. We show that seasonal differences in water uptake cannot sufficiently explain the magnitude of AOD increase. As CALIOP profiles indicate the presence of additional aerosol in the lower troposphere (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer. Next, we examine the usefulness of deriving premature mortality estimates from "satellite-based" PM2.5 concentrations. In particular, we examine how uncertainties in the model AOD-to-surface-PM2.5 relationship, satellite retrieved AOD, and particulars of the concentration-response function can impact these mortality estimates. We find that the satellite-based estimates suggest premature mortality due to chronic PM2.5 exposure is 2-16% higher in the U.S. and 4-13% lower in China compared to model-based estimates. However, this difference is overshadowed by the uncertainty in the methodology, which we quantify to be on order of 20% for the model-to- surface-PM2.5 relationship, 10% for the satellite AOD and 30-60% or greater with regards to the application of concentration response functions. Because there is a desire for acute exposure estimates, especially with regards to extreme events, we also examine how premature mortality due to acute exposure can be estimated from global models and satellite-observations. We find similar differences between model and satellite-based mortality estimates as with chronic exposure. However the range of uncertainty is much larger on these shorter timescales. This work suggests that although satellites can be useful for constraining model estimates of PM2.5, national mortality estimates from the two methods are not significantly different. In order to improve the efficacy of satellite-based PM2.5 mortality estimates, future work will need to focus on improving the model representation of the regional AOD-to-surface-PM2.5 relationship, reducing biases in satellite-retrieved AOD and advancing our understanding of personal and population-level responses to PM2.5 exposure.

Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Jiahang; He, Xianqiang; Chen, Tieqiao; Zhu, Feng; Wang, Yihao; Hao, Zengzhou; Chen, Peng

2017-10-01

Hangzhou Bay waters are often characterized by extremely high total suspended particulate matter (TSM) concentration due to terrestrial inputs, bottom sediment resuspension and human activities. The spatial-temporal variability of TSM directly contributes to the transport of carbon, nutrients, pollutants, and other materials. Therefore, it is essential to maintain and monitor sedimentary environment in coastal waters. Traditional field sampling methods limit observation capability for insufficient spatial-temporal resolution. Thus, it is difficult to synoptically monitor high diurnal dynamics of TSM. However, the in-orbit operation of the world's first geostationary satellite ocean color sensor, GOCI, thoroughly changes this situation with hourly observations of covered area. Taking advantage of GOCI high spatial-temporal resolution, we generated TSM maps from GOCI Level-1B data after atmospheric correction based on six TSM empirical algorithms. Validation of GOCI-retrieved normalized water-leaving radiances and TSM concentration was presented in comparison with matched-up in-situ measurements. The mean absolute percentage differences of those six TSM regional algorithms were 24.52%, 163.93%, 195.50%, 70.50%, 121.02%, 82.72%, respectively. In addition, the discrepancy reasons were presented, taking more factors such as diversified satellite data, various study area, and different research season into consideration. It is effective and indispensable to monitor and catch the diurnal dynamics of TSM in Hangzhou Bay coastal waters, with hourly GOCI observations data and appropriate inversion algorithm.

Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

PubMed Central

Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

2015-01-01

Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

Vegetation, topography and daily weather influenced burn severity in central Idaho and western Montana forests

Treesearch

Donovan S. Birch; Penelope Morgan; Crystal A. Kolden; John T. Abatzoglou; Gregory K. Dillon; Andrew T. Hudak; Alistair M. S. Smith

2015-01-01

Burn severity as inferred from satellite-derived differenced Normalized Burn Ratio (dNBR) is useful for evaluating fire impacts on ecosystems but the environmental controls on burn severity across large forest fires are both poorly understood and likely to be different than those influencing fire extent. We related dNBR to environmental variables including vegetation,...

Evaluation of the relation between evapotranspiration and normalized difference vegetation index for downscaling the simplified surface energy balance model

USGS Publications Warehouse

Haynes, Jonathan V.; Senay, Gabriel B.

2012-01-01

The Simplified Surface Energy Balance (SSEB) model uses satellite imagery to estimate actual evapotranspiration (ETa) at 1-kilometer resolution. SSEB ETa is useful for estimating irrigation water use; however, resolution limitations restrict its use to regional scale applications. The U.S. Geological Survey investigated the downscaling potential of SSEB ETa from 1 kilometer to 250 meters by correlating ETa with the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer instrument (MODIS). Correlations were studied in three arid to semiarid irrigated landscapes of the Western United States (Escalante Valley near Enterprise, Utah; Palo Verde Valley near Blythe, California; and part of the Columbia Plateau near Quincy, Washington) during several periods from 2002 to 2008. Irrigation season ETa-NDVI correlations were lower than expected, ranging from R2 of 0.20 to 0.61 because of an eastward 2–3 kilometer shift in ETadata. The shift is due to a similar shift identified in the land-surface temperature (LST) data from the MODIS Terra satellite, which is used in the SSEB model. Further study is needed to delineate the Terra LST shift, its effect on SSEB ETa, and the relation between ETa and NDVI.

Calibration of TOMS Radiances From Ground Observations

NASA Technical Reports Server (NTRS)

Bojkov, B. R.; Kowalewski, M.; Wellemeyer, C.; Labow, G.; Hilsenrath, E.; Bhartia, P. K.; Ahmad, Z.

2003-01-01

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify its recovery. We show that validation of radiances from the ground can be a very effective means for correcting long term drifts of backscatter type satellite measurements and can be used to cross calibrate all BUV instruments in orbit (TOMS, SBUV/2, GOME, SCIAMACHY, OMI, GOME-2, OMPS). This method bypasses the retrieval algorithms used to derive ozone products from both satellite and ground based measurements that are normally used to validate the satellite data. Radiance comparisons employ forward models, but they are inherently more accurate than the retrieval This method employs very accurate comparisons between ground based zenith sicy radiances and satellite nadir radiances and employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. The zenith sky observations are made by the SSBUV where its calibration is maintained to a high degree of accuracy and precision. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method. The effect of aerosols and varying ozone amounts are considered in the model simulations and the theoretical comparisons. The radiative transfer simulations show that the ground and satellite radiance comparisons can be made with an uncertainty of less than l\\% without the knowledge of the amount ozone viewed by either instrument on ground or in space. algorithms.

Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms

NASA Astrophysics Data System (ADS)

Yao, Yunjun; Liang, Shunlin; Yu, Jian; Zhao, Shaohua; Lin, Yi; Jia, Kun; Zhang, Xiaotong; Cheng, Jie; Xie, Xianhong; Sun, Liang; Wang, Xuanyu; Zhang, Lilin

2017-04-01

Accurate estimates of terrestrial latent heat of evaporation (LE) for different biomes are essential to assess energy, water and carbon cycles. Different satellite- based Priestley-Taylor (PT) algorithms have been developed to estimate LE in different biomes. However, there are still large uncertainties in LE estimates for different PT algorithms. In this study, we evaluated differences in estimating terrestrial water flux in different biomes from three satellite-based PT algorithms using ground-observed data from eight eddy covariance (EC) flux towers of China. The results reveal that large differences in daily LE estimates exist based on EC measurements using three PT algorithms among eight ecosystem types. At the forest (CBS) site, all algorithms demonstrate high performance with low root mean square error (RMSE) (less than 16 W/m2) and high squared correlation coefficient (R2) (more than 0.9). At the village (HHV) site, the ATI-PT algorithm has the lowest RMSE (13.9 W/m2), with bias of 2.7 W/m2 and R2 of 0.66. At the irrigated crop (HHM) site, almost all models algorithms underestimate LE, indicating these algorithms may not capture wet soil evaporation by parameterization of the soil moisture. In contrast, the SM-PT algorithm shows high values of R2 (comparable to those of ATI-PT and VPD-PT) at most other (grass, wetland, desert and Gobi) biomes. There are no obvious differences in seasonal LE estimation using MODIS NDVI and LAI at most sites. However, all meteorological or satellite-based water-related parameters used in the PT algorithm have uncertainties for optimizing water constraints. This analysis highlights the need to improve PT algorithms with regard to water constraints.

Producing remote sensing-based emission estimates of prescribed burning in the contiguous United States for the U.S. Environmental Protection Agency 2011 National Emissions Inventory

NASA Astrophysics Data System (ADS)

McCarty, J. L.; Pouliot, G. A.; Soja, A. J.; Miller, M. E.; Rao, T.

2013-12-01

Prescribed fires in agricultural landscapes generally produce smaller burned areas than wildland fires but are important contributors to emissions impacting air quality and human health. Currently, there are a variety of available satellite-based estimates of crop residue burning, including the NOAA/NESDIS Hazard Mapping System (HMS) the Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE 2), the Moderate Resolution Imaging Spectroradiometer (MODIS) Official Burned Area Product (MCD45A1)), the MODIS Direct Broadcast Burned Area Product (MCD64A1) the MODIS Active Fire Product (MCD14ML), and a regionally-tuned 8-day cropland differenced Normalized Burn Ratio product for the contiguous U.S. The purpose of this NASA-funded research was to refine the regionally-tuned product utilizing higher spatial resolution crop type data from the USDA NASS Cropland Data Layer and burned area training data from field work and high resolution commercial satellite data to improve the U.S. Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The final product delivered to the EPA included a detailed database of 25 different atmospheric emissions at the county level, emission distributions by crop type and seasonality, and GIS data. The resulting emission databases were shared with the U.S. EPA and regional offices, the National Wildfire Coordinating Group (NWGC) Smoke Committee, and all 48 states in the contiguous U.S., with detailed error estimations for Wyoming and Indiana and detailed analyses of results for Florida, Minnesota, North Dakota, Oklahoma, and Oregon. This work also provided opportunities in discovering the different needs of federal and state partners, including the various geospatial abilities and platforms across the many users and how to incorporate expert air quality, policy, and land management knowledge into quantitative earth observation-based estimations of prescribed fire emissions. Finally, this work created direct communication paths between federal and state partners to the scientists creating the remote sensing-based products, further improving the geospatial products and understanding of air quality impacts of prescribed burning at the state, regional, and national scales.

Global Intercomparison of 12 Land Surface Heat Flux Estimates

NASA Technical Reports Server (NTRS)

Jimenez, C.; Prigent, C.; Mueller, B.; Seneviratne, S. I.; McCabe, M. F.; Wood, E. F.; Rossow, W. B.; Balsamo, G.; Betts, A. K.; Dirmeyer, P. A.;

Transmission over EHF mobile satellite channels

NASA Technical Reports Server (NTRS)

Zhuang, W.; Chouinard, J.-Y.; Yongacoglu, A.

1993-01-01

Land mobile satellite communications at Ka-band (30/20 GHz) are attracting an increasing interest among researchers because of the frequency band availability and the possibility of small earth station designs. However, communications at the Ka-band pose significant challenges in the system designs due to severe channel impairments. Because only very limited experimental data for mobile applications at Ka-band is available, this paper studies the channel characteristics based on experimental data at L-band (1.6/1.5 GHz) and the use of frequency scaling. The land mobile satellite communication channel at Ka-band is modelled as log-normal Rayleigh fading channel. The first and second-order statistics of the fading channel are studied. The performance of a coherent BPSK system over the fading channel at L-band and K-band is evaluated theoretically and validated by computer simulations. Conclusions on the communication channel characteristics and system performance at L-band and Ka-band are presented.

Cross Calibration of TOMS, SBUV/2 and Sciamachy Radiances from Ground Observations

NASA Technical Reports Server (NTRS)

Hillsenrath, Ernest; Ahmad, Ziauddin; Bhartia, Pawan K. (Technical Monitor)

2001-01-01

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify recovery. We have shown that validation of radiances is the most effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. Validation of radiances will also improve all higher level data products derived from the satellite observations. Backscatter algorithms suffer from several errors such as unrepresentative a-priori data and air mass factor corrections. Radiance comparisons employ forward models but are inherently more accurate and than inverse (retrieval) algorithms. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called "Skyrad", employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS. SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOME-2, OMI, and OMPS. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method.

Spatial variation and seasonal dynamics of leaf-area index in the arctic tundra-implications for linking ground observations and satellite images

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Räsänen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika

2017-09-01

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Bias Reduction in Short Records of Satellite Soil Moisture

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Koster, Randal D.

2004-01-01

Although surface soil moisture data from different sources (satellite retrievals, ground measurements, and land model integrations of observed meteorological forcing data) have been shown to contain consistent and useful information in their seasonal cycle and anomaly signals, they typically exhibit very different mean values and variability. These biases pose a severe obstacle to exploiting the useful information contained in satellite retrievals through data assimilation. A simple method of bias removal is to match the cumulative distribution functions (cdf) of the satellite and model data. However, accurate cdf estimation typically requires a long record of satellite data. We demonstrate here that by wing spatial sampling with a 2 degree moving window we can obtain local statistics based on a one-year satellite record that are a good approximation to those that would be derived from a much longer time series. This result should increase the usefulness of relatively short satellite data records.

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

NASA Astrophysics Data System (ADS)

Zibordi, G.; Mélin, F.; Berthon, J.-F.; Talone, M.

2015-03-01

The accuracy of primary satellite ocean color data products from the Moderate Resolution Imaging Spectroradiometer on-board Aqua (MODIS-A) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) is investigated in the Western Black Sea using in situ measurements from the Gloria site included in the ocean color component of the Aerosol Robotic Network (AERONET-OC). The analysis is also extended to an additional well-established AERONET-OC site in the northern Adriatic Sea characterized by optically complex coastal waters exhibiting similarities to those observed at the Gloria site. Results from the comparison of normalized water-leaving radiance LWN indicate biases of a few percent between satellite-derived and in situ data at the center wavelengths relevant for the determination of chlorophyll a concentrations (443-547 nm, or equivalent). Remarkable is the consistency between the annual cycle determined with time series of satellite-derived and in situ LWN ratios at these center wavelengths. Contrarily, the differences between in situ and satellite-derived LWN are pronounced at the blue (i.e., 412 nm) and red (i.e., 667 nm, or equivalent) center wavelengths, confirming difficulties in confidently applying satellite-derived radiometric data from these spectral regions for quantitative analysis in optically complex waters.

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

NASA Astrophysics Data System (ADS)

Zibordi, G.; Mélin, F.; Berthon, J.-F.; Talone, M.

2014-12-01

The accuracy of primary satellite ocean color data products from the Moderate Resolution Imaging Spectroradiometer on-board Aqua (MODIS-A) and the Visible/Infrared Imager/Radiometer Suite (VIIRS), is investigated in the Western Black Sea using in situ measurements from the Gloria site included in the Ocean Color component of the Aerosol Robotic Network (AERONET-OC). The analysis is also extended to an additional well-established AERONET-OC site in the northern Adriatic Sea characterized by optically complex coastal waters exhibiting similarities with those observed at the Gloria site. Results from the comparison of normalized-water leaving radiance LWN indicate biases of a few percent between satellite derived and in situ data at the center-wavelengths relevant for the determination of chlorophyll a concentration (443-547 nm, or equivalent). Remarkable is the consistency among the annual cycle determined with time series of satellite-derived and in situ LWN ratios at these center-wavelengths. Contrarily, the differences between in situ and satellite-derived LWN are pronounced at the blue (i.e., 412 nm) and red (i.e., 667 nm, or equivalent) center-wavelengths, suggesting difficulties in confidently applying satellite-derived radiometric data from these spectral regions for quantitative analysis in optically complex waters.

Isolation, characterization, and molecular regulation of muscle stem cells

PubMed Central

Fukada, So-ichiro; Ma, Yuran; Ohtani, Takuji; Watanabe, Yoko; Murakami, Satoshi; Yamaguchi, Masahiko

2013-01-01

Skeletal muscle has great regenerative capacity which is dependent on muscle stem cells, also known as satellite cells. A loss of satellite cells and/or their function impairs skeletal muscle regeneration and leads to a loss of skeletal muscle power; therefore, the molecular mechanisms for maintaining satellite cells in a quiescent and undifferentiated state are of great interest in skeletal muscle biology. Many studies have demonstrated proteins expressed by satellite cells, including Pax7, M-cadherin, Cxcr4, syndecan3/4, and c-met. To further characterize satellite cells, we established a method to directly isolate satellite cells using a monoclonal antibody, SM/C-2.6. Using SM/C-2.6 and microarrays, we measured the genes expressed in quiescent satellite cells and demonstrated that Hesr3 may complement Hesr1 in generating quiescent satellite cells. Although Hesr1- or Hesr3-single knockout mice show a normal skeletal muscle phenotype, including satellite cells, Hesr1/Hesr3-double knockout mice show a gradual decrease in the number of satellite cells and increase in regenerative defects dependent on satellite cell numbers. We also observed that a mouse's genetic background affects the regenerative capacity of its skeletal muscle and have established a line of DBA/2-background mdx mice that has a much more severe phenotype than the frequently used C57BL/10-mdx mice. The phenotype of DBA/2-mdx mice also seems to depend on the function of satellite cells. In this review, we summarize the methodology of direct isolation, characterization, and molecular regulation of satellite cells based on our results. The relationship between the regenerative capacity of satellite cells and progression of muscular disorders is also summarized. In the last part, we discuss application of the accumulating scientific information on satellite cells to treatment of patients with muscular disorders. PMID:24273513

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2010-01-01

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Toward a Coherent Detailed Evaluation of Aerosol Data Products from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2011-01-01

Atmospheric aerosols represent one of the greatest uncertainties in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood, there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource, an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, TerraMISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MASS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

NASA Technical Reports Server (NTRS)

Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan

2014-01-01

Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop-insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two-day severe weather event across western Nebraska and central Kansas during 9-10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

Development of new index for forest fire risk using satellite images in Indonesia through the direct spectral measurements of soil

NASA Astrophysics Data System (ADS)

Hashimoto, A.; Akita, M.; Takahashi, Y.; Suzuki, H.; Hasegawa, Y.; Ogino, Y.; Naruse, N.; Takahashi, Y.

2016-12-01

In recent years, the smoke caused by the forest fires in Indonesia has become a serious problem. Most of the land in Indonesia is covered with peat moss, which occurs the expanding of fires due to the burning itself. Thus, the surface soil water, reflecting the amount of precipitation in the area, can become the indication of the risk of fires. This study aims to develop a new index reflecting the risk of forest fires in Indonesia using satellite remote sensing through the direct spectral measurements of peat moss soil.We have prepared the peat moss in 7 steps of soil water content measured at an accuracy of ±15 percent (Field pro, WD-3). We obtained spectra between 400nm and 1050nm (Source: halogen lamp, spectroscope: self-made space time, spectral analysis kit) from the peat moss.The obtained spectra show the difference from the previous spectral measurement for the soil in various water content. There are the features, especially, in the wavelength range of ultraviolet (400-450nm) and infrared (530-800nm) as shown in the figure; the more the soil water increases, the lower the reflectance becomes. We have developed a new index using the New deep blue band (433 453nm and NIR band 845 885nm of Landsat 8. The resulting satellite images calculated by our original index appears to reflect the risk of forest fires rather than well-known indices such as Normalized Difference Water Index and Normalized difference Soil Index.In conclusion, we have created a new index that highly reflects to the degree of soil water of a peat soil in Indonesia.

Standardized Photometric Calibrations for Panchromatic SSA Sensors

NASA Astrophysics Data System (ADS)

Castro, P.; Payne, T.; Battle, A.; Cole, Z.; Moody, J.; Gregory, S.; Dao, P.

2016-09-01

Panchromatic sensors used for Space Situational Awareness (SSA) have no standardized method for transforming the net flux detected by a CCD without a spectral filter into an exo-atmospheric magnitude in a standard magnitude system. Each SSA data provider appears to have their own method for computing the visual magnitude based on panchromatic brightness making cross-comparisons impossible. We provide a procedure in order to standardize the calibration of panchromatic sensors for the purposes of SSA. A technique based on theoretical modeling is presented that derives standard panchromatic magnitudes from the Johnson-Cousins photometric system defined by Arlo Landolt. We verify this technique using observations of Landolt standard stars and a Vega-like star to determine empirical panchromatic magnitudes and compare these to synthetically derived panchromatic magnitudes. We also investigate color terms caused by differences in the quantum efficiency (QE) between the Landolt standard system and panchromatic systems. We evaluate calibrated panchromatic satellite photometry by observing several GEO satellites and standard stars using three different sensors. We explore the effect of satellite color terms by comparing the satellite signatures. In order to remove other variables affecting the satellite photometry, two of the sensors are at the same site using different CCDs. The third sensor is geographically separate from the first two allowing for a definitive test of calibrated panchromatic satellite photometry.

Merging Satellite Precipitation Products for Improved Streamflow Simulations

NASA Astrophysics Data System (ADS)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical statistics, as well as bias reduction and correlation coefficient, with the Bayesian approach being superior to other methods. A study case in the Tiber river basin is also presented to discuss the performance of forcing a hydrological model with the merged satellite precipitation product to simulate streamflow time series.

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

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190

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

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

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

Satellite Ocean-Color Validation Using Ships of Opportunity. Chapter 5

NASA Technical Reports Server (NTRS)

Frouin, Robert; Cutchin, David L.; Gross-Colzy, Lydwine; Poteau, Antoine; Deschamps, Pierre-Yves

2003-01-01

The investigation s main objective is to collect from platforms of opportunity (merchant ships, research vessels) concomitant normalized water-leaving radiance and aerosol optical thickness data over the world s oceans. A global, long-term data set of these variables is needed to verify whether satellite retrievals of normalized water-leaving radiance are within acceptable error limits and, eventually, to adjust atmospheric correction schemes. To achieve this objective, volunteer officers, technicians, and scientists onboard the selected ships collect data from portable SIMBAD and Advanced SIMBAD (SIMBADA) radiometers. These instruments are specifically designed for evaluation of satellite-derived ocean color. They measure radiance in spectral bands typical of ocean-color sensors. The SIMBAD version measures in 5 spectral bands centered at 443, 490, 560, 670, and 870 nm, and the Advanced SIMBAD version in 11 spectral bands centered at 350, 380, 412, 443, 490, 510, 565, 620, 670, 750, and 870 nm. Aerosol optical thickness is obtained by viewing the sun disk like a classic sun photometer. Normalized water-leaving radiance, or marine reflectance, is obtained by viewing the ocean surface through a vertical polarizer in a specific geometry (nadir angle of 45o and relative azimuth angle of 135deg) to minimize direct sun glint and reflected sky radiation. The SIMBAD and SIMBADA data, after proper quality control and processing, are delivered to the SIMBIOS project office for inclusion in the SeaBASS archive. They complement data collected in a similar way by the Laboratoire d'Optique Atmospherique of the University of Lille, France. The SIMBAD and SIMBADA data are used to check the radiometric calibration of satellite ocean-color sensors after launch and to evaluate derived ocean-color variables (i.e., normalized water-leaving radiance, aerosol optical thickness, and aerosol type). Analysis of the SIMBAD and SIMBADA data provides information on the accuracy of satellite retrievals of normalized water-leaving radiance, an understanding of the discrepancies between satellite and in situ data, and algorithms that reduce the discrepancies, contributing to more accurate and consistent global ocean color data sets.

Linear wide angle sun sensor for spinning satellites

NASA Astrophysics Data System (ADS)

Philip, M. P.; Kalakrishnan, B.; Jain, Y. K.

1983-08-01

A concept is developed which overcomes the defects of the nonlinearity of response and limitation in range exhibited by the V-slit, N-slit, and crossed slit sun sensors normally used for sun elevation angle measurements on spinning spacecraft. Two versions of sensors based on this concept which give a linear output and have a range of nearly + or - 90 deg of elevation angle are examined. Results are presented for the application of the twin slit version of the sun sensor in the three Indian satellites, Rohini, Apple, and Bhaskara II, which was successfully used for spin rate control and spin axis orientation control corrections as well as for sun elevation angle and spin period measurements.

Comparisons between Nimbus 6 satellite and rawinsonde soundings for several geographical areas

NASA Technical Reports Server (NTRS)

Cheng, N. M.; Scoggins, J. R.

1981-01-01

Good agreement between satellite and weighted (linearly interpolated) rawinsonde temperature and temperature derived parameters was found in most instances with the poorest agreement either near the tropopause region or near the ground. However, satellite moisture data are highly questionable. The smallest discrepancy between satellite and weighted mean rawinsonde temperature and parameters derived from temperature was found over water and the largest discrepancy was found over mountains. Cumulative frequency distributions show that discrepancies between satellite and rawinsonde data can be represented by a normal distribution except for dew point temperature.

Research on orbit prediction for solar-based calibration proper satellite

NASA Astrophysics Data System (ADS)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

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

Normal mode Rossby waves observed in the upper stratosphere

NASA Technical Reports Server (NTRS)

Hirooka, T.; Hirota, I.

1985-01-01

In recent years, observational evidence has been obtained for westward traveling planetary waves in the middle atmosphere with the aid of global data from satellites. There is no doubt that the fair portion of the observed traveling waves can be understood as the manifestation of the normal mode Rossby waves which are theoretically derived from the tidal theory. Some observational aspects of the structure and behavior of the normal model Rossby waves in the upper stratosphere are reported. The data used are the global stratospheric geopotential thickness and height analyses which are derived mainly from the Stratospheric Sounding Units (SSUs) on board TIROS-N and NOAA satellites. A clear example of the influence of the normal mode Rossby wave on the mean flow is reported. The mechanism considered is interference between the normal mode Rossby wave and the quasi-stationary wave.

Agricultural Early Warning Informing Humanitarian Response in East Africa for 2012

NASA Astrophysics Data System (ADS)

Husak, G. J.; Funk, C. C.

2012-12-01

Long rains during the March-April-May (MAM) 2011 growing season were a failure for much of the Greater Horn of Africa. These conditions resulted in severe food shortages, with the Famine Early Warning Systems Network (FEWS NET) estimating that 12.4 million people were in need of food assistance in Kenya, Somalia, Ethiopia and Djibouti. Heading into the 2012 season, La Niña conditions, an exceptionally strong western-to-central Pacific sea surface temperature (SST) gradient, and warm SSTs in the eastern Indian Ocean foretold further dryness, compounding the difficulties faced by the already vulnerable populations of this region. In an effort to assess the potential for greater food insecurity in the region, FEWS NET scientists attempted to quantify the likelihood of a dry event. This work used satellite rainfall estimates with a 13-year rainfall history. Weights were assigned to previous years based on the similarity of existing SST conditions to those of previous years in the rainfall record. Scenarios were created by randomly combining dekadal rainfall from the historical record, in accordance with the weights. This bootstrapping resulted in a suite of simulations which could be used to identify the likelihood of specific rainfall outcomes. Areal averages of each simulation were used in the analysis. Analysis of the Global Precipitation Climatology Centre (GPCC) rainfall record, a gridded rainfall product based on available station data, showed that the mean rainfall value for the time period of the satellite data for this region was only about 80% of the 30-year mean. The bootstrapped scenarios were corrected for this bias during the period of the satellite record. Results were expressed as percent of average rather than in absolute rainfall amounts, to account for biases in the satellite products as well as variability in spatial amounts. The results showed that during a normal year the interquartile range is typically 80-120% of normal. However, using the weighted scenarios based on February SSTs, the interquartile range shifted to 75-105% of normal. As the season progressed, March turned out to be exceptionally dry, with a lack of onset of rains for much of the region. This delayed start to the season allowed for the combination of satellite estimates for the start of March to be combined with scenarios to look ahead to end-of-season values. By the end of March, combining estimated 2012 rains with the scenarios built before the season resulted in the interquartile range for expected outcomes dropping to 60-85% of normal. This information was relayed to FEWS NET food security analysts and used in a special report, highlighting the potential for crisis in the region. In April, this forecasting effort, combined with FEWS NET's extensive monitoring activities, helped motivate allocation of an additional $50M in food aid from the U.S. government. This presentation examines the climate conditions associated with MAM drought in the eastern sector of the Greater Horn, reviews the techniques behind the 2012 forecasts, and analyzes the actual outcome for the region. Methods for improving the work to more accurately reflect the variability and future directions and applications will be discussed.

Three potato centromeres are associated with distinct haplotypes with or without megabase-sized satellite repeat arrays.

PubMed

Wang, Linsheng; Zeng, Zixian; Zhang, Wenli; Jiang, Jiming

2014-02-01

We report discoveries of different haplotypes associated with the centromeres of three potato chromosomes, including haplotypes composed of long arrays of satellite repeats and haplotypes lacking the same repeats. These results are in favor of the hypothesis that satellite repeat-based centromeres may originate from neocentromeres that lack repeats.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

USGS Publications Warehouse

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-01-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

NASA Astrophysics Data System (ADS)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-08-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

An assessment of the differences between spatial resolution and grid size for the SMAP enhanced soil moisture product over homogeneous sites

USDA-ARS?s Scientific Manuscript database

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled...

Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

NASA Astrophysics Data System (ADS)

Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

2015-04-01

Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in order to improve planning, business strategies but also to target the drought relief in case of major drought event. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".

Comparison of remote sensing indices for monitoring of desert cienegas

USGS Publications Warehouse

Wilson, Natalie R.; Norman, Laura M.; Villarreal, Miguel; Gass, Leila; Tiller, Ron; Salywon, Andrew

2016-01-01

This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.

Comparison of spectral ultraviolet irradiance measured from satellite and ground-based instrument at Nakhon Pathom province

NASA Astrophysics Data System (ADS)

Sriwongsa, J.; Buntoung, S.

2017-09-01

In this study, comparisons of spectral ultraviolet irradiance at 305, 310, 324 and 380 nm at the overpass time retrieved from OMI/AURA satellite with that from ground-based measurements were performed at Nakhon Pathom (13.82°N,100.04°E), Thailand. The analyzed data period comprised from 1 January 2010 to 31 December 2015. The comparison results clearly showed the overestimation of satellite data with root mean square difference (RMSD) between 22.9 and 48.9%, and mean bias difference (MBD) between 5.3 and 39.8% for all sky conditions, and reduced to 10.6-40.5% and 0.18-34.9% for clear sky conditions. Further results showed that the differences between the two datasets depend on atmospheric aerosol loads and clouds.

Evaluation of the Geomagnetic Field Models based on Magnetometer Measurements for Satellite's Attitude Determination System

NASA Astrophysics Data System (ADS)

Cilden, Demet; Kaymaz, Zerefsan; Hajiyev, Chingiz

2016-07-01

Magnetometers are common attitude determination sensors for small satellites at low Earth orbit; therefore, magnetic field model of the Earth is necessary to estimate the satellite's attitude angles. Difference in the components of the magnetic field vectors -mostly used as unit vector. Therefore the angle between them (model and measurement data) affects the estimation accuracy of the satellite's attitude. In this study, geomagnetic field models are compared with satellite magnetic field observations in order to evaluate the models using the magnetometer results with high accuracy. For attitude determination system, IGRF model is used in most of the cases but the difference between the sensor and model increases when the geomagnetic activity occurs. Hence, several models including the empirical ones using the external variations in the Earth's geomagnetic field resulting from the solar wind and interplanetary magnetic field are of great importance in determination of the satellite's attitude correctly. IGRF model describes the internal-part of the geomagnetic field, on the other hand candidate models to IGRF, such as recently developed POMME-6 model based on Champ data, CHAOS-5 (CHAmp, Oersted, Swarm), T89 (Tsyganenko's model), include simple parameterizations of external fields of magnetospheric sources in addition to the internal field especially for low Earth orbiting satellites. Those models can be evaluated to see noticeable difference on extraterrestrial field effects on satellite's attitude determination system changing with its height. The comparisons are made between the models and observations and between the models under various magnetospheric activities. In this study, we will present our preliminary results from the comparisons and discuss their implications from the satellite attitude perspective.

Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome.

PubMed

Yuan, Wenping; Liu, Shuguang; Dong, Wenjie; Liang, Shunlin; Zhao, Shuqing; Chen, Jingming; Xu, Wenfang; Li, Xianglan; Barr, Alan; Andrew Black, T; Yan, Wende; Goulden, Mike L; Kulmala, Liisa; Lindroth, Anders; Margolis, Hank A; Matsuura, Yojiro; Moors, Eddy; van der Molen, Michiel; Ohta, Takeshi; Pilegaard, Kim; Varlagin, Andrej; Vesala, Timo

2014-06-26

The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.

Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome

USGS Publications Warehouse

Yuan, Wenping; Liu, Shuguang; Dong, Wenjie; Liang, Shunlin; Zhao, Shuqing; Chen, Jingming; Xu, Wenfang; Li, Xianglan; Barr, Alan; Black, T. Andrew; Yan, Wende; Goulden, Michael; Kulmala, Liisa; Lindroth, Anders; Margolis, Hank A.; Matsuura, Yojiro; Moors, Eddy; van der Molen, Michiel; Ohta, Takeshi; Pilegaard, Kim; Varlagin, Andrej; Vesala, Timo

2014-01-01

The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and Other Trace Species

NASA Technical Reports Server (NTRS)

Chance, Kelly

2003-01-01

This grant is an extension to our previous NASA Grant NAG5-3461, providing incremental funding to continue GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) studies. This report summarizes research done under these grants through December 31, 2002. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and participation in initial SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY was launched March 1, 2002 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and Other Trace Species

NASA Astrophysics Data System (ADS)

Chance, Kelly

2003-02-01

This grant is an extension to our previous NASA Grant NAG5-3461, providing incremental funding to continue GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) studies. This report summarizes research done under these grants through December 31, 2002. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and participation in initial SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY was launched March 1, 2002 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Tian, Y.Q.; Yu, Q.; Zimmerman, M.J.; Flint, S.; Waldron, M.C.

2010-01-01

This study evaluates the efficacy of remote sensing technology to monitor species composition, areal extent and density of aquatic plants (macrophytes and filamentous algae) in impoundments where their presence may violate water-quality standards. Multispectral satellite (IKONOS) images and more than 500 in situ hyperspectral samples were acquired to map aquatic plant distributions. By analyzing field measurements, we created a library of hyperspectral signatures for a variety of aquatic plant species, associations and densities. We also used three vegetation indices. Normalized Difference Vegetation Index (NDVI), near-infrared (NIR)-Green Angle Index (NGAI) and normalized water absorption depth (DH), at wavelengths 554, 680, 820 and 977 nm to differentiate among aquatic plant species composition, areal density and thickness in cases where hyperspectral analysis yielded potentially ambiguous interpretations. We compared the NDVI derived from IKONOS imagery with the in situ, hyperspectral-derived NDVI. The IKONOS-based images were also compared to data obtained through routine visual observations. Our results confirmed that aquatic species composition alters spectral signatures and affects the accuracy of remote sensing of aquatic plant density. The results also demonstrated that the NGAI has apparent advantages in estimating density over the NDVI and the DH. In the feature space of the three indices, 3D scatter plot analysis revealed that hyperspectral data can differentiate several aquatic plant associations. High-resolution multispectral imagery provided useful information to distinguish among biophysical aquatic plant characteristics. Classification analysis indicated that using satellite imagery to assess Lemna coverage yielded an overall agreement of 79% with visual observations and >90% agreement for the densest aquatic plant coverages. Interpretation of biophysical parameters derived from high-resolution satellite or airborne imagery should prove to be a valuable approach for assessing the effectiveness of management practices for controlling aquatic plant growth in inland waters, as well as for routine monitoring of aquatic plants in lakes and suitable lentic environments. ?? 2010 Blackwell Publishing Ltd.

Satellite-observed changes in vegetation sensitivities to surface soil moisture and total water storage variations since the 2011 Texas drought

NASA Astrophysics Data System (ADS)

A, Geruo; Velicogna, Isabella; Kimball, John S.; Du, Jinyang; Kim, Youngwook; Colliander, Andreas; Njoku, Eni

2017-05-01

We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallow-depth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation-moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on vegetation-moisture relationship, and unique information regarding vegetation resilience and the recovery of hydrological drought.

Vertical Structure of Ice Cloud Layers From CloudSat and CALIPSO Measurements and Comparison to NICAM Simulations

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki

2013-01-01

The shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low-level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.

OWLS as platform technology in OPTOS satellite

NASA Astrophysics Data System (ADS)

Rivas Abalo, J.; Martínez Oter, J.; Arruego Rodríguez, I.; Martín-Ortega Rico, A.; de Mingo Martín, J. R.; Jiménez Martín, J. J.; Martín Vodopivec, B.; Rodríguez Bustabad, S.; Guerrero Padrón, H.

2017-12-01

The aim of this work is to show the Optical Wireless Link to intraSpacecraft Communications (OWLS) technology as a platform technology for space missions, and more specifically its use within the On-Board Communication system of OPTOS satellite. OWLS technology was proposed by Instituto Nacional de Técnica Aeroespacial (INTA) at the end of the 1990s and developed along 10 years through a number of ground demonstrations, technological developments and in-orbit experiments. Its main benefits are: mass reduction, flexibility, and simplification of the Assembly, Integration and Tests phases. The final step was to go from an experimental technology to a platform one. This step was carried out in the OPTOS satellite, which makes use of optical wireless links in a distributed network based on an OLWS implementation of the CAN bus. OPTOS is the first fully wireless satellite. It is based on the triple configuration (3U) of the popular Cubesat standard, and was completely built at INTA. It was conceived to procure a fast development, low cost, and yet reliable platform to the Spanish scientific community, acting as a test bed for space born science and technology. OPTOS presents a distributed OBDH architecture in which all satellite's subsystems and payloads incorporate a small Distributed On-Board Computer (OBC) Terminal (DOT). All DOTs (7 in total) communicate between them by means of the OWLS-CAN that enables full data sharing capabilities. This collaboration allows them to perform all tasks that would normally be carried out by a centralized On-Board Computer.

Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

NASA Astrophysics Data System (ADS)

Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

2018-01-01

Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture.

PubMed

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M; Torres-Rua, Alfonso; McKee, Mac

2017-09-14

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from "AggieAir", an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products.

Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture

PubMed Central

Hassan-Esfahani, Leila; Ebtehaj, Ardeshir M.; McKee, Mac

2017-01-01

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising capabilities of the downscaling approach enabling effective increase of the spatial resolution of Landsat imageries by orders of 2 to 4. Specifically, the downscaling scheme retrieved the missing high-resolution feature of the imageries and reduced the root mean squared error by 15, 11, and 10 percent in visual, near infrared, and thermal infrared bands, respectively. This metric is reduced by 9% in the derived NDVI and remains negligibly for the soil moisture products. PMID:28906428

Satellite Observation of El Nino Effects on Amazon Forest Phenology and Productivity

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Townsend, Alan R.; Braswell, Bobby H.

2000-01-01

Climate variability may affect the functioning of Amazon moist tropical forests, and recent modeling analyses suggest that the carbon dynamics of the region vary interannually in response to precipitation and temperature anomalies. However, due to persistent orbital and atmospheric artifacts in the satellite record, remote sensing observations have not provided quantitative evidence that climate variation affects Amazon forest phenology or productivity, We developed a method to minimize and quantify non-biological artifacts in NOAA AVHRR satellite data, providing a record of estimated forest phenological variation from 1982-1993. The seasonal Normalized Difference Vegetation Index (NDVI) amplitude (a proxy for phenology) increased throughout much of the basin during El Nino periods when rainfall was anomalously low. Wetter La Nina episodes brought consistently smaller NDVI amplitudes. Using radiative transfer and terrestrial biogeochemical models driven by these satellite data, we estimate that canopy-energy absorption and net primary production of Amazon forests varied interannually by as much as 21% and 18%, respectively. These results provide large-scale observational evidence for interannual sensitivity to El Nino of plant phenology and carbon flux in Amazon forests.

Analysis of global land surface albedo climatology and spatial-temporal variation during 1981-2010 from multiple satellite products

NASA Astrophysics Data System (ADS)

He, Tao; Liang, Shunlin; Song, Dan-Xia

2014-09-01

For several decades, long-term time series data sets of multiple global land surface albedo products have been generated from satellite observations. These data sets have been used as one of the key variables in climate change studies. This study aims to assess the surface albedo climatology and to analyze long-term albedo changes, from nine satellite-based data sets for the period 1981-2010, on a global basis. Results show that climatological surface albedo data sets derived from satellite observations can be used to validate, calibrate, and further improve surface albedo simulations and parameterizations in current climate models. However, the albedo products derived from the International Satellite Cloud Climatology Project and the Global Energy and Water Exchanges Project have large seasonal biases. At latitudes higher than 50°, the maximal difference in winter zonal albedo ranges from 0.1 to 0.4 among the nine satellite data sets. Satellite-based albedo data sets agree relatively well during the summer at high latitudes, with a standard deviation of 0.04 for the 70°-80° zone in both hemispheres. The fine-resolution (0.05°) data sets agree well with each other for all the land cover types in middle to low latitudes; however, large spread was identified for their albedos at middle to high latitudes over land covers with mixed snow and sparse vegetation. By analyzing the time series of satellite-based albedo products over the past three decades, albedo of the Northern Hemisphere was found to be decreasing in July, likely due to the shrinking snow cover. Meanwhile, albedo in January was found to be increasing, likely because of the expansion of snow cover in northern winter. However, to improve the albedo estimation at high latitudes, and ultimately the climate models used for long-term climate change studies, a still better understanding of differences between satellite-based albedo data sets is required.

Filtering and Gridding Satellite Observations of Cloud Variables to Compare with Climate Model Output

NASA Astrophysics Data System (ADS)

Pitts, K.; Nasiri, S. L.; Smith, N.

2013-12-01

Global climate models have improved considerably over the years, yet clouds still represent a large factor of uncertainty for these models. Comparisons of model-simulated cloud variables with equivalent satellite cloud products are the best way to start diagnosing the differences between model output and observations. Gridded (level 3) cloud products from many different satellites and instruments are required for a full analysis, but these products are created by different science teams using different algorithms and filtering criteria to create similar, but not directly comparable, cloud products. This study makes use of a recently developed uniform space-time gridding algorithm to create a new set of gridded cloud products from each satellite instrument's level 2 data of interest which are each filtered using the same criteria, allowing for a more direct comparison between satellite products. The filtering is done via several variables such as cloud top pressure/height, thermodynamic phase, optical properties, satellite viewing angle, and sun zenith angle. The filtering criteria are determined based on the variable being analyzed and the science question at hand. Each comparison of different variables may require different filtering strategies as no single approach is appropriate for all problems. Beyond inter-satellite data comparison, these new sets of uniformly gridded satellite products can also be used for comparison with model-simulated cloud variables. Of particular interest to this study are the differences in the vertical distributions of ice and liquid water content between the satellite retrievals and model simulations, especially in the mid-troposphere where there are mixed-phase clouds to consider. This presentation will demonstrate the proof of concept through comparisons of cloud water path from Aqua MODIS retrievals and NASA GISS-E2-[R/H] model simulations archived in the CMIP5 data portal.

Satellite Derived Volcanic Ash Product Inter-Comparison in Support to SCOPE-Nowcasting

NASA Astrophysics Data System (ADS)

Siddans, Richard; Thomas, Gareth; Pavolonis, Mike; Bojinski, Stephan

2016-04-01

In support of aeronautical meteorological services, WMO organized a satellite-based volcanic ash retrieval algorithm inter-comparison activity, to improve the consistency of quantitative volcanic ash products from satellites, under the Sustained, Coordinated Processing of Environmental Satellite Data for Nowcasting (SCOPEe Nowcasting) initiative (http:/ jwww.wmo.int/pagesjprogjsatjscopee nowcasting_en.php). The aims of the intercomparison were as follows: 1. Select cases (Sarychev Peak 2009, Eyjafyallajökull 2010, Grimsvötn 2011, Puyehue-Cordón Caulle 2011, Kirishimayama 2011, Kelut 2014), and quantify the differences between satellite-derived volcanic ash cloud properties derived from different techniques and sensors; 2. Establish a basic validation protocol for satellite-derived volcanic ash cloud properties; 3. Document the strengths and weaknesses of different remote sensing approaches as a function of satellite sensor; 4. Standardize the units and quality flags associated with volcanic cloud geophysical parameters; 5. Provide recommendations to Volcanic Ash Advisory Centers (VAACs) and other users on how to best to utilize quantitative satellite products in operations; 6. Create a "road map" for future volcanic ash related scientific developments and inter-comparison/validation activities that can also be applied to SO2 clouds and emergent volcanic clouds. Volcanic ash satellite remote sensing experts from operational and research organizations were encouraged to participate in the inter-comparison activity, to establish the plans for the inter-comparison and to submit data sets. RAL was contracted by EUMETSAT to perform a systematic inter-comparison of all submitted datasets and results were reported at the WMO International Volcanic Ash Inter-comparison Meeting to held on 29 June - 2 July 2015 in Madison, WI, USA (http:/ /cimss.ssec.wisc.edujmeetings/vol_ash14). 26 different data sets were submitted, from a range of passive imagers and spectrometers and these were inter-compared against each other and against validation data such as CALIPSO lidar, ground-based lidar and aircraft observations. Results of the comparison exercise will be presented together with the conclusions and recommendations arising from the activity.

Aerosol typing - key information from aerosol studies

NASA Astrophysics Data System (ADS)

Mona, Lucia; Kahn, Ralph; Papagiannopoulos, Nikolaos; Holzer-Popp, Thomas; Pappalardo, Gelsomina

2016-04-01

Aerosol typing is a key source of aerosol information from ground-based and satellite-borne instruments. Depending on the specific measurement technique, aerosol typing can be used as input for retrievals or represents an output for other applications. Typically aerosol retrievals require some a priori or external aerosol type information. The accuracy of the derived aerosol products strongly depends on the reliability of these assumptions. Different sensors can make use of different aerosol type inputs. A critical review and harmonization of these procedures could significantly reduce related uncertainties. On the other hand, satellite measurements in recent years are providing valuable information about the global distribution of aerosol types, showing for example the main source regions and typical transport paths. Climatological studies of aerosol load at global and regional scales often rely on inferred aerosol type. There is still a high degree of inhomogeneity among satellite aerosol typing schemes, which makes the use different sensor datasets in a consistent way difficult. Knowledge of the 4d aerosol type distribution at these scales is essential for understanding the impact of different aerosol sources on climate, precipitation and air quality. All this information is needed for planning upcoming aerosol emissions policies. The exchange of expertise and the communication among satellite and ground-based measurement communities is fundamental for improving long-term dataset consistency, and for reducing aerosol type distribution uncertainties. Aerosol typing has been recognized as one of its high-priority activities of the AEROSAT (International Satellite Aerosol Science Network, http://aero-sat.org/) initiative. In the AEROSAT framework, a first critical review of aerosol typing procedures has been carried out. The review underlines the high heterogeneity in many aspects: approach, nomenclature, assumed number of components and parameters used for the classification. The harmonization of the aerosol typing procedures is a fundamental need in aerosol studies for long-term perspectives, satellite validation, and accuracy. However, the possibilities and limits in defining a common set of aerosol types for satellite missions and ground-based measurements depends on different information content among measurement techniques and for different retrieval conditions (e.g. for low aerosol content there is smaller satellite aerosol type retrieval sensitivity), as well as different historical choices. The concept of aReference database for aerosol typing (REDAT) is developed with the specific purpose of providing a dataset suitable for the comparison of typing procedures (from ground-based, and satellite measurements) and to be used as reference dataset for the modelling community. It will also allow the definition of translating rules between the different aerosol typing nomenclature, information strongly needed for the more and more increased audience of scientific data with no scientific background, as well as policy and decision makers. Acknowledgments: The research leading to these results is partially funded by ACTRIS2 Research Infrastructure Project by the European Union's Horizon 2020 research and innovation programme under the grant agreement n. 654169.

Geo-spatial distribution of cloud cover and influence of cloud induced attenuation and noise temperature on satellite signal propagation over Nigeria

NASA Astrophysics Data System (ADS)

Ojo, Joseph Sunday

2017-05-01

The study of the influence of cloud cover on satellite propagation links is becoming more demanding due to the requirement of larger bandwidth for different satellite applications. Cloud attenuation is one of the major factors to consider for optimum performance of Ka/V and other higher frequency bands. In this paper, the geo-spatial distribution of cloud coverage over some chosen stations in Nigeria has been considered. The substantial scale spatial dispersion of cloud cover based on synoptic meteorological data and the possible impact on satellite communication links at higher frequency bands was also investigated. The investigation was based on 5 years (2008-2012) achieved cloud cover data collected by the Nigerian Meteorological Agency (NIMET) Federal Ministry of Aviation, Oshodi Lagos over four synoptic hours of the day covering day and night. The performances of satellite signals as they traverse through the cloud and cloud noise temperature at different seasons and over different hours of days at Ku/W-bands frequency are also examined. The overall result shows that the additional total atmospheric noise temperature due to the clear air effect and the noise temperature from the cloud reduces the signal-to-noise ratio of the satellite receiver systems, leading to more signal loss and if not adequately taken care of may lead to significant outage. The present results will be useful for Earth-space link budgeting, especially for the proposed multi-sensors communication satellite systems in Nigeria.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

GNSS-SLR satellite co-location for the estimate of local ties

NASA Astrophysics Data System (ADS)

Bruni, Sara; Zerbini, Susanna; Errico, Maddalena; Santi, Efisio

2013-04-01

The current realization of the International Terrestrial Reference Frame (ITRF) is based on four different space-geodetic techniques, so that the benefits brought by each observing system to the definition of the frame can compensate for the drawbacks of the others and technique-specific systematic errors might be identified. The strategy used to combine the observations from the different techniques is then of prominent importance for the realization of a precise and stable reference frame. This study concentrates, in particular, on the combination of Satellite Laser Ranging (SLR) and Global Navigation Satellite System (GNSS) observations by exploiting satellite co-locations. This innovative approach is based on the fact that laser tracking of GNSS satellites, carrying on board laser reflector arrays, allows for the combination of optical and microwave signals in the determination of the spacecraft orbit. Besides, the use of satellite co-locations differs quite significantly from the traditional combination method in which each single technique solution is carried out autonomously and is interrelated in a second step. One of the benefits of the approach adopted in this study is that it allows for an independent validation of the local tie, i.e. of the vector connecting the SLR and GNSS reference points in a multi-techniques station. Typically, local ties are expressed by a single value, measured with ground-based geodetic techniques and taken as constant. In principle, however, local ties might show time variations likely caused by the different monumentation characteristics of the GNSS antennas with respect to those of a SLR system. This study evaluates the possibility of using the satellite co-location approach to generate local-ties time series by means of observations available for a selected network of ILRS stations. The data analyzed in this study were acquired as part of the NASA's Earth Science Data Systems and are archived and distributed by the Crustal Dynamics Data Information System (CDDIS).

Satellite-based phenology detection in broadleaf forests in South-Western Germany

NASA Astrophysics Data System (ADS)

Misra, Gourav; Buras, Allan; Menzel, Annette

2016-04-01

Many techniques exist for extracting phenological information from time series of satellite data. However, there have been only a few successful attempts to temporarily match satellite-derived observations with ground based phenological observations (Fisher et al., 2006; Hamunyela et al., 2013; Galiano et al., 2015). Such studies are primarily plagued with problems relating to shorter time series of satellite data including spatial and temporal resolution issues. A great challenge is to correlate spatially continuous and pixel-based satellite information with spatially discontinuous and point-based, mostly species-specific, ground observations of phenology. Moreover, the minute differences in phenology observed by ground volunteers might not be sufficient to produce changes in satellite-measured reflectance of vegetation, which also exposes the difference in the definitions of phenology (Badeck et al., 2004; White et al., 2014). In this study Start of Season (SOS) was determined for broadleaf forests at a site in south-western Germany using MODIS-sensor time series of Normalised Difference Vegetation Index (NDVI) data for the years covering 2001 to 2013. The NDVI time series raster data was masked for broadleaf forests using Corine Land Cover dataset, filtered and corrected for snow and cloud contaminations, smoothed with a Gaussian filter and interpolated to daily values. Several SOS techniques cited in literature, namely thresholds of amplitudes (20%, 50%, 60% and 75%), rates of change (1st, 2nd and 3rd derivative) and delayed moving average (DMA) were tested for determination of satellite SOS. The different satellite SOS were then compared with a species-rich ground based phenology information (e.g. understory leaf unfolding, broad leaf unfolding and greening of evergreen tree species). Working with all the pixels at a finer resolution, it is seen that the temporal trends in understory and broad leaf species are well captured. Initial analyses show promising results and suggest that different satellite SOS extraction techniques work well for specific phases of ground phenology information. More than half of the broadleaf pixels show an earliness in SOS which matches with the trend in ground phenology. References 1. F.-W. Badeck, A. Bondeau, K. Bottcher, D. Doktor, W. Lucht, J. Schaber, and S. Sitch, 2004, "Responses of spring phenology to climate change," New Phytologist, vol. 162, no. 2, pp. 295-309. 2. E. Hamunyela, J. Verbesselt, G. Roerink, and M. Herold, 2013, "Trends in Spring Phenology of Western European Deciduous Forests," Remote Sensing, vol. 5, no. 12, pp. 6159-6179. 3. V. F. Rodriguez-Galiano, J. Dash, and P. M. Atkinson, 2015, "Intercomparison of satellite sensor land surface phenology and ground phenology in Europe: Inter-annual comparison and modelling," Geophysical Research Letters, vol. 42, no. 7, pp. 2253-2260. 4. J. Fisher, J. Mustard, and M. Vadeboncoeur, 2006, "Green leaf phenology at Landsat resolution: Scaling from the field to the satellite," Remote Sensing of Environment, vol. 100, no. 2, pp. 265-279. 5. K. White, J. Pontius, and P. Schaberg, 2014, "Remote sensing of spring phenology in northeastern forests: A comparison of methods, field metrics and sources of uncertainty," Remote Sensing of Environment, vol. 148, pp. 97-107.

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

NASA Astrophysics Data System (ADS)

Lee, I.-Chieh

Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be manually connected, for its length was less than 3% of the total shoreline length in our dataset. Secondly, the parameters for satellite image classification needed to be manually determined. The need for manpower was significantly less compared to the ground surveying or aerial photogrammetry. The first phase of shoreline extraction was to utilize Normalized Difference Vegetation Index (NDVI), Mean-Shift segmentation on the coordinate (X, Y, Z), and attributes (multispectral bands from satellite images) of the LiDAR points to classify each LiDAR point into land or water surface. Boundary of the land points were then traced to create the shoreline. The second phase of shoreline extraction solely from satellite images utilized spectrum, NDVI, and shadow analysis to classify the satellite images into classes. These classes were then refined by mean-shift segmentation on the panchromatic band. By tracing the boundary of the water surface, the shoreline can be created. Since these two shorelines may represent different shoreline instances in time, evaluating the changes of shoreline was the first to be done. Then an independent scenario analysis and a procedure are performed for the shoreline of each of the three conditions: in the process of erosion, in the process of accession, and remaining the same. With these three conditions, we could analysis the actual terrain type and correct the classification errors to obtain a more accurate shoreline. Meanwhile, methods of evaluating the quality of shorelines had also been discussed. The experiment showed that there were three indicators could best represent the quality of the shoreline. These indicators were: (1) shoreline accuracy, (2) land area difference between extracted shoreline and ground truth shoreline, and (3) bias factor from shoreline quality metrics.

Consistency of forest presence and biomass predictions modeled across overlapping spatial and temporal extents

Treesearch

Mark D. Nelson; Sean Healey; W. Keith Moser; J.G. Masek; Warren Cohen

2011-01-01

We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical...

Can One Satellite Data Set Validation Another? Validation of Envisat SCIAMACHY Data by Comparisons with NOAA-16 SBUV/2 and ERS-2 GOME

NASA Technical Reports Server (NTRS)

Hilsenrath, E.; Bojkov, B. R.; Labow, G.; Weber, M.; Burrows, J.

2004-01-01

Validation of satellite data remains a high priority for the construction of climate data sets. Traditionally ground based measurements have provided the primary comparison data for validation. For some atmospheric parameters such as ozone, a thoroughly validated satellite data record can be used to validate a new instrument s data product in addition to using ground based data. Comparing validated data with new satellite data has several advantages; availability of much more data, which will improve precision, larger geographical coverage, and the footprints are closer in size, which removes uncertainty due to different observed atmospheric volumes. To demonstrate the applicability and some limitations of this technique, observations from the newly launched SCIAMACHY instrument were compared with the NOM-16 SBW/2 and ERS-2 GOME instruments. The SBW/2 data had all ready undergone validation by comparing to the total ozone ground network. Overall the SCIAMACHY data were found to low by 3% with respect to satellite data and 1% low with respect to ground station data. There appears to be seasonal and or solar zenith angle dependences in the comparisons with SBW/2 where differences increase with higher solar zenith angles. It is known that accuracies in both satellite and ground based total ozone algorithms decrease at high solar zenith angles. There is a strong need for more accurate measurement from and the ground under these conditions. At the present time SCIAMACHY data are limited and longer data set with more coverage in both hemispheres is needed to unravel the cause of these differences.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Satellite-Based Videoconferencing.

ERIC Educational Resources Information Center

Distance Education Report, 1997

1997-01-01

Educators can broadcast videoconferences to students in different parts of the world at an affordable cost using geostationary satellites. Describes the design and presentation of videoconferences and outlines steps in their development: budgeting, scheduling, selecting presenters and moderators, choosing production and telecast facilities,…

Analysis of Imp-C data from the magnetospheric tail

NASA Technical Reports Server (NTRS)

Speiser, T. W.

1973-01-01

Satellite magnetic field measurements in the geomagnetic tail current sheet are analyzed to determine the normal field component, and other CS parameters such as thickness, motion, vector current density, etc., and to make correlations with auroral activity as measured by the A sub e index. The satellite data used in the initial part of this study were from Explorer 28 and Explorer 34 satellites.

Mini All-purpose Satellite Control Center (MASCC)

NASA Technical Reports Server (NTRS)

Zaouche, Gerard

1994-01-01

A new generation of Mini All-purpose Satellite Control Centers (MASCC) has been developed by CNES (F). They turn out to be easily adaptable to different kinds of satellites, both Low Earth Orbital or Geostationary. The features of MASCC allow both standard satellite control activities, and checking of passengers experiments hosted on a space platform. In the different environments in which it may be used, MASCC provides standard broadcasting of telemetry parameters on animated synoptics (curves, bar graphs, alphanumeric displays, ...), which turns out to be a very useful and ergonomic medium for operational teams or satellite specialists. Special care has been taken during the MASCC development about two points: - automation of all routine tasks, allowing automated operation, and limiting human commitment to system supervision and decision making, - software adaptability. To reach these two main objectives, the MASCC design provides:(1) a simple, robust and flexible hardware architecture, based on powerful distributed workstations; and (2) a table-driven software architecture, easily adapted to various operational needs. Satellite characteristics are described in a central Data Base. Hence, the processing of telemetry and commands is largely independent from the satellite itself. In order to validate these capabilities, the MASCC has been customized to several types of satellites and orbital platforms: (1) SPOT4, the French new generation of remote sensing satellites; (2) TELECOM2, the French geostationary TV and telecommunication satellite; and (3) MIR, the Russian orbital platform. MASCC development has been completed by the third quarter of 1993. This paper will provide first a description of the MASCC basic functions, of its hardware and software design. It will then detail the increased automation capability, along with the easy adaptation of the MASCC to new satellites with minimal software modifications.

Diet-Induced Obesity Affects Muscle Regeneration After Murine Blunt Muscle Trauma-A Broad Spectrum Analysis.

PubMed

Xu, Pengfei; Werner, Jens-Uwe; Milerski, Sebastian; Hamp, Carmen M; Kuzenko, Tatjana; Jähnert, Markus; Gottmann, Pascal; de Roy, Luisa; Warnecke, Daniela; Abaei, Alireza; Palmer, Annette; Huber-Lang, Markus; Dürselen, Lutz; Rasche, Volker; Schürmann, Annette; Wabitsch, Martin; Knippschild, Uwe

2018-01-01

Injury to skeletal muscle affects millions of people worldwide. The underlying regenerative process however, is a very complex mechanism, time-wise highly coordinated, and subdivided in an initial inflammatory, a regenerative and a remodeling phase. Muscle regeneration can be impaired by several factors, among them diet-induced obesity (DIO). In order to evaluate if obesity negatively affects healing processes after trauma, we utilized a blunt injury approach to damage the extensor iliotibialis anticus muscle on the left hind limb of obese and normal weight C57BL/6J without showing any significant differences in force input between normal weight and obese mice. Magnetic resonance imaging (MRI) of the injury and regeneration process revealed edema formation and hemorrhage exudate in muscle tissue of normal weight and obese mice. In addition, morphological analysis of physiological changes revealed tissue necrosis, immune cell infiltration, extracellular matrix (ECM) remodeling, and fibrosis formation in the damaged muscle tissue. Regeneration was delayed in muscles of obese mice, with a higher incidence of fibrosis formation due to hampered expression levels of genes involved in ECM organization. Furthermore, a detailed molecular fingerprint in different stages of muscle regeneration underlined a delay or even lack of a regenerative response to injury in obese mice. A time-lapse heatmap determined 81 differentially expressed genes (DEG) with at least three hits in our model at all-time points, suggesting key candidates with a high impact on muscle regeneration. Pathway analysis of the DEG revealed five pathways with a high confidence level: myeloid leukocyte migration, regulation of tumor necrosis factor production, CD4-positive, alpha-beta T cell differentiation, ECM organization, and toll-like receptor (TLR) signaling. Moreover, changes in complement-, Wnt-, and satellite cell-related genes were found to be impaired in obese animals after trauma. Furthermore, histological satellite cell evaluation showed lower satellite cell numbers in the obese model upon injury. Ankrd1, C3ar1, Ccl8, Mpeg1 , and Myog expression levels were also verified by qPCR. In summary, increased fibrosis formation, the reduction of Pax7 + satellite cells as well as specific changes in gene expression and signaling pathways could explain the delay of tissue regeneration in obese mice post trauma.

The First Result of Relative Positioning and Velocity Estimation Based on CAPS

PubMed Central

Zhao, Jiaojiao; Ge, Jian; Wang, Liang; Wang, Ningbo; Zhou, Kai; Yuan, Hong

2018-01-01

The Chinese Area Positioning System (CAPS) is a new positioning system developed by the Chinese Academy of Sciences based on the communication satellites in geosynchronous orbit. The CAPS has been regarded as a pilot system to test the new technology for the design, construction and update of the BeiDou Navigation Satellite System (BDS). The system structure of CAPS, including the space, ground control station and user segments, is almost like the traditional Global Navigation Satellite Systems (GNSSs), but with the clock on the ground, the navigation signal in C waveband, and different principles of operation. The major difference is that the CAPS navigation signal is first generated at the ground control station, before being transmitted to the satellite in orbit and finally forwarded by the communication satellite transponder to the user. This design moves the clock from the satellite in orbit to the ground. The clock error can therefore be easily controlled and mitigated to improve the positioning accuracy. This paper will present the performance of CAPS-based relative positioning and velocity estimation as assessed in Beijing, China. The numerical results show that, (1) the accuracies of relative positioning, using only code measurements, are 1.25 and 1.8 m in the horizontal and vertical components, respectively; (2) meanwhile, they are about 2.83 and 3.15 cm in static mode and 6.31 and 10.78 cm in kinematic mode, respectively, when using the carrier-phase measurements with ambiguities fixed; and (3) the accuracy of the velocity estimation is about 0.04 and 0.11 m/s in static and kinematic modes, respectively. These results indicate the potential application of CAPS for high-precision positioning and velocity estimation and the availability of a new navigation mode based on communication satellites. PMID:29757204

Thermal remote sensing as a part of Exupéry volcano fast response system

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Hort, Matthias

2010-05-01

In order to understand the eruptive potential of a volcanic system one has to characterize the actual state of stress of a volcanic system that involves proper monitoring strategies. As several volcanoes in highly populated areas especially in south east Asia are still nearly unmonitored a mobile volcano monitoring system is currently being developed in Germany. One of the major novelties of this mobile volcano fast response system called Exupéry is the direct inclusion of satellite based observations. Remote sensing data are introduced together with ground based field measurements into the GIS database, where the statistical properties of all recorded data are estimated. Using physical modelling and statistical methods we hope to constrain the probability of future eruptions. The emphasis of this contribution is on using thermal remote sensing as tool for monitoring active volcanoes. One can detect thermal anomalies originating from a volcano by comparing signals in mid and thermal infrared spectra. A reliable and effective thermal anomalies detection algorithm was developed by Wright (2002) for MODIS sensor; it is based on the threshold of the so called normalized thermal index (NTI). This is the method we use in Exupéry, where we characterize each detected thermal anomaly by temperature, area, heat flux and effusion rate. The recent work has shown that radiant flux is the most robust parameter for this characterization. Its derivation depends on atmosphere, satellite viewing angle and sensor characteristics. Some of these influences are easy to correct using standard remote sensing pre-processing techniques, however, some noise still remains in data. In addition, satellites in polar orbits have long revisit times and thus they might fail to follow a fast evolving volcanic crisis due to long revisit times. Thus we are currently testing Kalman filter on simultaneous use of MODIS and AVHRR data to improve the thermal anomaly characterization. The advantage of this technique is that it increases the temporal resolution through using images from different satellites having different resolution and sensitivity. This algorithm has been tested for an eruption at Mt. Etna (2002) and successfully captures more details of the eruption evolution than would be seen by using only one satellite source. At the moment for Exupéry, merely MODIS (a sensor aboard NASA's Terra and Aqua satellite) data are used for the operational use. As MODIS is a meteorological sensor, it is suitable also for producing general overview images of the crisis area. Therefore, for each processed MODIS image we also produce RGB image where some basic meteorological features are classified: e.g. clouds, volcanic ash plumes, ocean, etc. In the case of detected hotspot an additional image is created; it contains the original measured radiances of the selected channels for the crisis area. All anomaly and processing parameters are additionally written into an XML file. The results are available in web GIS in the worst case two hours after NASA provides level 1b data online.

An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.

PubMed

Deb, Dibyendu; Singh, J P; Deb, Shovik; Datta, Debajit; Ghosh, Arunava; Chaurasia, R S

2017-10-20

Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with respect to the image data resolution (spatial and spectral) as well as the sensor platform position in space. Using Resourcesat-2 satellite data and Normalized Difference Vegetation Index (NDVI), this pilot scale study compared traditional linear and nonlinear models with an artificial intelligence-based non-parametric technique, i.e. artificial neural network (ANN) for formulation of the best-fit model to determine AGB of forest of the Bundelkhand region of India. The results confirmed the superiority of ANN over other models in terms of several statistical significance and reliability assessment measures. Accordingly, this study proposed the use of ANN instead of traditional models for determination of AGB and other bio-physical parameters of any dry deciduous forest of tropical sub-humid or semi-arid area. In addition, large numbers of sampling sites with different quadrant sizes for trees, shrubs, and herbs as well as application of LiDAR data as predictor variable were recommended for very high precision modelling in ANN for a large scale study.

Galileo FOC Satellite Group Delay Estimation based on Raw Method and published IOV Metadata

NASA Astrophysics Data System (ADS)

Reckeweg, Florian; Schönemann, Erik; Springer, Tim; Enderle, Werner

2017-04-01

In December 2016, the European GNSS Agency (GSA) published the Galileo In-Orbit Validation (IOV) satellite metadata. These metadata include among others the so-called Galileo satellite group delays, which were measured in an absolute sense by the satellite manufacturer on-ground for all three Galileo frequency bands E1, E5 and E6. Therewith Galileo is the first Global Navigation Satellite System (GNSS) for which absolute calibration values for satellite on-board group delays have been published. The different satellite group delays for the three frequency bands lead to the fact that the signals will not be transmitted at exactly the same epoch. Up to now, due to the lack of absolute group delays, it is common practice in GNSS analyses to estimate and apply the differences of these satellite group delays, commonly known as differential code biases (DCBs). However, this has the drawback that the determination of the "raw" clock and the absolute ionosphere is not possible. The use of absolute bias calibrations for satellites and receivers is a major step into the direction of more realistic (in a physical sense) clock and atmosphere estimates. The Navigation Support Office at the European Space Operation Centre (ESOC) was from the beginning involved in the validation process of the Galileo metadata. For the work presented in this presentation we will use the absolute bias calibrations of the Galileo IOV satellites to estimate and validate the absolute receiver group delays of the ESOC GNSS network and vice versa. The receiver group delays have exemplarily been calibrated in a calibration campaign with an IFEN GNSS Signal-Simulator at ESOC. Based on the calibrated network, making use of the ionosphere constraints given by the IOV satellites, GNSS raw observations are processed to estimate satellite group delays for the operational Galileo (Full Operational Capability) FOC satellites. In addition, "raw" satellite clock offsets are estimated, which are free of the ionosphere-free bias, which is inherent to all common satellite clock products, generated with the standard ionosphere-free linear combination processing approach. In the raw observation processing method, developed by the Navigation Support Office at ESOC, no differences or linear combinations of GNSS observations are formed and ionosphere parameters and multi-signal group delay parameters can be jointly estimated by making use of all available code and phase observations on multiple frequencies.

Development of hybrid fog detection algorithm (FDA) using satellite and ground observation data for nighttime

NASA Astrophysics Data System (ADS)

Kim, So-Hyeong; Han, Ji-Hae; Suh, Myoung-Seok

2017-04-01

In this study, we developed a hybrid fog detection algorithm (FDA) using AHI/Himawari-8 satellite and ground observation data for nighttime. In order to detect fog at nighttime, Dual Channel Difference (DCD) method based on the emissivity difference between SWIR and IR1 is most widely used. DCD is good at discriminating fog from other things (middle/high clouds, clear sea and land). However, it is difficult to distinguish fog from low clouds. In order to separate the low clouds from the pixels that satisfy the thresholds of fog in the DCD test, we conducted supplementary tests such as normalized local standard derivation (NLSD) of BT11 and the difference of fog top temperature (BT11) and air temperature (Ta) from NWP data (SST from OSTIA data). These tests are based on the larger homogeneity of fog top than low cloud tops and the similarity of fog top temperature and Ta (SST). Threshold values for the three tests were optimized through ROC analysis for the selected fog cases. In addition, considering the spatial continuity of fog, post-processing was performed to detect the missed pixels, in particular, at edge of fog or sub-pixel size fog. The final fog detection results are presented by fog probability (0 100 %). Validation was conducted by comparing fog detection probability with the ground observed visibility data from KMA. The validation results showed that POD and FAR are ranged from 0.70 0.94 and 0.45 0.72, respectively. The quantitative validation and visual inspection indicate that current FDA has a tendency to over-detect the fog. So, more works which reducing the FAR is needed. In the future, we will also validate sea fog using CALIPSO data.

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

NASA Technical Reports Server (NTRS)

Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

2016-01-01

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Satellite-based prediction of rainfall interception by tropical forest stands of a human-dominated landscape in Central Sulawesi, Indonesia

NASA Astrophysics Data System (ADS)

Nieschulze, Jens; Erasmi, Stefan; Dietz, Johannes; Hölscher, Dirk

2009-01-01

SummaryRainforest conversion to other land use types drastically alters the hydrological cycle in which changes in rainfall interception contribute significantly to the observed differences. However, little is known about the effects of more gradual changes in forest structure and at regional scales. We studied land use types ranging from natural forest over selectively-logged forest to cacao agroforest in a lower montane region in Central Sulawesi, Indonesia, and tested the suitability of high-resolution optical satellite imagery for modeling observed interception patterns. Investigated characteristics indicating canopy structure were mean and standard deviation of reflectance values, local maxima, and self-similarity measures based on the grey level co-occurrence matrix and geostatistical variogram analysis. Previously studied and published rainfall interception data comprised twelve plots and median values per land use type ranged from 30% in natural forest to 18% in cacao agroforests. A linear regression model with local maxima, mean contrast and normalized digital vegetation index (NDVI) as regressors was able to explain more than 84% ( Radj2) of the variation encountered in the data. Other investigated characteristics did not prove significant in the regression analysis. The model yielded stable results with respect to cross-validation and also produced realistic values and spatial patterns when applied at the landscape level (783.6 ha). High values of interception were rare and localized in natural forest stands distant to villages, whereas low interception characterized the intensively used sites close to settlements. We conclude that forest use intensity significantly reduced rainfall interception and satellite image analysis can successfully be applied for its regional prediction, and most forest in the study region has already been subject to human-induced structural changes.

InfoSequia: the first operational remote sensing-based Drought Monitoring System of Spain

NASA Astrophysics Data System (ADS)

Contreras, Sergio; Hunink, Johannes E.

2016-04-01

We present a satellite-based Drought Monitoring System that provides weekly updates of maps and bulletins with vegetation drought indices over the Iberian Peninsula. The web portal InfoSequía (http://infosequia.es) aims to complement the current Spanish Drought Monitoring System which relies on a hydrological drought index computed at the basin level using data on river flows and water stored in reservoirs. Drought indices computed by InfoSequia are derived from satellite data provided by MODIS sensors (TERRA and AQUA satellites), and report the relative anomaly observed in the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and in an additive combination of both. Similar to the U.S. Drought Monitoring System by NOAA, the indices include the Vegetation Condition Index (VCI, relative NDVI anomaly), the Temperature Condition Index (TCI, relative LST anomaly) and the Vegetation Health Index (VHI, relative NDVI-LST anomaly). Relative anomalies are codified into four warning levels, and all of them are provided for short periods of time (8-day windows), or longer periods (e.g. 1 year) in order to capture the cumulative effects of droughts in the state variables. Additionally, InfoSequia quantifies the seasonal trajectories of the cumulative deviation of the observed NDVI in relation with the averaged seasonal trajectory observed over a reference period. Through the weekly bulletins, the Drought Monitoring System InfoSequia aims to provide practical information to stakeholders on the sensitivity and resilience of native ecosystems and rainfed agrosystems during drought periods. Also, the remote sensed indices can be used as drought impact indicator to evaluate the skill of seasonal agricultural drought forecasting systems. InfoSequia is partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant.

A Quality Assessment Method Based on Common Distributed Targets for GF-3 Polarimetric SAR Data.

PubMed

Jiang, Sha; Qiu, Xiaolan; Han, Bing; Hu, Wenlong

2018-03-07

The GaoFen-3 (GF-3) satellite, launched on 10 August 2016, is the first C-band polarimetric synthetic aperture radar (PolSAR) satellite in China. The PolSAR system of GF-3 can collect a significant wealth of information for geophysical research and applications. Being used for related applications, GF-3 PolSAR images must be of good quality. It is necessary to evaluate the quality of polarimetric data and achieve the normalized quality monitoring during 8-year designed life of GF-3. In this study, a new quality assessment method of PolSAR data based on common distributed targets is proposed, and the performance of the method is analyzed by simulations and GF-3 experiments. We evaluate the quality of GF-3 PolSAR data by this method. Results suggest that GF-3 antenna is highly isolated, and the quality of calibrated data satisfies the requests of quantitative applications.

Spring Hydrology Determines Summer Net Carbon Uptake in Northern Ecosystems

NASA Technical Reports Server (NTRS)

Yi, Yonghong; Kimball, John; Reichle, Rolf H.

2014-01-01

Increased photosynthetic activity and enhanced seasonal CO2 exchange of northern ecosystems have been observed from a variety of sources including satellite vegetation indices (such as the Normalized Difference Vegetation Index; NDVI) and atmospheric CO2 measurements. Most of these changes have been attributed to strong warming trends in the northern high latitudes (greater than or equal to 50N). Here we analyze the interannual variation of summer net carbon uptake derived from atmospheric CO2 measurements and satellite NDVI in relation to surface meteorology from regional observational records. We find that increases in spring precipitation and snow pack promote summer net carbon uptake of northern ecosystems independent of air temperature effects. However, satellite NDVI measurements still show an overall benefit of summer photosynthetic activity from regional warming and limited impact of spring precipitation. This discrepancy is attributed to a similar response of photosynthesis and respiration to warming and thus reduced sensitivity of net ecosystem carbon uptake to temperature. Further analysis of boreal tower eddy covariance CO2 flux measurements indicates that summer net carbon uptake is positively correlated with early growing-season surface soil moisture, which is also strongly affected by spring precipitation and snow pack based on analysis of satellite soil moisture retrievals. This is attributed to strong regulation of spring hydrology on soil respiration in relatively wet boreal and arctic ecosystems. These results document the important role of spring hydrology in determining summer net carbon uptake and contrast with prevailing assumptions of dominant cold temperature limitations to high-latitude ecosystems. Our results indicate potentially stronger coupling of boreal/arctic water and carbon cycles with continued regional warming trends.

Monitoring green leaf tea quality parameters of different TV clones grown in northeast India using satellite data.

PubMed

Dutta, Rishiraj

2013-08-15

This study tries to quantify the effects of green leaf tea parameters that influence tea quality in Northeast India. The study is to identify the different parameters that have a significant influence on tea quality through the use of remote sensing. It investigates the methods for estimating tea quality based on remotely sensed Normalized Difference Vegetation Index (NDVI) data. Attention focused on high yielding TV clones (TV1, TV18, TV22, TV23, TV25 and TV26). NDVI was obtained from ASTER images. Statistical analysis shows that NDVI has a strong significant effect on the caffeine content followed by epicatechin (EC), epigallocatechin (EGC) and to some extent in other chemical parameters. Relationships therefore exist between quality parameters and remote sensing in particular for the TV clones. This leads to the conclusion that NDVI has a large potential to be used for monitoring tea quality of individual cultivars in the future. Copyright © 2013 Elsevier Ltd. All rights reserved.

Self-Assembled Core-Satellite Gold Nanoparticle Networks for Ultrasensitive Detection of Chiral Molecules by Recognition Tunneling Current.

PubMed

Zhang, Yuanchao; Liu, Jingquan; Li, Da; Dai, Xing; Yan, Fuhua; Conlan, Xavier A; Zhou, Ruhong; Barrow, Colin J; He, Jin; Wang, Xin; Yang, Wenrong

2016-05-24

Chirality sensing is a very challenging task. Here, we report a method for ultrasensitive detection of chiral molecule l/d-carnitine based on changes in the recognition tunneling current across self-assembled core-satellite gold nanoparticle (GNP) networks. The recognition tunneling technique has been demonstrated to work at the single molecule level where the binding between the reader molecules and the analytes in a nanojunction. This process was observed to generate a unique and sensitive change in tunneling current, which can be used to identify the analytes of interest. The molecular recognition mechanism between amino acid l-cysteine and l/d-carnitine has been studied with the aid of SERS. The different binding strength between homo- or heterochiral pairs can be effectively probed by the copper ion replacement fracture. The device resistance was measured before and after the sequential exposures to l/d-carnitine and copper ions. The normalized resistance change was found to be extremely sensitive to the chirality of carnitine molecule. The results suggested that a GNP networks device optimized for recognition tunneling was successfully built and that such a device can be used for ultrasensitive detection of chiral molecules.

Characterization and classification of South American land cover types using satellite data

NASA Technical Reports Server (NTRS)

Townshend, J. R. G.; Justice, C. O.; Kalb, V.

1987-01-01

Various methods are compared for carrying out land cover classifications of South America using multitemporal Advanced Very High Resolution Radiometer data. Fifty-two images of the normalized difference vegetation index (NDVI) from a 1-year period are used to generate multitemporal data sets. Three main approaches to land cover classification are considered, namely the use of the principal components transformed images, the use of a characteristic curves procedure based on NDVI values plotted against time, and finally application of the maximum likelihood rule to multitemporal data sets. Comparison of results from training sites indicates that the last approach yields the most accurate results. Despite the reliance on training site figures for performance assessment, the results are nevertheless extremely encouraging, with accuracies for several cover types exceeding 90 per cent.

The seasonality of AVHRR data of temperate coniferous forests - Relationship with leaf area index

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

1990-01-01

The relationship between the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) and coniferous forest leaf area index (LAI) over the western United States is examined. AVHRR data from the NOAA-9 satellite were acquired of the western U.S. from March 1986 to November 1987 and monthly maximum value composites of AVHRR NDVI were calculated for 19 coniferous forest stands in Oregon, Washington, Montana, and California. It is concluded that the relationships under investigation vary according to seasonal changes in surface reflectance based on key biotic and abiotic controls including phenological changes in LAI caused by seasonal temperature and precipitation variations, the proportions of surface cover types contributing to the overall reflectance, and effects resulting from large variations in the solar zenith angle.

An Extended ADOP for Performance Evaluation of Single-Frequency Single-Epoch Positioning by BDS/GPS in Asia-Pacific Region

PubMed Central

Liu, Xin; Zhang, Shubi; Zhang, Qiuzhao; Yang, Wei

2017-01-01

Single-Frequency Single-Epoch (SFSE) high-precision positioning has always been the hot spot of Global Navigation Satellite System (GNSS), and ambiguity dilution of precision (ADOP) is a well-known scalar measure for success rate of ambiguity resolution. Traditional ADOP expression is complicated, thus the SFSE extended ADOP (E-ADOP), with the newly defined Summation-Multiplication Ratio of Weight (SMRW) and two theorems for short baseline, was developed. This simplifies the ADOP expression; gives a clearer insight into the influences of SMRW and number of satellites on E-ADOP; and makes theoretical analysis of E-ADOP more convenient than that of ADOP, and through that the E-ADOP value can be predicted more accurately than through the ADOP expression for ADOP value. E-ADOP reveals that number of satellites and SMRW or high-elevation satellite are important for ADOP and, through E-ADOP, we studied which factor is dominant to control ADOP in different conditions and make ADOP different between BeiDou Navigation Satellite System (BDS), Global Positioning System (GPS), and BDS/GPS. Based on experimental results of SFSE positioning with different baselines, some conclusions are made: (1) ADOP decreases when new satellites are added mainly because the number of satellites becomes larger; (2) when the number of satellites is constant, ADOP is mainly affected by SMRW; (3) in contrast to systems where the satellites with low-elevation are the majority or where low- and high-elevation satellites are equally distributed, in systems where the high-elevation satellites are the majority, the SMRW mainly makes ADOP smaller, even if there are fewer satellites than in the two previous cases, and the difference in numbers of satellites can be expanded as the proportion of high-elevation satellites becomes larger; and (4) ADOP of BDS is smaller than ADOP of GPS mainly because of its SMRW. PMID:28973977

Image sharpening for mixed spatial and spectral resolution satellite systems

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Cox, S.

1983-01-01

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

RST (Robust Satellite Techniques) analysis for monitoring earth emitted radiation in seismically active area of California (US): a long term (2006-2011) analysis of GOES-W/IMAGER thermal data

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Armandi, B.; Filizzola, C.; Genzano, N.; Lisi, M.; Paciello, R.; Pergola, N.

2014-12-01

More than ten years of applications of the RST (Robust Satellite Techniques) methodology for monitoring earthquake prone area by using satellite TIR(Thermal InfraRed) data, have shown the ability of this approach to discern anomalous TIR signals possibly associated to seismic activity from normal fluctuations of Earth's thermal emission related to other causes independent on the earthquake occurrence. The RST approach was already tested in the case of tens of earthquakes occurred in different continents (Europe, Asia, America and Africa), in various geo-tectonic settings (compressive, extensional and transcurrent) and with a wide range of magnitudes (from 4.0 to 7.9), by analyzing time series of TIR images acquired by sensors on board of polar (like NOAA/AVHRR, EOS/MODIS) and geostationary satellites (like MFG/MVIRI, MSG/SEVIRI, GOES/IMAGER). In addition RST method has been independently tested by several researchers around the world as well as in the framework of several projects funded by different national space agencies (like the Italian ASI, the U.S. NASA and the German DLR) and recently during the EC-FP7 projectPRE-EARTHQUAKES (www.pre-earthquakes.org),which was devoted to study the earthquake precursors using satellite techniques. This paper will show the results of RST analysis on 6 years (2006-2011)of TIR satellite record collected by GOES-W/IMAGER over Southern part United State (California).Results will be discussed particularly in the prospective of an integrated approach devoted to systematically collectand analyze in real-time, independent observations for a time-Dependent Assessment of Seismic Hazard (t-DASH).

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

NASA Technical Reports Server (NTRS)

Steffen, K.; Abdalati, W.; Stroeve, J.; Key, J.

1994-01-01

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Study of the model of calibrating differences of brightness temperature from geostationary satellite generated by time zone differences

NASA Astrophysics Data System (ADS)

Li, Weidong; Shan, Xinjian; Qu, Chunyan

2010-11-01

In comparison with polar-orbiting satellites, geostationary satellites have a higher time resolution and wider field of visions, which can cover eleven time zones (an image covers about one third of the Earth's surface). For a geostationary satellite panorama graph at a point of time, the brightness temperature of different zones is unable to represent the thermal radiation information of the surface at the same point of time because of the effect of different sun solar radiation. So it is necessary to calibrate brightness temperature of different zones with respect to the same point of time. A model of calibrating the differences of the brightness temperature of geostationary satellite generated by time zone differences is suggested in this study. A total of 16 curves of four positions in four different stages are given through sample statistics of brightness temperature of every 5 days synthetic data which are from four different time zones (time zones 4, 6, 8, and 9). The above four stages span January -March (winter), April-June (spring), July-September (summer), and October-December (autumn). Three kinds of correct situations and correct formulas based on curves changes are able to better eliminate brightness temperature rising or dropping caused by time zone differences.

A fresh look at crater scaling laws for normal and oblique hypervelocity impacts

NASA Technical Reports Server (NTRS)

Watts, A. J.; Atkinson, D. R.; Rieco, S. R.; Brandvold, J. B.; Lapin, S. L.; Coombs, C. R.

1993-01-01

With the concomitant increase in the amount of man-made debris and an ever increasing use of space satellites, the issue of accidental collisions with particles becomes more severe. While the natural micrometeoroid population is unavoidable and assumed constant, continued launches increase the debris population at a steady rate. Debris currently includes items ranging in size from microns to meters which originated from spent satellites and rocket cases. To understand and model these environments, impact damage in the form of craters and perforations must be analyzed. Returned spacecraft materials such as those from LDEF and Solar Max have provided such a testbed. From these space-aged samples various impact parameters (i.e., particle size, particle and target material, particle shape, relative impact speed, etc.) may be determined. These types of analyses require the use of generic analytic scaling laws which can adequately describe the impact effects. Currently, most existing analytic scaling laws are little more than curve-fits to limited data and are not based on physics, and thus are not generically applicable over a wide range of impact parameters. During this study, a series of physics-based scaling laws for normal and oblique crater and perforation formation has been generated into two types of materials: aluminum and Teflon.

GNSS triple-frequency geometry-free and ionosphere-free track-to-track ambiguities

NASA Astrophysics Data System (ADS)

Wang, Kan; Rothacher, Markus

2015-06-01

During the last few years, more and more GNSS satellites have become available sending signals on three or even more frequencies. Examples are the GPS Block IIF and the Galileo In-Orbit-Validation (IOV) satellites. Various investigations have been performed to make use of the increasing number of frequencies to find a compromise between eliminating different error sources and minimizing the noise level, including the investigations in the triple-frequency geometry-free (GF) and ionosphere-free (IF) linear combinations, which eliminate all the geometry-related errors and the first-order term of the ionospheric delays. In contrast to the double-difference GF and IF ambiguity resolution, the resolution of the so-called track-to-track GF and IF ambiguities between two tracks of a satellite observed by the same station only requires one receiver and one satellite. Most of the remaining errors like receiver and satellite delays (electronics, cables, etc.) are eliminated, if they are not changing rapidly in time, and the noise level is reduced theoretically by a factor of square root of two compared to double-differences. This paper presents first results concerning track-to-track ambiguity resolution using triple-frequency GF and IF linear combinations based on data from the Multi-GNSS Experiment (MGEX) from April 29 to May 9, 2012 and from December 23 to December 29, 2012. This includes triple-frequency phase and code observations with different combinations of receiver tracking modes. The results show that it is possible to resolve the combined track-to-track ambiguities of the best two triple-frequency GF and IF linear combinations for the Galileo frequency triplet E1, E5b and E5a with more than 99.6% of the fractional ambiguities for the best linear combination being located within ± 0.03 cycles and more than 98.8% of the fractional ambiguities for the second best linear combination within ± 0.2 cycles, while the fractional parts of the ambiguities for the GPS frequency triplet L1, L2 and L5 are more disturbed by errors as e.g. the uncalibrated Phase Center Offsets (PCOs) and Phase Center Variations (PCVs), that have not been considered. The best two GF and IF linear combinations between tracks are helpful to detect problems in data and receivers. Furthermore, resolving the track-to-track ambiguities is helpful to connect the single-receiver ambiguities on the normal equation level and to improve ambiguity resolution.

Estimation of geopotential from satellite-to-satellite range rate data: Numerical results

NASA Technical Reports Server (NTRS)

Thobe, Glenn E.; Bose, Sam C.

1987-01-01

A technique for high-resolution geopotential field estimation by recovering the harmonic coefficients from satellite-to-satellite range rate data is presented and tested against both a controlled analytical simulation of a one-day satellite mission (maximum degree and order 8) and then against a Cowell method simulation of a 32-day mission (maximum degree and order 180). Innovations include: (1) a new frequency-domain observation equation based on kinetic energy perturbations which avoids much of the complication of the usual Keplerian element perturbation approaches; (2) a new method for computing the normalized inclination functions which unlike previous methods is both efficient and numerically stable even for large harmonic degrees and orders; (3) the application of a mass storage FFT to the entire mission range rate history; (4) the exploitation of newly discovered symmetries in the block diagonal observation matrix which reduce each block to the product of (a) a real diagonal matrix factor, (b) a real trapezoidal factor with half the number of rows as before, and (c) a complex diagonal factor; (5) a block-by-block least-squares solution of the observation equation by means of a custom-designed Givens orthogonal rotation method which is both numerically stable and tailored to the trapezoidal matrix structure for fast execution.

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

NASA Technical Reports Server (NTRS)

Li, Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey C.; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

2009-01-01

Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

A TT&C Performance Simulator for Space Exploration and Scientific Satellites - Architecture and Applications

NASA Astrophysics Data System (ADS)

Donà, G.; Faletra, M.

2015-09-01

This paper presents the TT&C performance simulator toolkit developed internally at Thales Alenia Space Italia (TAS-I) to support the design of TT&C subsystems for space exploration and scientific satellites. The simulator has a modular architecture and has been designed using a model-based approach using standard engineering tools such as MATLAB/SIMULINK and mission analysis tools (e.g. STK). The simulator is easily reconfigurable to fit different types of satellites, different mission requirements and different scenarios parameters. This paper provides a brief description of the simulator architecture together with two examples of applications used to demonstrate some of the simulator’s capabilities.

Effects of preprocessing Landsat MSS data on derived features

NASA Technical Reports Server (NTRS)

Parris, T. M.; Cicone, R. C.

1983-01-01

Important to the use of multitemporal Landsat MSS data for earth resources monitoring, such as agricultural inventories, is the ability to minimize the effects of varying atmospheric and satellite viewing conditions, while extracting physically meaningful features from the data. In general, the approaches to the preprocessing problem have been derived from either physical or statistical models. This paper compares three proposed algorithms; XSTAR haze correction, Color Normalization, and Multiple Acquisition Mean Level Adjustment. These techniques represent physical, statistical, and hybrid physical-statistical models, respectively. The comparisons are made in the context of three feature extraction techniques; the Tasseled Cap, the Cate Color Cube. and Normalized Difference.

The FAO/NASA/NLR Artemis system - An integrated concept for environmental monitoring by satellite in support of food/feed security and desert locust surveillance

NASA Technical Reports Server (NTRS)

Hielkema, J. U.; Howard, J. A.; Tucker, C. J.; Van Ingen Schenau, H. A.

1987-01-01

The African real time environmental monitoring using imaging satellites (Artemis) system, which should monitor precipitation and vegetation conditions on a continental scale, is presented. The hardware and software characteristics of the system are illustrated and the Artemis databases are outlined. Plans for the system include the use of hourly digital Meteosat data and daily NOAA/AVHRR data to study environmental conditions. Planned mapping activities include monthly rainfall anomaly maps, normalized difference vegetation index maps for ten day and monthly periods with a spatial resolution of 7.6 km, ten day crop/rangeland moisture availability maps, and desert locust potential breeding activity factor maps for a plague prevention program.

Using MODIS NDVI phenoclasses and phenoclusters to characterize wildlife habitat: Mexican spotted owl as a case study

Treesearch

Serra J. Hoagland; Paul Beier; Danny Lee

2018-01-01

Most uses of remotely sensed satellite data to characterize wildlife habitat have used metrics such as mean NDVI (Normalized Difference Vegetation Index) in a year or season. These simple metrics do not take advantage of the temporal patterns in NDVI within and across years and the spatial arrangement of cells with various temporal NDVI signatures. Here we use 13 years...

Multiple access techniques and spectrum utilization of the GLOBALSTAR mobile satellite system

NASA Astrophysics Data System (ADS)

Louie, Ming; Cohen, Michel; Rouffet, Denis; Gilhousen, Klein S.

The GLOBALSTAR System is a Low Earth Orbit (LEO) satellite-based mobile communications system that is interoperable with the current and future Public Land Mobile Network (PLMN). The GLOBALSTAR System concept is based upon technological advancement in two key areas: (1) the advancement in LEO satellite technology; (2) the advancement in cellular telephone technology, including the commercial applications of Code Division Multiple Access (CDMA) technologies, and of the most recent progress in Time Division Multiple Access technologies. The GLOBALSTAR System uses elements of CDMA, Frequency Division Multiple Access (FDMA), and Time Division Multiple Access (TDMA) technology, combining with satellite Multiple Beam Antenna (MBA) technology, to arrive at one of the most efficient modulation and multiple access system ever proposed for a satellite communications system. The technology used in GLOBALSTAR exploits the following techniques in obtaining high spectral efficiency and affordable cost per channel, with minimum coordination among different systems: power control, in open and closed loops, voice activation, spot beam satellite antenna for frequency reuse, weighted satellite antenna gain, multiple satellite coverage, and handoff between satellites. The GLOBALSTAR system design will use the following frequency bands: 1610-1626.5 MHz for up-link and 2483.5-2500 MHz for down-link.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

USGS Publications Warehouse

Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

2014-01-01

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

PubMed

Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

PubMed Central

Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

PubMed

Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

2006-08-01

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

Ionospheric Irregularities Characterization by Ground and Space-based GPS Observations

NASA Astrophysics Data System (ADS)

Zakharenkova, I.; Cherniak, I.; Krankowski, A.

2017-12-01

We present new results on detection and investigation of the topside ionospheric irregularities using GPS measurements from Precise Orbit Determination (POD) GPS antenna onboard Low Earth Orbit satellites. Our investigation is based on the recent ESA's Swarm mission launched on 22 November 2013 and consisted of three identical satellites, two of them fly in a tandem at an orbit altitude of 460 km while the third satellite - at an orbit altitude of 510 km. Each satellite is equipped with a zenith-looking antenna and 8-channel dual-frequency GPS receiver that delivered 1 Hz data for POD purposes, as well as Langmuir Probe instrument for in situ electron density. Additionally, we have analyzed GPS measurements onboard GRACE and TerraSAR-X satellite, which have rather similar to Swarm orbit altitude of 500 km. GPS measurements onboard MetOP-A and MetOP-B satellites (altitude of 840 km) can complement these observations in order to estimate an altitudinal extent of the ionospheric irregularities penetrating to higher altitudes. We demonstrate that space-based GPS observations can be effectively used for monitoring of the topside ionospheric irregularities occurrence in both high-latitude and equatorial regions and may essentially contribute to the multi-instrumental analysis of the ground-based and in situ data. Climatological characteristics of the equatorial ionospheric irregularities occurrence probability are derived from POD GPS measurements for all longitudinal sectors for the years 2013-2016. Several examples of strong geomagnetic storms, including the 2015 St. Patrick's Day storm, were analyzed to demonstrate differences between the climatlogical characteristics in space-based GPS data and storm-induced equatorial irregularities observations (postsunset suppression, night/morning-time occurrence). To support our observations and conclusions, we involve into our analysis in situ plasma density provided by Swarm constellation, GRACE KBR, DMSP satellites, as well as ground-based GNSS and digisonde networks. New International GNSS Service (IGS) product - the Northern Hemisphere GPS-based ROTI (rate of the TEC index) maps - was analyzed to determine similarities and differences in ionospheric irregularities signatures in the ground and space-based GPS observations.

Observed characteristics of dust storm events over the western United States using meteorological, satellite, and air quality measurements

NASA Astrophysics Data System (ADS)

Lei, H.; Wang, J. X. L.

2014-08-01

To improve dust storm identification over the western United States, historical dust events measured by air quality and satellite observations are analyzed based on their characteristics in data sets of regular meteorology, satellite-based aerosol optical depth (AOD), and air quality measurements. Based on the prevailing weather conditions associated with dust emission, dust storm events are classified into the following four typical types: (1) The key feature of cold front-induced dust storms is their rapid process with strong dust emissions. (2) Events caused by meso- to small-scale weather systems have the highest levels of emissions. (3) Dust storms caused by tropical disturbances show a stronger air concentration of dust and last longer than those in (1) and (2). (4) Dust storms triggered by cyclogenesis last the longest. In this paper, sample events of each type are selected and examined to explore characteristics observed from in situ and remote-sensing measurements. These characteristics include the lasting period, surface wind speeds, areas affected, average loading on ground-based optical and/or air quality measurements, peak loading on ground-based optical and/or air quality measurements, and loading on satellite-based aerosol optical depth. Based on these analyses, we compare the characteristics of the same dust events captured in different data sets in order to define the dust identification criteria. The analyses show that the variability in mass concentrations captured by in situ measurements is consistent with the variability in AOD from stationary and satellite observations. Our analyses also find that different data sets are capable of identifying certain common characteristics, while each data set also provides specific information about a dust storm event. For example, the meteorological data are good at identifying the lasting period and area impacted by a dust event; the ground-based air quality and optical measurements can capture the peak strength well; aerosol optical depth (AOD) from satellite data sets allows us to better identify dust-storm-affected areas and the spatial extent of dust. The current study also indicates that the combination of in situ and satellite observations is a better method to fill gaps in dust storm recordings.

Detecting plague-host abundance from space: Using a spectral vegetation index to identify occupancy of great gerbil burrows

NASA Astrophysics Data System (ADS)

Wilschut, Liesbeth I.; Heesterbeek, Johan A. P.; Begon, Mike; de Jong, Steven M.; Ageyev, Vladimir; Laudisoit, Anne; Addink, Elisabeth A.

2018-02-01

In Kazakhstan, plague outbreaks occur when its main host, the great gerbil, exceeds an abundance threshold. These live in family groups in burrows, which can be mapped using remote sensing. Occupancy (percentage of burrows occupied) is a good proxy for abundance and hence the possibility of an outbreak. Here we use time series of satellite images to estimate occupancy remotely. In April and September 2013, 872 burrows were identified in the field as either occupied or empty. For satellite images acquired between April and August, 'burrow objects' were identified and matched to the field burrows. The burrow objects were represented by 25 different polygon types, then classified (using a majority vote from 10 Random Forests) as occupied or empty, using Normalized Difference Vegetation Indices (NDVI) calculated for all images. Throughout the season NDVI values were higher for empty than for occupied burrows. Occupancy status of individual burrows that were continuously occupied or empty, was classified with producer's and user's accuracy values of 63 and 64% for the optimum polygon. Occupancy level was predicted very well and differed 2% from the observed occupancy. This establishes firmly the principle that occupancy can be estimated using satellite images with the potential to predict plague outbreaks over extensive areas with much greater ease and accuracy than previously.

An optical and X-ray survey of s-type Markarian galaxies

NASA Technical Reports Server (NTRS)

Hutter, D. J.; Mufson, S. L.

1981-01-01

The results of a study of 23 compact, lineless Markarian galaxies using broadband optical photometry and X-ray satellite observations are reported. The photometry shows that the sample can be broken into four groups. In one group (Mrk 180, 421, and 501) are composite objects in which a BL Lacertae object is embedded in an elliptical galaxy. For this group, the results of multiepoch X-ray observations using the HEAO-1 and -2 satellites are presented. In addition, photometry is used to decompose the optical emission into nonthermal and galactic components. In the second group are objects showing a small ultraviolet excess relative to normal galaxies. The X-ray survey indicates that the X-ray luminosity of objects in group 2 is much lower than those in group 1. This suggests that there is an intrinsic difference between objects in groups 1 and 2. The third and fourth groups are objects whose colors are indistinguishable from those of normal field galaxies and those of galactic stars, respectively. No X-ray emission was detected from objects in either of these groups.

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

The dynamics of the de Sitter resonance

NASA Astrophysics Data System (ADS)

Celletti, Alessandra; Paita, Fabrizio; Pucacco, Giuseppe

2018-02-01

We study the dynamics of the de Sitter resonance, namely the stable equilibrium configuration of the first three Galilean satellites. We clarify the relation between this family of configurations and the more general Laplace resonant states. In order to describe the dynamics around the de Sitter stable equilibrium, a one-degree-of-freedom Hamiltonian normal form is constructed and exploited to identify initial conditions leading to the two families. The normal form Hamiltonian is used to check the accuracy in the location of the equilibrium positions. Besides, it gives a measure of how sensitive it is with respect to the different perturbations acting on the system. By looking at the phase plane of the normal form, we can identify a Laplace-like configuration, which highlights many substantial aspects of the observed one.

Studies on the ionospheric-thermospheric coupling mechanisms using SLR

NASA Astrophysics Data System (ADS)

Panzetta, Francesca; Erdogan, Eren; Bloßfeld, Mathis; Schmidt, Michael

2016-04-01

Several Low Earth Orbiters (LEOs) have been used by different research groups to model the thermospheric neutral density distribution at various altitudes performing Precise Orbit Determination (POD) in combination with satellite accelerometry. This approach is, in principle, based on satellite drag analysis, driven by the fact that the drag force is one of the major perturbing forces acting on LEOs. The satellite drag itself is physically related to the thermospheric density. The present contribution investigates the possibility to compute the thermospheric density from Satellite Laser Ranging (SLR) observations. SLR is commonly used to compute very accurate satellite orbits. As a prerequisite, a very high precise modelling of gravitational and non-gravitational accelerations is necessary. For this investigation, a sensitivity study of SLR observations to thermospheric density variations is performed using the DGFI Orbit and Geodetic parameter estimation Software (DOGS). SLR data from satellites at altitudes lower than 500 km are processed adopting different thermospheric models. The drag coefficients which describe the interaction of the satellite surfaces with the atmosphere are analytically computed in order to obtain scaling factors purely related to the thermospheric density. The results are reported and discussed in terms of estimates of scaling coefficients of the thermospheric density. Besides, further extensions and improvements in thermospheric density modelling obtained by combining a physics-based approach with ionospheric observations are investigated. For this purpose, the coupling mechanisms between the thermosphere and ionosphere are studied.

TOPEX/El Niño Watch - Satellite shows Pacific Stabilizing, July 11, 1998

NASA Image and Video Library

1998-07-21

Height measurements taken by NASA U.S.-French TOPEX/Poseidon satellite. The image shows sea surface height relative to normal ocean conditions on July 11, 1998; sea surface height is an indicator of the heat content of the ocean.

An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions

DOE PAGES

Denton, M. H.; Henderson, M. G.; Jordanova, V. K.; ...

2016-07-01

In this study, a new empirical model of the electron fluxes and ion fluxes at geosynchronous orbit (GEO) is introduced, based on observations by Los Alamos National Laboratory (LANL) satellites. The model provides flux predictions in the energy range ~1 eV to ~40 keV, as a function of local time, energy, and the strength of the solar wind electric field (the negative product of the solar wind speed and the z component of the magnetic field). Given appropriate upstream solar wind measurements, the model provides a forecast of the fluxes at GEO with a ~1 h lead time. Model predictionsmore » are tested against in-sample observations from LANL satellites and also against out-of-sample observations from the Compact Environmental Anomaly Sensor II detector on the AMC-12 satellite. The model does not reproduce all structure seen in the observations. However, for the intervals studied here (quiet and storm times) the normalized root-mean-square deviation < ~0.3. It is intended that the model will improve forecasting of the spacecraft environment at GEO and also provide improved boundary/input conditions for physical models of the magnetosphere.« less

Characterization of turbidity in Florida's Lake Okeechobee and Caloosahatchee and St. Lucie estuaries using MODIS-Aqua measurements.

PubMed

Wang, Menghua; Nim, Carl J; Son, Seunghyun; Shi, Wei

2012-10-15

This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and estuarine ecosystems allows researchers to understand important factors such as light limitation and the potential release of nutrients from re-suspended sediments. Based on a strong correlation between water turbidity and normalized water-leaving radiance at the near-infrared (NIR) band (nL(w)(869)), a new satellite water turbidity algorithm has been developed for Lake Okeechobee. This study has shown important applications with satellite-measured nL(w)(869) data for water quality monitoring and measurements for turbid inland lakes. MODIS-Aqua-measured water property data are derived using the shortwave infrared (SWIR)-based atmospheric correction algorithm in order to remotely obtain synoptic turbidity data in Lake Okeechobee and normalized water-leaving radiance using the red band (nL(w)(645)) in the Caloosahatchee and St. Lucie estuaries. We found varied, but distinct seasonal, spatial, and event driven turbidity trends in Lake Okeechobee and the Caloosahatchee and St. Lucie estuary regions. Wind waves and hurricanes have the largest influence on turbidity trends in Lake Okeechobee, while tides, currents, wind waves, and hurricanes influence the Caloosahatchee and St. Lucie estuarine areas. Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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.

Survey of DMSP Charging Events During the Period Preceding Cycle 23 Solar Maximum

NASA Technical Reports Server (NTRS)

Parker, Linda Neergaard; Minow, Joseph I.

2013-01-01

It has been well established that POLAR orbiting satellites can see mild to severe charging levels during solar minimum conditions (Frooninckx and Sojka, 1992, Anderson and Koons, 1996, Anderson, 2012). However, spacecraft operations during solar maximum cannot be considered safe from auroral charging. Recently, we have seen examples of high level charging during the recent approach to solar maximum. We present here a survey of charging events seen by the Defense Meteorological Satellite Program (DMSP) satellites (F16, F17) during the solstices of 2011 and 2012. In this survey, we summarize the condition necessary for charging to occur in this environment, we describe how the lower than normal maximum conditions are conducive to the environment conditions necessary for charging in the POLAR orbit, and we show examples of the more extreme charging events, sometimes exceeding 1 kV, during this time period. We also show examples of other interesting phenomenological events seen in the DMSP data, but which are not considered surface charging events, and discuss the differences.

Survey of DMSP Charging During the Period Preceding Cycle 24 Solar Maximum

NASA Technical Reports Server (NTRS)

NeergaardParker, L.; Minow, Joseph I.

2013-01-01

It has been well established that polar orbiting satellites can see mild to severe charging levels during solar minimum conditions (Frooninckx and Sojka, 1992, Anderson and Koons, 1996, Anderson, 2012). However, spacecraft operations during solar maximum cannot be considered safe from auroral charging. Recently, we have seen examples of high level charging during the recent approach to solar maximum. We present here a survey of charging events seen by the Defense Meteorological Satellite Program (DMSP) satellites (F16, F17) during the solstices of 2011 and 2012. In this survey, we summarize the condition necessary for charging to occur in this environment, we describe how the lower than normal maximum conditions are conducive to the environment conditions necessary for charging in the polar orbit, and we show examples of the more extreme charging events, sometimes exceeding 1 kV, during this time period. We also show examples of other interesting phenomenological events seen in the DMSP data, but which are not considered surface charging events, and discuss the differences.

Evaluating the relationships between solar-induced chlorophyll fluorescence from Orbiting Carbon Observatory-2 and gross primary productivity from eddy covariance flux towers

NASA Astrophysics Data System (ADS)

Li, X.; Xiao, J.; He, B.

2017-12-01

Solar-induced chlorophyll fluorescence (SIF) opens a new perspective on the monitoring of vegetation photosynthesis from space, and has been recently used to estimate gross primary productivity (GPP). However, previous studies on SIF were mainly based on satellite observations from the Greenhouse Gases Observing Satellite (GOSAT) and Global Ozone Monitoring Experiment-2 (GOME-2), and the evaluation of these coarse-resolution SIF measurements using GPP derived from eddy covariance (EC) flux towers has been hindered by the scale mismatch between satellite and tower footprints. We use new far-red SIF observations from the Orbiting Carbon Observatory-2 (OCO-2) satellite with much finer spatial resolution and GPP data from EC flux towers from 2014 to 2016 to examine the relationship between GPP and SIF for temperate forests. The OCO-2 SIF tracked tower GPP fairly well, and had strong correlation with tower GPP at both retrieval bands (757nm and 771nm) and both instantaneous (mid-day) and daily timescales. Daily SIF at 757nm (SIF757) exhibited much stronger correlation with tower GPP compared to MODIS enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) derived from either Terra or Aqua and had a similarly strong relationship as EVI based on the bidirectional reflectance distribution function (BRDF) corrected reflectance product (Terra+Aqua). Absorbed photosynthetically active radiation (APAR) explained 85% of the variance in SIF757, while the product of APAR and two environmental scalars - fTmin and fVPD (representing minimum temperature stress and water stress) explained slightly higher variance (92%) in SIF757. This suggests that SIF mainly depends on APAR and also contains information on light use efficiency (LUE) reflecting environmental stresses and physiological or biochemical variations of vegetation. The hyperbolic model based on SIF757 estimated GPP well (R2=0.81, p<0.0001; RMSE=1.11 gC m-2 d-1), and its performance was comparable to or slightly better than that of a LUE-based GPP model - the MODSI GPP algorithm. Our findings demonstrate the strong predictive ability of OCO-2 SIF in estimating GPP for temperate forests and its potential in future ecosystem functioning and carbon cycling studies.

Satellite Observations of NO2 Trend over Romania

PubMed Central

Voiculescu, Mirela; Georgescu, Lucian

2013-01-01

Satellite-based measurements of atmospheric trace gases loading give a realistic image of atmospheric pollution at global, regional, and urban level. The aim of this paper is to investigate the trend of atmospheric NO2 content over Romania for the period 1996–2010 for several regions which are generally characterized by different pollutant loadings, resulting from GOME-1, SCIAMACHY, OMI, and GOME-2 instruments. Satellite results are then compared with ground-based in situ measurements made in industrial and relatively clean areas of one major city in Romania. This twofold approach will help in estimating whether the trend of NO2 obtained by means of data satellite retrievals can be connected with the evolution of national industry and transportation. PMID:24453819

Orbit Determination of the SELENE Satellites Using Multi-Satellite Data Types and Evaluation of SELENE Gravity Field Models

NASA Technical Reports Server (NTRS)

Goossens, S.; Matsumoto, K.; Noda, H.; Araki, H.; Rowlands, D. D.; Lemoine, F. G.

2011-01-01

The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether l-day data overlaps or I-day predictions are used.

Comparison of GOME-2/MetOp total ozone data with Brewer spectroradiometer data over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Antón, M.; Loyola, D.; López, M.; Vilaplana, J. M.; Bañón, M.; Zimmer, W.; Serrano, A.

2009-04-01

The main objective of this article is to compare the total ozone data from the new Global Ozone Monitoring Experiment instrument (GOME-2/MetOp) with reliable ground-based measurement recorded by five Brewer spectroradiometers in the Iberian Peninsula. In addition, a similar comparison for the predecessor instrument GOME/ERS-2 is described. The period of study is a whole year from May 2007 to April 2008. The results show that GOME-2/MetOp ozone data already has a very good quality, total ozone columns are on average 3.05% lower than Brewer measurements. This underestimation is higher than that obtained for GOME/ERS-2 (1.46%). However, the relative differences between GOME-2/MetOp and Brewer measurements show significantly lower variability than the differences between GOME/ERS-2 and Brewer data. Dependencies of these relative differences with respect to the satellite solar zenith angle (SZA), the satellite scan angle, the satellite cloud cover fraction (CF), and the ground-based total ozone measurements are analyzed. For both GOME instruments, differences show no significant dependence on SZA. However, GOME-2/MetOp data show a significant dependence on the satellite scan angle (+1.5%). In addition, GOME/ERS-2 differences present a clear dependence with respect to the CF and ground-based total ozone; such differences are minimized for GOME-2/MetOp. The comparison between the daily total ozone values provided by both GOME instruments shows that GOME-2/MetOp ozone data are on average 1.46% lower than GOME/ERS-2 data without any seasonal dependence. Finally, deviations of a priori climatological ozone profile used by the satellite retrieval algorithm from the true ozone profile are analyzed. Although excellent agreement between a priori climatological and measured partial ozone values is found for the middle and high stratosphere, relative differences greater than 15% are common for the troposphere and lower stratosphere.

Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems

DOE PAGES

Feng, Fei; Chen, Jiquan; Li, Xianglan; ...

2015-12-09

Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolutionmore » imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance over semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m 2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m 2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.« less

Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Fei; Chen, Jiquan; Li, Xianglan

Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolutionmore » imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance over semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m 2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m 2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.« less

A Wiener-Wavelet-Based filter for de-noising satellite soil moisture retrievals

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Ciabatta, Luca; Moramarco, Tommaso; Su, Chun-Hsu; Ryu, Dongryeol; Wagner, Wolfgang

2014-05-01

The reduction of noise in microwave satellite soil moisture (SM) retrievals is of paramount importance for practical applications especially for those associated with the study of climate changes, droughts, floods and other related hydrological processes. So far, Fourier based methods have been used for de-noising satellite SM retrievals by filtering either the observed emissivity time series (Du, 2012) or the retrieved SM observations (Su et al. 2013). This contribution introduces an alternative approach based on a Wiener-Wavelet-Based filtering (WWB) technique, which uses the Entropy-Based Wavelet de-noising method developed by Sang et al. (2009) to design both a causal and a non-causal version of the filter. WWB is used as a post-retrieval processing tool to enhance the quality of observations derived from the i) Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), ii) the Advanced SCATterometer (ASCAT), and iii) the Soil Moisture and Ocean Salinity (SMOS) satellite. The method is tested on three pilot sites located in Spain (Remedhus Network), in Greece (Hydrological Observatory of Athens) and in Australia (Oznet network), respectively. Different quantitative criteria are used to judge the goodness of the de-noising technique. Results show that WWB i) is able to improve both the correlation and the root mean squared differences between satellite retrievals and in situ soil moisture observations, and ii) effectively separates random noise from deterministic components of the retrieved signals. Moreover, the use of WWB de-noised data in place of raw observations within a hydrological application confirms the usefulness of the proposed filtering technique. Du, J. (2012), A method to improve satellite soil moisture retrievals based on Fourier analysis, Geophys. Res. Lett., 39, L15404, doi:10.1029/ 2012GL052435 Su,C.-H.,D.Ryu, A. W. Western, and W. Wagner (2013), De-noising of passive and active microwave satellite soil moisture time series, Geophys. Res. Lett., 40,3624-3630, doi:10.1002/grl.50695. Sang Y.-F., D. Wang, J.-C. Wu, Q.-P. Zhu, and L. Wang (2009), Entropy-Based Wavelet De-noising Method for Time Series Analysis, Entropy, 11, pp. 1123-1148, doi:10.3390/e11041123.

Validating NO2 measurements in the vertical atmospheric column with the OMI instrument aboard the EOS Aura satellite against ground-based measurements at the Zvenigorod Scientific Station

NASA Astrophysics Data System (ADS)

Gruzdev, A. N.; Elokhov, A. S.

2009-08-01

Data on the NO2 content in the vertical column of the atmosphere obtained with the Ozone Monitoring Instrument (OMI) aboard the EOS Aura satellite (United States) in the period from October 2004 to October 2007 are compared with the results of ground-based measurements at the Zvenigorod Scientific Station (55.7° N, 36.8° E). The “unpolluted”; part of the total NO2 content in the atmospheric column, which mostly represents the stratosphere, and the NO2 contents in the vertical column of the troposphere, including the lower layer, which is subject to pollution, are included in the comparison. The correlation coefficient between the results of ground-based and satellite measurements of the “unpolluted” total NO2 content is ˜0.9. The content values measured with the OMI instrument are smaller than the results of ground-based measurements (on average, by (0.30 ± 0.03) × 1015 cm-2 or by (11 ± 1)%). Therms discrepancy between the satellite and ground-based data is 0.6 × 1015 cm-2. The NO2 content in the vertical column of the troposphere from the results of satellite measurements is, on average, (1.4 ± 0.5) × 1015 cm-2, (or about 35%) smaller than from the results of ground-based measurements, and the rms discrepancy between them is about 200%. The correlation coefficient between these data is ˜0.4. This considerable discrepancy is evidently caused by the strong spatial (horizontal) inhomogeneity and the temporal variability of the NO2 field during episodes of pollution, which leads to different (and often uncorrelated) estimates of the NO2 content in the lower troposphere due to different spatial resolutions of ground-based and satellite measurements.

Robust Satellite Techniques to support the short-term assessment of the seismic hazard in Japan: an analysis on 11 years (2005-2015) of MTSAT TIR observations

NASA Astrophysics Data System (ADS)

Genzano, Nicola; Filizzola, Carolina; Hattori, Katsumi; Lisi, Mariano; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2017-04-01

In order to increase reliability and precision of short-term seismic hazard assessment (but also a possible earthquakes forecast), the integration of different kinds of observations (chemical, physical, biological, etc.) in a multi-parametric approach could be a useful strategy to be undertaken. Among the different observational methodologies, the fluctuations of Earth's thermally emitted radiation, measured by satellite sensors operating in the thermal infrared (TIR) spectral range, have been proposed since eighties as a potential earthquake precursor. Since 2001, the general change detention approach Robust Satellite Techniques (RST), used in combination with RETIRA (Robust Estimator of TIR Anomalies) index, showed good ability to discriminate anomalous TIR signals possibly associated to seismic activity, from the normal variability of TIR signal due to other causes (e.g. meteorological). In this paper, the RST data analysis approach has been implemented on TIR satellite records collected over Japan by the geostationary satellite sensor MTSAT (Multifunctional Transport SATellites) in the period June 2005 - December 2015 in order to evaluate its possible contribute to an improved multi parametric system for a time-Dependent Assessment of Seismic Hazard (t-DASH). For the first time, thermal anomalies have been identified comparing the daily TIR radiation of each location of the considered satellite portions, with its historical expected value and variation range (i.e. RST reference fields) computed using a a 30 days moving window (i.e. 15 days before and 15 days after the considered day of the year) instead than fixed monthly window. Preliminary results of correlation analysis among the appearance of Significant Sequences of TIR Anomalies (SSTAs) and time, location and magnitude of earthquakes (M≥5), performed by applying predefined space-temporal and magnitude constraints, show that 80% of SSTAs were in an apparent space-time relations with earthquakes with a false alarm rate of 20%.

Free geometric adjustment of the SECOR Equatorial Network (Solution SECOR-27)

NASA Technical Reports Server (NTRS)

Mueller, I. I.; Kumar, M.; Soler, T.

1973-01-01

The basic purpose of this experiment is to compute reduced normal equations from the observational data of the SECOR Equatorial Network obtained from DMA/Topographic Center, D/Geodesy, Geosciences Div. Washington, D.C. These reduced normal equations are to be combined with reduced normal equations of other satellite networks of the National Geodetic Satellite Program to provide station coordinates from a single least square adjustment. An individual SECOR solution was also obtained and is presented in this report, using direction constraints computed from BC-4 optical data from stations collocated with SECOR stations. Due to the critical configuration present in the range observations, weighted height constraints were also applied in order to break the near coplanarity of the observing stations.

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

The SAGA Survey. I. Satellite Galaxy Populations around Eight Milky Way Analogs

NASA Astrophysics Data System (ADS)

Geha, Marla; Wechsler, Risa H.; Mao, Yao-Yuan; Tollerud, Erik J.; Weiner, Benjamin; Bernstein, Rebecca; Hoyle, Ben; Marchi, Sebastian; Marshall, Phil J.; Muñoz, Ricardo; Lu, Yu

2017-09-01

We present the survey strategy and early results of the “Satellites Around Galactic Analogs” (SAGA) Survey. The SAGA Survey’s goal is to measure the distribution of satellite galaxies around 100 systems analogous to the Milky Way down to the luminosity of the Leo I dwarf galaxy ({M}r< -12.3). We define a Milky Way analog based on K-band luminosity and local environment. Here, we present satellite luminosity functions for eight Milky-Way-analog galaxies between 20 and 40 Mpc. These systems have nearly complete spectroscopic coverage of candidate satellites within the projected host virial radius down to {r}o< 20.75 using low-redshift gri color criteria. We have discovered a total of 25 new satellite galaxies: 14 new satellite galaxies meet our formal criteria around our complete host systems, plus 11 additional satellites in either incompletely surveyed hosts or below our formal magnitude limit. Combined with 13 previously known satellites, there are a total of 27 satellites around 8 complete Milky-Way-analog hosts. We find a wide distribution in the number of satellites per host, from 1 to 9, in the luminosity range for which there are 5 Milky Way satellites. Standard abundance matching extrapolated from higher luminosities predicts less scatter between hosts and a steeper luminosity function slope than observed. We find that the majority of satellites (26 of 27) are star-forming. These early results indicate that the Milky Way has a different satellite population than typical in our sample, potentially changing the physical interpretation of measurements based only on the Milky Way’s satellite galaxies.

The challenge of precise orbit determination for STSAT-2C using extremely sparse SLR data

NASA Astrophysics Data System (ADS)

Kim, Young-Rok; Park, Eunseo; Kucharski, Daniel; Lim, Hyung-Chul; Kim, Byoungsoo

2016-03-01

The Science and Technology Satellite (STSAT)-2C is the first Korean satellite equipped with a laser retro-reflector array for satellite laser ranging (SLR). SLR is the only on-board tracking source for precise orbit determination (POD) of STSAT-2C. However, POD for the STSAT-2C is a challenging issue, as the laser measurements of the satellite are extremely sparse, largely due to the inaccurate two-line element (TLE)-based orbit predictions used by the SLR tracking stations. In this study, POD for the STSAT-2C using extremely sparse SLR data is successfully implemented, and new laser-based orbit predictions are obtained. The NASA/GSFC GEODYN II software and seven-day arcs are used for the SLR data processing of two years of normal points from March 2013 to May 2015. To compensate for the extremely sparse laser tracking, the number of estimation parameters are minimized, and only the atmospheric drag coefficients are estimated with various intervals. The POD results show that the weighted root mean square (RMS) post-fit residuals are less than 10 m, and the 3D day boundaries vary from 30 m to 3 km. The average four-day orbit overlaps are less than 20/330/20 m for the radial/along-track/cross-track components. The quality of the new laser-based prediction is verified by SLR observations, and the SLR residuals show better results than those of previous TLE-based predictions. This study demonstrates that POD for the STSAT-2C can be successfully achieved against extreme sparseness of SLR data, and the results can deliver more accurate predictions.

Gravity Models from CHAMP and other Satellite Data

NASA Technical Reports Server (NTRS)

Lemoime, Frank G.; Cox, C. M.; Chinn, D. S.; Zelensky, N. P.; Thompson, B. F.; Rowlands, D. D.; Luthdke, S. B.; Nerem, R. S.

2003-01-01

CHAMP spacecraft is the first of a series of new spacecraft missions that are revolutionizing our ability to model the Earth's geopotential. We report on the analysis of over 100 days of CHAMP data in 2001 and 2002, merged with tracking data of other satellites such as Jason, Topex, GFO, Starlette, Stella, Spot-2, as well as satellite altimetry. We find that the CHAMP-only component of these solutions is a significant improvement over pre-CHAMP satellite only models with respect to the high degree information expressed by the geopotential model coefficients. For example, the variance of the differences with altimeter-derived anomalies through degree 70 is 2.80 mGal(sup 2) for the CHAMP-only solution based on 87 days of data vs. 10.19 mGal(sup 2) for EGM96S. Nonetheless, in order to model properly the various resonances to which different satellites are sensitive, we must include other satellite data. We evaluate the performance of these new CHAMP derived solutions with EGM96 and the EIGEN series of solutions. We review carefully the performance of these models for altimetric satellites.

TOPEX/El Nino Watch - Satellite shows El Nino-related Sea Surface Height, Mar, 14, 1998

NASA Technical Reports Server (NTRS)

1998-01-01

This image of the Pacific Ocean was produced using sea surface height measurements taken by the U.S.-French TOPEX/Poseidon satellite. The image shows sea surface height relative to normal ocean conditions on Mar. 14, 1998 and sea surface height is an indicator of the heat content of the ocean. The image shows that the sea surface height along the central equatorial Pacific has returned to a near normal state. Oceanographers indicate this is a classic pattern, typical of a mature El Nino condition. Remnants of the El Nino warm water pool, shown in red and white, are situated to the north and south of the equator. These sea surface height measurements have provided scientists with a detailed view of how the 1997-98 El Nino's warm pool behaves because the TOPEX/Poseidon satellite measures the changing sea surface height with unprecedented precision. In this image, the white and red areas indicate unusual patterns of heat storage; in the white areas, the sea surface is between 14 and 32 centimeters (6 to 13 inches) above normal; in the red areas, it's about 10 centimeters (4 inches) above normal. The green areas indicate normal conditions, while purple (the western Pacific) means at least 18 centimeters (7 inches) below normal sea level. The El Nino phenomenon is thought to be triggered when the steady westward blowing trade winds weaken and even reverse direction. This change in the winds allows a large mass of warm water (the red and white area) that is normally located near Australia to move eastward along the equator until it reaches the coast of South America. The displacement of so much warm water affects evaporation, where rain clouds form and, consequently, alters the typical atmospheric jet stream patterns around the world. Using satellite imagery, buoy and ship data, and a forecasting model of the ocean-atmosphere system, the National Oceanic and Atmospheric Administration, (NOAA), has continued to issue an advisory indicating the so-called El Nino weather conditions that have impacted much of the United States and the world are expected to remain through the spring.

Two-way satellite time transfer using low power CW tones

NASA Technical Reports Server (NTRS)

Costain, C. C.; Daams, H.; Boulanger, J. S.

1983-01-01

In the search for an economical means of precise time transfer, the NRC Time Laboratory decided to adapt the techniques used by radio astronomers in an experiment to compare the phases of the local oscillators at widely separated VLBI stations. The objective is to design a system which would use commercial satellites, and which would be of reasonable cost for the ground stations and for operations. Two satellite ground stations were installed at NRC about 100 m from the Time Laboratory. For the preliminary experiment, a channel on the Anik Al 6/4 GHz satellite was made available by TELESAT Canada. Two tones were transmitted + or - MHz from the suppressed carrier. The difference frequency of 32 MHz was recorded using narrow band receivers. A low level 1 MHz phase modulation was added to identify the 32 MHz cycle, giving 1 microsec ambiguity in the time transfer. With less than 1/4 W in each tone, the EIRP is 43 dB below that of a normal TV Earth station, and no frequency dispersion is required. The measurements taken each second for the 32 MHz have an rms scatter of 1 ns.

An a priori solar radiation pressure model for the QZSS Michibiki satellite

NASA Astrophysics Data System (ADS)

Zhao, Qile; Chen, Guo; Guo, Jing; Liu, Jingnan; Liu, Xianglin

2018-02-01

It has been noted that the satellite laser ranging (SLR) residuals of the Quasi-Zenith Satellite System (QZSS) Michibiki satellite orbits show very marked dependence on the elevation angle of the Sun above the orbital plane (i.e., the β angle). It is well recognized that the systematic error is caused by mismodeling of the solar radiation pressure (SRP). Although the error can be reduced by the updated ECOM SRP model, the orbit error is still very large when the satellite switches to orbit-normal (ON) orientation. In this study, an a priori SRP model was established for the QZSS Michibiki satellite to enhance the ECOM model. This model is expressed in ECOM's D, Y, and B axes (DYB) using seven parameters for the yaw-steering (YS) mode, and additional three parameters are used to compensate the remaining modeling deficiencies, particularly the perturbations in the Y axis, based on a redefined DYB for the ON mode. With the proposed a priori model, QZSS Michibiki's precise orbits over 21 months were determined. SLR validation indicated that the systematic β -angle-dependent error was reduced when the satellite was in the YS mode, and better than an 8-cm root mean square (RMS) was achieved. More importantly, the orbit quality was also improved significantly when the satellite was in the ON mode. Relative to ECOM and adjustable box-wing model, the proposed SRP model showed the best performance in the ON mode, and the RMS of the SLR residuals was better than 15 cm, which was a two times improvement over the ECOM without a priori model used, but was still two times worse than the YS mode.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

USGS Publications Warehouse

Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

2010-01-01

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Applications based on restored satellite images

NASA Astrophysics Data System (ADS)

Arbel, D.; Levin, S.; Nir, M.; Bhasteker, I.

2005-08-01

Satellites orbit the earth and obtain imagery of the ground below. The quality of satellite images is affected by the properties of the atmospheric imaging path, which degrade the image by blurring it and reducing its contrast. Applications involving satellite images are many and varied. Imaging systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality satellite images because of the variety of applications based on them. The more qualitative is the recorded image, the more information is yielded from the image. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., satellite communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) satellite images are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.

Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices

NASA Astrophysics Data System (ADS)

Yang, Xiucheng; Chen, Li

2017-04-01

Urban surface water is characterized by complex surface continents and small size of water bodies, and the mapping of urban surface water is currently a challenging task. The moderate-resolution remote sensing satellites provide effective ways of monitoring surface water. This study conducts an exploratory evaluation on the performance of the newly available Sentinel-2A multispectral instrument (MSI) imagery for detecting urban surface water. An automatic framework that integrates pixel-level threshold adjustment and object-oriented segmentation is proposed. Based on the automated workflow, different combinations of visible, near infrared, and short-wave infrared bands in Sentinel-2 image via different water indices are first compared. Results show that object-level modified normalized difference water index (MNDWI with band 11) and automated water extraction index are feasible in urban surface water mapping for Sentinel-2 MSI imagery. Moreover, comparative results are obtained utilizing optimal MNDWI from Sentinel-2 and Landsat 8 images, respectively. Consequently, Sentinel-2 MSI achieves the kappa coefficient of 0.92, compared with that of 0.83 from Landsat 8 operational land imager.

A data mining approach for sharpening satellite thermal imagery over land

USDA-ARS?s Scientific Manuscript database

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...

Dropout Prevention: Diversified Satellite Occupations Program and Career Development. Final Report.

ERIC Educational Resources Information Center

Jones, Hilda B.

The Diversified Satellite Occupations Program Career Development sought to prevent dropout through these strategies: registration at a school situation away from the normal school setting, creation of a close teacher-student relationship, and raise achievement levels and lower anxiety levels. Program emphases at elementary, junior and senior high…

Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

NASA Astrophysics Data System (ADS)

Geng, Guannan; Zhang, Qiang; Martin, Randall V.; Lin, Jintai; Huo, Hong; Zheng, Bo; Wang, Siwen; He, Kebin

2017-03-01

Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope = 1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

The deterioration of materials as a result of air pollution as derived from satellite and ground based observations

NASA Astrophysics Data System (ADS)

Christodoulakis, John; Varotsos, Costas A.; Cracknell, Arthur P.; Kouremadas, George A.

2018-07-01

Dose Response Functions (DRFs) are widely used in estimating corrosion and/or soiling levels of materials used in building constructions and cultural monuments. These functions quantify the effects of air pollution and environmental parameters on different materials through ground based measurements of specific air pollutants and climatic parameters. Here, we propose a new approach where available satellite observations are used instead of ground-based data. Through this approach, the use of DRFs is expanded to cover situations where there are no in situ measurements, introducing also a totally new field where satellite data can be shown to be very helpful. In the present work satellite observations made by MODIS (MODerate resolution Imaging Spectroradiometer) on board Terra and Aqua, OMI (Ozone Monitoring Instrument) on board Aura and AIRS (Atmospheric Infrared Sounder) on board Aqua have been used.

Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

NASA Astrophysics Data System (ADS)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

2017-04-01

The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of vegetation cover (taken for vegetation temperature) Ta and efficient radiation temperature Ts.eff, as well as land surface emissivity E, normalized difference vegetation index NDVI, vegetation cover fraction B, and leaf area index LAI. The SEVIRI-based retrievals have included precipitation, LST Tls and Ta, E at daylight and nighttime, LAI (daily), and B. From the MSU-MR data there have been retrieved values of all the same characteristics as from the AVHRR data. The MSU-MR-based daily and monthly sums of precipitation have been calculated using the developed earlier and modified Multi Threshold Method (MTM) intended for the cloud detection and identification of its types around the clock as well as allocation of precipitation zones and determination of instantaneous maximum rainfall intensities for each pixel at that the transition from assessing rainfall intensity to estimating their daily values is a key element of the MTM. Measurement data from 3 IR MSU-MR channels (3.8, 11 i 12 μm) as well as their differences have been used in the MTM as predictors. Controlling the correctness of the MSU-MR-derived rainfall estimates has been carried out when comparing with analogous AVHRR- and SEVIRI-based retrievals and with precipitation amounts measured at the agricultural meteorological station of the study region. Probability of rainfall zones determination from the MSU-MR data, to match against the actual ones, has been 75-85% as well as for the AVHRR and SEVIRI data. The time behaviors of satellite-derived and ground-measured daily and monthly precipitation sums for vegetation season and yeaŗ correspondingly, have been in good agreement with each other although the first ones have been smoother than the latter. Discrepancies have existed for a number of local maxima for which satellite-derived precipitation estimates have been less than ground-measured values. It may be due to the different spatial scales of areal satellite-derived and point ground-based estimates. Some spatial displacement of the satellite-determined rainfall maxima and minima regarding to ground-based data can be explained by the discrepancy between the cloud location on satellite images and in reality at high angles of the satellite sightings and considerable altitudes of the cloud tops. Reliability of MSU-MR-derived rainfall estimates at each time step obtained using the MTM has been verified by comparing their values determined from the MSU-MR, AVHRR and SEVIRI measurements and distributed over the study area with similar estimates obtained by interpolation of ground observation data. The MSU-MR-derived estimates of temperatures Tsg, Ts.eff, and Ta have been obtained using computational algorithm developed on the base of the MTM and matured on AVHRR and SEVIRI data for the region under investigation. Since the apparatus MSU-MR is similar to radiometer AVHRR, the developed methods of satellite estimating Tsg, Ts.eff, and Ta from AVHRR data could be easily transferred to the MSU-MR data. Comparison of the ground-measured and MSU-MR-, AVHRR- and SEVIRI-derived LSTs has shown that the differences between all the estimates for the vast majority of observation terms have not exceed the RMSE of these quantities built from the AVHRR data. The similar conclusion has been also made from the results of building the time behavior of the MSU-MR-derived value of LAI for vegetation season. Satellite-based estimates of precipitation, LST, LAI and B have been utilized in the model with the help of specially developed procedures of replacing these values determined from observations at agricultural meteorological stations by their satellite-derived values taking into account spatial heterogeneity of their fields. Adequacy of such replacement has been confirmed by the results of comparing modeled and ground-measured values of soil moisture content W and evapotranspiration Ev. Discrepancies between the modeled and ground-measured values of W and Ev have been in the range of 10-15 and 20-25 %, correspondingly. It may be considered as acceptable result. Resulted products of the model calculations using satellite data have been spatial fields of W, Ev, vertical sensible and latent heat fluxes and other water and heat regime characteristics for the region of interest over the year 2012-2015 vegetation seasons. Thus, there has been shown the possibility of utilizing MSU-MR/Meteor-M №2 data jointly with those of other satellites in the LSM to calculate characteristics of water and heat regimes for the area under consideration. Besides the first trial estimations of the soil surface moisture from ASCAT scatterometers data for the study region have been obtained for the years 2014-2015 vegetation seasons, their comparison has been performed with the results of modeling for several agricultural meteorological stations of the region that has been carried out utilizing ground-based and satellite data, specific requirements for the obtained information have been formulated. To date, estimates of surface moisture built from ASCAT data can be used for the selection of the model soil parameter values and the initial soil moisture conditions for the vegetation season.

Accuracy and impact of spatial aids based upon satellite enumeration to improve indoor residual spraying spatial coverage.

PubMed

Bridges, Daniel J; Pollard, Derek; Winters, Anna M; Winters, Benjamin; Sikaala, Chadwick; Renn, Silvia; Larsen, David A

2018-02-23

Indoor residual spraying (IRS) is a key tool in the fight to control, eliminate and ultimately eradicate malaria. IRS protection is based on a communal effect such that an individual's protection primarily relies on the community-level coverage of IRS with limited protection being provided by household-level coverage. To ensure a communal effect is achieved through IRS, achieving high and uniform community-level coverage should be the ultimate priority of an IRS campaign. Ensuring high community-level coverage of IRS in malaria-endemic areas is challenging given the lack of information available about both the location and number of households needing IRS in any given area. A process termed 'mSpray' has been developed and implemented and involves use of satellite imagery for enumeration for planning IRS and a mobile application to guide IRS implementation. This study assessed (1) the accuracy of the satellite enumeration and (2) how various degrees of spatial aid provided through the mSpray process affected community-level IRS coverage during the 2015 spray campaign in Zambia. A 2-stage sampling process was applied to assess accuracy of satellite enumeration to determine number and location of sprayable structures. Results indicated an overall sensitivity of 94% for satellite enumeration compared to finding structures on the ground. After adjusting for structure size, roof, and wall type, households in Nchelenge District where all types of satellite-based spatial aids (paper-based maps plus use of the mobile mSpray application) were used were more likely to have received IRS than Kasama district where maps used were not based on satellite enumeration. The probability of a household being sprayed in Nchelenge district where tablet-based maps were used, did not differ statistically from that of a household in Samfya District, where detailed paper-based spatial aids based on satellite enumeration were provided. IRS coverage from the 2015 spray season benefited from the use of spatial aids based upon satellite enumeration. These spatial aids can guide costly IRS planning and implementation leading to attainment of higher spatial coverage, and likely improve disease impact.

Cassini's motions and resonant librations of synchronous satellites of big planets

NASA Astrophysics Data System (ADS)

Barkin, Yu. V.

2008-09-01

Introduction. In the paper the rotations of synchronous satellites of the Jupiter, Saturn, Uran and Neptune are studied. On the base theory of resonant rotation of the rigid satellite on precessing elliptical orbit [1], [2] parameters of Cassini's motions and periods of free resonant librations have been determined for big grope of satellites of planets considered as rigid non-spherical bodies. Here I use observed values of coefficients of second harmonics of gravitational potensials ( 2 J and 22 C ) and of dimension less moment of inertia I = C / ?mr 2 ? of Io, Europa, Ganimede, Callisto and also Rhea and Titan, obtained on the base of data of space missions to these bodies [3]. Here C is the polar moment of inertia, m and r is the mass and the mean radius of satellite. Mentioned parameters 2 J , 22 C and I also have been evaluated for a wide set of another's satellites of big planets for their models as homogeneous ellipsoids of known forms and sizes (www.nasa.gov). These models also have been obtained here effective applications. For corresponding models the notation (e) is used here. For another from considered satellites (without indexes) we use also ellipsoidal models of hydrostatic equilibrium state of synchronous satellite [4]. The full list of discussed parameters for satellites of planets is presented in the paper [5]. Perturbed orbital motions of considered satellites we discribe by mean orbital elements reffered to local Laplacian planes of corresponding satellites ( http://ssd.jpl.nasa. gov/sat_elem. html). From them: the eccentricity ( e ), the inclination of orbit plane ( i ), the mean orbital motion and its period ( n and n T ), the angular velocity and period of preseccion of orbit plane of satellite on local Laplacian plane ( n? and T? ). In our approach all mentioned parameters are considered as constants and more fine effects in orbital motions of satellites do not take into account in this paper. The purpose of paper is to study syncronous motions of satellites in Solar system and for each of them to determine the values of the basic Cassini's parameter 0 ? (it is the average angle of inclination of the axis of rotation relatively to normal of the precessing orbit plane) and the periods of resonant librations in the longitude ( g T ), in the pole wobble ( l T ) and period of space precession ( h T ) (and their errors). Here we use the analytical formulas for mentioned parameters which were developed by study of the Moon Cassini's motion in my early papers [1], [2]. Specially for the case of small eccentricities and inclinations of orbits of synchronous satellites we have obtained the simple reduced formulas for all four considered parameters.

Nowcasting Aircraft Icing Conditions in Moscow Region Using Geostationary Meteorological Satellite Data

NASA Astrophysics Data System (ADS)

Barabanova, Olga

2013-04-01

Nowadays the Main Aviation Meteorological Centre in Moscow (MAMC) provides forecasts of icing conditions in Moscow Region airports using information of surface observation network, weather radars and atmospheric sounding. Unfortunately, satellite information is not used properly in aviation meteorological offices in Moscow Region: weather forecasters deal with satellites images of cloudiness only. The main forecasters of MAMC realise that it is necessary to employ meteorological satellite numerical data from different channels in aviation forecasting and especially in nowcasting. Algorithm of nowcasting aircraft in-flight icing conditions has been developed using data from geostationary meteorological satellites "Meteosat-7" and "Meteosat-9". The algorithm is based on the brightness temperature differences. Calculation of brightness temperature differences help to discriminate clouds with supercooled large drops where severe icing conditions are most likely. Due to the lack of visible channel data, the satellite icing detection methods will be less accurate at night. Besides this method is limited by optically thick ice clouds where it is not possible to determine the extent to which supercooled large drops exists within the underlying clouds. However, we determined that most of the optically thick cases are associated with convection or mid-latitude cyclones and they will nearly always have a layer where which supercooled large drops exists with an icing threat. This product is created hourly for the Moscow Air Space and mark zones with moderate or severe icing hazards. The results were compared with mesoscale numerical atmospheric model COSMO-RU output. Verification of the algorithms results using aircraft pilot reports shows that this algorithm is a good instrument for the operational practise in aviation meteorological offices in Moscow Region. The satellite-based algorithms presented here can be used in real time to diagnose areas of icing for pilots to avoid.

Satellite-Friendly Protocols and Standards

NASA Astrophysics Data System (ADS)

Koudelka, O.; Schmidt, M.; Ebert, J.; Schlemmer, H.; Kastner, S.; Riedler, W.

2002-01-01

We are currently observing a development unprecedented with other services, the enormous growth of the Internet. Video, voice and data applications can be supported via this network in high quality. Multi-media applications require high bandwidth which may not be available in many areas. When making proper use of the broadcast feature of a communications satellite, the performance of the satellite-based system can compare favourably to terrestrial solutions. Internet applications are in many cases highly asymmetric, making them very well suited to applications using small and inexpensive terminals. Data from one source may be used simultaneously by a large number of users. The Internet protocol suite has become the de-facto standard. But this protocol family in its original form has not been designed to support guaranteed quality of service, a prerequisite for real-time, high quality traffic. The Internet Protocol has to be adapted for the satellite environment, because long roundtrip delays and the error behaviour of the channel could make it inefficient over a GEO satellite. Another requirement is to utilise the satellite bandwidth as efficiently as possible. This can be achieved by adapting the access system to the nature of IP frames, which are variable in length. In the framework of ESA's ARTES project a novel satellite multimedia system was developed which utilises Multi-Frequency TDMA in a meshed network topology. The system supports Quality of Service (QoS) by reserving capacity with different QoS requirements. The system is centrally controlled by a master station with the implementation of a demand assignment (DAMA) system. A lean internal signalling system has been adopted. Network management is based on the SNMP protocol and industry-standard network management platforms, making interfaces to standard accounting and billing systems easy. Modern communication systems will have to be compliant to different standards in a very flexible manner. The developed system is based on a hardware architecture using FPGAs (Field-Programmable Gate Arrays). This provides means to configure the satellite gateway for different standards and to optimise the transmission parameters for varying user traffic, thus increasing the efficiency significantly. The paper describes the flexible system architecture and focuses particularly on the DAMA access scheme and the chosen quality-of-service implementation. Emphasis has been put on the support of IP Version 6. Different standards (e.g. RCS and possible follow-ups) and the possibility to support them are discussed.

Analysis of satellite altimeter signal characteristics and investigation of sea-truth data requirements

NASA Technical Reports Server (NTRS)

1972-01-01

Results are presented of analysis of satellite signal characteristics as influenced by ocean surface roughness and an investigation of sea truth data requirements. The first subject treated is that of postflight waveform reconstruction for the Skylab S-193 radar altimeter. Sea state estimation accuracies are derived based on analytical and hybrid computer simulation techniques. An analysis of near-normal incidence, microwave backscattering from the ocean's surface is accomplished in order to obtain the minimum sea truth data necessary for good agreement between theoretical and experimental scattering results. Sea state bias is examined from the point of view of designing an experiment which will lead to a resolution of the problem. A discussion is given of some deficiencies which were found in the theory underlying the Stilwell technique for spectral measurements.

A new concept of space solar power satellite

NASA Astrophysics Data System (ADS)

Li, Xun; Duan, Baoyan; Song, Liwei; Yang, Yang; Zhang, Yiqun; Wang, Dongxu

2017-07-01

Space solar power satellite (SSPS) is a tremendous energy system that collects and converts solar power to electric power in space, and then transmits the electric power to earth wirelessly. In this paper, a novel SSPS concept based on ε-near-zero (ENZ) metamaterial is proposed. A spherical condenser made of ENZ metamaterial is developed, by using the refractive property of the ENZ metamaterial sunlight can be captured and redirected to its center. To make the geometric concentration ratio of the PV array reasonable, a hemispherical one located at the center is used to collect and convert the normal-incidence sunlight to DC power, then through a phased array transmitting antenna the DC power is beamed down to the rectenna on the ground. Detailed design of the proposed concept is presented.

Lamp reliability studies for improved satellite rubidium frequency standard

NASA Technical Reports Server (NTRS)

Frueholz, R. P.; Wun-Fogle, M.; Eckert, H. U.; Volk, C. H.; Jones, P. F.

1982-01-01

In response to the premature failure of Rb lamps used in Rb atomic clocks onboard NAVSTAR GPS satellites experimental and theoretical investigations into their failure mechanism were initiated. The primary goal of these studies is the development of an accelerated life test for future GPS lamps. The primary failure mechanism was identified as consumption of the lamp's Rb charge via direct interaction between Rb and the lamp's glass surface. The most effective parameters to accelerate the interaction between the Rb and the glass are felt to be RF excitation power and lamp temperature. Differential scanning calorimetry is used to monitor the consumption of Rb within a lamp as a function of operation time. This technique yielded base line Rb consumption data for GPS lamps operating under normal conditions.

OSTM/Jason-2 and Jason-1 Tandem Mission View of the Gulf Stream

NASA Image and Video Library

2009-04-27

Created with altimeter data from NASA's Ocean Surface Topography Mission (OSTM)/Jason-2 satellite and the Jason-1 satellite, this image shows a portion of the Gulf Stream off the east coast of the United States. It demonstrates how much more detail is visible in the ocean surface when measured by two satellites than by one alone. The image on the left was created with data from OSTM/Jason-2. The image on the right is the same region but made with combined data from OSTM/Jason-2 and Jason-1.It shows the Gulf Stream's eddies and rings much more clearly. This image is a product of the new interleaved tandem mission of the Jason-1 and Ocean Surface Topography Mission (OSTM)/Jason-2 satellites. (The first global map from this tandem mission is available at PIA11859.) In January 2009, Jason-1 was maneuvered into orbit on the opposite side of Earth from its successor, OSTM/Jason-2 satellite. It takes 10 days for the satellites to cover the globe and return to any one place over the ocean. So, in this new tandem configuration, Jason-1 flies over the same region of the ocean that OSTM/Jason-2 flew over five days earlier. Its ground tracks fall mid-way between those of Jason-2, which are about 315 kilometers (195 miles) apart at the equator. Working together, the two spacecraft measure the surface topography of the ocean twice as often as would be possible with one satellite, and over a 10-day period, they return twice the amount of detailed measurements. Combining data from the two satellites makes it possible to map smaller, more rapidly changing features than one satellite could alone. These images show sea-level anomaly data from the first 14 days of the interleaved orbit of Jason-1 and OSTM/Jason-2, the period beginning on Feb. 20, 2009. An anomaly is a departure from a value averaged over a long period of time. Red and yellow are regions where sea levels are higher than normal. Purple and dark blue show where sea levels are lower. A higher-than-normal sea surface is usually a sign of warm waters below, while lower sea levels indicate cooler than normal temperatures. http://photojournal.jpl.nasa.gov/catalog/PIA11997

Mapping Crop Yield and Sow Date Using High Resolution Imagery

NASA Astrophysics Data System (ADS)

Royal, K.

2015-12-01

Keitasha Royal, Meha Jain, Ph.D., David Lobell, Ph.D Mapping Crop Yield and Sow Date Using High Resolution ImageryThe use of satellite imagery in agriculture is becoming increasingly more significant and valuable. Due to the emergence of new satellites, such as Skybox, these satellites provide higher resolution imagery (e.g 1m) therefore improving the ability to map smallholder agriculture. For the smallholder farm dominated area of northern India, Skybox high-resolution satellite imagery can aid in understanding how to improve farm yields. In particular, we are interested in mapping winter wheat in India, as this region produces approximately 80% of the country's wheat crop, which is important given that wheat is a staple crop that provides approximately 20% of household calories. In northeast India, the combination of increased heat stress, limited irrigation access, and the difficulty for farmers to access advanced farming technologies results in farmers only producing about 50% of their potential crop yield. The use of satellite imagery can aid in understanding wheat yields through time and help identify ways to increase crop yields in the wheat belt of India. To translate Skybox satellite data into meaningful information about wheat fields, we examine vegetation indices, such as the normalized difference vegetation index (NDVI), to measure the "greenness" of plants to help determine the health of the crops. We test our ability to predict crop characteristics, like sow date and yield, using vegetation indices of 59 fields for which we have field data in Bihar, India.

Orbit and clock determination of BDS regional navigation satellite system based on IGS M-GEX and WHU BETS tracking network

NASA Astrophysics Data System (ADS)

GENG, T.; Zhao, Q.; Shi, C.; Shum, C.; Guo, J.; Su, X.

2013-12-01

BeiDou Navigation Satellite System (BDS) began to provide the regional open service on December 27th 2012 and will provide the global open service by the end of 2020. Compared to GPS, the space segment of BDS Regional System consists of 5 Geostationary Earth Orbit satellites (GEO), 5 Inclined Geosynchronous Orbit satellites (IGSO) and 4 Medium Earth orbit (MEO) satellites. Since 2011, IGS Multiple-GNSS Experiment (M-GEX) focuses on tracking the newly available GNSS signals. This includes all signals from the modernized satellites of the GPS and GLONASS systems, as well as signals of the BDS, Galileo and QZSS systems. Up to now, BDS satellites are tracked by around 25 stations with a variety of different antennas and receivers from different GNSS manufacture communities in M-GEX network. Meanwhile, there are 17 stations with Unicore Communications Incorporation's GPS/BDS receivers in BeiDou Experimental Tracking Stations (BETS) network by Wuhan University. In addition, 5 BDS satellites have been tracking by the International Laser Ranging Service (ILRS). BDS performance is expected to be further studied by the GNSS communities. Following an introduction of the BDS system and above different tracking network, this paper discusses the achieved BDS characterization and performance assessment. Firstly, the BDS signal and measurement quality are analyzed with different antennas and receivers in detail compared to GPS. This includes depth of coverage for satellite observation, carrier-to-noise-density ratios, code noise and multipath, carrier phase errors. Secondly, BDS Precise Orbit Determination (POD) is processed. Different arc lengths and sets of orbit parameters are tested using Position And Navigation Data Analysis software (PANDA) which is developed at the Wuhan University. GEO, IGSO and MEO satellites orbit quality will be assessed using overlap comparison, 2-day orbit fit and external validations with Satellite Laser Range (SLR). Then BDS satellites are equipped with Rubidium clocks and clocks performance are also presented. Finally, benefits of BDS processing strategies and further developments are concluded.

Impact of multiconstellation satellite signal reception on performance of satellite-based navigation under adverse ionospheric conditions

NASA Astrophysics Data System (ADS)

Paul, Ashik; Paul, Krishnendu Sekhar; Das, Aditi

2017-03-01

Application of multiconstellation satellites to address the issue of satellite signal outages during periods of equatorial ionospheric scintillations could prove to be an effective tool for maintaining the performance of satellite-based communication and navigation without compromise in accuracy and integrity. A receiver capable of tracking GPS, Global Navigation Satellite System (GLONASS), and Galileo satellites is operational at the Institute of Radio Physics and Electronics, University of Calcutta, Calcutta, India, located near the northern crest of the equatorial ionization anomaly in the Indian longitude sector. The present paper shows increased availability of satellites combining GPS, GLONASS, and Galileo constellations from Calcutta compared to GPS-only scenario and estimates intense scintillation-free (S4 < 0.6) satellite vehicle look angles at different hours of the postsunset period 19:00-01:00 LT during March 2014. A representative case of 1 March 2014 is highlighted in the paper and overall statistics for March 2014 presented to indicate quantitative advantages in terms of scintillation-free satellite vehicle look angles that may be utilized for planning communication and navigation channel spatial distribution under adverse ionospheric conditions. The number of satellites tracked and receiver position deviations has been found to show a good correspondence with the occurrence of intense scintillations and poor user receiver-satellite link geometry. The ground projection of the 350 km subionospheric points corresponding to multiconstellation shows extended spatial coverage during periods of scintillations (0.2 < S4 < 0.6) compared to GPS.

ELF propagation in the plasmasphere based on satellite observations of discrete and continuous forms

NASA Technical Reports Server (NTRS)

Muzzio, J. L. R.

1971-01-01

The propagation of electromagnetic waves in a nonhomogeneous anisotropic medium is examined from the point of view of geometrical optics. In particular, the propagation of ELF waves in the magnetosphere is described in terms of the electron and ion densities and the intensity and inclination of the earth's magnetic field. The analysis of the variations of wave normal angle along the ray path is extended to include the effects of ions. A comparison of the relative importance of each of the above parameters in controlling the orientation of the wave normals is made in the region of the magnetosphere where most of the ion whistlers have been detected.

An atlas of ultraviolet spectra of star-forming galaxies

NASA Technical Reports Server (NTRS)

Kinney, A. L.; Bohlin, R. C.; Calzetti, D.; Panagia, N.; Wyse, Rosemary F. G.

1993-01-01

A systematic study is presented of the UV spectra of star-forming galaxies of different morphological type and activity class using a sample drawn from a uniformly reduced IUE data set. The spectra for a wide variety of galaxies, including normal spiral, LINER, starburst, blue compact, blue compact dwarf, and Seyfert 2 galaxies, are presented in the form of spectral energy distributions to demonstrate the overall characteristics according to morphology and activity class and in the form of absolute flux distributions to better show the absorption and emission features of individual objects. The data support the picture based on UV spectra of the Orbiting Astronomical Observatory and of the Astronautical Netherlands Satellite that spiral galaxies of later Hubble class have more flux at the shortest UV wavelengths than do spiral galaxies of earlier Hubble class.

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

PubMed Central

van Leeuwen, Willem J. D.

2008-01-01

This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests. PMID:27879809

Low-level infrared laser modulates muscle repair and chromosome stabilization genes in myoblasts.

PubMed

da Silva Neto Trajano, Larissa Alexsandra; Stumbo, Ana Carolina; da Silva, Camila Luna; Mencalha, Andre Luiz; Fonseca, Adenilson S

2016-08-01

Infrared laser therapy is used for skeletal muscle repair based on its biostimulative effect on satellite cells. However, shortening of telomere length limits regenerative potential in satellite cells, which occurs after each cell division cycle. Also, laser therapy could be more effective on non-physiologic tissues. This study evaluated low-level infrared laser exposure effects on mRNA expression from muscle injury repair and telomere stabilization genes in myoblasts in normal and stressful conditions. Laser fluences were those used in clinical protocols. C2C12 myoblast cultures were exposed to low-level infrared laser (10, 35, and 70 J/cm(2)) in standard or normal (10 %) and reduced (2 %) fetal bovine serum concentrations; total RNA was extracted for mRNA expression evaluation from muscle injury repair (MyoD and Pax7) and chromosome stabilization (TRF1 and TRF2) genes by real time quantitative polymerization chain reaction. Data show that low-level infrared laser increases the expression of MyoD and Pax7 in 10 J/cm(2) fluence, TRF1 expression in all fluences, and TRF2 expression in 70 J/cm(2) fluence in both 10 and 2 % fetal bovine serum. Low-level infrared laser increases mRNA expression from genes related to muscle repair and telomere stabilization in myoblasts in standard or normal and stressful conditions.

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Protat, Alain; Young, Stuart; McFarlane, Sally A.

2014-02-01

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar-lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (due to limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar - Cloud-Aerosol Lidar withmore » Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2 km height, due to instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar-lidar instruments and RT calculations are also found above 10 km (up to 0.35 Kday-1 for the shortwave and 0.8 Kday-1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud-radiation interactions in large-scale models and limitations of each set of instrumentation should be considered when interpreting model-observations differences.« less

An approach for real-time fast point positioning of the BeiDou Navigation Satellite System using augmentation information

NASA Astrophysics Data System (ADS)

Tu, Rui; Zhang, Rui; Zhang, Pengfei; Liu, Jinhai; Lu, Xiaochun

2018-07-01

This study proposes an approach to facilitate real-time fast point positioning of the BeiDou Navigation Satellite System (BDS) based on regional augmentation information. We term this as the precise positioning based on augmentation information (BPP) approach. The coordinates of the reference stations were highly constrained to extract the augmentation information, which contained not only the satellite orbit clock error correlated with the satellite running state, but also included the atmosphere error and unmodeled error, which are correlated with the spatial and temporal states. Based on these mixed augmentation corrections, a precise point positioning (PPP) model could be used for the coordinates estimation of the user stations, and the float ambiguity could be easily fixed for the single-difference between satellites. Thus, this technique provided a quick and high-precision positioning service. Three different datasets with small, medium, and large baselines (0.6 km, 30 km and 136 km) were used to validate the feasibility and effectiveness of the proposed BPP method. The validations showed that using the BPP model, 1–2 cm positioning service can be provided in a 100 km wide area after just 2 s of initialization. Thus, as the proposed approach not only capitalized on both PPP and RTK but also provided consistent application, it can be used for area augmentation positioning.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Augmentation method of XPNAV in Mars orbit based on Phobos and Deimos observations

NASA Astrophysics Data System (ADS)

Rong, Jiao; Luping, Xu; Zhang, Hua; Cong, Li

2016-11-01

Autonomous navigation for Mars probe spacecraft is required to reduce the operation costs and enhance the navigation performance in the future. X-ray pulsar-based navigation (XPNAV) is a potential candidate to meet this requirement. This paper addresses the use of the Mars' natural satellites to improve XPNAV for Mars probe spacecraft. Two observation variables of the field angle and natural satellites' direction vectors of Mars are added into the XPNAV positioning system. The measurement model of field angle and direction vectors is formulated by processing satellite image of Mars obtained from optical camera. This measurement model is integrated into the spacecraft orbit dynamics to build the filter model. In order to estimate position and velocity error of the spacecraft and reduce the impact of the system noise on navigation precision, an adaptive divided difference filter (ADDF) is applied. Numerical simulation results demonstrate that the performance of ADDF is better than Unscented Kalman Filter (UKF) DDF and EKF. In view of the invisibility of Mars' natural satellites in some cases, a visibility condition analysis is given and the augmented XPNAV in a different visibility condition is numerically simulated. The simulation results show that the navigation precision is evidently improved by using the augmented XPNAV based on the field angle and natural satellites' direction vectors of Mars in a comparison with the conventional XPNAV.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

The Ups and Downs of Measuring Sea Surface Salinity from Space

NASA Astrophysics Data System (ADS)

Banks, C. J.; Gommenginger, C. P.; Srokosz, M. A.; Snaith, H. M.

2012-12-01

In November 2009, the European Space Agency (ESA) launched the Soil Moisture and Ocean Salinity (SMOS) satellite and a new era of satellite oceanography began vastly improving our ability to synoptically measure sea surface salinity (SSS). SMOS was joined in June 2011 by the NASA/Argentine Aquarius/SAC-D mission designed specifically to measure SSS. Although there are significant differences in how both satellites retrieve SSS, both utilise passive systems to measure the response of the brightness temperature (Tb) at L-band (1.4 GHz). We report on-going investigations into the validation of SMOS and Aquarius 'Level 3' measurements of SSS using monthly data on a 1° by 1° global grid between 60°S and 60°N. Previous studies have indicated significant temporally varying differences between SSS from SMOS ascending passes and from SMOS descending passes: therefore, for both SMOS and Aquarius, data from ascending and descending passes will be studied separately. Both satellites have sun-synchronous orbits but the direction of travel for the two satellites are twelve hours out of phase (i.e. at approximately 6 a.m. local time SMOS is travelling south-to-north (ascending) and Aquarius is travelling north-to-south (descending) whereas at 6 p.m. the directions of travel are switched). For validation purposes two separate monthly, 1° by 1° datasets are used over the same locations as the satellite data. The first is based on averaged near-surface salinity (depth less than 10 m) as derived from the drifting Argo float programme. The second validation data source is output from the UK Met Office Forecasting Ocean Assimilation Model (FOAM) based on NEMO (Nucleus for European Modelling of the Ocean). The SMOS Level 3 products are developed from ESA Level 2 products after quality control (QC) based on flags and SSS error provided in the ESA Level 2 products. Aquarius data (QC) is based only on data flags and a simple selection of in-range SSS values ([30, 40]). The study is based on monthly products over the period from September 2011 to May 2012. We calculate maps of the difference between each possible pair of SSS datasets for each month, and consider their relationships using regression on the 1° values. The analysis is carried out for the global ocean, as well as for smaller, more homogeneous, study regions (e.g. SPURS). In addition, a study is made of the differences and similarities, at Level 2, between the two satellites and the direction of travel.

Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

EPA Science Inventory

We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

Statistical considerations in creating water vapor data records from combinations of satellite and other observation types, including in situ and ground-based remote sensing

NASA Astrophysics Data System (ADS)

Dykema, J. A.; Anderson, J. G.

2014-12-01

Measuring water vapor at the highest spatial and temporal at all vertical levels and at arbitrary times requires strategic utilization of disparate observations from satellites, ground-based remote sensing, and in situ measurements. These different measurement types have different response times and very different spatial averaging properties, both horizontally and vertically. Accounting for these different measurement properties and explicit propagation of associated uncertainties is necessary to test particular scientific hypotheses, especially in cases of detection of weak signals in the presence of natural fluctuations, and for process studies with small ensembles. This is also true where ancillary data from meteorological analyses are required, which have their own sampling limitations and uncertainties. This study will review two investigations pertaining to measurements of water vapor in the mid-troposphere and lower stratosphere that mix satellite observations with observations from other sources. The focus of the mid-troposphere analysis is to obtain improved estimates of water vapor at the instant of a sounding satellite overpass. The lower stratosphere work examines the uncertainty inherent in a small ensemble of anomalously elevated lower stratospheric water vapor observations when meteorological analysis products and aircraft in situ observations are required for interpretation.

Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

NASA Astrophysics Data System (ADS)

Park, Seohui; Im, Jungho

2017-04-01

Atmospheric aerosols are strongly associated with adverse human health effects. In particular, particulate matter less than 10 micrometers and 2.5 micrometers (i.e., PM10 and PM2.5, respectively) can cause cardiovascular and lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Air quality including PM has typically been monitored using station-based in-situ measurements over the world. However, in situ measurements do not provide spatial continuity over large areas. An alternative approach is to use satellite remote sensing as it provides data over vast areas at high temporal resolution. The literature shows that PM concentrations are related with Aerosol Optical Depth (AOD) that is derived from satellite observations, but it is still difficult to identify PM concentrations directly from AOD. Some studies used statistical approaches for estimating PM concentrations from AOD while some others combined numerical models and satellite-derived AOD. In this study, satellite-derived products were used to estimate ground PM concentrations based on machine learning over South Korea. Satellite-derived products include AOD from Geostationary Ocean Color Imager (GOCI), precipitation from Tropical Rainfall Measuring Mission (TRMM), soil moisture from AMSR-2, elevation from Shuttle Radar Topography Mission (SRTM), and land cover, land surface temperature and normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS). PM concentrations data were collected from 318 stations. A statistical ordinary least squares (OLS) approach was also tested and compared with the machine learning approach (i.e., random forest). PM concentration was estimated during spring season (from March to May) in 2015 that typically shows high concentration of PM. The randomly selected 80% of data were used for model calibration and the remaining 20% were used for validation. The developed models were further tested for prediction of PM concentration. Results show that the estimation of PM10 was better than that of PM2.5 for both approaches. The performance of machine learning random forest was better (R2=0.53 and RMSE=17.74µm/m3 for PM10; R2=0.36 and RMSE=26.17 µm/m3 for PM2.5) than the statistical OLS approach (R2=0.13 and RMSE=23.66µm/m3 for PM10; R2=0.09 and RMSE=27.74 µm/m3 for PM2.5). However, both approaches did not fully model the entire dynamic range of PM concentrations, especially for very high concentrations, resulting in moderate underestimation.

Improving Assessment of Lifetime Solar Ultraviolet Radiation Exposure in Epidemiologic Studies: Comparison of Ultraviolet Exposure Assessment Methods in a Nationwide United States Occupational Cohort.

PubMed

Little, Mark P; Tatalovich, Zaria; Linet, Martha S; Fang, Michelle; Kendall, Gerald M; Kimlin, Michael G

2018-06-13

Solar ultraviolet radiation is the primary risk factor for skin cancers and sun-related eye disorders. Estimates of individual ambient ultraviolet irradiance derived from ground-based solar measurements and from satellite measurements have rarely been compared. Using self-reported residential history from 67,189 persons in a nationwide occupational US radiologic technologists cohort, we estimated ambient solar irradiance using data from ground-based meters and noontime satellite measurements. The mean distance-moved from city of longest residence in childhood increased from 137.6 km at ages 13-19 to 870.3 km at ages ≥65, with corresponding increases in absolute latitude-difference moved. At ages 20/40/60/80, the Pearson/Spearman correlation coefficients of ground-based and satellite-derived solar potential ultraviolet exposure, using irradiance and cumulative radiant-exposure metrics, were high (=0.87-0.92). There was also moderate correlation (Pearson/Spearman correlation coefficients=0.51-0.60) between irradiance at birth and at last-known address, for ground-based and satellite data. Satellite-based lifetime estimates of ultraviolet radiation were generally 14-15% lower than ground-based estimates, albeit with substantial uncertainties, possibly because ground-based estimates incorporate fluctuations in cloud and ozone, which are incompletely incorporated in the single noontime satellite-overpass ultraviolet value. If confirmed elsewhere, the findings suggest that ground-based estimates may improve exposure-assessment accuracy and potentially provide new insights into ultraviolet-radiation-disease relationships in epidemiologic studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

NASA Astrophysics Data System (ADS)

Muench, R.; Jones, M.; Herndon, K. E.; Bell, J. R.; Anderson, E. R.; Markert, K. N.; Molthan, A.; Adams, E. C.; Shultz, L.; Cherrington, E. A.; Flores, A.; Lucey, R.; Munroe, T.; Layne, G.; Pulla, S. T.; Weigel, A. M.; Tondapu, G.

2017-12-01

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

NASA Technical Reports Server (NTRS)

Muench, Rebekke; Jones, Madeline; Herndon, Kelsey; Schultz, Lori; Bell, Jordan; Anderson, Eric; Markert, Kel; Molthan, Andrew; Adams, Emily; Cherrington, Emil;

Comparison of satellite-derived dynamical quantities for the stratosphere of the Southern Hemisphere

NASA Technical Reports Server (NTRS)

Miles, Thomas (Editor); Oneill, Alan (Editor)

1989-01-01

As part of the international Middle Atmosphere Program (MAP), a project was instituted to study the dynamics of the Middle Atmosphere in the Southern Hemisphere (MASH). A pre-MASH workshop was held with two aims: comparison of Southern Hemisphere dynamical quantities derived from various archives of satellite data; and assessing the impact of different base-level height information on such derived quantities. The dynamical quantities examined included geopotential height, zonal wind, potential vorticity, eddy heat and momentum fluxes, and Eliassen-Palm fluxes. It was found that while there was usually qualitative agreement between the different sets of fields, substantial quantitative differences were evident, particularly in high latitudes. The fidelity of the base-level analysis was found to be of prime importance in calculating derived quantities - especially the Eliassen-Palm flux divergence and potential vorticity. Improvements in base-level analyses are recommended. In particular, quality controls should be introduced to remove spurious localized features from analyses, and information from all Antarctic radiosondes should be utilized where possible. Caution in drawing quantitative inferences from satellite data for the middle atmosphere of the Southern Hemisphere is advised.

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

NASA Astrophysics Data System (ADS)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

NASA Astrophysics Data System (ADS)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

The autonomicity of self-scheduling on Earth observation satellite and the increasing scale of satellite network attract much attention from researchers in the last decades. In reality, the limited onboard computational resource presents challenge for the online scheduling algorithm. This study considered online scheduling problem for a single autonomous Earth observation satellite within satellite network environment. It especially addressed that the urgent tasks arrive stochastically during the scheduling horizon. We described the problem and proposed a hybrid online scheduling mechanism with revision and progressive techniques to solve this problem. The mechanism includes two decision policies, a when-to-schedule policy combining periodic scheduling and critical cumulative number-based event-driven rescheduling, and a how-to-schedule policy combining progressive and revision approaches to accommodate two categories of task: normal tasks and urgent tasks. Thus, we developed two heuristic (re)scheduling algorithms and compared them with other generally used techniques. Computational experiments indicated that the into-scheduling percentage of urgent tasks in the proposed mechanism is much higher than that in periodic scheduling mechanism, and the specific performance is highly dependent on some mechanism-relevant and task-relevant factors. For the online scheduling, the modified weighted shortest imaging time first and dynamic profit system benefit heuristics outperformed the others on total profit and the percentage of successfully scheduled urgent tasks.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS) versus C-/X-band (AMSR2) observations. The soil moisture products analyzed here were derived using the Land Parameter Retrieval Model.

Evaluating MODIS satellite versus terrestrial data driven productivity estimates in Austria

NASA Astrophysics Data System (ADS)

Petritsch, R.; Boisvenue, C.; Pietsch, S. A.; Hasenauer, H.; Running, S. W.

2009-04-01

Sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite, are developed for monitoring global and/or regional ecosystem fluxes like net primary production (NPP). Although these systems should allow us to assess carbon sequestration issues, forest management impacts, etc., relatively little is known about the consistency and accuracy in the resulting satellite driven estimates versus production estimates driven from ground data. In this study we compare the following NPP estimation methods: (i) NPP estimates as derived from MODIS and available on the internet; (ii) estimates resulting from the off-line version of the MODIS algorithm; (iii) estimates using regional meteorological data within the offline algorithm; (iv) NPP estimates from a species specific biogeochemical ecosystem model adopted for Alpine conditions; and (v) NPP estimates calculated from individual tree measurements. Single tree measurements were available from 624 forested sites across Austria but only the data from 165 sample plots included all the necessary information for performing the comparison on plot level. To ensure independence of satellite-driven and ground-based predictions, only latitude and longitude for each site were used to obtain MODIS estimates. Along with the comparison of the different methods, we discuss problems like the differing dates of field campaigns (<1999) and acquisition of satellite images (2000-2005) or incompatible productivity definitions within the methods and come up with a framework for combining terrestrial and satellite data based productivity estimates. On average MODIS estimates agreed well with the output of the models self-initialization (spin-up) and biomass increment calculated from tree measurements is not significantly different from model results; however, correlation between satellite-derived versus terrestrial estimates are relatively poor. Considering the different scales as they are 9km² from MODIS and 1000m² from the sample plots together with the heterogeneous landscape may qualify the low correlation, particularly as the correlation increases when strongly fragmented sites are left out.

Global tracking and inventory of military hardware via LEO satellite: A system approach and likely scenario

NASA Technical Reports Server (NTRS)

Bell, David; Estabrook, Polly; Romer, Richard

1995-01-01

A system for global inventory control of electronically tagged military hardware is achievable using a LEO satellite constellation. An equipment Tag can communicate directly to the satellite with a power of 5 watts or less at a data rate of 2400 to 50,000 bps. As examples, two proposed commercial LEO systems, IRIDIUM and ORBCOMM, are both capable of providing global coverage but with dramatically different telecom capacities. Investigation of these two LEO systems as applied to the Tag scenario provides insight into satellite design trade-offs, constellation trade-offs and signal dynamics that effect the performance of a satellite-based global inventory control system.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

First Jason-1 and OSTM/Jason-2 Tandem Global View

NASA Technical Reports Server (NTRS)

2009-01-01

This is the first global map of ocean surface topography produced with data from the new interleaved tandem mission of the Jason-1 and Ocean Surface Topography Mission (OSTM)/Jason-2 satellites.

In January 2009, Jason-1 was maneuvered into orbit on the opposite side of Earth from its successor, OSTM/Jason-2 satellite. It takes 10 days for the satellites to cover the globe and return to any one place over the ocean. So, in this new tandem configuration, Jason-1 flies over the same region of the ocean that OSTM/Jason-2 flew over five days earlier. Its ground tracks fall mid-way between those of Jason-2, which are about 315 kilometers (195 miles) apart at the equator.

Working together, the two spacecraft measure the surface topography of the ocean twice as often as would be possible with one satellite, and over a 10-day period, they return twice the amount of detailed measurements. Combining data from the two satellites makes it possible to map smaller, more rapidly changing features than one satellite could alone.

This image shows sea-level anomaly data from the first 14 days of the interleaved orbit of Jason-1 and OSTM/Jason-2, the period beginning on Feb. 20, 2009. An anomaly is a departure from a value averaged over a long period of time.

Red and yellow are regions where sea levels are higher than normal. Purple and dark blue show where sea levels are lower. A higher-than-normal sea surface is usually a sign of warm waters below, while lower sea levels indicate cooler than normal temperatures. The small-sized patches of highs and lows are ocean eddies, the storms of ocean weather that carry most of the energy of ocean circulation. These are not well observed with only one satellite.

Jason-1 is a joint mission of NASA and the French space agency, CNES. The U.S. portion of the Jason-1 mission is managed by JPL for NASA's Science Mission Directorate, Washington, D.C.

OSTM/Jason 2 is an international endeavor with responsibility for satellite development and launch shared between NASA and CNES. The U.S. National Oceanic and Atmospheric Administration (NOAA) is responsible for satellite operations, and JPL is managing the mission for NASA. Data processing is being carried out by CNES, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and NOAA.

Integration of remote sensing and geophysical techniques for coastal monitoring

NASA Astrophysics Data System (ADS)

Simoniello, T.; Carone, M. T.; Loperte, A.; Satriani, A.; Imbrenda, V.; D'Emilio, M.; Guariglia, A.

2009-04-01

Coastal areas are of great environmental, economic, social, cultural and recreational relevance; therefore, the implementation of suitable monitoring and protection actions is fundamental for their preservation and for assuring future use of this resource. Such actions have to be based on an ecosystem perspective for preserving coastal environment integrity and functioning and for planning sustainable resource management of both the marine and terrestrial components (ICZM-EU initiative). We implemented an integrated study based on remote sensing and geophysical techniques for monitoring a coastal area located along the Ionian side of Basilicata region (Southern Italy). This area, between the Bradano and Basento river mouths, is mainly characterized by a narrow shore (10-30 m) of fine sandy formations and by a pine forest planted in the first decade of 50's in order to preserve the coast and the inland cultivated areas. Due to drought and fire events and saltwater intrusion phenomena, such a forest is affected by a strong decline with consequent environmental problems. Multispectral satellite data were adopted for evaluating the spatio-temporal features of coastal vegetation and the structure of forested patterns. The increase or decrease in vegetation activity was analyzed from trends estimated on a time series of NDVI (Normalized Difference Vegetation Index) maps. The fragmentation/connection levels of vegetated patterns was assessed form a set of landscape ecology metrics elaborated at different structure scales (patch, class and landscape) on satellite cover classifications. Information on shoreline changes were derived form a multi-source data set (satellite data, field-GPS surveys and Aerial Laser Scanner acquisitions) by taking also into account tidal effects. Geophysical campaigns were performed for characterizing soil features and limits of salty water infiltrations. Form vertical resistivity soundings (VES), soil resistivity maps at different a deeps (0.5-1.0-1.5m) were obtained; in addition electrical resistivity tomographies (ERT) were acquired with different orientations and lengths. The analysis of vegetation activity from satellite data identified large patches affected by vegetation decline and fragmentation processes, where geophysical measurements highlighted a salt water infiltration. Moreover, they showed that such a phenomenon has not only a horizontal distribution, but also a vertical diffusion interesting the layer active for plant roots. Since a severe shoreline regression (up to 90m) was observed along the investigated coast, erosional process could have increased the saltwater intrusion process during the last 20 years. On the whole, the obtained results suggest that the integration of remote sensing peculiarities (synoptic view, multi-temporal availability) with those of geophysical techniques (local details, non-invasive soundings) can be a suitable support tool for planning and management activities in coastal areas (e.g., the identification of the most appropriated sites for ecological interventions or for barrage and earthen block construction).

Potential for Small Unmanned Aircraft Systems applications for identifying groundwater-surface water exchange in a meandering river reach

USGS Publications Warehouse

Pai, H.; Malenda, H.; Briggs, Martin A.; Singha, K.; González-Pinzón, R.; Gooseff, M.; Tyler, S.W.; ,

2017-01-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here, we describe the use of a suite of high spatial-resolution remote-sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index (NDVI) mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW “shortcutting” through meander necks, which was corroborated by temperature data at the riverbed interface.

Potential for Small Unmanned Aircraft Systems Applications for Identifying Groundwater-Surface Water Exchange in a Meandering River Reach

NASA Astrophysics Data System (ADS)

Pai, H.; Malenda, H. F.; Briggs, M. A.; Singha, K.; González-Pinzón, R.; Gooseff, M. N.; Tyler, S. W.

2017-12-01

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here we describe the use of a suite of high spatial resolution remote sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW "shortcutting" through meander necks, which was corroborated by temperature data at the riverbed interface.

Global assessment of Level 3 SMOS and Aquarius salinity measurements using Argo and an operational ocean model

NASA Astrophysics Data System (ADS)

Banks, Chris; Gommenginger, Christine; Srokosz, Meric; Snaith, Helen

2013-04-01

The launch of the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 marked a new era in satellite oceanography. SMOS was joined in orbit, in June 2011, by the NASA/Argentine Aquarius/SAC-D mission, specifically designed to measure sea surface salinity (SSS). These two satellites have significantly improved our ability to measure SSS synoptically. Despite significant differences in how the two satellites estimate SSS, both utilise passive systems to measure the response of the brightness temperature (Tb) at L-band (1.4 GHz) to SSS and initial results are encouraging. The UK National Oceanography Centre has produced 'Level 3' SSS data products for SMOS and Aquarius using monthly data on a 1° by 1° global grid, between 60°S and 60°N, from 1 September 2011 to 31 August 2012. Previous and on-going work shows for both satellites significant temporally varying differences between SSS from ascending passes (satellite moving south to north) and SSS from descending passes (satellite moving north to south). Therefore, for both SMOS and Aquarius, separate Level 3 products are produced from data for ascending and descending passes. For this study, two separate monthly validation datasets are used based on the same grid as the satellite data. The first is averaged near-surface salinity (depth less than 10 m) as derived from the drifting Argo float programme. The second validation data source is output from the UK Met Office Forecasting Ocean Assimilation Model (FOAM), which is based on NEMO (Nucleus for European Modelling of the Ocean). We calculate maps of the difference between all possible pairs of SSS data for each month, and consider their relationships using regression on the 1˚ values. The analysis is carried out for the global ocean, as well as for smaller, more homogeneous, study regions (e.g. SPURS in the subtropical North Atlantic).

Insitu aircraft verification of the quality of satellite cloud winds over oceanic regions

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Skillman, W. C.

1979-01-01

A five year aircraft experiment to verify the quality of satellite cloud winds over oceans using in situ aircraft inertial navigation system wind measurements is presented. The final results show that satellite measured cumulus cloud motions are very good estimators of the cloud base wind for trade wind and subtropical high regions. The average magnitude of the vector differences between the cloud motion and the cloud base wind is given. For cumulus clouds near frontal regions, the cloud motion agreed best with the mean cloud layer wind. For a very limited sample, cirrus cloud motions also most closely followed the mean wind in the cloud layer.

Direct Satellite Data Acquisition and its Application for Large -scale Monitoring Projects in Russia

NASA Astrophysics Data System (ADS)

Gershenzon, O.

2011-12-01

ScanEx RDC created an infrastructure (ground stations network) to acquire and process remote sensing data from different satellites: Terra, Aqua, Landsat, IRS-P5/P6, SPOT 4/5, FORMOSAT-2, EROS A/B, RADARSAT-1/2, ENVISAT-1. It owns image archives from these satellites as well as from SPOT-2 and CARTOSAT-2. ScanEx RDC builds and delivers remote sensing ground stations (working with up to 15 satellites); and owns the ground stations network to acquire data for Russia and surrounding territory. ScanEx stations are the basic component in departmental networks of remote sensing data acquisition for different state authorities (Roshydromet, Ministry of Natural Recourses, Emercom) and University- based remote sensing data acquisition and processing centers in Russia and abroad. ScanEx performs large-scale projects in collaboration with government agencies to monitor forests, floods, fires, sea surface pollution, and ice situation in Northern Russia. During 2010-2011 ScanEx conducted daily monitoring of wild fires in Russia detecting and registering thermal anomalies using data from Terra, Aqua, Landsat and SPOT satellites. Detailed SPOT 4/5 data is used to analyze burnt areas and to assess damage caused by fire. Satellite data along with other information about fire situation in Russia was daily updated and published via free-access Internet geoportal. A few projects ScanEx conducted together with environmental NGO. Project "Satellite monitoring of Especially Protected Natural Areas of Russia and its results visualization on geoportal was conducted in cooperation with NGO "Transparent World". The project's goal was to observe natural phenomena and economical activity, including illegal, by means of Earth remote sensing data. Monitoring is based on multi-temporal optical space imagery of different spatial resolution. Project results include detection of anthropogenic objects that appeared in the vicinity or even within the border of natural territories, that have never been touched by civilization before. "Satellite based technology for monitoring ship ice navigation and its influence on seal population in the White Sea" project was conducted in cooperation with IFAW. Results of the near real-time satellite monitoring were published on specially designed open web source. This allows project team to put image interpretation results in near real-time mode for on-line access to all interesting external stakeholders. During project realization Envisat, Radarsat, SPOT, EROS space images were used. In addition the methodology to locate seal population using EROS space images was developed. This methodology is based on detection of vital functions and displacement traces. Environmental satellite monitoring of Northern Russian territory and Arctic seas projects where the results are published via free-access Internet geoportal has a significant social importance.

US experiments flown on the Soviet satellite COSMOS 936

NASA Technical Reports Server (NTRS)

Rosenzweig, S. N.; Souza, K. A.

1978-01-01

Results of spaceborne experiments onboard the Cosmos 936 satellite are reported. Alterations in normal bone chemistry, muscle structure, and general physiology resulting from spaceflight are covered along with measurements of cosmic radiation and its potential hazard to man during prolonged spaceflights. Postflight activities involving the seven U.S. experiments are emphasized.

A molecular deletion of distal chromosome 4p in two families with a satellited chromosome 4 lacking the Wolf-Hirschhorn syndrome phenotype.

PubMed

Estabrooks, L L; Lamb, A N; Kirkman, H N; Callanan, N P; Rao, K W

1992-11-01

We report two families with a satellited chromosome 4 short arm (4ps). Satellites and stalks normally occur on the short arms of acrocentric chromosomes; however, the literature cites several reports of satellited nonacrocentric chromosomes, which presumably result from a translocation with an acrocentric chromosome. This is the first report of 4ps chromosomes. Our families are remarkable in that both unaffected and affected individuals carry the 4ps chromosome. The phenotypes observed in affected individuals, although dissimilar, were sufficient to encourage a search for a deletion of chromosome 4p. By Southern blot analysis and fluorescence in situ hybridization, a deletion of material mapping approximately 150 kb from chromosome 4pter was discovered. This deletion is notable because it does not result in the Wolf-Hirschhorn syndrome and can result in an apparently normal phenotype. We speculate that homology between subterminal repeat sequences on 4p and sequences on the acrocentric short arms may explain the origin of the rearrangement and that position effect may play a role in the expression of the abnormal phenotype.

History of telescopic observations of the Martian satellites

NASA Astrophysics Data System (ADS)

Pascu, D.; Erard, S.; Thuillot, W.; Lainey, V.

2014-11-01

This article intends to review the different studies of the Mars satellites Phobos and Deimos realized by means of ground-based telescopic observations as well in the astrometry and dynamics domain as in the physical one. This study spans the first period of investigations of the Martian satellites since their discovery in 1877 through the astrometry and the spectrometry methods, mainly before the modern period of the space era. It includes also some other observations performed thanks to the Hubble Space Telescope. The different techniques used and the main results obtained for the positionning, the size estimate, the albedo and surface composition are described.

Examining the NZESM Cloud representation with Self Organizing Maps

NASA Astrophysics Data System (ADS)

Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike

2017-04-01

Several different cloud regimes are identified from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our cloud classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS cloud top pressure - cloud optical thickness joint histograms. To evaluate the representation of the cloud within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only identifying differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of cloud the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall cloud fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the cloud fraction related to different cloud heights and phases were also analysed.

Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data.

PubMed

Fuentes, M V; Malone, J B; Mas-Coma, S

2001-04-27

The present paper aims to validate the usefulness of the Normalized Difference Vegetation Index (NDVI) obtained by satellite remote sensing for the development of local maps of risk and for prediction of human fasciolosis in the Northern Bolivian Altiplano. The endemic area, which is located at very high altitudes (3800-4100 m) between Lake Titicaca and the valley of the city of La Paz, presents the highest prevalences and intensities of fasciolosis known in humans. NDVI images of 1.1 km resolution from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the National Oceanic and Atmospheric Administration (NOAA) series of environmental satellites appear to provide adequate information for a study area such as that of the Northern Bolivian Altiplano. The predictive value of the remotely sensed map based on NDVI data appears to be better than that from forecast indices based only on climatic data. A close correspondence was observed between real ranges of human fasciolosis prevalence at 13 localities of known prevalence rates and the predicted ranges of fasciolosis prevalence using NDVI maps. However, results based on NDVI map data predicted zones as risk areas where, in fact, field studies have demonstrated the absence of lymnaeid populations during snail surveys, corroborated by the absence of the parasite in humans and livestock. NDVI data maps represent a useful data component in long-term efforts to develop a comprehensive geographical information system control program model that accurately fits real epidemiological and transmission situations of human fasciolosis in high altitude endemic areas in Andean countries.

Assessing the Impact of Earth Radiation Pressure Acceleration on Low-Earth Orbit Satellites

NASA Astrophysics Data System (ADS)

Vielberg, Kristin; Forootan, Ehsan; Lück, Christina; Kusche, Jürgen; Börger, Klaus

2017-04-01

The orbits of satellites are influenced by several external forces. The main non-gravitational forces besides thermospheric drag, acting on the surface of satellites, are accelerations due to the Earth and Solar Radiation Pres- sure (SRP and ERP, respectively). The sun radiates visible and infrared light reaching the satellite directly, which causes the SRP. Earth also emits and reflects the sunlight back into space, where it acts on satellites. This is known as ERP acceleration. The influence of ERP increases with decreasing distance to the Earth, and for low-earth orbit (LEO) satellites ERP must be taken into account in orbit and gravity computations. Estimating acceler- ations requires knowledge about energy emitted from the Earth, which can be derived from satellite remote sensing data, and also by considering the shape and surface material of a satellite. In this sensitivity study, we assess ERP accelerations based on different input albedo and emission fields and their modelling for the satellite missions Challenging Mini-Satellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE). As input fields, monthly 1°x1° products of Clouds and the Earth's Radiant En- ergy System (CERES), L3 are considered. Albedo and emission models are generated as latitude-dependent, as well as in terms of spherical harmonics. The impact of different albedo and emission models as well as the macro model and the altitude of satellites on ERP accelerations will be discussed.

Estimating fire severity and carbon emissions over Australian tropical savannas based on passive microwave satellite observations

NASA Astrophysics Data System (ADS)

Chen, X.; Liu, Y.; Evans, J. P.; Parinussa, R.

2017-12-01

Carbon emissions from large-scale fire activity over the Australian tropical savannas have strong inter-annual variability, due mainly to variations in fuel accumulation in response to rainfall. We investigated the use of a recently developed satellite-based vegetation optical depth (VOD) dataset to estimate fire severity and carbon emission. VOD is sensitive to the dynamics of all aboveground vegetation and available nearly every two days. For areas burned during 2003 - 2010, we calculated the VOD change (ΔVOD) pre- and post-fire and the associated loss in above ground biomass carbon. Both results compare well with widely-accepted approaches: ΔVOD agreed well with the Normalized Burn Ratio change (ΔNBR) and carbon loss with modelled emissions from the Global Fire Emissions Database (GFED). We found that the ΔVOD and ΔNBR are generally linearly related. The Pearson correlation coefficients (R) between VOD- and GFED-based fire carbon emissions for monthly and annual total estimates are very high, 0.92 and 0.96 respectively. A key feature of fire carbon emissions is the strong inter-annual variation, ranging from 21.1 million tonnes in 2010 to 84.3 million tonnes in 2004. This study demonstrates that a reasonable estimate of fire carbon emissions can be achieved in a timely manner based on multiple satellite observations over the regions where the emissions are primarily from aboveground vegetation loss, which can be complementary to the currently used approaches.

On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

NASA Astrophysics Data System (ADS)

Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

2015-04-01

Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbanceInternational Journal of Applied Earth Observation and Geoinformation 26 441-446 Lanorte A, M Danese, R Lasaponara, B Murgante 2014 Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis International Journal of Applied Earth Observation and Geoinformation 20, 42-51 Tuia D, F Ratle, R Lasaponara, L Telesca, M Kanevski 2008 Scan statistics analysis of forest fire clusters Communications in Nonlinear Science and Numerical Simulation 13 (8), 1689-1694 Telesca L, R Lasaponara 2006 Pre and post fire behavioral trends revealed in satellite NDVI time series Geophysical Research Letters 33 (14) Lasaponara R 2005 Intercomparison of AVHRR based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy International Journal of Remote Sensing 26 (5), 853-870

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Multisensor and Multispectral Approach in Documenting and Analyzing Liquefaction Hazard using Remote Sensing

NASA Astrophysics Data System (ADS)

Oommen, T.; Baise, L. G.; Gens, R.; Prakash, A.; Gupta, R. P.

2008-12-01

Seismic liquefaction is the loss of strength of soil due to shaking that leads to various ground failures such as lateral spreading, settlements, tilting, and sand boils. It is important to document these failures after earthquakes to advance our study of when and where liquefaction occurs. The current approach of mapping these failures by field investigation teams suffers due to the inaccessibility to some of the sites immediately after the event, short life of some of these failures, difficulties in mapping the aerial extent of the failure, incomplete coverage etc. After the 2001 Bhuj earthquake (India), researchers, using the Indian remote sensing satellite, illustrated that satellite remote sensing can provide a synoptic view of the terrain and offer unbiased estimates of liquefaction failures. However, a multisensor (data from different sensors onboard of the same or different satellites) and multispectral (data collected in different spectral regions) approach is needed to efficiently document liquefaction incidences and/or its potential of occurrence due to the possibility of a particular satellite being located inappropriately to image an area shortly after an earthquake. The use of SAR satellite imagery ensures the acquisition of data in all weather conditions at day and night as well as information complimentary to the optical data sets. In this study, we analyze the applicability of the various satellites (Landsat, RADARSAT, Terra-MISR, IRS-1C, IRS-1D) in mapping liquefaction failures after the 2001 Bhuj earthquake using Support Vector Data Description (SVDD). The SVDD is a kernel based nonparametric outlier detection algorithm inspired by the Support Vector Machines (SVMs), which is a new generation learning algorithm based on the statistical learning theory. We present the applicability of SVDD for unsupervised change-detection studies (i.e. to identify post-earthquake liquefaction failures). The liquefaction occurrences identified from the different satellites using SVDD have been compared to the ground truth in terms of documented liquefaction failures by other researchers. We present the applicability and appropriateness of the various satellites and spectral regions for documenting liquefaction related failures. Results illustrate that the SVDD is a promising unsupervised change-detection algorithm, which can help in automating the documentation of earthquake induced liquefaction failures.

Evolutionary Story of a Satellite DNA from Phodopus sungorus (Rodentia, Cricetidae)

PubMed Central

Paço, Ana; Adega, Filomena; Meštrović, Nevenka; Plohl, Miroslav; Chaves, Raquel

2014-01-01

With the goal to contribute for the understanding of satellite DNA evolution and its genomic involvement, in this work it was isolated and characterized the first satellite DNA (PSUcentSat) from Phodopus sungorus (Cricetidae). Physical mapping of this sequence in P. sungorus showed large PSUcentSat arrays located at the heterochromatic (peri)centromeric region of five autosomal pairs and Y-chromosome. The presence of orthologous PSUcentSat sequences in the genomes of other Cricetidae and Muridae rodents was also verified, presenting however, an interspersed chromosomal distribution. This distribution pattern suggests a PSUcentSat-scattered location in an ancestor of Muridae/Cricetidae families, that assumed afterwards, in the descendant genome of P. sungorus a restricted localization to few chromosomes in the (peri)centromeric region. We believe that after the divergence of the studied species, PSUcentSat was most probably highly amplified in the (peri)centromeric region of some chromosome pairs of this hamster by recombinational mechanisms. The bouquet chromosome configuration (prophase I) possibly displays an important role in this selective amplification, providing physical proximity of centromeric regions between chromosomes with similar size and/or morphology. This seems particularly evident for the acrocentric chromosomes of P. sungorus (including the Y-chromosome), all presenting large PSUcentSat arrays at the (peri)centromeric region. The conservation of this sequence in the studied genomes and its (peri)centromeric amplification in P. sungorus strongly suggests functional significance, possibly displaying this satellite family different functions in the different genomes. The verification of PSUcentSat transcriptional activity in normal proliferative cells suggests that its transcription is not stage-limited, as described for some other satellites. PMID:25336681

Results of Kirari optical communication demonstration experiments with NICT optical ground station (KODEN) aiming for future classical and quantum communications in space

NASA Astrophysics Data System (ADS)

Toyoshima, Morio; Takenaka, Hideki; Shoji, Yozo; Takayama, Yoshihisa; Koyama, Yoshisada; Kunimori, Hiroo

2012-05-01

Bi-directional ground-to-satellite laser communication experiments were successfully performed between the optical ground station developed by the National Institute of Information and Communications Technology (NICT), located in Koganei City in suburban Tokyo, and a low earth orbit (LEO) satellite, the "Kirari" Optical Inter-orbit Communications Engineering Test Satellite (OICETS). The experiments were conducted in cooperation with the Japan Aerospace Exploration Agency (JAXA), and called the Kirari Optical communication Demonstration Experiments with the NICT optical ground station (or KODEN). The ground-to-OICETS laser communication experiment was the first in-orbit demonstration involving the LEO satellite. The laser communication experiment was conducted since March 2006. The polarization characteristics of an artificial laser source in space, such as Stokes parameters, and the degree of polarization were measured through space-to-ground atmospheric transmission paths, which results contribute to the link estimation for quantum key distribution via space and provide the potential for enhancements in quantum cryptography on a global scale in the future. The Phase-5 experiment, international laser communications experiments were also successfully conducted with four optical ground stations located in the United States, Spain, Germany, and Japan from April 2009 to September 2009. The purpose of the Phase-5 experiment was to establish OICETS-to-ground laser communication links from the different optical ground stations and the statistical analyses such as the normalized power, scintillation index, probability density function, auto-covariance function, and power spectral density were performed. Thus the applicability of the satellite laser communications was demonstrated, aiming not only for geostationary earth orbit-LEO links but also for ground-to-LEO optical links. This paper presents the results of the KODEN experiments and mainly introduces the common analyses among the different optical ground stations.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Measuring phenological variability from satellite imagery

USGS Publications Warehouse

Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

1994-01-01

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

Fault tolerance in space-based digital signal processing and switching systems: Protecting up-link processing resources, demultiplexer, demodulator, and decoder

NASA Technical Reports Server (NTRS)

Redinbo, Robert

1994-01-01

Fault tolerance features in the first three major subsystems appearing in the next generation of communications satellites are described. These satellites will contain extensive but efficient high-speed processing and switching capabilities to support the low signal strengths associated with very small aperture terminals. The terminals' numerous data channels are combined through frequency division multiplexing (FDM) on the up-links and are protected individually by forward error-correcting (FEC) binary convolutional codes. The front-end processing resources, demultiplexer, demodulators, and FEC decoders extract all data channels which are then switched individually, multiplexed, and remodulated before retransmission to earth terminals through narrow beam spot antennas. Algorithm based fault tolerance (ABFT) techniques, which relate real number parity values with data flows and operations, are used to protect the data processing operations. The additional checking features utilize resources that can be substituted for normal processing elements when resource reconfiguration is required to replace a failed unit.

Flight measurement and analysis of AAFE RADSCAT wind speed signature of the ocean

NASA Technical Reports Server (NTRS)

Schroeder, L. C.; Jones, W. L.; Schaffner, P. R.; Mitchell, J. L.

1984-01-01

The advanced aerospace flight experiment radiometer scatterometer (AAFE RADSCAT) which was developed as a research tool to evaluate the use of microwave frequency remote sensors to provide wind speed information at the ocean surface is discussed. The AAFE RADSCAT helped establish the feasibility of the satellite scatterometer for measuring both wind speed and direction. The most important function of the AAFE RADSCAT was to provide a data base of ocean normalized radar cross section (NRCS) measurements as a function of surface wind vector at 13.9 GHz. The NRCS measurements over a wide parametric range of incidence angles, azimuth angles, and winds were obtained in a series of RADSCAT aircraft missions. The obtained data base was used to model the relationship between k sub u band radar signature and ocean surface wind vector. The models developed therefrom are compared with those used for inversion of the SEASAT-A satellite scatterometer (SASS) radar measurements to wind speeds.

Neighborhood Greenness and Chronic Health Conditions in Medicare Beneficiaries.

PubMed

Brown, Scott C; Lombard, Joanna; Wang, Kefeng; Byrne, Margaret M; Toro, Matthew; Plater-Zyberk, Elizabeth; Feaster, Daniel J; Kardys, Jack; Nardi, Maria I; Perez-Gomez, Gianna; Pantin, Hilda M; Szapocznik, José

2016-07-01

Prior studies suggest that exposure to the natural environment may impact health. The present study examines the association between objective measures of block-level greenness (vegetative presence) and chronic medical conditions, including cardiometabolic conditions, in a large population-based sample of Medicare beneficiaries in Miami-Dade County, Florida. The sample included 249,405 Medicare beneficiaries aged ≥65 years whose location (ZIP+4) within Miami-Dade County, Florida, did not change, from 2010 to 2011. Data were obtained in 2013 and multilevel analyses conducted in 2014 to examine relationships between greenness, measured by mean Normalized Difference Vegetation Index from satellite imagery at the Census block level, and chronic health conditions in 2011, adjusting for neighborhood median household income, individual age, gender, race, and ethnicity. Higher greenness was significantly associated with better health, adjusting for covariates: An increase in mean block-level Normalized Difference Vegetation Index from 1 SD less to 1 SD more than the mean was associated with 49 fewer chronic conditions per 1,000 individuals, which is approximately similar to a reduction in age of the overall study population by 3 years. This same level of increase in mean Normalized Difference Vegetation Index was associated with a reduced risk of diabetes by 14%, hypertension by 13%, and hyperlipidemia by 10%. Planned post-hoc analyses revealed stronger and more consistently positive relationships between greenness and health in lower- than higher-income neighborhoods. Greenness or vegetative presence may be effective in promoting health in older populations, particularly in poor neighborhoods, possibly due to increased time outdoors, physical activity, or stress mitigation. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Using satellite remote sensing to model and map the distribution of Bicknell's thrush (Catharus bicknelli) in the White Mountains of New Hampshire

NASA Astrophysics Data System (ADS)

Hale, Stephen Roy

Landsat-7 Enhanced Thematic Mapper satellite imagery was used to model Bicknell's Thrush (Catharus bicknelli) distribution in the White Mountains of New Hampshire. The proof-of-concept was established for using satellite imagery in species-habitat modeling, where for the first time imagery spectral features were used to estimate a species-habitat model variable. The model predicted rising probabilities of thrush presence with decreasing dominant vegetation height, increasing elevation, and decreasing distance to nearest Fir Sapling cover type. To solve the model at all locations required regressor estimates at every pixel, which were not available for the dominant vegetation height and elevation variables. Topographically normalized imagery features Normalized Difference Vegetation Index and Band 1 (blue) were used to estimate dominant vegetation height using multiple linear regression; and a Digital Elevation Model was used to estimate elevation. Distance to nearest Fir Sapling cover type was obtained for each pixel from a land cover map specifically constructed for this project. The Bicknell's Thrush habitat model was derived using logistic regression, which produced the probability of detecting a singing male based on the pattern of model covariates. Model validation using Bicknell's Thrush data not used in model calibration, revealed that the model accurately estimated thrush presence at probabilities ranging from 0 to <0.40 and from 0.50 to <0.60. Probabilities from 0.40 to <0.50 and greater than 0.60 significantly underestimated and overestimated presence, respectively. Applying the model to the study area illuminated an important implication for Bicknell's Thrush conservation. The model predicted increasing numbers of presences and increasing relative density with rising elevation, with which exists a concomitant decrease in land area. Greater land area of lower density habitats may account for more total individuals and reproductive output than higher density less abundant land area. Efforts to conserve areas of highest individual density under the assumption that density reflects habitat quality could target the smallest fraction of the total population.

Use of a Closed-Loop Tracking Algorithm for Orientation Bias Determination of an S-Band Ground Station

NASA Technical Reports Server (NTRS)

Welch, Bryan W.; Piasecki, Marie T.; Schrage, Dean S.

2015-01-01

The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

New Antenna Deployment, Pointing and Supporting Mechanism

NASA Technical Reports Server (NTRS)

Costabile, V.; Lumaca, F.; Marsili, P.; Noni, G.; Portelli, C.

1996-01-01

On ITALSAT Flight 2, the Italian telecommunications satellite, the two L-Ka antennas (Tx and Rx) use two large deployable reflectors (2000-mm diameter), whose deployment and fine pointing functions are accomplished by means of an innovative mechanism concept. The Antenna Deployment & Pointing Mechanism and Supporting Structure (ADPMSS) is based on a new configuration solution, where the reflector and mechanisms are conceived as an integrated, self-contained assembly. This approach is different from the traditional configuration solution. Typically, a rigid arm is used to deploy and then support the reflector in the operating position, and an Antenna Pointing Mechanism (APM) is normally interposed between the reflector and the arm for steering operation. The main characteristics of the ADPMSS are: combined implementation of deployment, pointing, and reflector support; optimum integration of active components and interface matching with the satellite platform; structural link distribution to avoid hyperstatic connections; very light weight and; high performance in terms of deployment torque margin and pointing range/accuracy. After having successfully been subjected to all component-level qualification and system-level acceptance tests, two flight ADPMSS mechanisms (one for each antenna) are now integrated on ITALSAT F2 and are ready for launch. This paper deals with the design concept, development, and testing program performed to qualify the ADPMSS mechanism.

Atmosphere-Ionosphere Response to the M9 Tohoku Earthquake Revealed by Joined Satellite and Ground Observations. Preliminary Results

NASA Technical Reports Server (NTRS)

Ouzounov, Dimitar; Pulinets, Sergey; Romanov, Alexey; Tsybulya, Konstantin; Davidenko, Dimitri; Kafatos, Menas; Taylor, Patrick

2011-01-01

The recent M9 Tohoku Japan earthquake of March 11, 2011 was the largest recorded earthquake ever to hit this nation. We retrospectively analyzed the temporal and spatial variations of four different physical parameters - outgoing long wave radiation (OLR), GPS/TEC, Low-Earth orbit tomography and critical frequency foF2. These changes characterize the state of the atmosphere and ionosphere several days before the onset of this earthquake. Our first results show that on March 8th a rapid increase of emitted infrared radiation was observed from the satellite data and an anomaly developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. Starting on this day in the lower ionospheric there was also confirmed an abnormal TEC variation over the epicenter. From March 3-11 a large increase in electron concentration was recorded at all four Japanese ground based ionosondes, which return to normal after the main earthquake. We found a positive correlation between the atmospheric and ionospheric anomalies and the Tohoku earthquake. This study may lead to a better understanding of the response of the atmosphere/ionosphere to the Great Tohoku earthquake.

Environmental drivers of variability in the movement ecology of turkey vultures (Cathartes aura) in North and South America.

PubMed

Dodge, Somayeh; Bohrer, Gil; Bildstein, Keith; Davidson, Sarah C; Weinzierl, Rolf; Bechard, Marc J; Barber, David; Kays, Roland; Brandes, David; Han, Jiawei; Wikelski, Martin

2014-01-01

Variation is key to the adaptability of species and their ability to survive changes to the Earth's climate and habitats. Plasticity in movement strategies allows a species to better track spatial dynamics of habitat quality. We describe the mechanisms that shape the movement of a long-distance migrant bird (turkey vulture, Cathartes aura) across two continents using satellite tracking coupled with remote-sensing science. Using nearly 10 years of data from 24 satellite-tracked vultures in four distinct populations, we describe an enormous amount of variation in their movement patterns. We related vulture movement to environmental conditions and found important correlations explaining how far they need to move to find food (indexed by the Normalized Difference Vegetation Index) and how fast they can move based on the prevalence of thermals and temperature. We conclude that the extensive variability in the movement ecology of turkey vultures, facilitated by their energetically efficient thermal soaring, suggests that this species is likely to do well across periods of modest climate change. The large scale and sample sizes needed for such analysis in a widespread migrant emphasizes the need for integrated and collaborative efforts to obtain tracking data and for policies, tools and open datasets to encourage such collaborations and data sharing.

Gridded sunshine duration climate data record for Germany based on combined satellite and in situ observations

NASA Astrophysics Data System (ADS)

Walawender, Jakub; Kothe, Steffen; Trentmann, Jörg; Pfeifroth, Uwe; Cremer, Roswitha

2017-04-01

The purpose of this study is to create a 1 km2 gridded daily sunshine duration data record for Germany covering the period from 1983 to 2015 (33 years) based on satellite estimates of direct normalised surface solar radiation and in situ sunshine duration observations using a geostatistical approach. The CM SAF SARAH direct normalized irradiance (DNI) satellite climate data record and in situ observations of sunshine duration from 121 weather stations operated by DWD are used as input datasets. The selected period of 33 years is associated with the availability of satellite data. The number of ground stations is limited to 121 as there are only time series with less than 10% of missing observations over the selected period included to keep the long-term consistency of the output sunshine duration data record. In the first step, DNI data record is used to derive sunshine hours by applying WMO threshold of 120 W/m2 (SDU = DNI ≥ 120 W/m2) and weighting of sunny slots to correct the sunshine length between two instantaneous image data due to cloud movement. In the second step, linear regression between SDU and in situ sunshine duration is calculated to adjust the satellite product to the ground observations and the output regression coefficients are applied to create a regression grid. In the last step regression residuals are interpolated with ordinary kriging and added to the regression grid. A comprehensive accuracy assessment of the gridded sunshine duration data record is performed by calculating prediction errors (cross-validation routine). "R" is used for data processing. A short analysis of the spatial distribution and temporal variability of sunshine duration over Germany based on the created dataset will be presented. The gridded sunshine duration data are useful for applications in various climate-related studies, agriculture and solar energy potential calculations.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

The determinations of remote sensing satellite data delivery service quality: A positivistic case study in Chinese context

NASA Astrophysics Data System (ADS)

Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun

2014-03-01

With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice.

In search of greener pastures: Using satellite images to predict the effects of environmental change on zebra migration

NASA Astrophysics Data System (ADS)

Bartlam-Brooks, Hattie L. A.; Beck, Pieter S. A.; Bohrer, Gil; Harris, Stephen

2013-12-01

ungulate migrations occurred in most grassland and boreal woodland ecosystems, but many have been lost due to increasing habitat loss and fragmentation. With the rate of environmental change increasing, identifying and prioritizing migration routes for conservation has taken on a new urgency. Understanding the cues that drive long-distance animal movements is critical to predicting the fate of migrations under different environmental change scenarios and how large migratory herbivores will respond to increasing resource heterogeneity and anthropogenic influences. We used an individual-based modeling approach to investigate the influence of environmental conditions, monitored using satellite data, on departure date and movement speed of migrating zebras in Botswana. Daily zebra movements between dry and rainy season ranges were annotated with coincident observations of precipitation from the Tropical Rainfall Measuring Mission data set and Moderate Resolution Imaging Spectroradiometer-derived normalized difference vegetation index (NDVI). An array of increasingly complex movement models representing alternative hypotheses regarding the environmental cues and controls for movement was parameterized and tested. The best and most justified model predicted daily zebra movement as two linear functions of precipitation rate and NDVI and included a modeled departure date as a function of cumulative precipitation. The model was highly successful at replicating both the timing and pace of seven actual migrations observed using GPS telemetry (R2 = 0.914). It shows how zebras rapidly adjust their movement to changing environmental conditions during migration and are able to reverse migration to avoid adverse conditions or exploit renewed resource availability, a nomadic behavior which should lend them a degree of resilience to climate and environmental change. Our results demonstrate how competing individual-based migration models, informed by freely available satellite data, can be used to evaluate the weight of evidence for multiple hypotheses regarding the use of environmental cues in animal movement. This modeling framework can be applied to quantify how animals adapt the timing and pace of their movements to prevailing environmental conditions and to forecast migrations in near real time or under alternative environmental scenarios.

Going beyond the green: senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

NASA Astrophysics Data System (ADS)

Mayes, Marc; Mustard, John; Melillo, Jerry; Neill, Christopher; Nyadzi, Gerson

2017-08-01

In sub-Saharan Africa (SSA), tropical dry forests and savannas cover over 2.5 million km2 and support livelihoods for millions in fast-growing nations. Intensifying land use pressures have driven rapid changes in tree cover structure (basal area, biomass) that remain poorly characterized at regional scales. Here, we posed the hypothesis that tree cover structure related strongly to senesced and non-photosynthetic (NPV) vegetation features in a SSA tropical dry forest landscape, offering improved means for satellite remote sensing of tree cover structure compared to vegetation greenness-based methods. Across regrowth miombo woodland sites in Tanzania, we analyzed relationships among field data on tree structure, land cover, and satellite indices of green and NPV features based on spectral mixture analyses and normalized difference vegetation index calculated from Landsat 8 data. From satellite-field data relationships, we mapped regional basal area and biomass using NPV and greenness-based metrics, and compared map performances at landscape scales. Total canopy cover related significantly to stem basal area (r 2 = 0.815, p < 0.01) and biomass (r 2 = 0.635, p < 0.01), and NPV dominated ground cover (> 60%) at all sites. From these two conditions emerged a key inverse relationship: skyward exposure of NPV ground cover was high at sites with low tree basal area and biomass, and decreased with increasing stem basal area and biomass. This pattern scaled to Landsat NPV metrics, which showed strong inverse correlations to basal area (Pearson r = -0.85, p < 0.01) and biomass (r = -0.86, p < 0.01). Biomass estimates from Landsat NPV-based maps matched field data, and significantly differentiated landscape gradients in woody biomass that greenness metrics failed to track. The results suggest senesced vegetation metrics at Landsat scales are a promising means for improved monitoring of tree structure across disturbance and ecological gradients in African and other tropical dry forests.

Utilization of downscaled microwave satellite data and GRACE Total Water Storage anomalies for improving streamflow prediction in the Lower Mekong Basin

NASA Astrophysics Data System (ADS)

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 simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Seasonal vegetation differences from ERTS imagery

NASA Technical Reports Server (NTRS)

Ashley, M. D.; Rea, J.

1975-01-01

Knowledge of the times when crop and forest vegetation experience seasonally related changes in development is important in understanding growth and yield relationships. This article describes how densitometry of earth resources technology satellite (ERTS-1) multispectral scanner (MSS) imagery can be used to identify such phenological events. Adjustments for instrument calibration, aperture size, gray-scale differences between overpasses, and normalization of changing solar elevation are considered in detail. Seasonal vegetation differences can be identified by densitometry of band 5 (0.6-0.7 microns) and band 7 (0.8-1.1 microns) MSS imagery. Band-to-band ratios of the densities depicted the changes more graphically than the individual band readings.

Differential correction capability of the GTDS using TDRSS data

NASA Technical Reports Server (NTRS)

Liu, S. Y.; Soskey, D. G.; Jacintho, J.

1980-01-01

A differential correction (DC) capability was implemented in the Goddard Trajectory Determination System (GTDS) to process satellite tracking data acquired via the Tracking and Data Relay Satellite System (TRDRSS). Configuration of the TDRSS is reviewed, observation modeling is presented, and major features of the capability are discussed. The following types of TDRSS data can be processed by GTDS: two way relay range and Doppler measurements, hybrid relay range and Doppler measurements, one way relay Doppler measurements, and differenced one way relay Doppler measurements. These data may be combined with conventional ground based direct tracking data. By using Bayesian weighted least squares techniques, the software allows the simultaneous determination of the trajectories of up to four different satellites - one user satellite and three relay satellites. In addition to satellite trajectories, the following parameters can be optionally solved: for drag coefficient, reflectivity of a satellite for solar radiation pressure, transponder delay, station position, and biases.

Infant Satellite Nurseries: Family Day Care with a Difference. Parent-Child Program Series, Report No. 4.

ERIC Educational Resources Information Center

Rosenfeld, Anne H.

Part of a series on early childhood demonstration programs designed to improve early parent-child relationships, stimulate positive child development, and prevent later behavior difficulties, the pamphlet describes the Infant Satellite Nursery Program, developed in Honolulu, Hawaii, to provide low-income families with subsidized, home-based care…