WorldWideScience

Sample records for satellite based estimates

  1. GPS SATELLITE SIMULATOR SIGNAL ESTIMATION BASED ON ANN

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Multi-channel Global Positioning System (GPS) satellite signal simulator is used to provide realistic test signals for GPS receivers and navigation systems. In this paper, signals arriving the antenna of GPS receiver are analyzed from the viewpoint of simulator design. The estimation methods are focused of which several signal parameters are difficult to determine directly according to existing experiential models due to various error factors. Based on the theory of Artificial Neural Network (ANN), an approach is proposed to simulate signal propagation delay,carrier phase, power, and other parameters using ANN. The architecture of the hardware-in-the-loop test system is given. The ANN training and validation process is described. Experimental results demonstrate that the ANN designed can statistically simulate sample data in high fidelity.Therefore the computation of signal state based on this ANN can meet the design requirement,and can be directly applied to the development of multi-channel GPS satellite signal simulator.

  2. Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

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

    2015-10-01

    A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  4. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  5. A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Hasager, Charlotte Bay

    Synthetic aperture radar (SAR) measurements from satellites can be used to estimate the spatial wind speed variation offshore in great detail. The radar senses cm-scale roughness at the sea surface which can be translated to wind speed at the height 10 m using an empirical geophysical model......-based wind climatology have improved gradually as more data were collected. The satellite scenes have been treated as random samples and weighted equally in our previous analyses. Here we introduce a novel sampling strategy based on the wind class methodology that is normally applied in numerical modeling...... climatologically representative large-scale meteorological conditions for the region of interest. The wind classes are used to make the most representative selection of satellite images from the ENVISAT image catalogue. A minimum of one satellite image is chosen per wind class. The frequency of occurrence of each...

  6. Satellite-based annual evaporation estimates of invasive alien plant ...

    African Journals Online (AJOL)

    2013-12-17

    Dec 17, 2013 ... Water (WFW) programme, have on total evaporation (ET) and the availability of water resources in two highly-invaded ... on water resources were based on the results from the paired catchment ...... Tourism, Pretoria. 85 pp.

  7. Characterization of satellite based proxies for estimating nucleation mode particles over South Africa

    Directory of Open Access Journals (Sweden)

    A.-M. Sundström

    2014-10-01

    Full Text Available In this work satellite observations from the NASA's A-Train constellation were used to derive the values of primary emission and regional nucleation proxies over South Africa to estimate the potential for new particle formation. As derived in Kulmala et al. (2011, the satellite based proxies consist of source terms (NO2, SO2 and UV-B radiation, and a sink term describing the pre-existing aerosols. The first goal of this work was to study in detail the use of satellite aerosol optical depth (AOD as a substitute to the in situ based condensation sink (CS. One of the major factors affecting the agreement of CS and AOD was the elevated aerosol layers that increased the value of column integrated AOD but not affected the in situ CS. However, when the AOD in the proxy sink was replaced by an estimate from linear bivariate fit between AOD and CS, the agreement with the actual nucleation mode number concentration improved somewhat. The second goal of the work was to estimate how well the satellite based proxies can predict the potential for new particle formation. For each proxy the highest potential for new particle formation were observed over the Highveld industrial area, where the emissions were high but the sink due to pre-existing aerosols was relatively low. Best agreement between the satellite and in situ based proxies were obtained for NO2/AOD and UV-B/AOD2, whereas proxies including SO2 in the source term had lower correlation. Even though the OMI SO2 boundary layer product showed reasonable spatial pattern and detected the major sources over the study area, some of the known minor point sources were not detected. When defining the satellite proxies only for days when new particle formation event was observed, it was seen that for all the satellite based proxies the event day medians were higher than the entire measurement period median.

  8. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

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

    2010-01-01

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

  9. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Verbist, Koen M. J.

    2016-04-01

    Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide.

  10. Assessing satellite AOD based and WRF/CMAQ output PM2.5 estimators

    Science.gov (United States)

    Cordero, Lina; Wu, Yonghua; Gross, Barry M.; Moshary, Fred

    2013-05-01

    Fine particulate matter measurements (PM2.5) are essential for air quality monitoring and related public health; however, the shortage of reliable measurmennts constrains researchers to use other means for obtaining reliable estimates over large scales. In particular, model forecasters and satellite community use their respective products to develop ground particulate matter estimations but few experiments have explored how the remote sensing approaches compare to the high resolution models. . In this paper we focus on studying the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Geostationary Operational Environmental Satellites (GOES) regression based estimates in comparison to more direct bias corrected outputs from the Community Multiscale Air Quality (CMAQ) model, We use a two-year dataset (2005-2006) and apply urban, season and hour filters to illustrate the agreement between estimated and in-situ measured fine particulate matter from the New York State Department of Environmental Conservation (NYSDEC). We first begin by analyzing the correspondence between ground aerosol optical depth (AOD) measurements from an AERONET (AErosol RObotic NETwork) Cimel sun/sky radiometer with both satellite and model products in one urban location; we show that satellite readings perform better than model outputs, especially during the summer (RMODIS>=0.65, RCMAQ>=0.37). This is a clear symptom of the difficulty in the models to properly model realistic optical properties. We then turn to a direct assessment of PM2.5 presenting individual comparisons between ground PM2.5 measurements with satellite/model predictions and demonstrate the higher accuracy from model estimations (RurbanMODIS >= 0.74, RurbanCMAQ >= 0.77; Rnon-urbanMODIS >= 0.48, Rnon-urbanCMAQ >= 0.78). In general, we find that the bias corrected CMAQ estimates are superior to satellite based estimators except at very high resolution. Finally, we show that when using both model and

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

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, M.; Gotseff, P.

    2013-12-01

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

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

    Science.gov (United States)

    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.

  13. Estimating Reliability of Disturbances in Satellite Time Series Data Based on Statistical Analysis

    Science.gov (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.

    2016-06-01

    Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with "Change/ No change" by most of the present methods, while few methods focus on estimating reliability (or confidence level) of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1) Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST). (2) Forecasting and detecting disturbances in new time series data. (3) Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI) and Confidence Levels (CL). The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

  14. Estimation of Satellite PCO Offsets for BeiDou based on MGEX Net Solution

    Science.gov (United States)

    Yize, Zhang; Junping, Chen; Bin, Wu; Jiexian, Wang

    2015-04-01

    BeiDou Satellite Navigation System currently has a total 14 satellites including GEO/IGSO/MEO satellites and providing a regional PNT service. Due to a lack of publicly available antenna phase center offsets (PCO) for the BeiDou satellites, conventional values of (+0.6 m, 0.0 m, +1.1 m) are recommended for orbit and clock determination of the GEO/IGSO/MEO satellites, which needs to be further estimation and refinement. In this paper, we propose a multi-GNSS network solution for the estimation of BeiDou satellite PCO. More than 35 ground stations of International GNSS MGEX tracking network are used to determine the BeiDou satellite PCO. In this strategy, the GPS and BeiDou satellite orbits and clocks are derived from IGS final products, and GPS satellite PCO and PCV are fixed according to igs08.atx. The BeiDou satellites PCO are estimated together with the station clock, troposphere delay and LC combination ambiguity parameter. Result shows that the RMS of phase residuals for all stations is 1.8cm and is 1.6m for code residual, respectively. The estimated PCO is different for each satellite. Appling the new PCO for precise point positioning, we found that the positioning error improves from 6cm to 2cm in height.

  15. Eliminating Obliquity Error from the Estimation of Ionospheric Delay in a Satellite-Based Augmentation System

    Science.gov (United States)

    Sparks, Lawrence

    2013-01-01

    Current satellite-based augmentation systems estimate ionospheric delay using algorithms that assume the electron density of the ionosphere is non-negligible only in a thin shell located near the peak of the actual profile. In its initial operating capability, for example, the Wide Area Augmentation System incorporated the thin shell model into an estimation algorithm that calculates vertical delay using a planar fit. Under disturbed conditions or at low latitude where ionospheric structure is complex, however, the thin shell approximation can serve as a significant source of estimation error. A recent upgrade of the system replaced the planar fit algorithm with an algorithm based upon kriging. The upgrade owes its success, in part, to the ability of kriging to mitigate the error due to this approximation. Previously, alternative delay estimation algorithms have been proposed that eliminate the need for invoking the thin shell model altogether. Prior analyses have compared the accuracy achieved by these methods to the accuracy achieved by the planar fit algorithm. This paper extends these analyses to include a comparison with the accuracy achieved by kriging. It concludes by examining how a satellite-based augmentation system might be implemented without recourse to the thin shell approximation.

  16. ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou

    2016-06-01

    Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

  17. Satellite-based estimate of aerosol direct radiative effect over the South-East Atlantic

    Directory of Open Access Journals (Sweden)

    L. Costantino

    2013-09-01

    Full Text Available The net effect of aerosol Direct Radiative Forcing (DRF is the balance between the scattering effect that reflects solar radiation back to space (cooling, and the absorption that decreases the reflected sunlight (warming. The amplitude of these two effects and their balance depends on the aerosol load, its absorptivity, the cloud fraction and the respective position of aerosol and cloud layers. In this study, we use the information provided by CALIOP (CALIPSO satellite and MODIS (AQUA satellite instruments as input data to a Rapid Radiative Transfer Model (RRTM and quantify the shortwave (SW aerosol direct atmospheric forcing, over the South-East Atlantic. The combination of the passive and active measurements allows estimates of the horizontal and vertical distributions of the aerosol and cloud parameters. We use a parametrization of the Single Scattering Albedo (SSA based on the satellite-derived Angstrom coefficient. The South East Atlantic is a particular region, where bright stratocumulus clouds are often topped by absorbing smoke particles. Results from radiative transfer simulations confirm the similar amplitude of the cooling effect, due to light scattering by the aerosols, and the warming effect, due to the absorption by the same particles. Over six years of satellite retrievals, from 2005 to 2010, the South-East Atlantic all-sky SW DRF is −0.03 W m−2, with a spatial standard deviation of 8.03 W m−2. In good agreement with previous estimates, statistics show that a cloud fraction larger than 0.5 is generally associated with positive all-sky DRF. In case of cloudy-sky and aerosol located only above the cloud top, a SSA larger than 0.91 and cloud optical thickness larger than 4 can be considered as threshold values, beyond which the resulting radiative forcing becomes positive.

  18. Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations

    Directory of Open Access Journals (Sweden)

    Checchi Francesco

    2013-01-01

    Full Text Available Abstract Background Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Methods Our method consisted of multiplying (i manual counts of assumed residential structures on a satellite image and (ii estimates of the mean number of people per structure (structure occupancy obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons’ camps and two urban neighbourhoods with a mixture of residents and displaced ranging in population from 1,969 to 90,547, and compared these to “gold standard” reference population figures from census or other robust methods. Results Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of Conclusions In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method’s development.

  19. Evaluation of a physically-based snow model with infrared and microwave satellite-derived estimates

    Science.gov (United States)

    Wang, L.

    2013-05-01

    Snow (with high albedo, as well as low roughness and thermal conductivity) has significant influence on the land-atmosphere interactions in the cold climate and regions of high elevation. The spatial and temporal variability of the snow distribution on a basin scale greatly determines the timing and magnitude of spring snowmelt runoff. For improved water resources management, a physically-based distributed snow model has been developed and applied to the upper Yellow River Basin to provide the outputs of snow variables as well as streamflows from 2001 to 2005. Remotely-sensed infrared information from MODIS satellites has been used to evaluate the model's outputs of spatially-distributed snow cover extent (SCE) and land surface temperature (LST); while the simulated snow depth (SD) and snow water equivalent (SWE) have been compared with the microwave information from SSM/I and AMSR-E satellites. In general, the simulated streamflows (including spring snowmelt) agree fairly well with the gauge-based observations; while the modeled snow variables show acceptable accuracies through comparing to various satellite-derived estimates from infrared or microwave information.;

  20. BeiDou satellite's differential code biases estimation based on uncombined precise point positioning with triple-frequency observable

    Science.gov (United States)

    Fan, Lei; Li, Min; Wang, Cheng; Shi, Chuang

    2017-02-01

    The differential code bias (DCB) of BeiDou satellite is an important topic to make better use of BeiDou system (BDS) for many practical applications. This paper proposes a new method to estimate the BDS satellite DCBs based on triple-frequency uncombined precise point positioning (UPPP). A general model of both triple-frequency UPPP and Geometry-Free linear combination of Phase-Smoothed Range (GFPSR) is presented, in which, the ionospheric observable and the combination of triple-frequency satellite and receiver DCBs (TF-SRDCBs) are derived. Then the satellite and receiver DCBs (SRDCBs) are estimated together with the ionospheric delay that is modeled at each individual station in a weighted least-squares estimator, and the satellite DCBs are determined by introducing the zero-mean condition of all available BDS satellites. To validate the new method, 90 day's real tracking GNSS data (from January to March in 2014) collected from 9 Multi-GNSS Experiment (MGEX) stations (equipped with Trimble NETR9 receiver) is used, and the BDS satellite DCB products from German Aerospace Center (DLR) are taken as reference values for comparison. Results show that the proposed method is able to precisely estimate BDS satellite DCBs: (1) the mean value of the day-to-day scattering for all available BDS satellites is about 0.24 ns, which is reduced in average by 23% when compared with the results derived by only GFPSR. Moreover, the mean value of the day-to-day scattering of IGSO satellites is lower than that of GEO and MEO satellites; (2) the mean value of RMS of the difference with respect to DLR DCB products is about 0.39 ns, which is improved by an average of 11% when compared with the results derived by only GFPSR. Besides, the RMS of IGSO and MEO satellites is at the same level which is better than that of GEO satellites.

  1. Bias reduction for Satellite Based Precipitation Estimates using statistical transformations in Guiana Shield

    Science.gov (United States)

    Ringard, Justine; Becker, Melanie; Seyler, Frederique; Linguet, Laurent

    2016-04-01

    Currently satellite-based precipitation estimates exhibit considerable biases, and there have been many efforts to reduce these biases by merging surface gauge measurements with satellite-based estimates. In Guiana Shield all products exhibited better performances during the dry season (August- December). All products greatly overestimate very low intensities (50 mm). Moreover the responses of each product are different according to hydro climatic regimes. The aim of this study is to correct spatially the bias of precipitation, and compare various correction methods to define the best methods depending on the rainfall characteristic correcting (intensity, frequency). Four satellites products are used: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (3B42V7) and real time product (3B42RT), the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network (PERSIANN) and the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), for six hydro climatic regimes between 2001 and 2012. Several statistical transformations are used to correct the bias. Statistical transformations attempt to find a function h that maps a simulated variable Ps such that its new distribution equals the distribution of the observed variable Po. The first is the use of a distribution derived transformations which is a mixture of the Bernoulli and the Gamma distribution, where the Bernoulli distribution is used to model the probability of precipitation occurrence and the Gamma distribution used to model precipitation intensities. The second a quantile-quantile relation using parametric transformation, and the last one is a common approach using the empirical CDF of observed and modelled values instead of assuming parametric distributions. For each correction 30% of both, simulated and observed data sets, are used to calibrate and the other part used to validate. The validation are test with statistical

  2. Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

    Science.gov (United States)

    Olson, William S.; Grecu, Mircea; Yang, Song; Tao, Wei-Kuo

    2004-01-01

    In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression

  3. Estimating crop yield using a satellite-based light use efficiency model

    DEFF Research Database (Denmark)

    Yuan, Wenping; Chen, Yang; Xia, Jiangzhou

    2016-01-01

    for simulating crops’ GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation...... primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model...... for improving crop yield estimations from satellite-based methods....

  4. Assessing the utility of satellite-based whitecap fraction to estimate sea spray production and CO2 transfer velocity

    Science.gov (United States)

    Anguelova, M. D.

    2016-05-01

    The utility of a satellite-based whitecap database for estimates of surface sea spray production and bubble-mediated gas transfer on a global scale is presented. Existing formulations of sea spray production and bubble-mediated CO2 transfer velocity involve whitecap fraction parametrization as a function of wind speed at 10 m reference height W(U 10) based on photographic measurements of whitecaps. Microwave radiometric measurements of whitecaps from satellites provide whitecap fraction data over the world oceans for all seasons. Parametrizations W(U 10) based on such radiometric data are thus applicable for a wide range of conditions and can account for influences secondary to the primary forcing factor, the wind speed. Radiometric satellite-based W(U 10) relationship was used as input to: (i) the Coupled Ocean-Atmosphere Response Experiment Gas transfer (COAREG) algorithm to obtain CO2 transfer velocity and total CO2 flux; and (ii) the sea spray source function (SSSF) recommended by Andreas in 2002 to obtain fluxes of sea spray number and mass. The outputs of COAREG and SSSF obtained with satellite-based W(U 10) are compared with respective outputs obtained with the nominal W(U 10) relationship based on photographic data. Good comparisons of the gas and sea spray fluxes with direct measurements and previous estimates imply that the satellite- based whitecap database can be useful to obtain surface fluxes of particles and gases in regions and conditions difficult to access and sample in situ. Satellite and in situ estimates of surface sea spray production and bubble-mediated gas transfer thus complement each other: accurate in situ observations can constrain radiometric whitecap fraction and mass flux estimates, while satellite observations can provide global coverage of whitecap fraction and mass flux estimates.

  5. Estimation of evapotranspiration over heterogeneous surfaces based on HJ1B satellite data in China

    Science.gov (United States)

    Xin, Xiaozhou; Jiao, Jingjun

    2014-05-01

    The HJ1B satellite of China is equipped with two CCD cameras with 30m resolution and one infrared multispectral camera with 300m resolution. And the revisit period of HJ1B satellite is 4 days. Compared to MODIS or TM, HJ1B data has the advantage of high spatial-temporal resolution. Methodology based on the one-source energy balance model was developed for net radiation (Rn), soil heat flux (G), sensible heat flux (H) and latent heat flux (LE) estimation from HI1B data. The core procedure is a scheme that was designed for correcting the spatial scale error over heterogeneous surfaces by taking advantage of the HJ1B data characteristics, i.e., high resolution CCD data (30m) along with thermal data (300m). First of all, a regression relationship between Ts and NDVI was built up at 300m resolution based on the data of Ts and NDVI of the selected "pure" pixels. And then the relationship function was applied at 30m resolution to derive Ts at high resolution, i.e., at the subpixel level. Furthermore, the 30m land class data was also used in the parameterization of surface energy balance and surface aerodynamic transfer, which is important since significant error may be resulted by using one land class type to represent the whole mixed pixel. By using high resolution NDVI and land class data, we are able to mitigate the spatial scale error of the mixed pixels at 300m resolution. At last, the 300m surface energy fluxes were obtained by aggregation of the 30m estimation. HJ1B data at Hai river basin in north China in 2010 were used to verify this method. The eddy-correlation system data were used as validation. The results of the method were compared with the results of a simple method that estimates the fluxes at 300m by aggregating all of the input parameters to 300m. It is shown that the method proposed in this study shows higher agreement with in-suit measurement, and the fluxes maps also show much more details of the spatial variation. By using this method, it can be

  6. Comparison of Historical Satellite-Based Estimates of Solar Radiation Resources with Recent Rotating Shadowband Radiometer Measurements: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Myers, D. R.

    2009-03-01

    The availability of rotating shadow band radiometer measurement data at several new stations provides an opportunity to compare historical satellite-based estimates of solar resources with measurements. We compare mean monthly daily total (MMDT) solar radiation data from eight years of NSRDB and 22 years of NASA hourly global horizontal and direct beam solar estimates with measured data from three stations, collected after the end of the available resource estimates.

  7. Estimation of land remote sensing satellites productivity based on the simulation technique

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.; Yakischik, Artem A.

    2017-01-01

    The problem of estimating land remote sensing satellites productivity is considered. Here, productivity is treated as a number of separate survey objects taken in a definite time. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  8. South African Weather Service operational satellite based precipitation estimation technique: applications and improvements

    Directory of Open Access Journals (Sweden)

    E. de Coning

    2010-11-01

    Full Text Available Extreme weather related to heavy or more frequent precipitation events seem to be a likely possibility for the future of our planet. While precipitation measurements can be done by means of rain gauges, the obvious disadvantages of point measurements are driving meteorologists towards remotely sensed precipitation methods. In South Africa more sophisticated and expensive nowcasting technology such as radar and lightning networks are available, supported by a fairly dense rain gauge network of about 1500 gauges. In the rest of southern Africa rainfall measurements are more difficult to obtain. The availability of the local version of the Unified Model and the Meteosat Second Generation satellite data make these products ideal components of precipitation measurement in data sparse regions such as Africa. In this article the local version of the Hydroestimator (originally from NOAA/NESDIS is discussed as well as its applications for precipitation measurement in this region. Hourly accumulations of the Hydroestimator are currently used as a satellite based precipitation estimator for the South African Flash Flood Guidance system. However, the Hydroestimator is by no means a perfect representation of the real rainfall. In this study the Hydroestimator and the stratiform rainfall field from the Unified Model are both bias corrected and then combined into a new precipitation field which can feed into the South African Flash Flood Guidance system. This new product should provide a more accurate and comprehensive input to the Flash Flood Guidance systems in South Africa as well as southern Africa. In this way the southern African region where data is sparse and very few radars are available can have access to more accurate flash flood guidance.

  9. ROBUST AND FAST FREQUENCY OFFSET ESTIMATION FOR OFDM BASED SATELLITE COMMUNICATION

    Institute of Scientific and Technical Information of China (English)

    Wei Li; Xu Youyun; Cai Yueming

    2009-01-01

    A pilot-aided Orthogonal Frequency Division Multiplexing (OFDM) frequency offset estimator designed for satellite communication system is proposed in the paper. The estimator focuses on the acquisition of the integer part of carrier frequency offset and the acquisition range is as large as the whole signal bandwidth. Making full use of the phase difference between received pilot and local referential pilot, a fast estimation is obtained. Compared with existing method, our method can also work well even in SNR as low as 0dB. Simulations verify the good performance of our method.

  10. Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

    Directory of Open Access Journals (Sweden)

    B. Ford

    2015-09-01

    Full Text Available The negative impacts of fine particulate matter (PM2.5 exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodology. Satellite observations of aerosol optical depth (AOD have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004–2011. We estimate that in the United States, exposure to PM2.5 accounts for approximately 4 % of total deaths compared to 22 % in China (using satellite-based exposure, which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 9 % for the US and 4 % for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on order of 20 % due to uncertainties in the AOD-to-surface-PM2.5 relationship, 10 % due to the satellite observational uncertainty, and 30 % or greater uncertainty associated with the application of concentration response functions to estimated exposure.

  11. Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

    Science.gov (United States)

    Ford, Bonne; Heald, Colette L.

    2016-03-01

    The negative impacts of fine particulate matter (PM2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the data sets and methodology. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and data sets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004-2011. Using the Burnett et al. (2014) integrated exposure response function, we estimate that in the United States, exposure to PM2.5 accounts for approximately 2 % of total deaths compared to 14 % in China (using satellite-based exposure), which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 14 % for the US and 2 % for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on the order of 20 % due to uncertainties in the AOD-to-surface-PM2.5 relationship, 10 % due to the satellite observational uncertainty, and 30 % or greater uncertainty associated with the application of concentration response functions to estimated exposure.

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

    Science.gov (United States)

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

    2015-12-01

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

  13. Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

    Science.gov (United States)

    Peng, Jian; Loew, Alexander; Chen, Xuelong; Ma, Yaoming; Su, Zhongbo

    2016-08-01

    The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to north-west over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land-atmosphere-biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed.

  14. Air-sea fluxes and satellite-based estimation of water masses formation

    Science.gov (United States)

    Sabia, Roberto; Klockmann, Marlene; Fernandez-Prieto, Diego; Donlon, Craig

    2015-04-01

    and monthly water mass formation rates for different SST and SSS ranges are presented. The formation peaks are remapped geographically, to analyze the extent of the formation area. Water mass formation derived from SMOS and OSTIA compares well with the results obtained from in-situ data, although slight differences in magnitude and peak location occur. Known water masses can then be identified. Ongoing/future work aims at extending this study along different avenues by: 1) expand systematically the spatial and temporal domain of the study to additional ocean basins and to the entire time period of available SSS observations from SMOS/Aquarius; 2) perform a thorough error propagation to assess how errors in satellite SSS and SST translate into errors in water masses formation rates and geographical areas extent; and 3) explore the different options to connect the surface information to the vertical buoyancy structure to assess potential density instability (e.g., Turner angle). References [1] Sabia, R., M. Klockmann, D. Fernández-Prieto, and C. Donlon (2014), A first estimation of SMOS-based ocean surface T-S diagrams, J. Geophys. Res. Oceans, 119, 7357-7371, doi:10.1002/2014JC010120. [2] Klockmann, M., R. Sabia, D. Fernández-Prieto, C. Donlon, J. Font; Towards an estimation of water masses formation areas from SMOS-based T-S diagrams; EGU general assembly 2014, April 27-May 2, 2014. [3] Klockmann, M., R. Sabia, D. Fernández-Prieto, C. Donlon, Linking satellite SSS and SST to water mass formation; Ocean salinity science and salinity remote sensing workshop, Exeter, UK, November 26-28, 2014. [4] Font, J., A. Camps, A. Borges, M. Martín-Neira, J. Boutin, N. Reul, Y. H. Kerr, A. Hahne, and S. Mecklenburg, "SMOS: The challenging sea surface salinity measurement from space," Proceedings of the IEEE, vol. 98, pp. 649-665, 2010. [5] Le Vine, D.M.; Lagerloef, G.S.E.; Torrusio, S.E.; "Aquarius and Remote Sensing of Sea Surface Salinity from Space," Proceedings of the IEEE

  15. Fault estimation of satellite reaction wheels using covariance based adaptive unscented Kalman filter

    Science.gov (United States)

    Rahimi, Afshin; Kumar, Krishna Dev; Alighanbari, Hekmat

    2017-05-01

    Reaction wheels, as one of the most commonly used actuators in satellite attitude control systems, are prone to malfunction which could lead to catastrophic failures. Such malfunctions can be detected and addressed in time if proper analytical redundancy algorithms such as parameter estimation and control reconfiguration are employed. Major challenges in parameter estimation include speed and accuracy of the employed algorithm. This paper presents a new approach for improving parameter estimation with adaptive unscented Kalman filter. The enhancement in tracking speed of unscented Kalman filter is achieved by systematically adapting the covariance matrix to the faulty estimates using innovation and residual sequences combined with an adaptive fault annunciation scheme. The proposed approach provides the filter with the advantage of tracking sudden changes in the system non-measurable parameters accurately. Results showed successful detection of reaction wheel malfunctions without requiring a priori knowledge about system performance in the presence of abrupt, transient, intermittent, and incipient faults. Furthermore, the proposed approach resulted in superior filter performance with less mean squared errors for residuals compared to generic and adaptive unscented Kalman filters, and thus, it can be a promising method for the development of fail-safe satellites.

  16. Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

    Science.gov (United States)

    Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

    2016-12-01

    Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

  17. Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

    Science.gov (United States)

    Anderson, H. Ross; Butland, Barbara K.; Donkelaar, Aaron Matthew Van; Brauer, Michael; Strachan, David P.; Clayton, Tadd; van Dingenen, Rita; Amann, Marcus; Brunekreef, Bert; Cohen, Aaron; Dentener, Frank; Lai, Christopher; Lamsal, Lok N.; Martin, Randall V.

    2012-01-01

    Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.

  18. Parametric fault estimation based on H∞ optimization in a satellite launch vehicle

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Stoustrup, Jakob

    2008-01-01

    Correct diagnosis under harsh environmental conditions is crucial for space vehiclespsila health management systems to avoid possible hazardous situations. Consequently, the diagnosis methods are required to be robust toward these conditions. Design of a parametric fault detector, where the fault...... estimation is formulated in the so-called standard set-up for Hinfin control design problem, is addressed in this paper. In particular, we investigate the tunability of the design through the dedicated choice of the fault model. The method is applied to the model of turbopump as a subsystem of the jet engine...... for the satellite launch vehicle and the results are discussed....

  19. Evaluation of satellite based indices for primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2008-07-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modelling within a water limited environment. Results show a strong correlation between EVI against gross primary production (GPP, demonstrating the significance of EVI for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modelling in similar semi-arid ecosystems is limited.

  20. Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

    Science.gov (United States)

    Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

    2016-12-01

    Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

  1. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

    Science.gov (United States)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  2. The first estimates of global nucleation mode aerosol concentrations based on satellite measurements

    Directory of Open Access Journals (Sweden)

    M. Kulmala

    2011-11-01

    Full Text Available Atmospheric aerosols play a key role in the Earth's climate system by scattering and absorbing solar radiation and by acting as cloud condensation nuclei. Satellites are increasingly used to obtain information on properties of aerosol particles with a diameter larger than about 100 nm. However, new aerosol particles formed by nucleation are initially much smaller and grow into the optically active size range on time scales of many hours. In this paper we derive proxies, based on process understanding and ground-based observations, to determine the concentrations of these new particles and their spatial distribution using satellite data. The results are applied to provide seasonal variation of nucleation mode concentration. The proxies describe the concentration of nucleation mode particles over continents. The source rates are related to both regional nucleation and nucleation associated with more restricted sources. The global pattern of nucleation mode particle number concentration predicted by satellite data using our proxies is compared qualitatively against both observations and global model simulations.

  3. Development and validation of satellite-based estimates of surface visibility

    Science.gov (United States)

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

    2016-02-01

    A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear-sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  4. Multiscale Estimation of Leaf Area Index from Satellite Observations Based on an Ensemble Multiscale Filter

    Directory of Open Access Journals (Sweden)

    Jingyi Jiang

    2016-03-01

    Full Text Available Currently, multiple leaf area index (LAI products retrieved from remote sensing data are widely used in crop growth monitoring, land-surface process simulation and studies of climate change. However, most LAI products are only retrieved from individual satellite observations, which may result in spatial-temporal discontinuities and low accuracy in these products. In this paper, a new method was developed to simultaneously retrieve multiscale LAI data from satellite observations with different spatial resolutions based on an ensemble multiscale filter (EnMsF. The LAI average values corresponding to the date of satellite observations were calculated from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS LAI product and were used as a priori knowledge for LAI in order to construct an initial ensemble multiscale tree (EnMsT. Satellite observations obtained at different spatial resolutions were then applied to update the LAI values at each node of the EnMsT using a two-sweep filtering procedure. Next, the retrieved LAI values at the finest scale were used as a priori knowledge for LAI for the new round of construction and updating of the EnMsT, until the sum of the difference of LAI values at each node of the EnMsT between two adjacent updates is less than a given threshold. The method was tested using Thematic Mapper (TM or Enhanced Thematic Mapper Plus (ETM+ surface reflectance data and MODIS surface reflectance data from five sites that have different vegetation types. The results demonstrate that the retrieved LAI values for each spatial resolution were in good agreement with the aggregated LAI reference map values for the corresponding spatial resolution. The retrieved LAI values at the coarsest scale provided better accuracy with the aggregated LAI reference map values (root mean square error (RMSE = 0.45 compared with that obtained from the MODIS LAI values (RMSE = 1.30.

  5. Evaluation of satellite and reanalysis-based global net surface energy flux and uncertainty estimates

    Science.gov (United States)

    Allan, Richard; Liu, Chunlei

    2017-04-01

    The net surface energy flux is central to the climate system yet observational limitations lead to substantial uncertainty (Trenberth and Fasullo, 2013; Roberts et al., 2016). A combination of satellite-derived radiative fluxes at the top of atmosphere (TOA) adjusted using the latest estimation of the net heat uptake of the Earth system, and the atmospheric energy tendencies and transports from the ERA-Interim reanalysis are used to estimate surface energy flux globally (Liu et al., 2015). Land surface fluxes are adjusted through a simple energy balance approach using relations at each grid point with the consideration of snowmelt to improve regional realism. The energy adjustment is redistributed over the oceans using a weighting function to avoid meridional discontinuities. Uncertainties in surface fluxes are investigated using a variety of approaches including comparison with a range of atmospheric reanalysis input data and products. Zonal multiannual mean surface flux uncertainty is estimated to be less than 5 Wm-2 but much larger uncertainty is likely for regional monthly values. The meridional energy transport is calculated using the net surface heat fluxes estimated in this study and the result shows better agreement with observations in Atlantic than before. The derived turbulent fluxes (difference between the net heat flux and the CERES EBAF radiative flux at surface) also have good agreement with those from OAFLUX dataset and buoy observations. Decadal changes in the global energy budget and the hemisphere energy imbalances are quantified and present day cross-equator heat transports is re-evaluated as 0.22±0.15 PW southward by the atmosphere and 0.32±0.16 PW northward by the ocean considering the observed ocean heat sinks (Roemmich et al., 2006) . Liu et al. (2015) Combining satellite observations and reanalysis energy transports to estimate global net surface energy fluxes 1985-2012. J. Geophys. Res., Atmospheres. ISSN 2169-8996 doi: 10.1002/2015JD

  6. Comparison of satellite reflectance algorithms for estimating ...

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

  7. Comparing near-earth and satellite remote sensing based phenophase estimates: an analysis using multiple webcams and MODIS (Invited)

    Science.gov (United States)

    Hufkens, K.; Richardson, A. D.; Migliavacca, M.; Frolking, S. E.; Braswell, B. H.; Milliman, T.; Friedl, M. A.

    2010-12-01

    In recent years several studies have used digital cameras and webcams to monitor green leaf phenology. Such "near-surface" remote sensing has been shown to be a cost effective means of accurately capturing phenology. Specifically, it allows for accurate tracking of intra- and inter-annual phenological dynamics at high temporal frequency and over broad spatial scales compared to visual observations or tower-based fAPAR and broadband NDVI measurements. Near surface remote sensing measurements therefore show promise for bridging the gap between traditional in-situ measurements of phenology and satellite remote sensing data. For this work, we examined the relationship between phenophase estimates derived from satellite remote sensing (MODIS) and near-earth remote sensing derived from webcams for a select set of sites with high-quality webcam data. A logistic model was used to characterize phenophases for both the webcam and MODIS data. We documented model fit accuracy, phenophase estimates, and model biases for both data sources. Our results show that different vegetation indices (VI's) derived from MODIS produce significantly different phenophase estimates compared to corresponding estimates derived from webcam data. Different VI's showed markedly different radiometric properties, and as a result, influenced phenophase estimates. The study shows that phenophase estimates are not only highly dependent on the algorithm used but also depend on the VI used by the phenology retrieval algorithm. These results highlight the need for a better understanding of how near-earth and satellite remote data relate to eco-physiological and canopy changes during different parts of the growing season.

  8. Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

    Directory of Open Access Journals (Sweden)

    Giancarmine Fasano

    2013-09-01

    Full Text Available An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

  9. Using satellite-based evapotranspiration estimates to improve the structure of a simple conceptual rainfall-runoff model

    Science.gov (United States)

    Roy, Tirthankar; Gupta, Hoshin V.; Serrat-Capdevila, Aleix; Valdes, Juan B.

    2017-02-01

    Daily, quasi-global (50° N-S and 180° W-E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.

  10. Modeling of groundwater draft based on satellite-derived crop acreage estimation over an arid region of northwest India

    Science.gov (United States)

    Bhadra, Bidyut Kumar; Kumar, Sanjay; Paliwal, Rakesh; Jeyaseelan, A. T.

    2016-11-01

    Over-exploitation of groundwater for agricultural crops puts stress on the sustainability of natural resources in the arid region of Rajasthan state, India. Hydrogeological study of groundwater levels of the study area during the pre-monsoon (May to June), post-monsoon (October to November) and post-irrigation (February to March) seasons of 2004-2005 to 2011-2012 shows a steady decline of groundwater levels at the rate of 1.28-1.68 m/year, mainly due to excessive groundwater draft for irrigation. Due to the low density of the groundwater observation-well network in the study area, assessment of groundwater draft, and thus groundwater resource management, becomes a difficult task. To overcome the situation, a linear groundwater draft model (LGDM) has been developed based on the empirical relationship between satellite-derived crop acreage and the observed groundwater draft for the year 2003-2004. The model has been validated for a decade, during three year-long intervals (2005-2006, 2008-2009 and 2011-2012) using groundwater draft, estimated through a discharge factor method. Further, the estimated draft was validated through observed pumping data from random sampled villages (2011-2012). The results suggest that the developed LGDM model provides a good alternative to the estimation of groundwater draft based on satellite-based crop area in the absence of groundwater observation wells in arid regions of northwest India.

  11. Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection

    Directory of Open Access Journals (Sweden)

    Sanggyun Lee

    2016-08-01

    Full Text Available Satellite altimeters have been used to monitor Arctic sea ice thickness since the early 2000s. In order to estimate sea ice thickness from satellite altimeter data, leads (i.e., cracks between ice floes should first be identified for the calculation of sea ice freeboard. In this study, we proposed novel approaches for lead detection using two machine learning algorithms: decision trees and random forest. CryoSat-2 satellite data collected in March and April of 2011–2014 over the Arctic region were used to extract waveform parameters that show the characteristics of leads, ice floes and ocean, including stack standard deviation, stack skewness, stack kurtosis, pulse peakiness and backscatter sigma-0. The parameters were used to identify leads in the machine learning models. Results show that the proposed approaches, with overall accuracy >90%, produced much better performance than existing lead detection methods based on simple thresholding approaches. Sea ice thickness estimated based on the machine learning-detected leads was compared to the averaged Airborne Electromagnetic (AEM-bird data collected over two days during the CryoSat Validation experiment (CryoVex field campaign in April 2011. This comparison showed that the proposed machine learning methods had better performance (up to r = 0.83 and Root Mean Square Error (RMSE = 0.29 m compared to thickness estimation based on existing lead detection methods (RMSE = 0.86–0.93 m. Sea ice thickness based on the machine learning approaches showed a consistent decline from 2011–2013 and rebounded in 2014.

  12. Statistical theory for estimating sampling errors of regional radiation averages based on satellite measurements

    Science.gov (United States)

    Smith, G. L.; Bess, T. D.; Minnis, P.

    1983-01-01

    The processes which determine the weather and climate are driven by the radiation received by the earth and the radiation subsequently emitted. A knowledge of the absorbed and emitted components of radiation is thus fundamental for the study of these processes. In connection with the desire to improve the quality of long-range forecasting, NASA is developing the Earth Radiation Budget Experiment (ERBE), consisting of a three-channel scanning radiometer and a package of nonscanning radiometers. A set of these instruments is to be flown on both the NOAA-F and NOAA-G spacecraft, in sun-synchronous orbits, and on an Earth Radiation Budget Satellite. The purpose of the scanning radiometer is to obtain measurements from which the average reflected solar radiant exitance and the average earth-emitted radiant exitance at a reference level can be established. The estimate of regional average exitance obtained will not exactly equal the true value of the regional average exitance, but will differ due to spatial sampling. A method is presented for evaluating this spatial sampling error.

  13. Carbon export fluxes in the Southern Ocean: results from inverse modeling and comparison with satellite-based estimates

    Science.gov (United States)

    Schlitzer, Reiner

    The use of dissolved nutrients and carbon for photosynthesis in the euphotic zone and the subsequent downward transport of particulate and dissolved organic material strongly affect carbon concentrations in surface water and thus the air-sea exchange of CO 2. Efforts to quantify the downward carbon flux for the whole ocean or on basin-scales are hampered by the sparseness of direct productivity or flux measurements. Here, a global ocean circulation, biogeochemical model is used to determine rates of export production and vertical carbon fluxes in the Southern Ocean. The model exploits the existing large sets of hydrographic, oxygen, nutrient and carbon data that contain information on the underlying biogeochemical processes. The model is fitted to the data by systematically varying circulation, air-sea fluxes, production, and remineralization rates simultaneously. Use of the adjoint method yields model property simulations that are in very good agreement with measurements. In the model, the total integrated export flux of particulate organic matter necessary for the realistic reproduction of nutrient data is significantly larger than export estimates derived from primary productivity maps. Of the 10,000 TgC yr -1(10 GtC yr -1) required globally, the Southern Ocean south of 30°S contributes about 3000 TgC yr -1 (33%), most of it occurring in a zonal belt along the Antarctic Circumpolar Current and in the Peru, Chile and Namibia coastal upwelling regions. The export flux of POC for the area south of 50°S amounts to 1000±210 TgC yr -1, and the particle flux in 1000 m for the same area is 115±20 TgC yr -1. Unlike for the global ocean, the contribution of the downward flux of dissolved organic carbon is significant in the Southern Ocean in the top 500 m of the water column. Comparison with satellite-based productivity estimates (CZCS and SeaWiFS) shows a relatively good agreement over most of the ocean except for the Southern Ocean south of 50°S, where the model

  14. Regional Bias of Satellite Precipitation Estimates

    Science.gov (United States)

    Modrick, T. M.; Georgakakos, K. P.; Spencer, C. R.

    2012-12-01

    Satellite-based estimates of precipitation have improved the spatial availability of precipitation data particularly for regions with limited gauge networks due to limited accessibility or infrastructure. Understanding the quality and reliability of satellite precipitation estimates is important, especially when the estimates are utilitized for real-time hydrologic forecasting and for fast-responding phenomena. In partnership with the World Meteorological Organization (WMO), the U.S. Agency of International Development (USAID) and the National Ocean and Atmospheric Administration (NOAA), the Hydrologic Research Center has begun implementation of real-time flash flood warning systems for diverse regions around the world. As part of this effort, bias characteristics of satellite precipitation have been examined in these various regions, such includes portions of Southeastern Asia, Southeastern Europe, the Middle East, Central America, and the southern half of the African continent. The work has focused on the Global Hydro-Estimator (GHE) precipitation product from NOAA/NESDIS. These real-time systems utilize the GHE given low latency times of this product. This presentation focuses on the characterization of precipitation bias as compared to in-situ gauge records, and the regional variations or similarities. Additional analysis is currently underway considering regional bias for other satellite precipitation products (e.g., CMORPH) for comparison with the GHE results.

  15. Satellite-based estimates of light-use efficiency in a subtropical mangrove forest equipped with CO2 eddy covariance

    Directory of Open Access Journals (Sweden)

    D. O. Fuller

    2012-11-01

    Full Text Available Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based carbon dioxide eddy covariance (EC systems are installed in only a few mangrove forests worldwide and the longest EC record from the Florida Everglades contains less than 9 yr of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger-scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE and we present the first-ever tower-based estimates of mangrove forest RE derived from night-time CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt increases in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and

  16. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

    Directory of Open Access Journals (Sweden)

    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  17. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    Science.gov (United States)

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM2.5 is a promising way to fill the areas that are not covered by ground PM2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R(2) = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM2.5 estimates.

  18. Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations

    Directory of Open Access Journals (Sweden)

    Samuel A. Andam‑Akorful

    2013-07-01

    Full Text Available The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM, evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC, and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E. This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

  19. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

  20. Estimating Particulate Matter using satellite based aerosol optical depth and meteorological variables in Malaysia

    Science.gov (United States)

    Kamarul Zaman, Nurul Amalin Fatihah; Kanniah, Kasturi Devi; Kaskaoutis, Dimitris G.

    2017-09-01

    The insufficient number of ground-based stations for measuring Particulate Matter training are performed via comparison with measured PM10 at 29 stations over Malaysia and reveal that the ANN provides slightly higher accuracy with R2 = 0.71 and RMSE = 11.61 μg m- 3 compared to the MLR method (R2 = 0.66 and RMSE = 12.39 μg m- 3). Stepwise regression analysis performed on the MLR method reveals that the MODIS AOD550 is the most important parameter for PM10 estimations (R2 = 0.59 and RMSE = 13.61 μg m- 3); however, the inclusion of the meteorological parameters in the MLR increases the accuracy of the retrievals (R2 = 0.66, RMSE = 12.39 μg m- 3). The estimated PM10 concentrations are finally validated against surface measurements at 16 stations resulting in similar performance from the ANN model (R2 = 0.58, RMSE = 10.16 μg m- 3) and MLR technique (R2 = 0.56, RMSE = 10.58 μg m- 3). The significant accuracy that has been attained in PM10 estimations from space allows us to assess the pollution levels in Malaysia and map the PM10 distribution at large spatial and temporal scales. Supplementary Figure 2: Seasonal-mean Terra-MODIS AOD550 values at 10 x 10 km over the 45 air-pollution monitoring stations in Malaysia during 2007 - 2011 for (a) dry season (June - September), (b) wet season (November - March), (c) April - May and (d) October.

  1. Multi-annual changes of NOx emissions in megacity regions: nonlinear trend analysis of satellite measurement based estimates

    Directory of Open Access Journals (Sweden)

    J. P. Burrows

    2010-09-01

    Full Text Available Hazardous impact of air pollutant emissions from megacities on atmospheric composition on regional and global scales is currently an important issue in atmospheric research. However, the quantification of emissions and related effects is frequently a difficult task, especially in the case of developing countries, due to the lack of reliable data and information. This study examines possibilities to retrieve multi-annual NOx emissions changes in megacity regions from satellite measurements of nitrogen dioxide and to quantify them in terms of linear and nonlinear trends. By combining the retrievals of the GOME and SCIAMACHY satellite instrument data with simulations performed by the CHIMERE chemistry transport model, we obtain the time series of NOx emission estimates for the 12 largest urban agglomerations in Europe and the Middle East in the period from 1996 to 2008. We employ then a novel method allowing estimation of a nonlinear trend in a noisy time series of an observed variable. The method is based on the probabilistic approach and the use of artificial neural networks; it does not involve any quantitative a priori assumptions. As a result, statistically significant nonlinearities in the estimated NOx emission trends are detected in 5 megacities (Bagdad, Madrid, Milan, Moscow and Paris. Statistically significant upward linear trends are detected in Istanbul and Tehran, while downward linear trends are revealed in Berlin, London and the Ruhr agglomeration. The presence of nonlinearities in NOx emission changes in Milan, Paris and Madrid is confirmed by comparison of simulated NOx concentrations with independent air quality monitoring data. A good quantitative agreement between the linear trends in the simulated and measured near surface NOx concentrations is found in London.

  2. An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations.

    Science.gov (United States)

    Feng, Fei; Li, Xianglan; Yao, Yunjun; Liang, Shunlin; Chen, Jiquan; Zhao, Xiang; Jia, Kun; Pintér, Krisztina; McCaughey, J Harry

    2016-01-01

    Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.

  3. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

    2014-04-01

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m-2 yr-1 and total NPP in the range of 318–490 Tg C yr-1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m-2 yr-1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m-2 yr-1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  4. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    Science.gov (United States)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

    2014-01-01

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  5. A biophysical process based approach for estimating net primary production using satellite and ground observations

    Science.gov (United States)

    Choudhury, Bhaskar J.

    An approach is presented for calculating interannual variation of net primary production (C) of terrestrial plant communities at regional scale using satellite and ground measurements. C has been calculated as the difference of gross photosynthesis (A g) and respiration (R), recognizing that different biophysical factors exert major control on these two processes. A g has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R g and R m. The R m has been determined from nitrogen content of plant tissue per unit ground area, while R g has been obtained as a fraction of the difference of A g and R m. Model parameters have not been determined by matching the calculated fluxes against observations at any location. Results are presented for cultivated and temperate deciduous forest areas over North America for five consecutive years (1986-1990) and compared with observations.

  6. Vision-Based 3D Motion Estimation for On-Orbit Proximity Satellite Tracking and Navigation

    Science.gov (United States)

    2015-06-01

    Network .....................................................................................58 3. Telemetry Computer...screenshot of the telemetry software and the SSH terminals. ...........61 Figure 25. View of the VICON cameras above the granite flat floor of the FSS...point-wise kinematic models. The pose of the 3D structure is then estimated using a dual quaternion method [19]. The robustness and validity of this

  7. Tree canopy light interception estimates in almond and a walnut orchards using ground, low flying aircraft, and satellite based methods to improve irrigation scheduling programs.

    Science.gov (United States)

    Rosecrance, R. C.; Johnson, L.; Soderstrom, D.

    2016-12-01

    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  8. Tree Canopy Light Interception Estimates in Almond and a Walnut Orchards Using Ground, Low Flying Aircraft, and Satellite Based Methods to Improve Irrigation Scheduling Programs

    Science.gov (United States)

    Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic

    2016-01-01

    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  9. Satellite based classification (haze, fog) and affected area estimation over Indo - Pak Sub-Continent

    Science.gov (United States)

    Ghauri, Badar; Zafar, Sumaira

    2016-07-01

    Northern Pakistan and bordering Indian Punjab experience intense smog and fog during fall and winters. Environmentalists have been raising their voices over the situation and demanded control over regional emissions to save the livelihood of millions of dwellers whose trade, commerce and agriculture is at stake because of long smog/ fog spells.. This paper estimates the area affected by haze, smog and fog during 2006- 2010. MODIS (geo-referenced MODIS subsets India1, 2 &3) of the area in Pakistan and India from 2006 to 2010 for the period October to February) were analyzed using state of the art software ENVI 4.2 and ArcGIS 10.2. This process resulted in area belonging to each class that is; haze, smog and fog. On the basis of density, haze and fog cover was determined. Variations in fog cover, its density and identification of location of fog initiation process were also determined using near real time (30 minutes) METEOSAT-7 IODC data where actually fog formation started and then extended to the area of favorable conditions. Haze has been noticed to intensify due to massive burning of agricultural waste (rice husk) in India and Pakistan towards the end of October each year. MODIS thermal anomalies/fire data (MYD 14) were also used to verify this activity on the ground, which results in hazy conditions at regional level during fall months. Haze-affected area during 2006 to 2010 in Pakistan ranged from 155,000 Km2 to 354,000 Km2 and in India it ranged from 333,000 Km2 to 846,000 Km2. Similarly winter fog cover during this period in Pakistan varied from 136,000 Km2 to 381,000 Km2 and in India it was estimated at 327,000 Km2 to 566,000 Km2. This phenomenon was more prominent in India than in Pakistan where and fog cover was at least twice than that was observed in Pakistan. It has been noted that area covered by fog, smog and haze doubled during the study period in the region. Atmospheric dimming during autumn/ fall also reduces the mixing height leading to greater

  10. Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

    Science.gov (United States)

    Wang, Lei; Sun, Litao; Shrestha, Maheswor; Li, Xiuping; Liu, Wenbin; Zhou, Jing; Yang, Kun; Lu, Hui; Chen, Deliang

    2016-10-01

    In distributed hydrological modeling, surface air temperature (Tair) is of great importance in simulating cold region processes, while the near-surface-air-temperature lapse rate (NLR) is crucial to prepare Tair (when interpolating Tair from site observations to model grids). In this study, a distributed biosphere hydrological model with improved snow physics (WEB-DHM-S) was rigorously evaluated in a typical cold, large river basin (e.g., the upper Yellow River basin), given a mean monthly NLRs. Based on the validated model, we have examined the influence of the NLR on the simulated snow processes and streamflows. We found that the NLR has a large effect on the simulated streamflows, with a maximum difference of greater than 24% among the various scenarios for NLRs considered. To supplement the insufficient number of monitoring sites for near-surface-air-temperature at developing/undeveloped mountain regions, the nighttime Moderate Resolution Imaging Spectroradiometer land surface temperature is used as an alternative to derive the approximate NLR at a finer spatial scale (e.g., at different elevation bands, different land covers, different aspects, and different snow conditions). Using satellite-based estimation of NLR, the modeling of snow processes has been greatly refined. Results show that both the determination of rainfall/snowfall and the snowpack process were significantly improved, contributing to a reduced summer evapotranspiration and thus an improved streamflow simulation.

  11. Fast converging with high accuracy estimates of satellite attitude and orbit based on magnetometer augmented with gyro, star sensor and GPS via extended Kalman filter

    Directory of Open Access Journals (Sweden)

    Tamer Mekky Ahmed Habib

    2011-12-01

    Full Text Available The primary goal of this work is to extend the work done in, Tamer (2009, to provide high accuracy satellite attitude and orbit estimates needed for imaging purposes and also before execution of spacecraft orbital maneuvers for the next Egyptian scientific satellite. The problem of coarse satellite attitude and orbit estimation based on magnetometer measurements has been treated in the literature. The current research expands the field of application from coarse and slow converging estimates to accurate and fast converging attitude and orbit estimates within 0.1°, and 10 m for attitude angles and spacecraft location respectively (1-σ. The magnetometer is used for both spacecraft attitude and orbit estimation, aided with gyro to provide angular velocity measurements, star sensor to provide attitude quaternion, and GPS receiver to provide spacecraft location. The spacecraft under consideration is subject to solar radiation pressure forces and moments, aerodynamics forces and moments, earth’s oblateness till the fourth order (i.e. J4, gravity gradient moments, and residual magnetic dipole moments. The estimation algorithm developed is powerful enough to converge quickly (actually within 10 s despite very large initial estimation errors with sufficiently high accuracy estimates.

  12. Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

    DEFF Research Database (Denmark)

    Diouf, Abdoul Aziz; Hiernaux, Pierre; Brandt, Martin Stefan;

    2016-01-01

    Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosyn......Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed...... evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483...

  13. Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

    Directory of Open Access Journals (Sweden)

    Julien Morel

    2014-07-01

    Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

  14. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  15. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  16. Estimation of snowpack matching ground-truth data and MODIS satellite-based observations by using regression kriging

    Science.gov (United States)

    Juan Collados-Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David

    2016-04-01

    The estimation of Snow Water Equivalent (SWE) is essential for an appropriate assessment of the available water resources in Alpine catchment. The hydrologic regime in these areas is dominated by the storage of water in the snowpack, which is discharged to rivers throughout the melt season. An accurate estimation of the resources will be necessary for an appropriate analysis of the system operation alternatives using basin scale management models. In order to obtain an appropriate estimation of the SWE we need to know the spatial distribution snowpack and snow density within the Snow Cover Area (SCA). Data for these snow variables can be extracted from in-situ point measurements and air-borne/space-borne remote sensing observations. Different interpolation and simulation techniques have been employed for the estimation of the cited variables. In this paper we propose to estimate snowpack from a reduced number of ground-truth data (1 or 2 campaigns per year with 23 observation point from 2000-2014) and MODIS satellite-based observations in the Sierra Nevada Mountain (Southern Spain). Regression based methodologies has been used to study snowpack distribution using different kind of explicative variables: geographic, topographic, climatic. 40 explicative variables were considered: the longitude, latitude, altitude, slope, eastness, northness, radiation, maximum upwind slope and some mathematical transformation of each of them [Ln(v), (v)^-1; (v)^2; (v)^0.5). Eight different structure of regression models have been tested (combining 1, 2, 3 or 4 explicative variables). Y=B0+B1Xi (1); Y=B0+B1XiXj (2); Y=B0+B1Xi+B2Xj (3); Y=B0+B1Xi+B2XjXl (4); Y=B0+B1XiXk+B2XjXl (5); Y=B0+B1Xi+B2Xj+B3Xl (6); Y=B0+B1Xi+B2Xj+B3XlXk (7); Y=B0+B1Xi+B2Xj+B3Xl+B4Xk (8). Where: Y is the snow depth; (Xi, Xj, Xl, Xk) are the prediction variables (any of the 40 variables); (B0, B1, B2, B3) are the coefficients to be estimated. The ground data are employed to calibrate the multiple regressions. In

  17. An enhanced algorithm to estimate BDS satellite's differential code biases

    Science.gov (United States)

    Shi, Chuang; Fan, Lei; Li, Min; Liu, Zhizhao; Gu, Shengfeng; Zhong, Shiming; Song, Weiwei

    2016-02-01

    This paper proposes an enhanced algorithm to estimate the differential code biases (DCB) on three frequencies of the BeiDou Navigation Satellite System (BDS) satellites. By forming ionospheric observables derived from uncombined precise point positioning and geometry-free linear combination of phase-smoothed range, satellite DCBs are determined together with ionospheric delay that is modeled at each individual station. Specifically, the DCB and ionospheric delay are estimated in a weighted least-squares estimator by considering the precision of ionospheric observables, and a misclosure constraint for different types of satellite DCBs is introduced. This algorithm was tested by GNSS data collected in November and December 2013 from 29 stations of Multi-GNSS Experiment (MGEX) and BeiDou Experimental Tracking Stations. Results show that the proposed algorithm is able to precisely estimate BDS satellite DCBs, where the mean value of day-to-day scattering is about 0.19 ns and the RMS of the difference with respect to MGEX DCB products is about 0.24 ns. In order to make comparison, an existing algorithm based on IGG: Institute of Geodesy and Geophysics, China (IGGDCB), is also used to process the same dataset. Results show that, the DCB difference between results from the enhanced algorithm and the DCB products from Center for Orbit Determination in Europe (CODE) and MGEX is reduced in average by 46 % for GPS satellites and 14 % for BDS satellites, when compared with DCB difference between the results of IGGDCB algorithm and the DCB products from CODE and MGEX. In addition, we find the day-to-day scattering of BDS IGSO satellites is obviously lower than that of GEO and MEO satellites, and a significant bias exists in daily DCB values of GEO satellites comparing with MGEX DCB product. This proposed algorithm also provides a new approach to estimate the satellite DCBs of multiple GNSS systems.

  18. Understanding satellite-based monthly-to-seasonal reservoir outflow estimation as a function of hydrologic controls

    Science.gov (United States)

    Bonnema, Matthew; Sikder, Safat; Miao, Yabin; Chen, Xiaodong; Hossain, Faisal; Ara Pervin, Ismat; Mahbubur Rahman, S. M.; Lee, Hyongki

    2016-05-01

    Growing population and increased demand for water is causing an increase in dam and reservoir construction in developing nations. When rivers cross international boundaries, the downstream stakeholders often have little knowledge of upstream reservoir operation practices. Satellite remote sensing in the form of radar altimetry and multisensor precipitation products can be used as a practical way to provide downstream stakeholders with the fundamentally elusive upstream information on reservoir outflow needed to make important and proactive water management decisions. This study uses a mass balance approach of three hydrologic controls to estimate reservoir outflow from satellite data at monthly and annual time scales: precipitation-induced inflow, evaporation, and reservoir storage change. Furthermore, this study explores the importance of each of these hydrologic controls to the accuracy of outflow estimation. The hydrologic controls found to be unimportant could potentially be neglected from similar future studies. Two reservoirs were examined in contrasting regions of the world, the Hungry Horse Reservoir in a mountainous region in northwest U.S. and the Kaptai Reservoir in a low-lying, forested region of Bangladesh. It was found that this mass balance method estimated the annual outflow of both reservoirs with reasonable skill. The estimation of monthly outflow from both reservoirs was however less accurate. The Kaptai basin exhibited a shift in basin behavior resulting in variable accuracy across the 9 year study period. Monthly outflow estimation from Hungry Horse Reservoir was compounded by snow accumulation and melt processes, reflected by relatively low accuracy in summer and fall, when snow processes control runoff. Furthermore, it was found that the important hydrologic controls for reservoir outflow estimation at the monthly time scale differs between the two reservoirs, with precipitation-induced inflow being the most important control for the Kaptai

  19. Estimating Soil Moisture from Satellite Microwave Observations

    Science.gov (United States)

    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

  20. Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2009-01-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate NDVI, EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modeling within a water limited environment. Results show a strong correlation between vegetation indices and gross primary production (GPP, demonstrating the significance of vegetation indices for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modeling in similar semi-arid ecosystems is limited.

  1. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  2. Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

    Science.gov (United States)

    Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

    2015-12-01

    A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each

  3. AQA-PM: Extension of the Air-Quality Model For Austria with Satellite based Particulate Matter Estimates

    Science.gov (United States)

    Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Triebnig, Gerhard; Flandorfer, Claudia

    2013-04-01

    Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. The Air Quality model for Austria (AQA) is operated at ZAMG in cooperation with the University of Natural Resources and Life Sciences in Vienna (BOKU) by order of the regional governments since 2005. AQA conducts daily forecasts of gaseous and particulate (PM10) air pollutants over Austria. In the frame of the project AQA-PM (funded by FFG), satellite measurements of the Aerosol Optical Thickness (AOT) and ground-based PM10-measurements are combined to highly-resolved initial fields using regression- and assimilation techniques. For the model simulations WRF/Chem is used with a resolution of 3 km over the alpine region. Interfaces have been developed to account for the different measurements as input data. The available local emission inventories provided by the different Austrian regional governments were harmonized and used for the model simulations. An episode in February 2010 is chosen for the model evaluation. During that month exceedances of PM10-thresholds occurred at many measurement stations of the Austrian network. Different model runs (only model/only ground stations assimilated/satellite and ground stations assimilated) are compared to the respective measurements. The goal of this project is to improve the PM10-forecasts for Austria with the integration of satellite based measurements and to provide a comprehensive product-platform.

  4. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    Science.gov (United States)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  5. Channel Estimation And Multiuser Detection In Asynchronous Satellite Communications

    CERN Document Server

    Chaouech, Helmi; 10.5121/ijwmn.2010.2411

    2010-01-01

    In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.

  6. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

    Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

  7. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    Science.gov (United States)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  8. Improved frequency and time of arrival estimation methods in search and rescue system based on MEO satellites

    Science.gov (United States)

    Lin, Mo; Li, Rui; Li, Jilin

    2007-11-01

    This paper deals with several key points including parameter estimation such as frequency of arrival (FOA), time of arrival (TOA) estimation algorithm and signal processing techniques in Medium-altitude Earth Orbit Local User Terminals (MEOLUT) based on Cospas-Sarsat Medium-altitude Earth Orbit Search and Rescue system (MEOSAR). Based on an analytical description of distress beacon, improved TOA and FOA estimation methods have been proposed. An improved FOA estimation method which integrates bi-FOA measurement, FFT method, Rife algorithm and Gaussian window is proposed to improve the accuracy of FOA estimation. In addition, TPD algorithm and signal correlation techniques are used to achieve a high performance of TOA estimation. Parameter estimation problems are solved by proposed FOA/TOA methods under quite poor Carrier-to-Noise (C/N0). A number of simulations are done to show the improvements. FOA and TOA estimation error are lower than 0.1Hz and 11μs respectively which is very high system requirement for MEOSAR system MEOLUT.

  9. Satellite based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, H. M.; Cheng, Y.; Pfister, G.; Carmichael, G. R.; Zhang, Q.; Streets, D. G.; Deeter, M. N.; Edwards, D. P.; Gille, J. C.; Worden, J.

    2012-12-01

    We present estimates of the reductions in CO and CO2 emissions resulting from the control measures on the Beijing transportation sector taken during the 2008 Beijing Olympics. This study used MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite measurements of near surface CO along with WRF Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008 to estimate changes in CO due to meteorology and emissions. Using fractional changes in the emissions inventory transportation sector along with a reported CO/CO2 emission ratio for Beijing vehicles, we find the corresponding reduction in CO2 emissions. We then compare this reduction to target CO2 emissions in the RCP (representative concentration pathway) scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report). Our result suggests that urban traffic reductions could play a significant role in meeting target cuts for global CO2 emissions, even for the most aggressive control scenario (RCP2.6).

  10. Satellite-based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, Helen M.; Cheng, Yafang; Pfister, Gabriele; Carmichael, Gregory R.; Zhang, Qiang; Streets, David G.; Deeter, Merritt; Edwards, David P.; Gille, John C.; Worden, John R.

    2012-07-01

    During the 2008 Olympics, the Chinese government made a significant effort to improve air quality in Beijing, including restrictions on traffic. Here we estimate the reductions in carbon monoxide (CO) and carbon dioxide (CO2) emissions resulting from the control measures on Beijing transportation. Using MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite observations of near-surface CO along with WRF-Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008, we estimate changes in CO due to meteorology and transportation sector emissions. Applying a reported CO/CO2 emission ratio for fossil fuels, we find the corresponding reduction in CO2, 60 ± 36 Gg[CO2]/day. As compared to emission scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report), this result suggests that urban traffic controls on the Beijing Olympics scale could play a significant role in meeting target reductions for global CO2 emissions.

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

    Science.gov (United States)

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

    2014-12-01

    accumulation and this increase can be efficiently estimated at a landscape scale using satellite data.

  12. Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio; Nauditt, Alexandra; Birkel, Christian; Verbist, Koen; Ribbe, Lars

    2017-03-01

    Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate - for the first time - the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7° S) and Central Chile (32.18-36.4° S), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere

  13. Measurement-based perturbation theory and differential equation parameter estimation for high-precision high-resolution reconstruction of the Earth's gravitational field from satellite tracking measurements

    CERN Document Server

    Xu, Peiliang

    2016-01-01

    The numerical integration method has been routinely used to produce global standard gravitational models from satellite tracking measurements of CHAMP/GRACE types. It is implemented by solving the differential equations of the partial derivatives of a satellite orbit with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical point of view, satellite gravimetry from satellite tracking is the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in satellite gravimetry and statistics, is groundless. We use three different methods to derive new local solutions to the Newton's nonlinear governing differential equations of motion with a nominal reference orbit. Bearing in mind that satellite orbits ...

  14. Sampling errors in rainfall estimates by multiple satellites

    Science.gov (United States)

    North, Gerald R.; Shen, Samuel S. P.; Upson, Robert

    1993-01-01

    This paper examines the sampling characteristics of combining data collected by several low-orbiting satellites attempting to estimate the space-time average of rain rates. The several satellites can have different orbital and swath-width parameters. The satellite overpasses are allowed to make partial coverage snapshots of the grid box with each overpass. Such partial visits are considered in an approximate way, letting each intersection area fraction of the grid box by a particular satellite swath be a random variable with mean and variance parameters computed from exact orbit calculations. The derivation procedure is based upon the spectral minimum mean-square error formalism introduced by North and Nakamoto. By using a simple parametric form for the spacetime spectral density, simple formulas are derived for a large number of examples, including the combination of the Tropical Rainfall Measuring Mission with an operational sun-synchronous orbiter. The approximations and results are discussed and directions for future research are summarized.

  15. Antarctic ice-mass balance 2003 to 2012: regional reanalysis of GRACE satellite gravimetry measurements with improved estimate of glacial-isostatic adjustment based on GPS uplift rates

    NARCIS (Netherlands)

    Sasgen, I.; Konrad, H.; Ivins, E.R.; van den Broeke, M.R.|info:eu-repo/dai/nl/073765643; Bamber, J.L.; Martinec, Z.; Klemann, V.

    2013-01-01

    We present regional-scale mass balances for 25 drainage basins of the Antarctic Ice Sheet (AIS) from satellite observations of the Gravity and Climate Experiment (GRACE) for time period January 2003 to September 2012. Satellite gravimetry estimates of the AIS mass balance are strongly influenced by

  16. Antarctic ice-mass balance 2003 to 2012: regional reanalysis of GRACE satellite gravimetry measurements with improved estimate of glacial-isostatic adjustment based on GPS uplift rates

    NARCIS (Netherlands)

    Sasgen, I.; Konrad, H.; Ivins, E.R.; van den Broeke, M.R.; Bamber, J.L.; Martinec, Z.; Klemann, V.

    2013-01-01

    We present regional-scale mass balances for 25 drainage basins of the Antarctic Ice Sheet (AIS) from satellite observations of the Gravity and Climate Experiment (GRACE) for time period January 2003 to September 2012. Satellite gravimetry estimates of the AIS mass balance are strongly influenced by

  17. SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

    Directory of Open Access Journals (Sweden)

    G. Snider

    2014-07-01

    Full Text Available Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5 at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD. We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of global regions, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by an order of magnitude. Initial measurements indicate that the AOD column to PM2.5 ratio is driven temporally primarily by the vertical profile of aerosol scattering; and spatially by a~ more complex interaction

  18. Real-Time Estimation of Satellite-Derived PM2.5 Based on a Semi-Physical Geographically Weighted Regression Model

    Science.gov (United States)

    Zhang, Tianhao; Liu, Gang; Zhu, Zhongmin; Gong, Wei; Ji, Yuxi; Huang, Yusi

    2016-01-01

    The real-time estimation of ambient particulate matter with diameter no greater than 2.5 μm (PM2.5) is currently quite limited in China. A semi-physical geographically weighted regression (GWR) model was adopted to estimate PM2.5 mass concentrations at national scale using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth product fused by the Dark Target (DT) and Deep Blue (DB) algorithms, combined with meteorological parameters. The fitting results could explain over 80% of the variability in the corresponding PM2.5 mass concentrations, and the estimation tends to overestimate when measurement is low and tends to underestimate when measurement is high. Based on World Health Organization standards, results indicate that most regions in China suffered severe PM2.5 pollution during winter. Seasonal average mass concentrations of PM2.5 predicted by the model indicate that residential regions, namely Jing-Jin-Ji Region and Central China, were faced with challenge from fine particles. Moreover, estimation deviation caused primarily by the spatially uneven distribution of monitoring sites and the changes of elevation in a relatively small region has been discussed. In summary, real-time PM2.5 was estimated effectively by the satellite-based semi-physical GWR model, and the results could provide reasonable references for assessing health impacts and offer guidance on air quality management in China. PMID:27706054

  19. DOA estimation for attitude determination on communication satellites

    Directory of Open Access Journals (Sweden)

    Yang Bin

    2014-06-01

    Full Text Available In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival (DOA estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system (GPS attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit (LEO satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio (SNR with DOA estimation.

  20. DOA estimation for attitude determination on communication satellites

    Institute of Scientific and Technical Information of China (English)

    Yang Bin; He Feng; Jin Jin; Xiong Huagang; Xu Guanghan

    2014-01-01

    In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival (DOA) estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system (GPS) attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit (LEO) satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio (SNR) with DOA estimation.

  1. Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

    Science.gov (United States)

    Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

    2015-05-01

    Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  2. Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations: NE Pacific Aerosol-Cloud Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Painemal, David [Science Systems and Applications, Inc., Hampton Virginia USA; NASA Langley Research Center, Hampton Virginia USA; Chiu, J. -Y. Christine [Department of Meteorology, University of Reading, Reading UK; Minnis, Patrick [NASA Langley Research Center, Hampton Virginia USA; Yost, Christopher [Science Systems and Applications, Inc., Hampton Virginia USA; Zhou, Xiaoli [Department of Atmospheric and Oceanic Sciences, McGill University, Montreal Quebec Canada; Cadeddu, Maria [Environmental Science Division, Argonne National Laboratory, Lemont Illinois USA; Eloranta, Edwin [Space Science and Engineering Center, University of Wisconsin-Madison, Madison Wisconsin USA; Lewis, Ernie R. [Brookhaven National Laboratory, Upton New York USA; Ferrare, Richard [NASA Langley Research Center, Hampton Virginia USA; Kollias, Pavlos [School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook New York USA

    2017-02-27

    Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship-based retrievals of cloud optical depth (τ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration Nd and compute a cloud-aerosol interaction (ACI) metric defined as ACICCN = ∂ ln(Nd)/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN0.4) and 0.3% (CCN0.3) supersaturation. Analysis of CCN0.4, accumulation mode aerosol concentration (Na), and extinction coefficient (σext) indicates that Na and σext can be used as CCN0.4 proxies for estimating ACI. ACICCN derived from 10 min averaged Nd and CCN0.4 and CCN0.3, and CCN0.4 regressions using Na and σext, produce high ACICCN: near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in Nd. ACICCN computed in deep boundary layers was small (ACICCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate-resolution Imaging Spectroradiometer and GOES-15 data were compared against ship-based retrievals and further analyzed to compute a satellite-based ACICCN. Satellite data correlated well with their ship-based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite Nd and ship-based CCN0.4 and Na yielded a maximum ACICCN = 0.88–0.92, a value slightly less than the ship-based ACICCN, but still consistent with aircraft-based studies in the eastern Pacific.

  3. Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin

    Science.gov (United States)

    Gao, Zhen; Long, Di; Tang, Guoqiang; Zeng, Chao; Huang, Jiesheng; Hong, Yang

    2017-07-01

    Flood frequency analysis (FFA) is critical for water resources engineering projects, particularly the design of hydraulic structures such as dams and reservoirs. However, it is often difficult to implement FFA in ungauged or poorly gauged basins because of the lack of consistent and long-term records of streamflow observations. The objective of this study was to evaluate the utility of satellite-based precipitation estimates for performing FFA in two presumably ungauged tributaries, the Jialing and Tuojiang Rivers, of the upper Yangtze River. Annual peak flow series were simulated using the Coupled Routing and Excess STorage (CREST) hydrologic model. Flood frequency was estimated by fitting the Pearson type III distribution of both observed and modeled streamflow with historic floods. Comparison of satellite-based precipitation products with a ground-based daily precipitation dataset for the period 2002-2014 reveals that 3B42V7 outperformed 3B42RT. The 3B42V7 product also shows consistent reliability in streamflow simulation and FFA (e.g., relative errors -20%-5% in the Jialing River). The results also indicate that complex terrain, drainage area, and reservoir construction are important factors that impact hydrologic model performance. The larger basin (156,736 km2) is more likely to produce satisfactory results than the small basin (19,613 km2) under similar circumstances (e.g., Jialing/Tuojiang calibrated by 3B42V7 for the calibration period: NSCE = 0.71/0.56). Using the same calibrated parameter sets from the entire Jialing River basin, the 3B42V7/3B42RT-driven hydrologic model performs better for two tributaries of the Jialing River (e.g., for the calibration period, NSCE = 0.71/0.60 in the Qujiang River basin and 0.54/0.38 in the Fujiang River basin) than for the upper mainstem of the Jialing River (NSCE = 0.34/0.32), which has more cascaded reservoirs with all these tributaries treated as ungauged basins for model validation. Overall, this study underscores

  4. The relationship between cloud condensation nuclei (CCN concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates

    Directory of Open Access Journals (Sweden)

    Y. Shinozuka

    2015-01-01

    Full Text Available We examine the relationship between the number concentration of boundary-layer cloud condensation nuclei (CCN and light extinction to investigate underlying aerosol processes and satellite-based CCN estimates. Regression applied to a variety of airborne and ground-based measurements identifies the CCN (cm−3 at 0.4 ± 0.1% supersaturation with 100.3α +1.3 σ0.75 where σ (M m−1 is the 500 nm extinction coefficient by dried particles and α is the Angstrom exponent. The deviation of one kilometer horizontal average data from this approximation is typically within a factor of 2.0. ∂ log CCN/∂ log σ is less than unity because, among other explanations, aerosol growth processes generally make particles scatter more light without increasing their number. This, barring extensive data aggregation and special meteorology-aerosol connections, associates doubling of aerosol optical depth with less than doubling of CCN, contrary to common assumptions in satellite-based analysis of aerosol-cloud interactions.

  5. Estimation of satellite antenna phase center offsets for Galileo

    Science.gov (United States)

    Steigenberger, P.; Fritsche, M.; Dach, R.; Schmid, R.; Montenbruck, O.; Uhlemann, M.; Prange, L.

    2016-08-01

    Satellite antenna phase center offsets for the Galileo In-Orbit Validation (IOV) and Full Operational Capability (FOC) satellites are estimated by two different analysis centers based on tracking data of a global GNSS network. The mean x- and y-offsets could be determined with a precision of a few centimeters. However, daily estimates of the x-offsets of the IOV satellites show pronounced systematic effects with a peak-to-peak amplitude of up to 70 cm that depend on the orbit model and the elevation of the Sun above the orbital plane. For the IOV y-offsets, no dependence on the orbit model exists but the scatter strongly depends on the elevation of the Sun above the orbital plane. In general, these systematic effects are significantly smaller for the FOC satellites. The z-offsets of the two analysis centers agree within the 10-15 cm level, and the time series do not show systematic effects. The application of an averaged Galileo satellite antenna model obtained from the two solutions results in a reduction of orbit day boundary discontinuities by up to one third—even if an independent software package is used.

  6. A new estimate of the global 3D geostrophic ocean circulation based on satellite data and in-situ measurements

    Science.gov (United States)

    Mulet, S.; Rio, M.-H.; Mignot, A.; Guinehut, S.; Morrow, R.

    2012-11-01

    A new estimate of the Global Ocean 3D geostrophic circulation from the surface down to 1500 m depth (Surcouf3D) has been computed for the 1993-2008 period using an observation-based approach that combines altimetry with temperature and salinity through the thermal wind equation. The validity of this simple approach was tested using a consistent dataset from a model reanalysis. Away from the boundary layers, errors are less than 10% in most places, which indicate that the thermal wind equation is a robust approximation to reconstruct the 3D oceanic circulation in the ocean interior. The Surcouf3D current field was validated in the Atlantic Ocean against in-situ observations. We considered the ANDRO current velocities deduced at 1000 m depth from Argo float displacements as well as velocity measurements at 26.5°N from the RAPID-MOCHA current meter array. The Surcouf3D currents show similar skill to the 3D velocities from the GLORYS Mercator Ocean reanalysis in reproducing the amplitude and variability of the ANDRO currents. In the upper 1000 m, high correlations are also found with in-situ velocities measured by the RAPID-MOCHA current meters. The Surcouf3D current field was then used to compute estimates of the Atlantic Meridional Overturning Circulation (AMOC) through the 25°N section, showing good comparisons with hydrographic sections from 1998 and 2004. Monthly averaged AMOC time series are also consistent with the RAPID-MOCHA array and with the GLORYS Mercator Ocean reanalysis over the April 2004-September 2007 period. Finally a 15 years long time series of monthly estimates of the AMOC was computed. The AMOC strength has a mean value of 16 Sv with an annual (resp. monthly) standard deviation of 2.4 Sv (resp. 7.1 Sv) over the 1993-2008 period. The time series, characterized by a strong variability, shows no significant trend.

  7. Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

    Science.gov (United States)

    Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

    2002-01-01

    The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

  8. Development of an improved aerosol product over the Indian subcontinent: Blending model, satellite, and ground-based estimates

    Science.gov (United States)

    Singh, Randhir; Singh, Charu; Ojha, Satya P.; Kumar, A. Senthil; Kumar, A. S. Kiran

    2017-01-01

    A comprehensive assessment of the aerosol optical depth (AOD) at 550 nm from European Centre for Medium-Range Weather Forecasts (ECMWF), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer (MISR) has been performed with respect to the Aerosol Robotic Network (AERONET) measurements at 35 locations over the Indian subcontinent. For all of the stations, the mean relative errors for the collocated ECMWF, MODIS, and MISR AOD are 46.15%, 41.81%, and 39.98%, respectively. Compared with AERONET, ECMWF estimates suffer from a negative bias, whereas MODIS and MISR estimates suffer from a positive bias. The correlation of ECMWF, MODIS, and MISR AOD with AERONET observation is 0.73, 0.80, and 0.78, respectively. Analysis shows that approximately 52.12% of ECMWF, 60.51% of MODIS, and 62.63% of MISR AOD fall within the error envelopes (± 0.05 ± 0.15AODAERONET) of validation data from AERONET. This analysis indicates that both modeled and space-based AOD measurements have large discrepancies over the Indian subcontinent. Due to the aerosol's significant role in altering the Earth radiation budget, there is an urgent need to develop an AOD product with reduced error. Therefore, a new AOD product at 550 nm has been developed using an optimum interpolation (OI) technique. For this purpose, a model-derived AOD from ECMWF, remotely sensed AOD from MODIS, MISR, and in situ measured AOD from AERONET have been blended using the OI technique. A new product has been generated for 13 years (2003 to 2015) at 0.25° by 0.25° latitude/longitude and daily temporal resolution over the Indian subcontinent. When compared with AERONET observations, the new product has a negligible bias, with a mean relative error of 12.31% and a correlation of 0.99.

  9. Velocity estimation of an airplane through a single satellite image

    Institute of Scientific and Technical Information of China (English)

    Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

    2012-01-01

    The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

  10. Single-source surface energy balance algorithms to estimate evapotranspiration from satellite-based remotely sensed data

    Science.gov (United States)

    Bhattarai, Nishan

    The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on

  11. Satellite images analysis for shadow detection and building height estimation

    Science.gov (United States)

    Liasis, Gregoris; Stavrou, Stavros

    2016-09-01

    Satellite images can provide valuable information about the presented urban landscape scenes to remote sensing and telecommunication applications. Obtaining information from satellite images is difficult since all the objects and their surroundings are presented with feature complexity. The shadows cast by buildings in urban scenes can be processed and used for estimating building heights. Thus, a robust and accurate building shadow detection process is important. Region-based active contour models can be used for satellite image segmentation. However, spectral heterogeneity that usually exists in satellite images and the feature similarity representing the shadow and several non-shadow regions makes building shadow detection challenging. In this work, a new automated method for delineating building shadows is proposed. Initially, spectral and spatial features of the satellite image are utilized for designing a custom filter to enhance shadows and reduce intensity heterogeneity. An effective iterative procedure using intensity differences is developed for tuning and subsequently selecting the most appropriate filter settings, able to highlight the building shadows. The response of the filter is then used for automatically estimating the radiometric property of the shadows. The customized filter and the radiometric feature are utilized to form an optimized active contour model where the contours are biased to delineate shadow regions. Post-processing morphological operations are also developed and applied for removing misleading artefacts. Finally, building heights are approximated using shadow length and the predefined or estimated solar elevation angle. Qualitative and quantitative measures are used for evaluating the performance of the proposed method for both shadow detection and building height estimation.

  12. Satellite-based estimation of watershed groundwater storage dynamics in a freeze-thaw area under intensive agricultural development

    Science.gov (United States)

    Ouyang, Wei; Liu, Bing; Wu, Yuyang

    2016-06-01

    Understanding the temporal-spatial characteristics of groundwater storage is critical for agricultural planning and management in the future, thereby causing more challenges in water resource management. However, the special hydrological features of the snow water equivalent, soil moisture, and total canopy water storage in the freeze-thawing agricultural area requires the innovative methods for the water resource analysis. The watershed land cover variation and the expanding pattern of the farmlands over a decade were identified using the TM-Landsat series data. Combined with the traditional measurements of the water resource, the monthly gravity field data from the Gravity Recovery And Climate Experiment (GRACE) was validated and applied. The water resources distribution based on the remotely sensed data demonstrated that the forest in the watershed center had a larger amount of water storage. The inter-annual and seasonal variability of total water storage (TWS) over the agricultural area was analyzed and the higher value appeared in the thawing period of April. The correlations of the TWS streamflow, soil moisture and snow water equivalent with precipitation were all identified. The precipitation was the dominant factor for the watershed TWS and the groundwater dynamics. Under the similar precipitation condition, the lower groundwater storage in recent years was the consequence of the expanding of farmland. The watershed averaged decrease rate of groundwater level from 2003 to 2012 was 1.06 mm/year, which was much lower than the rates in other agricultural areas. The freeze-thawing process with smelt snow and rainfall in summer had more time and chance to recharge the groundwater resource and provided the sustainable water resource. This study proved that the application of GRACE was an effective method for the temporal-spatial estimation of the TWS anomalies in the freeze-thawing agricultural area.

  13. Global Estimates of Average Ground-Level Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth

    Science.gov (United States)

    Van Donkelaar, A.; Martin, R. V.; Brauer, M.; Kahn, R.; Levy, R.; Verduzco, C.; Villeneuve, P.

    2010-01-01

    Exposure to airborne particles can cause acute or chronic respiratory disease and can exacerbate heart disease, some cancers, and other conditions in susceptible populations. Ground stations that monitor fine particulate matter in the air (smaller than 2.5 microns, called PM2.5) are positioned primarily to observe severe pollution events in areas of high population density; coverage is very limited, even in developed countries, and is not well designed to capture long-term, lower-level exposure that is increasingly linked to chronic health effects. In many parts of the developing world, air quality observation is absent entirely. Instruments aboard NASA Earth Observing System satellites, such as the MODerate resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR), monitor aerosols from space, providing once daily and about once-weekly coverage, respectively. However, these data are only rarely used for health applications, in part because the can retrieve the amount of aerosols only summed over the entire atmospheric column, rather than focusing just on the near-surface component, in the airspace humans actually breathe. In addition, air quality monitoring often includes detailed analysis of particle chemical composition, impossible from space. In this paper, near-surface aerosol concentrations are derived globally from the total-column aerosol amounts retrieved by MODIS and MISR. Here a computer aerosol simulation is used to determine how much of the satellite-retrieved total column aerosol amount is near the surface. The five-year average (2001-2006) global near-surface aerosol concentration shows that World Health Organization Air Quality standards are exceeded over parts of central and eastern Asia for nearly half the year.

  14. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Science.gov (United States)

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  15. Blending Model Output with satellite-based and in-situ observations to produce high-resolution estimates of population exposure to wildfire smoke

    Science.gov (United States)

    Lassman, William

    In the western US, emissions from wildfires and prescribed fire have been associated with degradation of regional air quality. Whereas atmospheric aerosol particles with aerodynamic diameters less than 2.5 mum (PM2.5) have known impacts on human health, there is uncertainty in how particle composition, concentrations, and exposure duration impact the associated health response. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of PM2.5 in the western US. While composition and source of the aerosol is thought to be an important factor in the resulting human health-effects, this is currently not well-understood; therefore, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools are commonly used to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations, and each of these exposure-estimation tools have associated strengths and weakness. In this thesis, we investigate the utility of blending these tools together to produce highly accurate estimates of smoke exposure during the 2012 fire season in Washington for use in an epidemiological case study. For blending, we use a ridge regression model, as well as a geographically weighted ridge regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using Leave-One-Out Cross-Validation. Due to the number of in-situ monitors present during this time period, we find that predictions based on in-situ monitors were more accurate for this particular fire season than the CTM simulations and

  16. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  17. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

    Directory of Open Access Journals (Sweden)

    G. R. van der Werf

    2009-02-01

    Full Text Available Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year−1, mostly stemming from fires associated with deforestation (74% with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19% and pasture fires (7%. In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation

  18. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

    Science.gov (United States)

    van der Werf, G. R.; Morton, D. C.; Defries, R. S.; Giglio, L.; Randerson, J. T.; Collatz, G. J.; Kasibhatla, P. S.

    2009-02-01

    Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001-2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year-1, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although

  19. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

    OpenAIRE

    van der Werf, G. R.; D. C. Morton; R. S. DeFries; Giglio, L.; Randerson, J. T.; Collatz, G. J.; Kasibhatla, P. S.

    2009-01-01

    Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activ...

  20. Satellite Formation based on SDDF Method

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2014-04-01

    Full Text Available The technology of satellite formation flying has being a research focus in flight application. The relative position and velocity between satellites are basic parameters to achieve the control of formation flight during the satellite formation flying mission. In order to improve the navigation accuracy, a new filter different from Extended Kalman Filter (EKF should be adopted to estimate the errors of relative position and velocity, which is based on the nonlinearity of the kinetic model for the satellite formation flying. A nonlinear Divided Difference Filter (DDF based on Stirling interpolation formula was proposed in this paper. According to the linearity of the measurement equation for the filter, a simplified differential filter was designed by means of expanding the polynomial of the nonlinear system equation and linear approximating of the finite differential interpolation. Digital simulation experiment for the relative positioning of satellite formation flying was carried out. The result demonstrates that the filter proposed in this paper has a higher filtering accuracy, faster convergence speed and better stability. Compared with the EKF, the estimation accuracy of the relative position and velocity has improved by 77.1%and 47% respectively in the method of simplified DDF, which indicates the significance for practical applications. 

  1. Hydrological parameter estimation for ungauged basin based on satellite altimeter data and discharge modeling. A simulation for the Caqueta River (Amazonian Basin, Colombia

    Directory of Open Access Journals (Sweden)

    J. G. Leon

    2006-09-01

    Full Text Available The main objective of this paper is to review the usefulness of altimetric data in ungauged or very poorly monitored basin. It is shown that altimetric measurements can be combined with a single in-situ gauge to derive a reliable stage-discharge relationship upstream from the gauge. The Caqueta River in the Colombian Amazon Basin was selected to simulate a poorly monitored basin. Thus it was possible to derive the stage-discharge relationship for 13 "virtual gauge stations'' defined at river crossing with radar altimetric ground tracks. Stage measurements are derived from altimetric data following the methodology developed by Leon et al. (2006. Discharge is modeled using PROGUM – a flow routing model based on the Muskingum Cunge (M-C approach considering a diffusion-cum-dynamic wave propagation (Leon et al., 2006 using a single gauge located downstream from the basin under study. Rating curve parameters at virtual stations are estimated by fitting with a power law the temporal series of water surface altitude derived from satellite measurements and the modelled discharges. The methodology allows the ellipsoidal height of effective zero flow to be estimated. This parameter is a good proxy of the mean water depth from which the bottom slope of the reaches can be computed. Validation has been conducted by comparing the results with stages and discharges measured at five other gauges available on the Caqueta basin. Outflow errors range from 10% to 20% between the upper basin and the lower basin, respectively. Mean absolute differences less than 1.10 m between estimated equivalent water depth and measured water depth indicates the reliability of the proposed method. Finally, a 1.2×10−4 mm−1 mean bottom slope has been obtained for the 730 km long reach of the Caqueta main stream considered.

  2. Estimation of surface insolation using sun-synchronous satellite data

    Science.gov (United States)

    Darnell, Wayne L.; Staylor, W. Frank; Gupta, Shashi K.; Denn, Fred M.

    1988-01-01

    A technique is presented for estimating insolation at the earth's surface using only sun-synchronous satellite data. The technique was tested by comparing the insolation results from year-long satellite data sets with simultaneous ground-measured insolation taken at five continental United States sites. Monthly average insolation values derived from the satellite data showed a standard error of 4.2 W/sq m, or 2.7 percent of the average ground insolation value.

  3. Optimizing Satellite-Based Precipitation Estimation for Nowcasting of Rainfall and Flash Flood Events over the South African Domain

    OpenAIRE

    Estelle de Coning

    2013-01-01

    The South African Weather Service is mandated to issue warnings of hazardous weather events, including those related to heavy precipitation, in order to safeguard life and property. Flooding and flash flood events are common in South Africa. Frequent updates and real-time availability of precipitation data are crucial to support hydrometeorological warning services. Satellite rainfall estimation provides a very important data source for flash flood guidance systems as well as nowcasting of pr...

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

    Science.gov (United States)

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

    1993-01-01

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

  5. A Space Based Solar Power Satellite System

    Science.gov (United States)

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

    2002-01-01

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

  6. Satellite-based terrestrial production efficiency modeling

    Directory of Open Access Journals (Sweden)

    Obersteiner Michael

    2009-09-01

    Full Text Available Abstract Production efficiency models (PEMs are based on the theory of light use efficiency (LUE which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP monitoring. The objectives of this review are as follows: 1 to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS identified in the literature; 2 to review each model to determine potential improvements to the general PEM methodology; 3 to review the related literature on satellite-based gross primary productivity (GPP and NPP modeling for additional possibilities for improvement; and 4 based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra; there is an urgent need for

  7. Using satellite image-based maps to improve sugarcane straw burning emission estimates in the state of São Paulo, Brazil

    Science.gov (United States)

    França, D.; Longo, K.; Rudorff, B.; Aguiar, D.; Freitas, S. R.; Stockler, R.; Pereira, G.

    2014-12-01

    Since the last decade, the global demand for biofuel production has been increasing every year due to the growing need for energy supply security and mitigation of greenhouse gases (GHG). Currently, sugarcane ethanol is one of the most widely used biofuels and Brazil is already the world's largest sugarcane producer, devoting almost 50% of it to ethanol production. The state of São Paulo is the major sugarcane producer in this country, with a cultivated area of about 5.4 Mha in 2011. Approximately 2 million hectares were harvested annually from 2006 to 2011 with the pre-harvest straw burning practice, which emits trace gases and particulate material to the atmosphere. The assessment and monitoring of sugarcane burning impacts are fundamental in order to mitigate the negative impacts of pre-harvest burning and consolidate the environmental benefits of sugarcane ethanol. Although some official inventories created by the Brazilian government have indicated the prevalence of emissions from sugarcane straw burning in total agricultural residue emissions, specific information about emissions of gases and aerosols during pre-harvest burning of sugarcane is still scarce in Brazil. This study aimed to contribute to the improvement of estimates of emissions from sugarcane burning through the use of specific parameters for sugarcane straw burning and a method which has avoided underestimations resulting from the unique characteristics of this type of biomass fire. In this investigation, emissions of several air pollutants released by sugarcane burning during the harvest season were estimated through the integrated use of remote sensing based maps of sugarcane burned area and a numerical tool for the state of São Paulo from 2006 to 2011. Average estimated emissions (Gg/year) were 1,130 ± 152 for CO, 26 ± 4 for NOX, 16 ± 2 for CH4, 45 ± 6 for PM2.5, 120 ± 16 for PM10 and 154 ± 21 for NMHC (non-methane hydrocarbons). An intercomparison among annual emissions from this

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

    Data.gov (United States)

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

  9. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

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

  10. Models for estimation of land remote sensing satellites operational efficiency

    Science.gov (United States)

    Kurenkov, Vladimir I.; Kucherov, Alexander S.

    2017-01-01

    The paper deals with the problem of estimation of land remote sensing satellites operational efficiency. Appropriate mathematical models have been developed. Some results obtained with the help of the software worked out in Delphi programming support environment are presented.

  11. Estimation of glacier mass balance: An approach based on satellite-derived transient snowlines and a temperature index driven by meteorological observations

    Science.gov (United States)

    Tawde, S. A.; Kulkarni, A. V.; Bala, G.

    2015-12-01

    In the Himalaya, large area is comprised of glaciers and seasonal snow, mainly due to its high elevated mountain ranges. Long term and continuous assessment of glaciers in this region is important for climatological and hydrological applications. However, rugged terrains and severe weather conditions in the Himalaya lead to paucity in field observations. Therefore, in recent decades, glacier dynamics are extensively monitored using remote sensing in inaccessible terrain like Himalaya. Estimation of glacier mass balance using empirical relationship between mass balance and area accumulation ratio (AAR) requires an accurate estimate of equilibrium-line altitude (ELA). ELA is defined as the snowline at the end of the hydrological year. However, identification of ELA, using remote sensing is difficult because of temporal gaps, cloud cover and intermediate snowfall on glaciers. This leads to large uncertainty in glacier mass-balance estimates by the conventional AAR method that uses satellite-derived highest snowline in ablation season as an ELA. The present study suggests a new approach to improve estimates of ELA location. First, positions of modelled snowlines are optimized using satellite-derived snowlines in the early melt season. Secondly, ELA at the end of the glaciological year is estimated by the melt and accumulation models driven using in situ temperature and precipitation records. From the modelled ELA, mass balance is estimated using the empirical relationship between AAR and mass balance. The modelled mass balance is validated using field measurements on Chhota Shigri and Hamtah glaciers, Himachal Pradesh, India. The new approach shows a substantial improvement in glacier mass-balance estimation, reducing bias by 46% and 108% for Chhota Shigiri and Hamtah glaciers respectively. The cumulative mass loss reconstructed from our approach is 0.85 Gt for nine glaciers in the Chandra basin from 2001 to 2009. The result of the present study is in agreement with

  12. Computer based satellite design

    Science.gov (United States)

    Lashbrook, David D.

    1992-06-01

    A computer program to design geosynchronous spacecraft has been developed. The program consists of four separate but interrelated executable computer programs. The programs are compiled to run on a DOS based personnel computer. The source code is written in DoD mandated Ada programming language. The thesis presents the design technique and design equations used in the program. Detailed analysis is performed in the following areas for both dual spin and three axis stabilized spacecraft configurations: (1) Mass Propellent Budget and Mass Summary; (2) Battery Cell and Solar Cell Requirements for a Payload Power Requirement; and (3) Passive Thermal Control Requirements. A user's manual is included as Appendix A, and the source code for the computer programs as Appendix B.

  13. How Well Can We Estimate Error Variance of Satellite Precipitation Data Around the World?

    Science.gov (United States)

    Gebregiorgis, A. S.; Hossain, F.

    2014-12-01

    The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location. However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics. Thus, providing error information associated with existing satellite precipitation estimates is crucial to advancing applications in hydrologic modeling. In this study, we present a method of estimating satellite precipitation error variance using regression model for three satellite precipitation products (3B42RT, CMORPH, and PERSIANN-CCS) using easily available geophysical features and satellite precipitation rate. The goal of this work is to explore how well the method works around the world in diverse geophysical settings. Topography, climate, and seasons are considered as the governing factors to segregate the satellite precipitation uncertainty and fit a nonlinear regression equation as function of satellite precipitation rate. The error variance models were tested on USA, Asia, Middle East, and Mediterranean region. Rain-gauge based precipitation product was used to validate the errors variance of satellite precipitation products. Our study attests that transferability of model estimators (which help to estimate the error variance) from one region to another is practically possible by leveraging the similarity in geophysical features. Therefore, the quantitative picture of satellite precipitation error over ungauged regions can be discerned even in the absence of ground truth data.

  14. Satellite-Based Quantum Communications

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Richard J [Los Alamos National Laboratory; Nordholt, Jane E [Los Alamos National Laboratory; McCabe, Kevin P [Los Alamos National Laboratory; Newell, Raymond T [Los Alamos National Laboratory; Peterson, Charles G [Los Alamos National Laboratory

    2010-09-20

    Single-photon quantum communications (QC) offers the attractive feature of 'future proof', forward security rooted in the laws of quantum physics. Ground based quantum key distribution (QKD) experiments in optical fiber have attained transmission ranges in excess of 200km, but for larger distances we proposed a methodology for satellite-based QC. Over the past decade we have devised solutions to the technical challenges to satellite-to-ground QC, and we now have a clear concept for how space-based QC could be performed and potentially utilized within a trusted QKD network architecture. Functioning as a trusted QKD node, a QC satellite ('QC-sat') could deliver secret keys to the key stores of ground-based trusted QKD network nodes, to each of which multiple users are connected by optical fiber or free-space QC. A QC-sat could thereby extend quantum-secured connectivity to geographically disjoint domains, separated by continental or inter-continental distances. In this paper we describe our system concept that makes QC feasible with low-earth orbit (LEO) QC-sats (200-km-2,000-km altitude orbits), and the results of link modeling of expected performance. Using the architecture that we have developed, LEO satellite-to-ground QKD will be feasible with secret bit yields of several hundred 256-bit AES keys per contact. With multiple ground sites separated by {approx} 100km, mitigation of cloudiness over any single ground site would be possible, potentially allowing multiple contact opportunities each day. The essential next step is an experimental QC-sat. A number of LEO-platforms would be suitable, ranging from a dedicated, three-axis stabilized small satellite, to a secondary experiment on an imaging satellite. to the ISS. With one or more QC-sats, low-latency quantum-secured communications could then be provided to ground-based users on a global scale. Air-to-ground QC would also be possible.

  15. Lessons Learned from the Deployment and Integration of a Microwave Sounder Based Tropical Cyclone Intensity and Surface Wind Estimation Algorithm into NOAA/NESDIS Satellite Product Operations

    Science.gov (United States)

    Longmore, S. P.; Knaff, J. A.; Schumacher, A.; Dostalek, J.; DeMaria, R.; Chirokova, G.; Demaria, M.; Powell, D. C.; Sigmund, A.; Yu, W.

    2014-12-01

    The Colorado State University (CSU) Cooperative Institute for Research in the Atmosphere (CIRA) has recently deployed a tropical cyclone (TC) intensity and surface wind radii estimation algorithm that utilizes Suomi National Polar-orbiting Partnership (S-NPP) satellite Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit (AMSU) from the NOAA18, NOAA19 and METOPA polar orbiting satellites for testing, integration and operations for the Product System Development and Implementation (PSDI) projects at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS). This presentation discusses the evolution of the CIRA NPP/AMSU TC algorithms internally at CIRA and its migration and integration into the NOAA Data Exploitation (NDE) development and testing frameworks. The discussion will focus on 1) the development cycle of internal NPP/AMSU TC algorithms components by scientists and software engineers, 2) the exchange of these components into the NPP/AMSU TC software systems using the subversion version control system and other exchange methods, 3) testing, debugging and integration of the NPP/AMSU TC systems both at CIRA/NESDIS and 4) the update cycle of new releases through continuous integration. Lastly, a discussion of the methods that were effective and those that need revision will be detailed for the next iteration of the NPP/AMSU TC system.

  16. 14 CFR 141.91 - Satellite bases.

    Science.gov (United States)

    2010-01-01

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

  17. Using satellite image-based maps and ground inventory data to estimate the area of the remaining Atlantic forest in the Brazilian state of Santa Catarina

    Science.gov (United States)

    Alexander C. Vibrans; Ronald E. McRoberts; Paolo Moser; Adilson L. Nicoletti

    2013-01-01

    Estimation of large area forest attributes, such as area of forest cover, from remote sensing-based maps is challenging because of image processing, logistical, and data acquisition constraints. In addition, techniques for estimating and compensating for misclassification and estimating uncertainty are often unfamiliar. Forest area for the state of Santa Catarina in...

  18. Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

    Science.gov (United States)

    Seevers, P.M.; Ottmann, R. W.

    1994-01-01

    Evapotranspiration of irrigated crops on two irrigation service areas along the lower Colorado River was estimated using a normalized difference vegetation index of satellite data. A procedure was developed which equated the index to crop coefficients. Evapotranspiration estimates for fields for three dates of thematic mapper data were highly correlated with ground estimates. Service area estimates using thematic mapper and Advanced Very High Resolution Radiometer data agreed well with estimates based on US Geological Survey gauging station data.

  19. Satellite air temperature estimation for monitoring the canopy layer heat island of Milan

    DEFF Research Database (Denmark)

    Pichierri, Manuele; Bonafoni, Stefania; Biondi, Riccardo

    2012-01-01

    2007 and 2010 were processed. Analysis of the canopy layer heat island (CLHI) maps during summer months reveals an average heat island effect of 3–4K during nighttime (with some peaks around 5K) and a weak CLHI intensity during daytime. In addition, the satellite maps reveal a well defined island shape......In this work, satellite maps of the urban heat island of Milan are produced using satellite-based infrared sensor data. For this aim, we developed suitable algorithms employing satellite brightness temperatures for the direct air temperature estimation 2 m above the surface (canopy layer), showing...

  20. Neural network-based estimates of Southern Ocean net community production from in-situ O2 / Ar and satellite observation: a methodological study

    Directory of Open Access Journals (Sweden)

    C.-H. Chang

    2013-10-01

    Full Text Available Southern Ocean organic carbon export plays an important role in the global carbon cycle, yet its basin-scale climatology and variability are uncertain due to limited coverage of in situ observations. In this study, a neural network approach based on the self-organizing map (SOM is adopted to construct weekly gridded (1° × 1° maps of organic carbon export for the Southern Ocean from 1998 to 2009. The SOM is trained with in situ measurements of O2 / Ar-derived net community production (NCP that are tightly linked to the carbon export in the mixed layer on timescales of 1–2 weeks, and six potential NCP predictors: photosynthetically available radiation (PAR, particulate organic carbon (POC, chlorophyll (Chl, sea surface temperature (SST, sea surface height (SSH, and mixed layer depth (MLD. This non-parametric approach is based entirely on the observed statistical relationships between NCP and the predictors, and therefore is strongly constrained by observations. A thorough cross-validation yields three retained NCP predictors, Chl, PAR, and MLD. Our constructed NCP is further validated by good agreement with previously published independent in situ derived NCP of weekly or longer temporal resolution through real-time and climatological comparisons at various sampling sites. The resulting November–March NCP climatology reveals a pronounced zonal band of high NCP roughly following the subtropical front in the Atlantic, Indian and western Pacific sectors, and turns southeastward shortly after the dateline. Other regions of elevated NCP include the upwelling zones off Chile and Namibia, Patagonian Shelf, Antarctic coast, and areas surrounding the Islands of Kerguelen, South Georgia, and Crozet. This basin-scale NCP climatology closely resembles that of the satellite POC field and observed air-sea CO2 flux. The long-term mean area-integrated NCP south of 50° S from our dataset, 14 mmol C m–2 d–1, falls within the range of 8.3–24 mmol C m

  1. THE STOCHASTIC ESTIMATION OF SATELLITE CLOCK CORRECTION INFORMATION IN WADGPS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Using autocorrelation information of the pseudorange errors generated by se lective availability (SA) frequency dithering, we have constructed a simple first order stochas tic model for SA effects. This model has been used in a Kalman filter to account for the stochastic behavior of SA dithering in estimating satellite clock information in wide area dif ferential GPS. We have obtained fifteen percent improvement in the user positioning using the correlation information on the satellite clock information in a Kalman filter, when comparing the results obtained using a regular least square estimation.

  2. A Method for Estimating BeiDou Inter-frequency Satellite Clock Bias

    Directory of Open Access Journals (Sweden)

    LI Haojun

    2016-02-01

    Full Text Available A new method for estimating the BeiDou inter-frequency satellite clock bias is proposed, considering the shortage of the current methods. The constant and variable parts of the inter-frequency satellite clock bias are considered in the new method. The data from 10 observation stations are processed to validate the new method. The characterizations of the BeiDou inter-frequency satellite clock bias are also analyzed using the computed results. The results of the BeiDou inter-frequency satellite clock bias indicate that it is stable in the short term. The estimated BeiDou inter-frequency satellite clock bias results are molded. The model results show that the 10 parameters of model for each satellite can express the BeiDou inter-frequency satellite clock bias well and the accuracy reaches cm level. When the model parameters of the first day are used to compute the BeiDou inter-frequency satellite clock bias of the second day, the accuracy also reaches cm level. Based on the stability and modeling, a strategy for the BeiDou satellite clock service is presented to provide the reference of our BeiDou.

  3. Estimating the yaw-attitude of BDS IGSO and MEO satellites

    Science.gov (United States)

    Dai, Xiaolei; Ge, Maorong; Lou, Yidong; Shi, Chuang; Wickert, Jens; Schuh, Harald

    2015-10-01

    Precise knowledge and consistent modeling of the yaw-attitude of GNSS satellites are essential for high-precision data processing and applications. As the exact attitude control mechanism for the satellites of the BeiDou Satellite Navigation System (BDS) is not yet released, the reverse kinematic precise point positioning (PPP) method was applied in our study. However, we confirm that the recent precise orbit determination (POD) processing for GPS satellites could not provide suitable products for estimating BDS attitude using the reverse PPP because of the special attitude control switching between the nominal and the orbit-normal mode. In our study, we propose a modified processing schema for studying the attitude behavior of the BDS satellites. In this approach, the observations of the satellites during and after attitude switch are excluded in the POD processing, so that the estimates, which are needed in the reverse PPP, are not contaminated by the inaccurate initial attitude mode. The modified process is validated by experimental data sets and the attitude yaw-angles of the BDS IGSO and MEO satellites are estimated with an accuracy of better than . Furthermore, the results confirm that the switch is executed when the Sun elevation is about and the actual orientation is very close to its target one. Based on the estimated yaw-angles, a preliminary attitude switch model was established and reintroduced into the POD, yielding to a substantial improvement in the orbit overlap RMS.

  4. Satellite Driven Estimation of Primary Productivity of Agroecosystems in India

    Science.gov (United States)

    Patel, N. R.; Dadhwal, V. K.; Agrawal, S.; Saha, S. K.

    2011-08-01

    Earth observation driven ecosystem modeling have played a major role in estimation of carbon budget components such as gross primary productivity (GPP) and net primary production (NPP) over terrestrial ecosystems, including agriculture. The present study therefore evaluate satellite-driven vegetation photosynthesis (VPM) model for GPP estimation over agro-ecosystems in India by using time series of the Normalized Difference Vegetation Index (NDVI) from SPOT-VEGETATION, cloud cover observation from MODIS, coarse-grid C3/C4 crop fraction and decadal grided databases of maximum and minimum temperatures. Parameterization of VPM parameters e.g. maximum light use efficiency (ɛ*) and Tscalar was done based on eddy-covariance measurements and literature survey. Incorporation of C3/C4 crop fraction is a modification to commonly used constant maximum LUE. Modeling results from VPM captured very well the geographical pattern of GPP and NPP over cropland in India. Well managed agro-ecosystems in Trans-Gangetic and upper Indo-Gangetic plains had the highest magnitude of GPP with peak GPP during kharif occurs in sugarcane-wheat system (western UP) and it occurs in rice-wheat system (Punjab) during Rabi season. Overall, croplands in these plains had more annual GPP (> 1000 g C m-2) and NPP (> 600 g C m-2) due to input-intensive cultivation. Desertic tracts of western Rajasthan showed the least GPP and NPP values. Country-level contribution of croplands to national GPP and NPP amounts to1.34 Pg C year-1 and 0.859 Pg C year-1, respectively. Modeled estimates of cropland NPP agrees well with ground-based estimates for north-western India (R2 = 0.63 and RMSE = 108 g C m-2). Future research will focus on evaluating the VPM model with medium resolution sensors such as AWiFS and MODIS for rice-wheat system and validating with eddy-covariance measurements.

  5. SATELLITE DRIVEN ESTIMATION OF PRIMARY PRODUCTIVITY OF AGROECOSYSTEMS IN INDIA

    Directory of Open Access Journals (Sweden)

    N. R. Patel

    2012-08-01

    Full Text Available Earth observation driven ecosystem modeling have played a major role in estimation of carbon budget components such as gross primary productivity (GPP and net primary production (NPP over terrestrial ecosystems, including agriculture. The present study therefore evaluate satellite-driven vegetation photosynthesis (VPM model for GPP estimation over agro-ecosystems in India by using time series of the Normalized Difference Vegetation Index (NDVI from SPOT-VEGETATION, cloud cover observation from MODIS, coarse-grid C3/C4 crop fraction and decadal grided databases of maximum and minimum temperatures. Parameterization of VPM parameters e.g. maximum light use efficiency (ε* and Tscalar was done based on eddy-covariance measurements and literature survey. Incorporation of C3/C4 crop fraction is a modification to commonly used constant maximum LUE. Modeling results from VPM captured very well the geographical pattern of GPP and NPP over cropland in India. Well managed agro-ecosystems in Trans-Gangetic and upper Indo-Gangetic plains had the highest magnitude of GPP with peak GPP during kharif occurs in sugarcane-wheat system (western UP and it occurs in rice-wheat system (Punjab during Rabi season. Overall, croplands in these plains had more annual GPP (> 1000 g C m-2 and NPP (> 600 g C m-2 due to input-intensive cultivation. Desertic tracts of western Rajasthan showed the least GPP and NPP values. Country-level contribution of croplands to national GPP and NPP amounts to1.34 Pg C year-1 and 0.859 Pg C year-1, respectively. Modeled estimates of cropland NPP agrees well with ground-based estimates for north-western India (R2 = 0.63 and RMSE = 108 g C m-2. Future research will focus on evaluating the VPM model with medium resolution sensors such as AWiFS and MODIS for rice-wheat system and validating with eddy-covariance measurements.

  6. Effects of systematic sampling on satellite estimates of deforestation rates

    Energy Technology Data Exchange (ETDEWEB)

    Steininger, M K; Godoy, F; Harper, G, E-mail: msteininger@conservation.or [Center for Applied Biodiversity Science-Conservation International, 2011 Crystal Drive Suite 500, Arlington, VA 22202 (United States)

    2009-09-15

    Options for satellite monitoring of deforestation rates over large areas include the use of sampling. Sampling may reduce the cost of monitoring but is also a source of error in estimates of areas and rates. A common sampling approach is systematic sampling, in which sample units of a constant size are distributed in some regular manner, such as a grid. The proposed approach for the 2010 Forest Resources Assessment (FRA) of the UN Food and Agriculture Organization (FAO) is a systematic sample of 10 km wide squares at every 1 deg. intersection of latitude and longitude. We assessed the outcome of this and other systematic samples for estimating deforestation at national, sub-national and continental levels. The study is based on digital data on deforestation patterns for the five Amazonian countries outside Brazil plus the Brazilian Amazon. We tested these schemes by varying sample-unit size and frequency. We calculated two estimates of sampling error. First we calculated the standard errors, based on the size, variance and covariance of the samples, and from this calculated the 95% confidence intervals (CI). Second, we calculated the actual errors, based on the difference between the sample-based estimates and the estimates from the full-coverage maps. At the continental level, the 1 deg., 10 km scheme had a CI of 21% and an actual error of 8%. At the national level, this scheme had CIs of 126% for Ecuador and up to 67% for other countries. At this level, increasing sampling density to every 0.25 deg. produced a CI of 32% for Ecuador and CIs of up to 25% for other countries, with only Brazil having a CI of less than 10%. Actual errors were within the limits of the CIs in all but two of the 56 cases. Actual errors were half or less of the CIs in all but eight of these cases. These results indicate that the FRA 2010 should have CIs of smaller than or close to 10% at the continental level. However, systematic sampling at the national level yields large CIs unless the

  7. Estimated Satellite Cluster Elements in Near Circular Orbit

    Science.gov (United States)

    1988-12-01

    values of the covariance matriz P to see if the filter performs as well as it believes it is performing [4:page 3391. 1.1.. Thuth Model The truth...between satellites will bc affected. Since the measurements contain no informa- L tion on absolute downrange position, it is impossible to estimate

  8. Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

    Science.gov (United States)

    Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus; Kauffman, Jobriath; Prisley, Stephen

    2016-01-01

    Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119

  9. Local gravity disturbance estimation from multiple-high-single-low satellite-to-satellite tracking

    Science.gov (United States)

    Jekeli, Christopher

    1989-01-01

    The idea of satellite-to-satellite tracking in the high-low mode has received renewed attention in light of the uncertain future of NASA's proposed low-low mission, Geopotential Research Mission (GRM). The principal disadvantage with a high-low system is the increased time interval required to obtain global coverage since the intersatellite visibility is often obscured by Earth. The U.S. Air Force has begun to investigate high-low satellite-to-satellite tracking between the Global Positioning System (GPS) of satellites (high component) and NASA's Space Transportation System (STS), the shuttle (low component). Because the GPS satellites form, or will form, a constellation enabling continuous three-dimensional tracking of a low-altitude orbiter, there will be no data gaps due to lack of intervisibility. Furthermore, all three components of the gravitation vector are estimable at altitude, a given grid of which gives a stronger estimate of gravity on Earth's surface than a similar grid of line-of-sight gravitation components. The proposed Air Force mission is STAGE (Shuttle-GPS Tracking for Anomalous Gravitation Estimation) and is designed for local gravity field determinations since the shuttle will likely not achieve polar orbits. The motivation for STAGE was the feasibility to obtain reasonable accuracies with absolutely minimal cost. Instead of simulating drag-free orbits, STAGE uses direct measurements of the nongravitational forces obtained by an inertial package onboard the shuttle. The sort of accuracies that would be achievable from STAGE vis-a-vis other satellite tracking missions such as GRM and European Space Agency's POPSAT-GRM are analyzed.

  10. Potential for Using Satellite Lidar for Seasonal Snow Depth Estimation

    Science.gov (United States)

    Jasinski, M. F.; Stoll, J.; Harding, D. J.; Fassnacht, S. R.; Carabajal, C. C.; Markus, T.

    2013-12-01

    This study evaluates the potential for estimating snow depth in complex mountainous terrain using high resolution satellite lidar. For over three decades, satellite remote sensing of snow depth and water equivalent has relied primarily on passive microwave sensors with an approximately 25 km footprint. While successfully employed in many global water balance analyses, their large footprints, necessary to capture the natural emission of the surface, are too coarse to define the spatial heterogeneity of mountain watershed-scale snow due to variable topography and vegetation. In this study, the capability of satellite lidar altimetry for estimating snow depth was evaluated primarily using surface elevations observed by the Geoscience Laser Altimeter Sensor (GLAS) flown on board the Ice, Cloud, and land Elevation Satellite from 2003-2009, with a footprint size of ~70m. The evaluation includes the analysis of GLAS waveforms at near-repeat locations during snow-off and snow on conditions, using several snow depth estimation approaches, focusing on the Uinta Mountains of NE Utah. Also presented is the concept for the ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS), currently set to launch in July 2016, and its potential capability for characterizing snow depth. The opportunity for partnering through NASA's Early Adopter Program using prototype aircraft observations also is presented.

  11. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

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

    2016-01-01

    Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper......, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  12. Sampling error study for rainfall estimate by satellite using a stochastic model

    Science.gov (United States)

    Shin, Kyung-Sup; North, Gerald R.

    1988-01-01

    In a parameter study of satellite orbits, sampling errors of area-time averaged rain rate due to temporal sampling by satellites were estimated. The sampling characteristics were studied by accounting for the varying visiting intervals and varying fractions of averaging area on each visit as a function of the latitude of the grid box for a range of satellite orbital parameters. The sampling errors were estimated by a simple model based on the first-order Markov process of the time series of area averaged rain rates. For a satellite of nominal Tropical Rainfall Measuring Mission (Thiele, 1987) carrying an ideal scanning microwave radiometer for precipitation measurements, it is found that sampling error would be about 8 to 12 pct of estimated monthly mean rates over a grid box of 5 X 5 degrees. It is suggested that an observation system based on a low inclination satellite combined with a sunsynchronous satellite simultaneously might be the best candidate for making precipitation measurements from space.

  13. Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.; Shie, Chung-Lin; L'Ecuyer, Tristan S.; Tao, Wei-Kuo

    2009-01-01

    In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

  14. Satellite-scale Estimates of the "b Parameter" Relating Vegetation Water Content and SMOS Optical Thickness

    Science.gov (United States)

    Patton, J. C.; Hornbuckle, B. K.

    2013-12-01

    Microwave radiation emitted by Earth's land surface is primarily determined by soil moisture and vegetation. One of the effects of vegetation on surface microwave emissions is often termed the "vegetation optical thickness" or "vegetation opacity" and is often abbreviated as tau. Retrievals of soil moisture from microwave radiometer measurements requires knowledge of tau. The Soil Moisture and Ocean Salinity (SMOS) satellite measures microwave radiation at multiple incidence angles, enabling the simultaneous retrieval of soil moisture and tau. Other soil moisture satellites, such as the upcoming Soil Moisture Active Passive (SMAP) satellite, only measure at single incidence angles and may need auxiliary sources of tau data in order to retrieve soil moisture. One proposed method for estimating tau for these satellites is by relating reflectance data, e.g. the normalized difference vegetation index, to vegetation water content (VWC), then relating VWC to tau. VWC and tau can be related through the b parameter, i.e. tau = b x VWC. Values of b for different land cover types have been estimated from tower (~1 m) and airplane (~10-100 m) data, but have not been measured at the satellite scale (~10 km). Estimating b at the satellite scale from measurements at smaller scales is difficult because the effective value of b in a satellite pixel may not be well represented by linear weighted average based on the fraction of each land cover type in the pixel. However, by relating county crop yields, estimated by the USDA National Agricultural Statistics Service, to measurements of SMOS tau, and by using certain allometric relationships, such as the ratio of water to dry matter and the harvest index of crops, we can estimate b at the satellite scale. We have used this method to estimate b for each Iowa county for the years 2010-2012. Initial results suggest that b may change year to year; our current estimates for b in Iowa range from 0.065 in 2010 to 0.100 in 2012. These

  15. Daily Emission Estimates in China Constrained by Satellite Observations

    Science.gov (United States)

    Mijling, B.; van der A, R.

    2013-01-01

    Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. We present a new algorithm specifically designed to use daily satellite observations of column concentrations for fast updates of emission estimates of short-lived atmospheric constituents on a mesoscopic scale (~25Å~25 km2). The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates of East China, using the CHIMERE model on a 0.25 degree resolution together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments.

  16. Sampling errors in satellite estimates of tropical rain

    Science.gov (United States)

    Mcconnell, Alan; North, Gerald R.

    1987-01-01

    The GATE rainfall data set is used in a statistical study to estimate the sampling errors that might be expected for the type of snapshot sampling that a low earth-orbiting satellite makes. For averages over the entire 400-km square and for the duration of several weeks, strong evidence is found that sampling errors less than 10 percent can be expected in contributions from each of four rain rate categories which individually account for about one quarter of the total rain.

  17. A GIS-based assessment of the suitability of SCIAMACHY satellite sensor measurements for estimating reliable CO concentrations in a low-latitude climate.

    Science.gov (United States)

    Fagbeja, Mofoluso A; Hill, Jennifer L; Chatterton, Tim J; Longhurst, James W S

    2015-02-01

    An assessment of the reliability of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) satellite sensor measurements to interpolate tropospheric concentrations of carbon monoxide considering the low-latitude climate of the Niger Delta region in Nigeria was conducted. Monthly SCIAMACHY carbon monoxide (CO) column measurements from January 2,003 to December 2005 were interpolated using ordinary kriging technique. The spatio-temporal variations observed in the reliability were based on proximity to the Atlantic Ocean, seasonal variations in the intensities of rainfall and relative humidity, the presence of dust particles from the Sahara desert, industrialization in Southwest Nigeria and biomass burning during the dry season in Northern Nigeria. Spatial reliabilities of 74 and 42 % are observed for the inland and coastal areas, respectively. Temporally, average reliability of 61 and 55 % occur during the dry and wet seasons, respectively. Reliability in the inland and coastal areas was 72 and 38 % during the wet season, and 75 and 46 % during the dry season, respectively. Based on the results, the WFM-DOAS SCIAMACHY CO data product used for this study is therefore relevant in the assessment of CO concentrations in developing countries within the low latitudes that could not afford monitoring infrastructure due to the required high costs. Although the SCIAMACHY sensor is no longer available, it provided cost-effective, reliable and accessible data that could support air quality assessment in developing countries.

  18. Calibration of Ocean Forcing with satellite Flux Estimates (COFFEE)

    Science.gov (United States)

    Barron, Charlie; Jan, Dastugue; Jackie, May; Rowley, Clark; Smith, Scott; Spence, Peter; Gremes-Cordero, Silvia

    2016-04-01

    Predicting the evolution of ocean temperature in regional ocean models depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. Within the COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates, real-time satellite observations are used to estimate shortwave, longwave, sensible, and latent air-sea heat flux corrections to a background estimate from the prior day's regional or global model forecast. These satellite-corrected fluxes are used to prepare a corrected ocean hindcast and to estimate flux error covariances to project the heat flux corrections for a 3-5 day forecast. In this way, satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. While traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle, COFFEE endeavors to appropriately partition and reduce among various surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using operational global or regional atmospheric forcing. Experiment cases combine different levels of flux calibration with assimilation alternatives. The cases use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is

  19. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  20. Improvement in airsea flux estimates derived from satellite observations

    OpenAIRE

    Bentamy, Abderrahim; Grodsky, Semyon A.; Katsaros, Kristina; Mestas-nunez, Alberto M.; Blanke, Bruno; Desbiolles, Fabien

    2013-01-01

    A new method is developed to estimate daily turbulent airsea fluxes over the global ocean on a 0.25 degrees grid. The required surface wind speed (w(10)) and specific air humidity (q(10)) at 10m height are both estimated from remotely sensed measurements. w(10) is obtained from the SeaWinds scatterometer on board the QuikSCAT satellite. A new empirical model relating brightness temperatures (T-b) from the Special Sensor Microwave Imager (SSM/I) and q(10) is developed. It is an extension of th...

  1. The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution

    Science.gov (United States)

    Beirle, Steffen; Hörmann, Christoph; Jöckel, Patrick; Liu, Song; Penning de Vries, Marloes; Pozzer, Andrea; Sihler, Holger; Valks, Pieter; Wagner, Thomas

    2016-07-01

    The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1-0.2 × 1015 molecules cm-2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

  2. SAW based systems for mobile communications satellites

    Science.gov (United States)

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

    1993-01-01

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

  3. 一种基于谱分析的非带限卫星信号信噪比估计算法%An SNR Estimator Based on Spectrum Analysis for Non-Band-Limited Satellite Signals

    Institute of Scientific and Technical Information of China (English)

    易辉; 侯孝民; 马宏; 吴涛

    2016-01-01

    为了实现对非带限卫星信号信噪比的快速高精度估计,分析了传统的基于谱分析的信噪比估计算法的对非带限卫星信号估计不准的原因,提出了一种新的基于谱分析的信噪比估计算法;该方法利用主瓣范围内信号功率与信号总功率之比和主瓣范围内噪声功率与噪声总功率之比求得信号功率和噪声功率,从而得出信噪比;对BPSK和QPSK信号的仿真结果表明:新算法性能稳定,可有效提高估计精度,在-10~10 dB的范围内,估计的偏差和均方根误差基本都小于0.5 dB;提出的新的基于谱分析的信噪比估计算法可用于各种调制方式,计算复杂度小,可以满足对非带限卫星信号信噪比估计的需求。%In order to estimate the SNR (Signal to Noise Ratio )of non-band-limited satellite signals in high precision,a new SNR estimator based on spectrum analysis was proposed after an investigation of the traditional SNR estimator based on spectrum analysis.The new estimator utilized the ratio of signal power in main lobe to total signal power and the ratio of noise power in main lobe to total noise power to calculate signal power and noise power,and then got the SNR.Simulations for BPSK (Binary Phase Shift Keying) and QPSK (Quadrature Phase Shift Keying ) signals indicate that the new estimator is stable and can improve the estimation precision effectively.The bias and root mean square error of the new estimator are almost less than 0.5 dB when the true SNR range is from -10 dB to 10 dB.The new estimator can be used to different modulations.It has low complexity and can satisfy the SNR estimation demand of non-band-limited satellite signals.

  4. Estimation of clear-sky insolation using satellite and ground meteorological data

    Science.gov (United States)

    Staylor, W. F.; Darnell, W. L.; Gupta, S. K.

    1983-01-01

    Ground based pyranometer measurements were combined with meteorological data from the Tiros N satellite in order to estimate clear-sky insolations at five U.S. sites for five weeks during the spring of 1979. The estimates were used to develop a semi-empirical model of clear-sky insolation for the interpretation of input data from the Tiros Operational Vertical Sounder (TOVS). Using only satellite data, the estimated standard errors in the model were about 2 percent. The introduction of ground based data reduced errors to around 1 percent. It is shown that although the errors in the model were reduced by only 1 percent, TOVS data products are still adequate for estimating clear-sky insolation.

  5. Improved infrared precipitation estimation approaches based on k-means clustering: Application to north Algeria using MSG-SEVIRI satellite data

    Science.gov (United States)

    Mokdad, Fatiha; Haddad, Boualem

    2017-06-01

    In this paper, two new infrared precipitation estimation approaches based on the concept of k-means clustering are first proposed, named the NAW-Kmeans and the GPI-Kmeans methods. Then, they are adapted to the southern Mediterranean basin, where the subtropical climate prevails. The infrared data (10.8 μm channel) acquired by MSG-SEVIRI sensor in winter and spring 2012 are used. Tests are carried out in eight areas distributed over northern Algeria: Sebra, El Bordj, Chlef, Blida, Bordj Menael, Sidi Aich, Beni Ourthilane, and Beni Aziz. The validation is performed by a comparison of the estimated rainfalls to rain gauges observations collected by the National Office of Meteorology in Dar El Beida (Algeria). Despite the complexity of the subtropical climate, the obtained results indicate that the NAW-Kmeans and the GPI-Kmeans approaches gave satisfactory results for the considered rain rates. Also, the proposed schemes lead to improvement in precipitation estimation performance when compared to the original algorithms NAW (Nagri, Adler, and Wetzel) and GPI (GOES Precipitation Index).

  6. Fast Emission Estimates in China Constrained by Satellite Observations (Invited)

    Science.gov (United States)

    Mijling, B.; van der A, R.

    2013-12-01

    Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for an emerging economy such as China, where rapid economic growth changes emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. Constraining emissions from concentration measurements is, however, computationally challenging. Within the GlobEmission project of the European Space Agency (ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China, using the CHIMERE model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission estimates result in a better

  7. Bayesian estimation of animal movement from archival and satellite tags.

    Directory of Open Access Journals (Sweden)

    Michael D Sumner

    Full Text Available The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools.

  8. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  9. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-09-01

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

  11. Modifications of the heliostat procedures for irradiance estimates from satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, H.G.; Costanzo, Claudio; Heinemann, Detlev [Oldenburg Univ. (Germany). Fachbereich 8 - Physik

    1996-03-01

    Images taken by geostationary satellites may be used to estimate solar irradiance fluxes at the earth`s surface. The Heliostat method is a widely applied procedure for this task. It is based on the empirical correlation between a satellite derived cloud index and the irradiance at the ground. Modifications to this procedure that may reduce the temporal variability of the correlation are presented. The modified method may open the way to the use of a generic relation of cloud index and global irradiance. (author)

  12. Effect of satellite formations and imaging modes on global albedo estimation

    Science.gov (United States)

    Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.

    2016-05-01

    We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static referencecase. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/m2 or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than

  13. Combining Satellite and Ground Magnetic Measurements to Improve Estimates of Electromagnetic Induction Transfer Functions

    Science.gov (United States)

    Balasis, G.; Egbert, G. D.

    2005-12-01

    Electromagnetic (EM) induction studies using satellite and ground-based magnetic data may ultimately provide critical new constraints on the electrical conductivity of Earth's mantle. Unlike ground-based observatories, which leave large areas of the Earth (especially the ocean basins) unsampled, satellites have the potential for nearly complete global coverage. However, because the number of operating satellites is limited, spatially complex (especially non-zonal) external current sources are sampled relatively poorly by satellites at any fixed time. The comparatively much larger number of ground-based observatories provides more complete synoptic sampling of external source structure. By combining data from both satellites and observatories models of external sources can be improved, leading to more reliable global mapping of Earth conductivity. For example, estimates of EM induction transfer functions estimated from night-side CHAMP data have been previously shown to have biases which depend systematically on local time (LT). This pattern of biases suggests that a purely zonal model does not adequately describe magnetospheric sources. As a first step toward improved modeling of spatial complexity in sources, we have applied empirical orthogonal function (EOF) methods to exploratory analysis of night-side observatory data. After subtraction of the predictions of the CM4 comprehensive model, which includes a zonally symmetric storm-time correction based on Dst, we find significant non-axisymmetric, but large scale coherent variability in the mid-latitude night-side observatory residuals. Over the restricted range of local times (18:00-6:00) and latitudes (50°S to 50°N) considered, the dominant spatial mode of variability is reasonably approximated by a q21 quadrupole spherical harmonic. Temporal variability of this leading EOF mode is well correlated with Dst. Strategies for moving beyond this initial exploratory EOF analysis to combine observatory data with

  14. Satellite clock corrections estimation to accomplish real time ppp: experiments for brazilian real time network

    Science.gov (United States)

    Marques, Haroldo; Monico, João; Aquino, Marcio; Melo, Weyller

    2014-05-01

    The real time PPP method requires the availability of real time precise orbits and satellites clocks corrections. Currently, it is possible to apply the solutions of clocks and orbits available by BKG within the context of IGS Pilot project or by using the operational predicted IGU ephemeris. The accuracy of the satellite position available in the IGU is enough for several applications requiring good quality. However, the satellites clocks corrections do not provide enough accuracy (3 ns ~ 0.9 m) to accomplish real time PPP with the same level of accuracy. Therefore, for real time PPP application it is necessary to further research and develop appropriated methodologies for estimating the satellite clock corrections in real time with better accuracy. Currently, it is possible to apply the real time solutions of clocks and orbits available by Federal Agency for Cartography and Geodesy (BKG) within the context of IGS Pilot project. The BKG corrections are disseminated by a new proposed format of the RTCM 3.x and can be applied in the broadcasted orbits and clocks. Some investigations have been proposed for the estimation of the satellite clock corrections using GNSS code and phase observable at the double difference level between satellites and epochs (MERVAT, DOUSA, 2007). Another possibility consists of applying a Kalman Filter in the PPP network mode (HAUSCHILD, 2010) and it is also possible the integration of both methods, using network PPP and observables at double difference level in specific time intervals (ZHANG; LI; GUO, 2010). For this work the methodology adopted consists in the estimation of the satellite clock corrections based on the data adjustment in the PPP mode, but for a network of GNSS stations. The clock solution can be solved by using two types of observables: code smoothed by carrier phase or undifferenced code together with carrier phase. In the former, we estimate receiver clock error; satellite clock correction and troposphere, considering

  15. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  16. Evaluation of short-period rainfall estimates from Kalpana-1 satellite using MET software

    Indian Academy of Sciences (India)

    Soma Sen Roy; Subhendu Brata Saha; Hashmi Fatima; S K Roy Bhowmik; P K Kundu

    2012-10-01

    The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study evaluates the 3-hourly precipitation estimates by this technique as well as the rainfall estimates by the GPI technique using data of the Kalpana-1 satellite, over the Indian region for the south-west monsoon season of 2010 to understand their relative strengths and weaknesses in estimating short period rainfall. The gridded 3 hourly accumulated TRMM satellite (3B42 V6 product or TMPA product) and surface raingauge data for stations over the Indian region for the same period is used as the standard measure of rainfall estimates. The Method for Object-based Diagnostic Evaluation (MODE) utility of the METv3.0 software, has been used for the evaluation purpose. The results show that the new IMSRA technique is closer to the TMPA rainfall estimate, in terms of areal spread, geometric shape and location of rainfall areas, as compared to the GPI technique. The overlap of matching rainfall areas with respect to TMPA rainfall patches is also higher for the IMSRA estimates as compared to the GPI values. However, both satellite rainfall estimates are observed to be generally higher compared to the TMPA measurements. However, the values for the highest 10% of the rainfall rates in any rainfall patch, is generally higher for rainfall measured by the IMSRA technique, as compared to the estimates by the GPI technique. This may partly be due to the capping maximum limit of 3 mm/hr for rainfall measured by the GPI technique limits the total 3-hour accumulation to 9 mm even during heavy rainfall episodes. This is not so with IMSRA technique, which has no such limiting value. However, this general overestimation of the rainfall amount, measured by both techniques

  17. Spatio-Temporal Analysis of Model and Satellite Based Soil Moisture Estimations for Assessing Coupling Hot Spots in the Southern La Plata Basin

    Science.gov (United States)

    Bruscantini, C. A.; Karszenbaum, H.; Ruscica, R. C.; Spennemann, P.; Salvia, M.; Sorensson, A. A.; Grings, F. M.; Saulo, C.

    2015-12-01

    The southern La Plata Basin, located in southeastern South America (SESA), a region of great importance because of its hydrological characteristics, the fact that it has the largest population density and is one of the most productive regions in terms of agriculture, cattle raising and industry of the continent, has been identified as a strong hotspot between soil moisture (SM) and the atmosphere by different regional studies. Among them, Ruscica et al. (2014, Atmos. Sci. Let, Int. J. Climatol.), and Spennemann et al. (2015, Int. J. Climatol.) show, through different modeling approaches, the presence of strong soil moisture-precipitation and evapotranspiration interactions during austral summer in SESA, revealing similar hotspots. Nevertheless these studies have diverse limitations related to model assumptions and to vegetation parameterizations, as well as the lack of observational data for the evaluation of models performance (Ferguson and Wood, 2011, J. of Hydrometeorology). On the other hand, in the last decade several instruments on board satellites are providing soil moisture products globally and in a continuous way. A recent work by Grings et al. (2015, IEEE JSTARS, in press), done over the Pampas Plains in SESA showed characteristic soil moisture patterns that follow the Standardized Precipitation Index (SPI) under extreme wet and dry conditions In order to deepen and overcome some of the mentioned model limitations, this work adds satellite soil moisture and vegetation products in the spatio-temporal analysis of the regions of strong soil moisture-atmosphere interactions. The main objectives and related outcomes are: the verification of already identified regions where soil moisture anomalies may have an influence on subsequent precipitation, evapotranspiration and temperature anomalies, and the study of their seasonal characteristics and land cover influences.

  18. Lorentz Force Based Satellite Attitude Control

    Science.gov (United States)

    Giri, Dipak Kumar; Sinha, Manoranjan

    2016-07-01

    Since the inception of attitude control of a satellite, various active and passive control strategies have been developed. These include using thrusters, momentum wheels, control moment gyros and magnetic torquers. In this present work, a new technique named Lorentz force based Coulombic actuators for the active control is proposed. This method uses electrostatic charged shells, which interact with the time varying earth's magnetic field to establish a full three axes control of the satellite. It is shown that the proposed actuation mechanism is similar to a satellite actuated by magnetic coils except that the resultant magnetic moment vanishes under two different conditions. The equation for the required charges on the the Coulomb shells attached to the satellite body axes is derived, which is in turn used to find the available control torque for actuating the satellite along the orbit. Stability of the proposed system for very high initial angular velocity and exponential stability about the origin are proved for a proportional-differential control input. Simulations are carried out to show the efficacy of the proposed system for the attitude control of the earth-pointing satellite.

  19. Estimation of volcanic ash refractive index from satellite infrared sounder data

    Science.gov (United States)

    Ishimoto, H.; Masuda, K.

    2014-12-01

    The properties of volcanic ash clouds (cloud height, optical depth, and effective radius of the particles) are planned to estimate from the data of the next Japanese geostationary meteorological satellite, Himawari 8/9. The volcanic ash algorithms, such as those proposed by NOAA/NESDIS and by EUMETSAT, are based on the infrared absorption properties of the ash particles, and the refractive index of a typical volcanic rock (i.e. andesite) has been used in the forward radiative transfer calculations. Because of a variety of the absorption properties for real volcanic ash particles at infrared wavelengths (9-13 micron), a large retrieval error may occur if the refractive index of the observed ash particles was different from that assumed in the retrieval algorithm. Satellite infrared sounder provides spectral information for the volcanic ash clouds. If we can estimate the refractive index of the ash particles from the infrared sounder data, a dataset of the optical properties for similar rock type of the volcanic ash can be prepared for the ash retrieval algorithms of geostationary/polar-orbiting satellites in advance. Furthermore, the estimated refractive index can be used for a diagnostic and a correction of the ash particle model in the retrieval algorithm within a period of the volcanic activities. In this work, optimal estimation of the volcanic ash parameters was conducted through the radiative transfer calculations for the window channels of the atmospheric infrared sounder (AIRS). The estimated refractive indices are proposed for the volcanic ash particles of some eruption events.

  20. A Simple Statistical Model to Estimate Incident Solar Radiation at the Surface from NOAA AVHRR Satellite Data

    Directory of Open Access Journals (Sweden)

    Mst. Ashrafunnahar Hena

    2013-01-01

    Full Text Available Processing of meteorological satellite image data provides a wealth of information useful in earth surface and environmental applications. Particularly, it is important for the estimation of different parameters of surface energy budget. In this work, a method has been developed to estimation of hourly incoming solar radiation on the surface of Bangladesh using NOAA-AVHRR satellite digital images. The model is based on the statistical regressions between the ground truth and satellite estimated values. Hundreds of full resolution images (1.1 km for two months of the year have been processed using ERDAS IMAGINE software. Ground solar global irradiation for one place has been estimated for two months through this application. The efficiency of this method for calculating surface insolation has been checked by estimating the relative deviation between the estimated Irradiation and measured Irradiation. The method can be used for calculation of hourly irradiation over areas in a tropical environment.

  1. Estimates of lightning NOx production from GOME satellite observations

    Directory of Open Access Journals (Sweden)

    K. F. Boersma

    2005-01-01

    Full Text Available Tropospheric NO2 column retrievals from the Global Ozone Monitoring Experiment (GOME satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NOx=NO+NO2. A sharp increase of NO2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO2 is used to construct a 10:30 local time global lightning NO2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO2 to observed NO2 columns. It exploits a masking scheme to minimise the interference of other NOx sources on the observed total columns. Simulations are performed with two lightning parameterizations, one relating convective preciptation (CP scheme to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme to lightning distributions. The satellite-retrieved NO2 fields show significant correlations with the simulated lightning contribution to the NO2 concentrations for both parameterizations. Over tropical continents modelled lightning NO2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parameterizations overestimate the retrieved NO2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO2 and modelled lightning NO2 is used to rescale the original modelled lightning NOx production. Eight estimates of the lightning NOx production in 1997 are obtained from spatial and temporal

  2. Estimates of lightning NOx production from GOME satellite observations

    Directory of Open Access Journals (Sweden)

    H. M. Kelder

    2005-05-01

    Full Text Available Tropospheric NO2 column retrievals from the Global Ozone Monitoring Experiment (GOME satellite spectrometer are used to quantify the source strength and 3D distribution of lightning produced nitrogen oxides (NOx=NO2+NO2. A sharp increase of NO2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO2 is used to construct a 10:30 local time global lightning NO2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO2 to observed NO2 columns. It exploits a masking scheme to minimise the interference of other NOx sources on the observed total columns. Simulations are performed with two lightning parametrisations, one relating convective preciptation (CP scheme to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme to lightning distributions. The satellite-retrieved NO2 fields show significant correlations with the simulated lightning contribution to the NO2 concentrations for both parametrisations. Over tropical continents modelled lightning NO2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parametrisations overestimate the retrieved NO2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO2 and modelled lightning NO2 is used to rescale the original modelled lightning NOx production. Eight estimates of the lightning NOx production in 1997 are obtained from spatial and temporal correlation

  3. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

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

    2009-01-01

    Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy......’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direction e.g. the satellite-based ASCAT wind directions as demonstrated by CLS. The wind direction has to known...

  4. Liu Estimator Based on An M Estimator

    Directory of Open Access Journals (Sweden)

    Hatice ŞAMKAR

    2010-01-01

    Full Text Available Objective: In multiple linear regression analysis, multicollinearity and outliers are two main problems. In the presence of multicollinearity, biased estimation methods like ridge regression, Stein estimator, principal component regression and Liu estimator are used. On the other hand, when outliers exist in the data, the use of robust estimators reducing the effect of outliers is prefered. Material and Methods: In this study, to cope with this combined problem of multicollinearity and outliers, it is studied Liu estimator based on M estimator (Liu M estimator. In addition, mean square error (MSE criterion has been used to compare Liu M estimator with Liu estimator based on ordinary least squares (OLS estimator. Results: OLS, Huber M, Liu and Liu M estimates and MSEs of these estimates have been calculated for a data set which has been taken form a study of determinants of physical fitness. Liu M estimator has given the best performance in the data set. It is found as both MSE (?LM = 0.0078< MSE (?M = 0.0508 and MSE (?LM = 0.0078< MSE (?L= 0.0085. Conclusion: When there is both outliers and multicollinearity in a dataset, while using of robust estimators reduces the effect of outliers, it could not solve problem of multicollinearity. On the other hand, using of biased methods could solve the problem of multicollinearity, but there is still the effect of outliers on the estimates. In the occurence of both multicollinearity and outliers in a dataset, it has been shown that combining of the methods designed to deal with this problems is better than using them individually.

  5. A review of satellite-based methods of estimating live fuel moisture content for fire danger assessment: moving towards operational products

    Science.gov (United States)

    One of the primary variables affecting ignition and spread of wildfire is fuel moisture content (FMC), which is the ratio of water mass to dry mass in living and dead plant material. Because dead FMC may be estimated from available weather data, remote sensing is needed to monitor the spatial distr...

  6. Verification of satellite radar remote sensing based estimates of boreal and subalpine growing seasons using an ecosystem process model and surface biophysical measurement network information

    Science.gov (United States)

    McDonald, K. C.; Kimball, J. S.; Zimmerman, R.

    2002-01-01

    We employ daily surface Radar backscatter data from the SeaWinds Ku-band Scatterometer onboard Quikscat to estimate landscape freeze-thaw state and associated length of the seasonal non-frozen period as a surrogate for determining the annual growing season across boreal and subalpine regions of North America for 2000 and 2001.

  7. Fault Diagnosis of Satellite Based on IMM and Moving Horizon Estimation%基于多模型滚动时域估计的卫星故障诊断

    Institute of Scientific and Technical Information of China (English)

    赵石磊; 吴丽娜

    2011-01-01

    This paper studies the fault diagnosis problems of the satellite attitude control system. Since the satellite works in space, the attitude control system of satellite is easy to be effected by uncertainties and disturbances in the harsh working environment. Interacting Multiple Model (IMM) is one of the effective fault diagnosis methods of the satellite control system but it is subjected to strong noise or wrong data. For this reason, this paper proposes to combine the moving horizon estimation instead of the Kahnan filter with the IMM algorithm. The moving horizon estimation, which adopts not the estimation error of one time but the interval estimation error of a time span, is used to estimate the system states and the transition probabilities. So it could effectively decrease the influences of the wrong data or strong noise. Finally, the mathematical simulation results for diagnosis problem of the satellite attitude control system are presented to show the effectiveness of the proposed scheme.%研究了卫星姿态控制系统故障诊断问题,将滚动时域估计与交互式多模型(IMM)方法相结合,利用滚动时域估计方法对系统状态进行估计,系统转换概率也相应地利用了一个时间段的估计误差作为依据,而不是只考虑一个时刻的估计误差,因此有效减少了大噪声以及个别错误测量对诊断结果的影响.最后的仿真结果证明了该算法的有效性.

  8. Rainfall estimation for real time flood monitoring using geostationary meteorological satellite data

    Science.gov (United States)

    Veerakachen, Watcharee; Raksapatcharawong, Mongkol

    2015-09-01

    Rainfall estimation by geostationary meteorological satellite data provides good spatial and temporal resolutions. This is advantageous for real time flood monitoring and warning systems. However, a rainfall estimation algorithm developed in one region needs to be adjusted for another climatic region. This work proposes computationally-efficient rainfall estimation algorithms based on an Infrared Threshold Rainfall (ITR) method calibrated with regional ground truth. Hourly rain gauge data collected from 70 stations around the Chao-Phraya river basin were used for calibration and validation of the algorithms. The algorithm inputs were derived from FY-2E satellite observations consisting of infrared and water vapor imagery. The results were compared with the Global Satellite Mapping of Precipitation (GSMaP) near real time product (GSMaP_NRT) using the probability of detection (POD), root mean square error (RMSE) and linear correlation coefficient (CC) as performance indices. Comparison with the GSMaP_NRT product for real time monitoring purpose shows that hourly rain estimates from the proposed algorithm with the error adjustment technique (ITR_EA) offers higher POD and approximately the same RMSE and CC with less data latency.

  9. Remote sensing estimation of winter wheat leaf nitrogen content based on GF-1 satellite data%基于GF-1卫星数据的冬小麦叶片氮含量遥感估算

    Institute of Scientific and Technical Information of China (English)

    李粉玲; 常庆瑞; 申健; 王力

    2016-01-01

    Nitrogen is a major element for plant growth and yield formation in agronomic crops. Crop nitrogen content estimation by remote sensing technique has been being a topic research in remote sensing monitoring of agricultural parameters. Hyper-spectral remote sensing with wealth of spectral information has been widely used in crop physiological and biochemical information extraction. It provides theoretical basis for estimating crop biochemical parameters based on multi-spectral satellite data. In terms of multi-spectral satellite remote sensing, spectral reflectances and spectral indices are effective ways to establish estimation models of biochemical parameters, but which bands and spectral indices are more effective and reliable for leaf nitrogen concentration monitoring in winter wheat is still debatable. In this article, ground-based canopy spectral reflectance and leaf nitrogen content (LNC) of winter wheat were measured from field and plot experiments including varied nitrogen fertilization levels and winter wheat varieties across the whole growth stages. Multi-spectral broadband reflectance was simulated by using the measured hyper-spectral reflectance and spectral response functions of multi-spectral camera of GF-1 satellite with a spatial resolution of 8 m, and then, they were used for the establishment of spectral index (SI). Eight spectral indices significantly correlated with LNC at the 0.01 probability level were used to construct the LNC estimation models in a linear, quadratic polynomial and exponential regression model respectively. Considering the influence factors in evaluating the efficiency of the SI–LNC model, i.e., the stability of the SI to other perturbing factors, the sensitivity of the SI to a unit change of LNC, and the dynamic range of the SI, the improved sensitivity index was proposed based on the NE andTVIindex models. The optimal LNC estimation model was given according to the sensitivity and accuracy analysis, and the model was used

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

    Science.gov (United States)

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

    2008-01-01

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

  11. GNSS Carrier Phase-based Attitude Determination: Estimation and Applications

    NARCIS (Netherlands)

    Giorgi, G.

    2011-01-01

    Attitude determination through the use of Global Navigation Satellite System (GNSS) signals is one of the many applications of satellite-based navigation. Multiple GNSS antennas installed on a given platform are used to provide orientation estimates, thus adding attitude information to the standard

  12. GNSS Carrier Phase-based Attitude Determination: Estimation and Applications

    NARCIS (Netherlands)

    Giorgi, G.

    2011-01-01

    Attitude determination through the use of Global Navigation Satellite System (GNSS) signals is one of the many applications of satellite-based navigation. Multiple GNSS antennas installed on a given platform are used to provide orientation estimates, thus adding attitude information to the standard

  13. Satellite-rainfall estimation for identification of rainfall thresholds used for landslide/debris flow prediction

    Science.gov (United States)

    Maggioni, Viviana; Nikolopoulos, Efthymios I.; Marra, Francesco; Destro, Elisa; Borga, Marco

    2016-04-01

    Rainfall-induced landslides and debris flows pose a significant and widespread hazard, resulting in a large number of casualties and enormous economic damages worldwide. Rainfall thresholds are often used to identify the local or regional rainfall conditions that, when reached or exceeded, are likely to result in landslides or debris flows. Rain gauge data are the typical source of information for the definition of these rainfall thresholds. However, in-situ observations over mountainous areas, where these hazards mainly occur, are very sparse or inexistent. Therefore identification and use of gauge-based rainfall thresholds is impossible in many landslide prone areas over the globe. The vast advancements in satellite-based precipitation estimation over the last couple of decades have lead to the creation of a number of global precipitation datasets at various spatiotemporal resolutions. Although several investigations have shown that these datasets can be associated with considerable uncertainty, they provide the only source of precipitation information over many areas around the globe. Therefore it is important to assess their performance in the context of landslide/debris flow prediction and investigate how we can potentially benefit from the information they provide. In this work, we evaluate the performance of three widely used quasi-global satellite precipitation products (3B42v7, PERSIANN and CMORPH) for the identification of rainfall threshold for landslide/debris flow triggering. Products are available at 0.25deg/3h resolution. The study region is focused over the Upper Adige river basin, northern Italy where a detailed database of more than 400 identified debris flows (during period 2000-2015) and a raingauge network of 95 stations, is available. Rain-gauge based rainfall thresholds are compared against satellite-based thresholds to evaluate strengths and limitations in using satellite precipitation estimates for defining rainfall thresholds. Analysis of

  14. An Efficient Two-Fold Marginalized Bayesian Filter for Multipath Estimation in Satellite Navigation Receivers

    Directory of Open Access Journals (Sweden)

    Robertson Patrick

    2010-01-01

    Full Text Available Multipath is today still one of the most critical problems in satellite navigation, in particular in urban environments, where the received navigation signals can be affected by blockage, shadowing, and multipath reception. Latest multipath mitigation algorithms are based on the concept of sequential Bayesian estimation and improve the receiver performance by exploiting the temporal constraints of the channel dynamics. In this paper, we specifically address the problem of estimating and adjusting the number of multipath replicas that is considered by the receiver algorithm. An efficient implementation via a two-fold marginalized Bayesian filter is presented, in which a particle filter, grid-based filters, and Kalman filters are suitably combined in order to mitigate the multipath channel by efficiently estimating its time-variant parameters in a track-before-detect fashion. Results based on an experimentally derived set of channel data corresponding to a typical urban propagation environment are used to confirm the benefit of our novel approach.

  15. Estimation of Satellite Orientation from Space Surveillance Imagery Measured with an Adaptive Optics Telescope

    Science.gov (United States)

    1996-12-01

    SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE THESIS Gregory E. Wood Lieutenant, USAF AFIT/GSO/ENP...the official policy or position of the Department of Defense or the U. S. Government. AFIT/GSO/ENP/96D-02 ESTIMATION OF SATELLITE ORIENTATION FROM...surveillance operations. xii ESTIMATION OF SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE

  16. Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors.

    Science.gov (United States)

    Esteban, Segundo; Girón-Sierra, Jose M; Polo, Óscar R; Angulo, Manuel

    2016-10-31

    Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

  17. Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors

    Directory of Open Access Journals (Sweden)

    Segundo Esteban

    2016-10-01

    Full Text Available Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

  18. Satellite Type Estination from Ground-based Photometric Observation

    Science.gov (United States)

    Endo, T.; Ono, H.; Suzuki, J.; Ando, T.; Takanezawa, T.

    2016-09-01

    The optical photometric observation is potentially a powerful tool for understanding of the Geostationary Earth Orbit (GEO) objects. At first, we measured in laboratory the surface reflectance of common satellite materials, for example, Multi-layer Insulation (MLI), mono-crystalline silicon cells, and Carbon Fiber Reinforced Plastic (CFRP). Next, we calculated visual magnitude of a satellite by simplified shape and albedo. In this calculation model, solar panels have dimensions of 2 by 8 meters, and the bus area is 2 meters squared with measured optical properties described above. Under these conditions, it clarified the brightness can change the range between 3 and 4 magnitudes in one night, but color index changes only from 1 to 2 magnitudes. Finally, we observed the color photometric data of several GEO satellites visible from Japan multiple times in August and September 2014. We obtained that light curves of GEO satellites recorded in the B and V bands (using Johnson filters) by a ground-base optical telescope. As a result, color index changed approximately from 0.5 to 1 magnitude in one night, and the order of magnitude was not changed in all cases. In this paper, we briefly discuss about satellite type estimation using the relation between brightness and color index obtained from the photometric observation.

  19. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  20. A strategy for merging objective estimates of global daily precipitation from gauge observations, satellite estimates, and numerical predictions

    Science.gov (United States)

    Nie, Suping; Wu, Tongwen; Luo, Yong; Deng, Xueliang; Shi, Xueli; Wang, Zaizhi; Liu, Xiangwen; Huang, Jianbin

    2016-07-01

    This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.

  1. Temporal and Spatial Assessment of Four Satellite Rainfall Estimates over French Guiana and North Brazil

    Directory of Open Access Journals (Sweden)

    Justine Ringard

    2015-12-01

    Full Text Available Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis V7 (Version 7 and RT (real time, CMORPH (Climate Prediction Center (CPC MORPHing technique and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network, for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio. Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and

  2. Satellite Contamination and Materials Outgassing Knowledge base

    Science.gov (United States)

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

    2001-01-01

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

  3. Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over Sparsely Vegetated Area

    Directory of Open Access Journals (Sweden)

    Pei Leng

    2015-04-01

    Full Text Available Based on a novel bare surface soil moisture (SSM retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (LST and net surface shortwave radiation (NSSR (Leng et al. 2014. “Bare Surface Soil Moisture Retrieval from the Synergistic Use of Optical and Thermal Infrared Data”. International Journal of Remote Sensing 35: 988–1003., this paper mainly investigated the model’s capability to estimate SSM using geostationary satellite observations over vegetated area. Results from the simulated data primarily indicated that the previous bare SSM retrieval model is capable of estimating SSM in the low vegetation cover condition with fractional vegetation cover (FVC ranging from 0 to 0.3. In total, the simulated data from the Common Land Model (CoLM on 151 cloud-free days at three FLUXNET sites that with different climate patterns were used to describe SSM estimates with different underlying surfaces. The results showed a strong correlation between the estimated SSM and the simulated values, with a mean Root Mean Square Error (RMSE of 0.028 m3·m−3 and a coefficient of determination (R2 of 0.869. Moreover, diurnal cycles of LST and NSSR derived from the Meteosat Second Generation (MSG satellite data on 59 cloud-free days were utilized to estimate SSM in the REMEDHUS soil moisture network (Spain. In particular, determination of the model coefficients synchronously using satellite observations and SSM measurements was explored in detail in the cases where meteorological data were not available. A preliminary validation was implemented to verify the MSG pixel average SSM in the REMEDHUS area with the average SSM calculated from the site measurements. The results revealed a significant R2 of 0.595 and an RMSE of 0.021 m3·m−3.

  4. Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

    Directory of Open Access Journals (Sweden)

    Sandra Eckert

    2012-03-01

    Full Text Available Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC and the Kyoto Protocol. In order to develop improved forest stratum–specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson’s correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression. Pearson’s correlation coefficients revealed that (a texture measures correlated more with biomass and carbon than spectral parameters, and (b correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%. For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%. These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a developing and applying forest stratum–specific models, and (b including textural information in addition to spectral information.

  5. Elastic thickness and heat flux estimates for the uranian satellite Ariel

    Science.gov (United States)

    Peterson, G.; Nimmo, F.; Schenk, P.

    2015-04-01

    The surface of Ariel, an icy satellite orbiting Uranus, shows extensional tectonic features suggesting an episode of endogenic heating in the satellite's past. Using topography derived from stereo-photoclinometry, we identified flexural uplift at a rift zone suggesting elastic thickness values in the range 3.8-4.4 km. We estimate the temperature at the base of the lithosphere to be in the range 99-146 K, depending on the strain rate assumed, with corresponding heat fluxes of 28-92 mW/m2. Neither tidal heating, assuming Ariel's current eccentricity, nor radiogenic heat production from the silicate core are enough to cause the inferred heat fluxes. None of three proposed ancient mean-motion resonances produce equilibrium tidal heating values in excess of 4.3 mW/m2. Thus, the origin of the inferred high heat fluxes is currently mysterious.

  6. Satellite Estimates of Crop Area and Maize Yield in Zambia's Agricultural Districts

    Science.gov (United States)

    Azzari, G.; Lobell, D. B.

    2015-12-01

    Predicting crop yield and area from satellite is a valuable tool to monitor different aspects of productivity dynamics and food security. In Sub-Saharan Africa, where the agricultural landscape is complex and dominated by smallholder systems, such dynamics need to be investigated at the field scale. We leveraged the large data pool and computational power of Google Earth Engine to 1) generate 30 m resolution cover maps of selected provinces of Zambia, 2) estimate crop area, and 3) produce yearly maize yield maps using the recently developed SCYM (Scalable satellite-based Crop Yield Mapper) algorithm. We will present our results and their validation against a ground survey dataset collected yearly by the Zambia Ministry of Agriculture from about 12,500 households.

  7. Satellite Based Extrusion Rates for the 2006 Augustine Eruption

    Science.gov (United States)

    Dehn, J.; Bailey, J. E.; Dean, K. G.; Skoog, R.; Valcic, L.

    2006-12-01

    Extrusion rates were calculated from polar orbiting infrared satellite data for the 2006 eruption of Augustine Volcano, Alaska. The pixel integrated brightness temperatures from the satellite data were converted to estimates of ground temperature by making assumptions and using first hand observations about the geometry of the hot area (lava dome, flows and pyroclastic flow deposits) relative to the cold area in the kilometer scale pixels. Extrusion rate is calculated by assuming that at a given temperature, a lava emits an amount of radiation proportional to its volume. On ten occasions during the activity, helicopter based infrared imagers were used to validate the satellite observations. The pre-January 11 thermal activity was not significantly above background in satellite data. The first strong thermal anomalies were recorded during the first explosive phase on January 11. During successive explosive phases in January, bright thermal signals were observed, often saturating the sensors. Large areas (many km2) were observed to be warm in the satellite data, indicative of pyroclastic flows. Sometime during or after January 29, during a phase of sustained ash emission, the thermal signal became persistent, suggesting the beginning of lava effusion. The extrusion rates derived from satellite data varied from 0 to nearly 7 m3/s, giving an eruption rate of 2.7 m3/s. The extrusion event produced two blocky lava flows which moved down the north flank of the volcano. Extrusion occurred through at least March 15 (day 76) when a sharp drop in extrusion rate and thermal signal is observed. Based on the derived extrusion rates, it is estimated that 18 million m3 of lava was extruded during the course of the eruption. This value agreed well with photogrammetric measurements, but does not agree with volumes derived through subtraction of digital elevation models post- and pre- eruption. It should be noted that the thermal approach only works for hot lavas, and does not

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

    KAUST Repository

    Lopez Valencia, Oliver M.

    2016-06-15

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

  9. Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

    Science.gov (United States)

    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

  10. Femto-satellite Swarm State and Density Estimation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is planning future missions involving fleets of small satellites in LEO and GEO that can exhibit autonomous collective behavior. Such a "swarm of...

  11. Gravity Anomalies and Estimated Topography Derived from Satellite Altimetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds of kilometers apart. Satellites carrying...

  12. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3)sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

  13. Frequency Estimation in Iterative Interference Cancellation Applied to Multibeam Satellite Systems

    Directory of Open Access Journals (Sweden)

    Ducasse A

    2007-01-01

    Full Text Available This paper deals with interference cancellation techniques to mitigate cochannel interference on the reverse link of multibeam satellite communication systems. The considered system takes as a starting point the DVB-RCS standard with the use of convolutional coding. The considered algorithm consists of an iterative parallel interference cancellation scheme which includes estimation of beamforming coefficients. This algorithm is first derived in the case of a symbol asynchronous channel with time-invariant carrier phases. The aim of this article is then to study possible extensions of this algorithm to the case of frequency offsets affecting user terminals. The two main approaches evaluated and discussed here are based on (1 the use of block processing for estimation of beamforming coefficients in order to follow carrier phase variations and (2 the use of single-user frequency offset estimations.

  14. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    Directory of Open Access Journals (Sweden)

    Patrick Marina

    2017-01-01

    Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

  15. Satellite-based Tropical Cyclone Monitoring Capabilities

    Science.gov (United States)

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

    2012-12-01

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

  16. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

    Science.gov (United States)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

    2008-07-01

    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  17. Operational evapotranspiration based on Earth observation satellites

    Science.gov (United States)

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

    2016-04-01

    Geostationary satellites have the potential to follow fast evolving atmospheric and Earth surface phenomena such those related to cloud cover evolution and diurnal cycle. Since about 15 years, EUMETSAT has set up a network named 'Satellite Application Facility' (SAF, http://www.eumetsat.int/website/home/Satellites/GroundSegment/Safs/index.html) to complement its ground segment. The Land Surface Analysis (LSA) SAF (http://landsaf.meteo.pt/) is devoted to the development of operational products derived from the European meteorological satellites. In particular, an evapotranspiration (ET) product has been developed by the Royal Meteorological Institute of Belgium. Instantaneous and daily integrated results are produced in near real time and are freely available respectively since the end of 2009 and 2010. The products cover Europe, Africa and the Eastern part of South America with the spatial resolution of the SEVIRI sensor on-board Meteosat Second Generation (MSG) satellites. The ET product algorithm (Ghilain et al., 2011) is based on a simplified Soil-Vegetation-Atmosphere transfer (SVAT) scheme, forced with MSG derived radiative products (LSA SAF short and longwave surface fluxes, albedo). It has been extensively validated against in-situ validation data, mainly FLUXNET observations, demonstrating its good performances except in some arid or semi-arid areas. Research has then been pursued to develop an improved version for those areas. Solutions have been found in reviewing some of the model parameterizations and in assimilating additional satellite products (mainly vegetation indices and land surface temperature) into the model. The ET products will be complemented with related latent and sensible heat fluxes, to allow the monitoring of land surface energy partitioning. The new algorithm version should be tested in the LSA-SAF operational computer system in 2016 and results should become accessible to beta-users/regular users by the end of 2016/early 2017. In

  18. Wave Period and Coastal Bathymetry Estimations from Satellite Images

    Science.gov (United States)

    Danilo, Celine; Melgani, Farid

    2016-08-01

    We present an approach for wave period and coastal water depth estimation. The approach based on wave observations, is entirely independent of ancillary data and can theoretically be applied to SAR or optical images. In order to demonstrate its feasibility we apply our method to more than 50 Sentinel-1A images of the Hawaiian Islands, well-known for its long waves. Six wave buoys are available to compare our results with in-situ measurements. The results on Sentinel-1A images show that half of the images were unsuitable for applying the method (no swell or wavelength too small to be captured by the SAR). On the other half, 78% of the estimated wave periods are in accordance with buoy measurements. In addition, we present preliminary results of the estimation of the coastal water depth on a Landsat-8 image (with characteristics close to Sentinel-2A). With a squared correlation coefficient of 0.7 for ground truth measurement, this approach reveals promising results for monitoring coastal bathymetry.

  19. Application of satellite estimates of rainfall distribution to simulate the potential for malaria transmission in Africa

    Science.gov (United States)

    Yamana, T. K.; Eltahir, E. A.

    2009-12-01

    The Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) is a mechanistic model developed to assess malaria risk in areas where the disease is water-limited. This model relies on precipitation inputs as its primary forcing. Until now, applications of the model have used ground-based precipitation observations. However, rain gauge networks in the areas most affected by malaria are often sparse. The increasing availability of satellite based rainfall estimates could greatly extend the range of the model. The minimum temporal resolution of precipitation data needed was determined to be one hour. The CPC Morphing technique (CMORPH ) distributed by NOAA fits this criteria, as it provides 30-minute estimates at 8km resolution. CMORPH data were compared to ground observations in four West African villages, and calibrated to reduce overestimation and false alarm biases. The calibrated CMORPH data were used to force HYDREMATS, resulting in outputs for mosquito populations, vectorial capacity and malaria transmission.

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

    Directory of Open Access Journals (Sweden)

    S. Kotsuki

    2015-01-01

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

  1. Estimation of fossil-fuel CO2 emissions using satellite measurements of "proxy" species

    Science.gov (United States)

    Konovalov, Igor B.; Berezin, Evgeny V.; Ciais, Philippe; Broquet, Grégoire; Zhuravlev, Ruslan V.; Janssens-Maenhout, Greet

    2016-11-01

    Fossil-fuel (FF) burning releases carbon dioxide (CO2) together with many other chemical species, some of which, such as nitrogen dioxide (NO2) and carbon monoxide (CO), are routinely monitored from space. This study examines the feasibility of estimation of FF CO2 emissions from large industrial regions by using NO2 and CO column retrievals from satellite measurements in combination with simulations by a mesoscale chemistry transport model (CTM). To this end, an inverse modeling method is developed that allows estimating FF CO2 emissions from different sectors of the economy, as well as the total CO2 emissions, in a given region. The key steps of the method are (1) inferring "top-down" estimates of the regional budget of anthropogenic NOx and CO emissions from satellite measurements of proxy species (NO2 and CO in the case considered) without using formal a priori constraints on these budgets, (2) the application of emission factors (the NOx-to-CO2 and CO-to-CO2 emission ratios in each sector) that relate FF CO2 emissions to the proxy species emissions and are evaluated by using data of "bottom-up" emission inventories, and (3) cross-validation and optimal combination of the estimates of CO2 emission budgets derived from measurements of the different proxy species. Uncertainties in the top-down estimates of the NOx and CO emissions are evaluated and systematic differences between the measured and simulated data are taken into account by using original robust techniques validated with synthetic data. To examine the potential of the method, it was applied to the budget of emissions for a western European region including 12 countries by using NO2 and CO column amounts retrieved from, respectively, the OMI and IASI satellite measurements and simulated by the CHIMERE mesoscale CTM, along with the emission conversion factors based on the EDGAR v4.2 emission inventory. The analysis was focused on evaluation of the uncertainty levels for the top-down NOx and CO emission

  2. Global lightning NOx production estimated by an assimilation of multiple satellite data sets

    Science.gov (United States)

    Miyazaki, K.; Eskes, H. J.; Sudo, K.; Zhang, C.

    2014-04-01

    The global source of lightning-produced NOx (LNOx) is estimated by assimilating observations of NO2, O3, HNO3, and CO measured by multiple satellite measurements into a chemical transport model. Included are observations from the Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS), Tropospheric Emission Spectrometer (TES), and Measurements of Pollution in the Troposphere (MOPITT) instruments. The assimilation of multiple chemical data sets with different vertical sensitivity profiles provides comprehensive constraints on the global LNOx source while improving the representations of the entire chemical system affecting atmospheric NOx, including surface emissions and inflows from the stratosphere. The annual global LNOx source amount and NO production efficiency are estimated at 6.3 Tg N yr-1 and 310 mol NO flash-1, respectively. Sensitivity studies with perturbed satellite data sets, model and data assimilation settings lead to an error estimate of about 1.4 Tg N yr-1 on this global LNOx source. These estimates are significantly different from those estimated from a parameter inversion that optimizes only the LNOx source from NO2 observations alone, which may lead to an overestimate of the source adjustment. The total LNOx source is predominantly corrected by the assimilation of OMI NO2 observations, while TES and MLS observations add important constraints on the vertical source profile. The results indicate that the widely used lightning parameterization based on the C-shape assumption underestimates the source in the upper troposphere and overestimates the peak source height by up to about 1 km over land and the tropical western Pacific. Adjustments are larger over ocean than over land, suggesting that the cloud height dependence is too weak over the ocean in the Price and Rind (1992) approach. The significantly improved agreement between the analyzed ozone fields and independent observations gives confidence in the performance of the LNOx source

  3. Satellite estimates of urban development for hydrological modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    We investigate the applicability of medium resolution Landsat satellite imagery for mapping temporal changes in urban land cover in European cities for direct use in urban flood models. The overarching aim is to provide accurate and costand resource-efficient quantification of temporal changes...

  4. Estimation of evaporation rates over the Arabian Sea from Satellite data

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, M.V.; RameshBabu, V.; Rao, L.V.G.; Sastry, J.S.

    Utilizing both the SAMIR brightness temperatures of Bhaskara 2 and GOSSTCOMP charts of NOAA satellite series, the evaporation rates over the Arabian Sea for June 1982 are estimated through the bulk aerodynamic method. The spatial distribution...

  5. Analytic Perturbation Method for Estimating Ground Flash Fraction from Satellite Lightning Observations

    Science.gov (United States)

    Koshak, William; Solakiewicz, Richard

    2013-01-01

    An analytic perturbation method is introduced for estimating the lightning ground flash fraction in a set of N lightning flashes observed by a satellite lightning mapper. The value of N is large, typically in the thousands, and the observations consist of the maximum optical group area produced by each flash. The method is tested using simulated observations that are based on Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) data. National Lightning Detection NetworkTM (NLDN) data is used to determine the flash-type (ground or cloud) of the satellite-observed flashes, and provides the ground flash fraction truth for the simulation runs. It is found that the mean ground flash fraction retrieval errors are below 0.04 across the full range 0-1 under certain simulation conditions. In general, it is demonstrated that the retrieval errors depend on many factors (i.e., the number, N, of satellite observations, the magnitude of random and systematic measurement errors, and the number of samples used to form certain climate distributions employed in the model).

  6. Estimation of Leaf Area Index Using IRS Satellite Images

    Directory of Open Access Journals (Sweden)

    A Faridhosseini

    2012-12-01

    Full Text Available Estimation of vegetation cover attributes, such as the Leaf Area Index (LAI, is an important step in identifying the amount of water use for some plants. The goal of this study is to investigate the feasibility of using IRS LISS-III data to retrieve LAI. To get a LAI retrieval model based on reflectance and vegetation index, detailed field data were collected in the study area of eastern Iran. In this study, atmospheric corrected IRS LISS-III imagery was used to calculate Normalized Difference Vegetation Index (NDVI. Data of 50 samples of LAI were measured by Sun Scan System – SS1 in the study area. In situ measurements of LAI were related to widely use spectral vegetation indices (NDVI. The best model through analyzing the results was LAI = 19.305×NDVI+5.514 using the method of linear-regression analysis. The results showed that the correlation coefficient R2 was 0.534 and RMSE was 0.67. Thereby, suggesting that, when using remote sensing NDVI for LAI estimation, not only is the choice of NDVI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using multi- spectral imagery for large-scale mapping of vegetation biophysical variables.

  7. Monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, Scot S.; Pertica, Alexander J.; Riot, Vincent J.; De Vries, Willem H.; Bauman, Brian J.; Nikolaev, Sergei; Henderson, John R.; Phillion, Donald W.

    2015-06-30

    An ephemeris refinement system includes satellites with imaging devices in earth orbit to make observations of space-based objects ("target objects") and a ground-based controller that controls the scheduling of the satellites to make the observations of the target objects and refines orbital models of the target objects. The ground-based controller determines when the target objects of interest will be near enough to a satellite for that satellite to collect an image of the target object based on an initial orbital model for the target objects. The ground-based controller directs the schedules to be uploaded to the satellites, and the satellites make observations as scheduled and download the observations to the ground-based controller. The ground-based controller then refines the initial orbital models of the target objects based on the locations of the target objects that are derived from the observations.

  8. Earth Observation Satellites Scheduling Based on Decomposition Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Feng Yao

    2010-11-01

    Full Text Available A decomposition-based optimization algorithm was proposed for solving Earth Observation Satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy were introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony optimization algorithm, which can guide the search process of ant colony optimization. Computation results showed that the approach was effective to the satellites observation scheduling problem.

  9. Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations

    Science.gov (United States)

    Wong, A.; Jin, Y.; Snyder, R. L.; Daniele, Z.; Gao, F.

    2016-12-01

    Irrigation accounts for 80% of human freshwater consumption, and most of it return to the atmosphere through Evapotranspiration (ET). Given the challenges of already-stressed water resources and ground water regulation in California, a cost-effective, timely, and consistent spatial estimate of crop ET, from the farm to watershed level, is becoming increasingly important. The Priestley-Taylor (PT) approach, calibrated with field data and driven by satellite observations, shows great promise for accurate ET estimates across diverse ecosystems. We here aim to improve the robustness of the PT approach in agricultural lands, to enable growers and farm managers to tailor irrigation management based on in-field spatial variability and in-season variation. We optimized the PT coefficients for each crop type with available ET measurements from eddy covariance towers and/or surface renewal stations at six crop fields (Alfalfa, Almond, Citrus, Corn, Pistachio and Rice) in California. Good agreement was found between satellite-based estimates and field measurements of net radiation, with a RMSE of less than 36 W m-2. The crop type specific optimization performed well, with a RMSE of 30 W m-2 and a correlation of 0.81 for predicted daily latent heat flux. The calibrated algorithm was used to estimate ET at 30 m resolution over the Sacramento-San Joaquin Delta region for 2015 water year. It captures well the seasonal dynamics and spatial distribution of ET in Sacramento-San Joaquin Delta. A continuous monitoring of the dynamics and spatial heterogeneity of canopy and consumptive water use at a field scale, will help the growers to be well prepared and informed to adaptively manage water, canopy, and grove density to maximize the yield with the least amount of water.

  10. Estimation of micrometeorites and satellite dust flux surrounding Mars in the light of MAVEN results

    Science.gov (United States)

    Pabari, J. P.; Bhalodi, P. J.

    2017-05-01

    Recently, MAVEN observed dust around Mars from ∼150 km to ∼1000 km and it is a puzzling question to the space scientists about the presence of dust at orbital altitudes and about its source. A continuous supply of dust from various sources could cause existence of dust around Mars and it is expected that the dust could mainly be from either the interplanetary source or the Phobos/Deimos. We have studied incident projectiles or micrometeorites at Mars using the existing model, in this article. Comparison of results with the MAVEN results gives a new value of the population index S, which is reported here. The index S has been referred in a power law model used to describe the number of impacting particles on Mars. In addition, the secondary ejecta from natural satellites of Mars can cause a dust ring or torus around Mars and remain present for its lifetime. The dust particles whose paths are altered by the solar wind over its lifetime, could present a second plausible source of dust around Mars. We have investigated escaping particles from natural satellites of Mars and compared with the interplanetary dust flux estimation. It has been found that flux rate at Mars is dominated (∼2 orders of magnitude higher) by interplanetary particles in comparison with the satellite originated dust. It is inferred that the dust at high altitudes of Mars could be interplanetary in nature and our expectation is in agreement with the MAVEN observation. As a corollary, the mass loss from Martian natural satellites is computed based on the surface erosion by incident projectiles.

  11. Monitoring Niger River Floods from satellite Rainfall Estimates : overall skill and rainfall uncertainty propagation.

    Science.gov (United States)

    Gosset, Marielle; Casse, Claire; Peugeot, christophe; boone, aaron; pedinotti, vanessa

    2015-04-01

    Global measurement of rainfall offers new opportunity for hydrological monitoring, especially for some of the largest Tropical river where the rain gauge network is sparse and radar is not available. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of satellite rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them into the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This paper analyses the potential of satellite rainfall products combined with hydrological modeling to monitor the Niger river floods in the city of Niamey, Niger. A dramatic increase of these floods has been observed in the last decades. The study focuses on the 125000 km2 area in the vicinity of Niamey, where local runoff is responsible for the most extreme floods recorded in recent years. Several rainfall products are tested as forcing to the SURFEX-TRIP hydrological simulations. Differences in terms of rainfall amount, number of rainy days, spatial extension of the rainfall events and frequency distribution of the rain rates are found among the products. Their impacts on the simulated outflow is analyzed. The simulations based on the Real time estimates produce an excess in the discharge. For flood prediction, the problem can be overcome by a prior adjustment of the products - as done here with probability matching - or by analysing the simulated discharge in terms of percentile or anomaly. All tested products exhibit some

  12. Analysis on BDS Satellite Internal Multipath and Its Impact on Wide-lane FCB Estimation

    Directory of Open Access Journals (Sweden)

    RUAN Rengui

    2017-08-01

    Full Text Available To the issue of the satellite internal multipath (SIMP of BeiDou satellites, it proposed and emphasized that the SIMP model should be established as a function of the nadir angle with respect to the observed satellite rather than the elevation of the measurement, so that it can be used for receivers at various altitude. BDS data from global distributed stations operated by the International Monitoring and Assessment System (iGMAS and the Multi-GNSS Experiment (MGEX of the International GNSS Service (IGS are collected and a new SIMP model as a piece-wise linear function of the nadir angle is released for the IGSO-and MEO-satellite groups and for B1, B2 and B3 frequency band individually. The SIMP of GEO,IGSO and MEO satellites is further analyzed with B1/B2 dual-frequency data onboard the FengYun-3 C(FY3C satellite at an altitude of~830 km, and it showed that, for nadir angles smaller than 7°, the SIMP values for GEO is quite close to the IGSO's, especially for B2, which may suggest that the SIMP model for IGSO satellites possibly also works for GEO satellites. It also demonstrated that, when the nadir angle is smaller than 12°for the MEO and 7°for the IGSO, the estimated SIMP model with data from FY3C is considerable consistent with that estimated with data collected at ground stations. Experiments are carried out to investigate the impacts of the SIMP on wide-lane fractional cycle bias (FCB estimation for BDS satellites. The result indicates that, with the correction of the estimated SIMP, the repeatability of the FCB series is significantly improved by more than 60% for all satellites. Specifically, for the MEO and IGSO satellites, the repeatability is smaller than 0.05 cycle; the repeatability of 0.023 and 0.068 cycles achieved for GEO satellites C01 and C02 respectively with the estimated SIMP model for IGSO satellites.

  13. GPS satellite and receiver instrumental biases estimation using least squares method for accurate ionosphere modelling

    Indian Academy of Sciences (India)

    G Sasibhushana Rao

    2007-10-01

    The positional accuracy of the Global Positioning System (GPS)is limited due to several error sources.The major error is ionosphere.By augmenting the GPS,the Category I (CAT I)Precision Approach (PA)requirements can be achieved.The Space-Based Augmentation System (SBAS)in India is known as GPS Aided Geo Augmented Navigation (GAGAN).One of the prominent errors in GAGAN that limits the positional accuracy is instrumental biases.Calibration of these biases is particularly important in achieving the CAT I PA landings.In this paper,a new algorithm is proposed to estimate the instrumental biases by modelling the TEC using 4th order polynomial.The algorithm uses values corresponding to a single station for one month period and the results confirm the validity of the algorithm.The experimental results indicate that the estimation precision of the satellite-plus-receiver instrumental bias is of the order of ± 0.17 nsec.The observed mean bias error is of the order − 3.638 nsec and − 4.71 nsec for satellite 1 and 31 respectively.It is found that results are consistent over the period.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  15. A Fault-tolerance Estimating Method for Ionosphere Corrections in Satellite Navigation System

    Institute of Scientific and Technical Information of China (English)

    GAO Shuliang; LI Rui; HUANG Zhigang

    2011-01-01

    Aiming to the reliable estimates of the ionosphere differential corrections for the satellite navigation system in the presence of the ionosphere anomaly,a fault-tolerance estimating method,which is based on the distributed Kalman filtering,is proposed.The method utilizes the parallel sub-filters for estimating the ionosphere differential corrections.Meanwhile,an infinite norm (IN) method is proposed for the detection of the ionosphere irregularity in the filter processing.Once the anomaly is detected,the sub-filter contaminated by the anomaly measurements will be excluded to ensure the reliability of the estimates.The simulation is conducted to validate the method and the results indicate that the anomaly can be found timely due to the novel fault detection method based on the infinite norm.Because of the parallel sub-filter architecture,the measurements are classified by the spatial distribution so that the ionosphere anomaly can be positioned and excluded more easily.Thus,the method can provide the robust and accurate ionosphere differential corrections.

  16. The electrical conductivity of the upper mantle as estimated from satellite magnetic field data

    Science.gov (United States)

    Didwall, E. M.

    1984-01-01

    The electrical conductivity of the upper mantle is estimated from low-latitude magnetic field variations caused by large fluctuations in the equatorial ring current. The data base is derived from magnetic field magnitude data measured by satellites OGO 2, 4, and 6, which offer better global coverage than land-based observatories. The procedures of analysis consist of: (1) separation of the disturbance field into internal and external parts relative to the surface of the earth, (2) estimation of an electromagnetic response function Q(omega) which relates the internally generated magnetic field variations to the external variations due to the ring current, and (3) interpretation of the estimated response function using theoretical response functions for assumed conductivity profiles. Special consideration is given to possible oceanic and ionospheric effects. Best estimates of the geomagnetic response function Q(omega) for 0.2 to 2.0 cpd indicate an upper mantle conductivity of the order of 0.01 S/m.

  17. The electrical conductivity of the upper mantle as estimated from satellite magnetic field data

    Science.gov (United States)

    Didwall, E. M.

    1984-01-01

    The electrical conductivity of the upper mantle is estimated from low-latitude magnetic field variations caused by large fluctuations in the equatorial ring current. The data base is derived from magnetic field magnitude data measured by satellites OGO 2, 4, and 6, which offer better global coverage than land-based observatories. The procedures of analysis consist of: (1) separation of the disturbance field into internal and external parts relative to the surface of the earth, (2) estimation of an electromagnetic response function Q(omega) which relates the internally generated magnetic field variations to the external variations due to the ring current, and (3) interpretation of the estimated response function using theoretical response functions for assumed conductivity profiles. Special consideration is given to possible oceanic and ionospheric effects. Best estimates of the geomagnetic response function Q(omega) for 0.2 to 2.0 cpd indicate an upper mantle conductivity of the order of 0.01 S/m.

  18. Global Ocean Surveillance With Electronic Intelligence Based Satellite System

    Science.gov (United States)

    Venkatramanan, Haritha

    2016-07-01

    The objective of this proposal is to design our own ELINT based satellite system to detect and locate the target by using satellite Trilateration Principle. The target position can be found by measuring the radio signals arrived at three satellites using Time Difference of Arrival(TDOA) technique. To locate a target it is necessary to determine the satellite position. The satellite motion and its position is obtained by using Simplified General Perturbation Model(SGP4) in MATLAB. This SGP4 accepts satellite Two Line Element(TLE) data and returns the position in the form of state vectors. These state vectors are then converted into observable parameters and then propagated in space. This calculations can be done for satellite constellation and non - visibility periods can be calculated. Satellite Trilateration consists of three satellites flying in formation with each other. The satellite constellation design consists of three satellites with an inclination of 61.3° maintained at equal distances between each other. The design is performed using MATLAB and simulated to obtain the necessary results. The target's position can be obtained using the three satellites ECEF Coordinate system and its position and velocity can be calculated in terms of Latitude and Longitude. The target's motion is simulated to obtain the Speed and Direction of Travel.

  19. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    Science.gov (United States)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, L. Ruby

    2014-12-01

    Estimation of soil organic carbon (SOC) stock using models typically requires long term spin-up of the carbon-nitrogen (CN) models, which has become a bottleneck for global modeling. We report a new numerical approach to estimate global SOC stock that can alleviate long spin-up. The approach uses satellite-based canopy leaf area index (LAI) and takes advantage of a reaction-based biogeochemical module—Next Generation BioGeoChemical Module (NGBGC) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as in CLM4CN, it can be easily configured to run prognostic or steady state simulations. The new approach was applied at point and global scales and compared with SOC derived from spin-up by running NGBGC in the prognostic mode, and SOC from the Harmonized World Soil Database (HWSD). The steady state solution is comparable to the spin-up value when the satellite LAI is close to that from the spin-up solution, and largely captured the global variability of the HWSD SOC across the different dominant plant functional types (PFTs). The correlation between the simulated and HWSD SOC was, however, weak at both point and global scales, suggesting the needs for improving the biogeochemical processes described in CLM4 and updating HWSD. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, which makes the tested approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare multiple aspects simulated by different CN mechanisms in the model.

  20. Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

    Science.gov (United States)

    Li, Zhanqing; Whitlock, Charles H.; Charlock, Thomas P.

    1995-01-01

    Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

  1. Spaceborne GPS receiver antenna phase center offset and variation estimation for the Shiyan 3 satellite

    Directory of Open Access Journals (Sweden)

    Gu Defeng

    2016-10-01

    Full Text Available In determining the orbits of low Earth orbit (LEO satellites using spaceborne GPS, the errors caused by receiver antenna phase center offset (PCO and phase center variations (PCVs are gradually becoming a major limiting factor for continued improvements to accuracy. Shiyan 3, a small satellite mission for space technology experimentation and climate exploration, was developed by China and launched on November 5, 2008. The dual-frequency GPS receiver payload delivers 1 Hz data and provides the basis for precise orbit determination within the range of a few centimeters. The antenna PCO and PCV error characteristics and the principles influencing orbit determination are analyzed. The feasibility of PCO and PCV estimation and compensation in different directions is demonstrated through simulation and in-flight tests. The values of receiver antenna PCO and PCVs for Gravity Recovery and Climate Experiment (GRACE and Shiyan 3 satellites are estimated from one month of data. A large and stable antenna PCO error, reaching up to 10.34 cm in the z-direction, is found with the Shiyan 3 satellite. The PCVs on the Shiyan 3 satellite are estimated and reach up to 3.0 cm, which is slightly larger than that of GRACE satellites. Orbit validation clearly improved with independent k-band ranging (KBR and satellite laser ranging (SLR measurements. For GRACE satellites, the average root mean square (RMS of KBR residuals improved from 1.01 cm to 0.88 cm. For the Shiyan 3 satellite, the average RMS of SLR residuals improved from 4.95 cm to 4.06 cm.

  2. Spaceborne GPS receiver antenna phase center offset and variation estimation for the Shiyan 3 satellite

    Institute of Scientific and Technical Information of China (English)

    Gu Defeng; Lai Yuwang; Liu Junhong; Ju Bing; Tu Jia

    2016-01-01

    In determining the orbits of low Earth orbit (LEO) satellites using spaceborne GPS, the errors caused by receiver antenna phase center offset (PCO) and phase center variations (PCVs) are gradually becoming a major limiting factor for continued improvements to accuracy. Shiyan 3, a small satellite mission for space technology experimentation and climate exploration, was developed by China and launched on November 5, 2008. The dual-frequency GPS receiver payload delivers 1 Hz data and provides the basis for precise orbit determination within the range of a few centime-ters. The antenna PCO and PCV error characteristics and the principles influencing orbit determi-nation are analyzed. The feasibility of PCO and PCV estimation and compensation in different directions is demonstrated through simulation and in-flight tests. The values of receiver antenna PCO and PCVs for Gravity Recovery and Climate Experiment (GRACE) and Shiyan 3 satellites are estimated from one month of data. A large and stable antenna PCO error, reaching up to 10.34 cm in the z-direction, is found with the Shiyan 3 satellite. The PCVs on the Shiyan 3 satellite are estimated and reach up to 3.0 cm, which is slightly larger than that of GRACE satellites. Orbit validation clearly improved with independent k-band ranging (KBR) and satellite laser ranging (SLR) measurements. For GRACE satellites, the average root mean square (RMS) of KBR resid-uals improved from 1.01 cm to 0.88 cm. For the Shiyan 3 satellite, the average RMS of SLR resid-uals improved from 4.95 cm to 4.06 cm.

  3. Controlling the Chaos Using Fuzzy Estimation in a Gyrostat Satellite

    Science.gov (United States)

    Guran, Ardeshir

    In this paper, we present a study of the dynamical behavior in a Kelvin type gyrostat satellite. We firstly obtain the Hamiltonian equations of our model by using Cardan angles as generalized coordinates. Then, we make this Hamiltonian dimensionless and calculate motion equations for this dimensionless system. The study of the Poincare's sections of this system shows us that chaotic motion regimes are present for specific parameter values. The main goal of this work is the finding of stabilizing orbits by using a control technique, the fuzzy control of Poincare map method, so that it can be applied to stabilize special periodic orbits in this system. Finally, we expect that the technique can be useful for a better understanding of control theory and their applications in gyrostat problems.

  4. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  5. Parameterization of oceanic whitecap fraction based on satellite observations

    Directory of Open Access Journals (Sweden)

    M. F. M. A. Albert

    2015-08-01

    Full Text Available In this study the utility of satellite-based whitecap fraction (W values for the prediction of sea spray aerosol (SSA emission rates is explored. More specifically, the study is aimed at improving the accuracy of the sea spray source function (SSSF derived by using the whitecap method through the reduction of the uncertainties in the parameterization of W by better accounting for its natural variability. The starting point is a dataset containing W data, together with matching environmental and statistical data, for 2006. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz. A global scale assessment of the data set to evaluate the wind speed dependence of W revealed a quadratic correlation between W and U10, as well as a relatively larger spread in the 37 GHz data set. The latter could be attributed to secondary factors affecting W in addition to U10. To better visualize these secondary factors, a regional scale assessment over different seasons was performed. This assessment indicates that the influence of secondary factors on W is for the largest part imbedded in the exponent of the wind speed dependence. Hence no further improvement can be expected by looking at effects of other factors on the variation in W explicitly. From the regional analysis, a new globally applicable quadratic W(U10 parameterization was derived. An intrinsic correlation between W and U10 that could have been introduced while estimating W from TB was determined, evaluated and presumed to lie within the error margins of the newly derived W(U10 parameterization. The satellite-based parameterization was compared to parameterizations from other studies and was applied in a SSSF to estimate the global SSA emission rate. The thus obtained SSA production for 2006 of 4.1 × 1012 kg is within previously reported estimates. While recent studies that account for

  6. An Objective TC Intensity Estimation Method Based on Satellite Data%基于卫星资料进行热带气旋强度客观估算

    Institute of Scientific and Technical Information of China (English)

    鲁小琴; 雷小途; 余晖; 赵兵科

    2014-01-01

    Researches prove that TC (tropical cyclone)intensity is mainly determined by the top cloud convection strength,distribution and size.Then how to extract this information from TC cloud image is very impor-tant for TC intensity estimation.In 1988,Adler put forward a method named CST (convective-stratiform technique)to extract tropical convective cores from TC cloud image.Using MTSAT (multi-functional transport satellite)IR1 black body temperature data,the TC cloud top strong convection is extracted. Based on the convective cores number,convective core distance to TC center and convective core black body temperature extreme value,which are closely related to TC intensity,a TC intensity (expressed by V max ,the maximum sustained wind speed near surface TC center)estimation model is put forward using stepwise regress method.The experiment result shows that there is a linear correlation between their esti-mation error and their intensity forV max>40 m·s-1 andV max Statistical tests show this model is equivalent to Dvorak method and AMSU in TC intensity estimation accuracy.It’s also reliable based on the relationship between the convective cores,convective cores distri-bution,brightness temperature and TC intensity.It could be used in all TC life span automatically and ob-jectively,so it could be applied in the operation. Comparing with the advanced objective dvorak technique (AODT)and objective Dvorak technique (ODT),this algorithm gives accurate results in the Western North Pacific,but it’s simpler with no com-plicated pattern types identifying process or other rules.A fixed radius of 135 km area is used as TC con-vective cores searching effective area in the model,but actually the maximum wind speed radius of the TC is variable,the TC size and the strongest convective area size are different for different TC in different stage.So using the fixed searching area may affect TC intensity estimation accuracy.The research on how to get the dynamical maximum wind speed

  7. RICE YIELD ESTIMATION THROUGH ASSIMILATING SATELLITE DATA INTO A CROP SIMUMLATION MODEL

    Directory of Open Access Journals (Sweden)

    N. T. Son

    2016-06-01

    Full Text Available Rice is globally the most important food crop, feeding approximately half of the world’s population, especially in Asia where around half of the world’s poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government’s yield statistics indicated the root mean square error (RMSE of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  8. Rice Yield Estimation Through Assimilating Satellite Data Into a Crop Simumlation Model

    Science.gov (United States)

    Son, N. T.; Chen, C. F.; Chen, C. R.; Chang, L. Y.; Chiang, S. H.

    2016-06-01

    Rice is globally the most important food crop, feeding approximately half of the world's population, especially in Asia where around half of the world's poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT) for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO) algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI) and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount) in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government's yield statistics indicated the root mean square error (RMSE) of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  9. An empirical method of RH correction for satellite estimation of ground-level PM concentrations

    Science.gov (United States)

    Wang, Zifeng; Chen, Liangfu; Tao, Jinhua; Liu, Yang; Hu, Xuefei; Tao, Minghui

    2014-10-01

    A hygroscopic growth model suitable for local aerosol characteristics and their temporal variations is necessary for accurate satellite retrieval of ground-level particulate matters (PM). This study develops an empirical method to correct the relative humidity (RH) impact on aerosol extinction coefficient and to further derive PM concentrations from satellite observations. Not relying on detailed information of aerosol chemical and microphysical properties, this method simply uses the in-situ observations of visibility (VIS), RH and PM concentrations to characterize aerosol hygroscopicity, and thus makes the RH correction capable of supporting the satellite PM estimations with large spatial and temporal coverage. In this method, the aerosol average mass extinction efficiency (αext) is used to describe the general hygroscopic growth behaviors of the total aerosol populations. The association between αext and RH is obtained through empirical model fitting, and is then applied to carry out RH correction. Nearly one year of in-situ measurements of VIS, RH and PM10 in Beijing urban area are collected for this study and RH correction is made for each of the months with sufficient data samples. The correlations between aerosol extinction coefficients and PM10 concentrations are significantly improved, with the monthly correlation R2 increasing from 0.26-0.63 to 0.49-0.82, as well as the whole dataset's R2 increasing from 0.36 to 0.68. PM10 concentrations are retrieved through RH correction and validated for each season individually. Good agreements between the retrieved and observed PM10 concentrations are found in all seasons, with R2 ranging from 0.54 in spring to 0.73 in fall, and the mean relative errors ranging from -2.5% in winter to -10.8% in spring. Based on the satellite AOD and the model simulated aerosol profiles, surface PM10 over Beijing area is retrieved through the RH correction. The satellite retrieved PM10 and those observed at ground sites agree well

  10. Multiple satellite estimates of urban fractions and climate effects at regional scale

    Science.gov (United States)

    Jia, G.; Xu, R.; He, Y.

    2014-12-01

    Regional climate is controlled by large scale forcing at lateral boundary and physical processes within the region. Landuse in East Asia has been changed substantially in the last three decades, featured with expansion of urban built-up at unprecedented scale and speed. The fast expansion of urban areas could contribute to local even regional climate change. However, current spatial datasets of urban fractions do not well represent extend and expansion of urban areas in the regions, and the best available satellite data and remote sensing techniques have not been well applied to serve regional modeling of urbanization impacts on near surface temperature and other climate variables. Better estimates of localized urban fractions and urban climate effects are badly needed. Here we use high and mid resolution satellite data to estimate urban fractions and to assess effects of urban heat islands at local and regional scales. With our fractional cover, data fusion, and differentiated threshold approaches, estimated urban extent was greater than previously reported in many global datasets. Many city clusters were merging into each other, with gradual blurring boundaries and disappearing of gaps among member cities. Cities and towns were more connected with roads and commercial corridors, while wildland and urban greens became more isolated as patches among built-up areas. Those new estimates are expected to effectively improve climate simulation at local and regional scales in East Asia. There were significant positive relations between urban fraction and urban heat island effects as demonstrated by VNIR and TIR data from multiple satellites. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in

  11. Estimating the impact of satellite observations on large-scale river flood forecasting

    Science.gov (United States)

    Andreadis, Konstantinos; Schumann, Guy

    2014-05-01

    Floods are one of the costliest natural disasters, posing severe risks to human population. Hydraulic models are able to predict flood characteristics, such as water surface elevations and inundated area, and are being used for forecasting operationally although there are many uncertainties. In this work, the potential value of satellite observations to initialize these hydraulic models (and their forecasts correspondingly) is explored. The Ensemble Sensitivity method is adapted to evaluate the impact of potential satellite observations on the forecasting of flood characteristics. The estimation of the impact is based on the Local Ensemble Transform Kalman Filter, allowing for the forecast error reductions to be computed without additional model runs. The study area was located in the Ohio River basin, and the model used was the LISFLOOD-FP hydrodynamic model. The experimental design consisted of two configurations of the LISFLOOD-FP model. The first (baseline) simulation represents a calibrated 'best effort' model based on a sub-grid channel structure using observations for parameters and boundary conditions, whereas the second (background) simulation consists of estimated parameters and SRTM-based boundary conditions. Results showed that the forecast skill was improved for water heights up to lead times of 11 days, while even partial observations of the river contained information for the entire river's water surface profile and allowed forecasting 5 to 7 days ahead. On the other hand, discharge forecasts were not improved as much when assimilating water height observations although forecast errors were reduced. Finally, the potential for identifying errors in the model structure and parameterizations via the ensemble sensitivity method is discussed.

  12. Multi-satellite rainfall sampling error estimates – a comparative study

    Directory of Open Access Journals (Sweden)

    A. Loew

    2012-10-01

    Full Text Available This study focus is set on quantifying sampling related uncertainty in the satellite rainfall estimates. We conduct observing system simulation experiment to estimate sampling error for various constellations of Low-Earth orbiting and geostationary satellites. There are two types of microwave instruments currently available: cross track sounders and conical scanners. We evaluate the differences in sampling uncertainty for various satellite constellations that carry instruments of the common type as well as in combination with geostationary observations. A precise orbital model is used to simulate realistic satellite overpasses with orbital shifts taken into account. With this model we resampled rain gauge timeseries to simulate satellites rainfall estimates free of retrieval and calibration errors. We concentrate on two regions, Germany and Benin, areas with different precipitation regimes. Our results show that sampling uncertainty for all satellite constellations does not differ greatly depending on the area despite the differences in local precipitation patterns. Addition of 3 hourly geostationary observations provides equal performance improvement in Germany and Benin, reducing rainfall undersampling by 20–25% of the total rainfall amount. Authors do not find a significant difference in rainfall sampling between conical imager and cross-track sounders.

  13. Global top-down smoke aerosol emissions estimation using satellite fire radiative power measurements

    Directory of Open Access Journals (Sweden)

    C. Ichoku

    2013-10-01

    Full Text Available Biomass burning occurs seasonally in most vegetated parts of the world, consuming large amounts of biomass fuel, generating intense heat energy, and emitting corresponding amounts of smoke plumes that comprise different species of aerosols and trace gases. Accurate estimates of these emissions are required as model inputs to evaluate and forecast smoke plume transport and impacts on air quality, human health, clouds, weather, radiation, and climate. Emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. Fortunately, a series of recent studies have revealed that both the rate of biomass consumption and the rate of emission of aerosol particulate matter (PM by open biomass burning are directly proportional to the rate of release of fire radiative energy (FRE, which is fire radiative power (FRP that is measurable from satellite. This direct relationship enables the determination of coefficients of emission (Ce, which can be used to convert FRP or FRE to smoke aerosol emissions in the same manner as emission factors (EFs are used to convert burned biomass to emissions. We have leveraged this relationship to generate the first global 1° × 1° gridded Ce product for smoke aerosol or total particulate matter (TPM emissions using coincident measurements of FRP and aerosol optical thickness (AOT from the Moderate-resolution Imaging Spectro-radiometer (MODIS sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1 Ce product has now been released to the community and can be obtained from http://feer.gsfc.nasa.gov/, along with the corresponding 1-to-1 mapping of their quality assurance (QA flags that will enable the Ce values to be filtered by quality for use in various applications. The regional averages of Ce values for different ecosystem types were found to be in the ranges of: 16–21 g MJ−1 for savanna

  14. Satellite-Based EMI Detection, Identification, and Mitigation

    Science.gov (United States)

    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.

  15. Estimating stream discharge from a Himalayan Glacier using coupled satellite sensor data

    Science.gov (United States)

    Child, S. F.; Stearns, L. A.; van der Veen, C. J.; Haritashya, U. K.; Tarpanelli, A.

    2015-12-01

    The 4th IPCC report highlighted our limited understanding of Himalayan glacier behavior and contribution to the region's hydrology. Seasonal snow and glacier melt in the Himalayas are important sources of water, but estimates greatly differ about the actual contribution of melted glacier ice to stream discharge. A more comprehensive understanding of the contribution of glaciers to stream discharge is needed because streams being fed by glaciers affect the livelihoods of a large part of the world's population. Most of the streams in the Himalayas are unmonitored because in situ measurements are logistically difficult and costly. This necessitates the use of remote sensing platforms to obtain estimates of river discharge for validating hydrological models. In this study, we estimate stream discharge using cost-effective methods via repeat satellite imagery from Landsat-8 and SENTINEL-1A sensors. The methodology is based on previous studies, which show that ratio values from optical satellite bands correlate well with measured stream discharge. While similar, our methodology relies on significantly higher resolution imagery (30 m) and utilizes bands that are in the blue and near-infrared spectrum as opposed to previous studies using 250 m resolution imagery and spectral bands only in the near-infrared. Higher resolution imagery is necessary for streams where the source is a glacier's terminus because the width of the stream is often only 10s of meters. We validate our methodology using two rivers in the state of Kansas, where stream gauges are plentiful. We then apply our method to the Bhagirathi River, in the North-Central Himalayas, which is fed by the Gangotri Glacier and has a well monitored stream gauge. The analysis will later be used to couple river discharge and glacier flow and mass balance through an integrated hydrologic model in the Bhagirathi Basin.

  16. Estimating the global surface area of rivers and streams using satellite imagery

    Science.gov (United States)

    Allen, George; Pavelsky, Tamlin

    2017-04-01

    Global observational assessments of river and stream systems are based largely on gauge station data, which are fragmented and often limited to country-level statistics. This limitation severely impedes our understanding of global-scale hydrologic, geomorphic, and biogeochemical fluvial processes. In contrast, satellite remote sensing data provide a globally-consistent and spatially-continuous tool for studying rivers. Here we present a novel method estimate the total surface area of all rivers and stream globally using measurements from the recently-developed Global River Widths from Landsat (GRWL) database and field surveys. The surface area of rivers and streams is a key model parameter in global evaluations of greenhouse gas emissions from inland waters. Preliminary analysis suggests that rivers occupy a total area of 80 thousand square kilometers, or 0.58% of Earth's land surface. This result is 30% greater than the previous best estimate that is based on digital elevation models and gauge station measurements. Compared to previous regional assessments, we find that rivers and streams occupy a greater proportion of the land surface in the arctic and in the tropics, and a lower proportion of land surface in the United States and in Europe. Our results suggest that current estimates of greenhouse gas emissions from inland waters should be revised upwards to account for the greater abundance of river and stream surface area.

  17. Employing satellite retrieved soil moisture for parameter estimation of the hydrologic model mHM

    Science.gov (United States)

    Zink, Matthias; Mai, Juliane; Rakovec, Oldrich; Schrön, Martin; Kumar, Rohini; Schäfer, David; Samaniego, Luis

    2016-04-01

    Hydrological models are usually calibrated against observed streamflow at the catchment outlet and thus they are conditioned by an integral catchment signal. Rakovec et al. 2016 (JHM) recently demonstrated that constraining model parameters against river discharge is a necessary, but not a sufficient condition. Such a procedure ensures the fulfillment of the catchment's water balance but can lead to high predictive uncertainties of model internal states, like soil moisture, or a lack in spatial representativeness of the model. However, some hydrologic applications, as e.g. soil drought monitoring and prediction, rely on this information. Within this study we propose a framework in which the mesoscale Hydrologic Model (mHM) is calibrated with soil moisture retrievals from various sources. The aim is to condition the model on soil moisture (SM), while preserving good performance in streamflow estimation. We identify the most appropriate objective functions by conducting synthetic experiments. The best objective function is determined based on: 1) deviation between synthetic and simulated soil moisture, 2) nonparametric comparison of SM fields (e.g. copulas), and 3) by euclidian distance of model parameters, which is zero if the parameters of the synthetic data are recovered. Those objective functions performing best are used to calibrate mHM against different satellite soil moisture products, e.g. ESA-CCI, H-SAF, and in situ observations. This procedure is tested in three distinct European basins (upper Sava, Neckar, and upper Guadalquivir basin) ranging from snow domination to semi arid climatic conditions. Results obtained with the synthetic experiment indicate that objective functions focusing on the temporal dynamics of SM are preferable to objective functions aiming at spatial patterns or catchment averages. Since the deviation of soil moisture fields (1) and their copulas (2) don't lead to conclusive results, the decision of the best performing objective

  18. Efficiency assessment of using satellite data for crop area estimation in Ukraine

    Science.gov (United States)

    Gallego, Francisco Javier; Kussul, Nataliia; Skakun, Sergii; Kravchenko, Oleksii; Shelestov, Andrii; Kussul, Olga

    2014-06-01

    The knowledge of the crop area is a key element for the estimation of the total crop production of a country and, therefore, the management of agricultural commodities markets. Satellite data and derived products can be effectively used for stratification purposes and a-posteriori correction of area estimates from ground observations. This paper presents the main results and conclusions of the study conducted in 2010 to explore feasibility and efficiency of crop area estimation in Ukraine assisted by optical satellite remote sensing images. The study was carried out on three oblasts in Ukraine with a total area of 78,500 km2. The efficiency of using images acquired by several satellite sensors (MODIS, Landsat-5/TM, AWiFS, LISS-III, and RapidEye) combined with a field survey on a stratified sample of square segments for crop area estimation in Ukraine is assessed. The main criteria used for efficiency analysis are as follows: (i) relative efficiency that shows how much time the error of area estimates can be reduced with satellite images, and (ii) cost-efficiency that shows how much time the costs of ground surveys for crop area estimation can be reduced with satellite images. These criteria are applied to each satellite image type separately, i.e., no integration of images acquired by different sensors is made, to select the optimal dataset. The study found that only MODIS and Landsat-5/TM reached cost-efficiency thresholds while AWiFS, LISS-III, and RapidEye images, due to its high price, were not cost-efficient for crop area estimation in Ukraine at oblast level.

  19. Observer-based Satellite Attitude Control and Simulation Researches

    Institute of Scientific and Technical Information of China (English)

    王子才; 马克茂

    2002-01-01

    Observer design method is applied to the realization of satellite attitude control law baaed on simplified control model. Exact mathematical model of the satellite attitude control system is also constructed, together with the observer-based control law, to conduct simulation research. The simulation results justify the effectiveness andfeasibility of the observer-based control method.

  20. Temporal scaling analysis of irradiance estimated from daily satellite data and numerical modelling

    Science.gov (United States)

    Vindel, Jose M.; Navarro, Ana A.; Valenzuela, Rita X.; Ramírez, Lourdes

    2016-11-01

    The temporal variability of global irradiance estimated from daily satellite data and numerical models has been compared for different spans of time. According to the time scale considered, a different behaviour can be expected for each climate. Indeed, for all climates and at small scale, the persistence decreases as this scale increases, but the mediterranean climate, and its continental variety, shows higher persistence than oceanic climate. The probabilities of maintaining the values of irradiance after a certain period of time have been used as a first approximation to analyse the quality of each source, according to the climate. In addition, probability distributions corresponding to variations of clearness indices measured at several stations located in different climate zones have been compared with those obtained from satellite and modelling estimations. For this work, daily radiation data from the reanalysis carried out by the European Centre for Medium-Range Weather Forecasts and from the Satellite Application Facilities on climate monitoring have been used for mainland Spain. According to the results, the temporal series estimation of irradiance is more accurate when using satellite data, independent of the climate considered. In fact, the coefficients of determination corresponding to the locations studied are always above 0.92 in the case of satellite data, while this coefficient decreases to 0.69 for some cases of the numerical model. This conclusion is more evident in oceanic climates, where the most important errors can be observed. Indeed, in this case, the RRMSE derived from the CM-SAF estimations is 20.93%, while in the numerical model, it is 48.33%. Analysis of the probabilities corresponding to variations in the clearness indices also shows a better behaviour of the satellite-derived estimates for oceanic climate. For the standard mediterranean climate, the satellite also provides better results, though the numerical model improves

  1. Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

    Directory of Open Access Journals (Sweden)

    Z. Hasirci

    2016-04-01

    Full Text Available Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ray tracing method. It is showed that different geometrical shapes have different vegetation depths even if they have same foliage volume for different elevation angles. The proposed method is validated with the related literature in terms of average single tree attenuation. On the other hand, due to decrease system requirements (speed, memory usage etc. of ray tracing method, an artificial neural network is proposed as an alternative. A graphical user interface is created for the above processes in MATLAB environment named vegetation depth estimation tool (VdET.

  2. SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-11-01

    To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004-2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (disadvantage of our method is that the mixture of several crops in a grid is not considered in SACRA. The assumption of one dominant crop in each grid is a major source of discrepancy in crop calendars between SACRA and other products. The disadvantages of our approach may be reduced with future improvements based on finer satellite sensors and crop-type classification studies to consider several dominant crops in each grid. The comparison of the CC also demonstrates that identification of wheat type (sowing in spring or fall) is a major source of

  3. Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

    Science.gov (United States)

    Robertson, Franklin R.; Marshall, Susan; Roads, John; Oglesby, Robert J.; Fitzjarrald, Dan; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

  4. Discrepant estimates of primary and export production from satellite algorithms, a biogeochemical model, and geochemical tracer measurements in the North Pacific Ocean

    Science.gov (United States)

    Palevsky, Hilary I.; Quay, Paul D.; Nicholson, David P.

    2016-08-01

    Estimates of primary and export production (PP and EP) based on satellite remote sensing algorithms and global biogeochemical models are widely used to provide year-round global coverage not available from direct observations. However, observational data to validate these approaches are limited. We find that no single satellite algorithm or model can reproduce seasonal and annual geochemically determined PP, export efficiency (EP/PP), and EP rates throughout the North Pacific basin, based on comparisons throughout the full annual cycle at time series stations in the subarctic and subtropical gyres and basin-wide regions sampled by container ship transects. The high-latitude regions show large PP discrepancies in winter and spring and strong effects of deep winter mixed layers on annual EP that cannot be accounted for in current satellite-based approaches. These results underscore the need to evaluate satellite- and model-based estimates using multiple productivity parameters measured over broad ocean regions throughout the annual cycle.

  5. Lava discharge rate estimates from thermal infrared satellite data for Pacaya Volcano during 2004-2010

    Science.gov (United States)

    Morgan, Hilary A.; Harris, Andrew J. L.; Gurioli, Lucia

    2013-08-01

    Pacaya is one of the most active volcanoes in Central America and has produced lava flows frequently since 1961. All effusive activity between 1961 and 2009 was confined by an arcuate collapse scarp surrounding the northern and eastern flanks. However, the recent breaching of this topographic barrier, and the eruption of a large lava flow outside of the main center of activity, have allowed lava to extend into nearby populated areas, indicating the need for assessment and monitoring of lava flow hazards. We investigated whether a commonly used satellite-based model could produce accurate lava discharge rates for the purpose of near-real-time assessment of hazards during future eruptions and to assess the dynamics of this persistently degassing system. The model assumes a linear relationship between active lava flow area and time-averaged discharge rate (TADR) via a simple conversion factor. We calculated the conversion factor via two methods: (1) best-fitting of satellite-derived flow areas to ground-based estimates of lava flow volume, and (2) theoretically via a parameterized model that takes into account the physical properties of the lava. To apply the latter method, we sampled four lava flows and measured density, vesicularity, crystal content, and major element composition. We found the best agreement of conversion factors in the eruption with the most complete satellite coverage, and used data for these flows to define the linear relationship between area and discharge rate. The physical properties of the sampled flows were essentially identical, so that any discrepancy between the two methods of calculating conversion factors must be due to modeling errors or environmental factors unaccounted for by the parameterized model. However, our best-fitting method provides a new means to set the conversion appropriately, and to obtain self-consistent TADRs. We identified two distinct types of effusive activity at Pacaya: Type 1 activity characterized by initially

  6. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information

    Science.gov (United States)

    Behrangi, Ali

    In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation

  7. Geothermal Heat Flux Underneath Ice Sheets Estimated From Magnetic Satellite Data

    DEFF Research Database (Denmark)

    Fox Maule, Cathrine; Purucker, M.E.; Olsen, Nils

    The geothermal heat flux is an important factor in the dynamics of ice sheets, and it is one of the important parameters in the thermal budgets of subglacial lakes. We have used satellite magnetic data to estimate the geothermal heat flux underneath the ice sheets in Antarctica and Greenland....... By using satellite data, we are able to make heat flux maps covering the entire Antarctic continent and all of Greenland. We find that the heat flux varies from less than 50 to more than 150~mW/m2 underneath the ice sheets. To validate our results, we have compared our heat flux estimate with geologic...

  8. Pico satellite attitude estimation via Robust Unscented Kalman Filter in the presence of measurement faults.

    Science.gov (United States)

    Soken, Halil Ersin; Hajiyev, Chingiz

    2010-07-01

    In the normal operation conditions of a pico satellite, a conventional Unscented Kalman Filter (UKF) gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunction in the estimation system, UKF gives inaccurate results and diverges by time. This study introduces Robust Unscented Kalman Filter (RUKF) algorithms with the filter gain correction for the case of measurement malfunctions. By the use of defined variables named as measurement noise scale factor, the faulty measurements are taken into consideration with a small weight, and the estimations are corrected without affecting the characteristics of the accurate ones. Two different RUKF algorithms, one with single scale factor and one with multiple scale factors, are proposed and applied for the attitude estimation process of a pico satellite. The results of these algorithms are compared for different types of measurement faults in different estimation scenarios and recommendations about their applications are given.

  9. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban

    2012-06-01

    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

  10. Estimating Carbon STOCK Changes of Mangrove Forests Using Satellite Imagery and Airborne LiDAR Data in the South Sumatra State, Indonesia

    Science.gov (United States)

    Maeda, Y.; Fukushima, A.; Imai, Y.; Tanahashi, Y.; Nakama, E.; Ohta, S.; Kawazoe, K.; Akune, N.

    2016-06-01

    The purposes of this study were 1) to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2) to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1) Classification of types of tree species using Satellite imagery in the study area, (2) Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3) Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.

  11. ESTIMATING CARBON STOCK CHANGES OF MANGROVE FORESTS USING SATELLITE IMAGERY AND AIRBORNE LiDAR DATA IN THE SOUTH SUMATRA STATE, INDONESIA

    Directory of Open Access Journals (Sweden)

    Y. Maeda

    2016-06-01

    Full Text Available The purposes of this study were 1 to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2 to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1 Classification of types of tree species using Satellite imagery in the study area, (2 Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3 Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.

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

    NARCIS (Netherlands)

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

    2007-01-01

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

  13. Estimation of vegetation cover resilience from satellite time series

    Directory of Open Access Journals (Sweden)

    T. Simoniello

    2008-07-01

    Full Text Available Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity.

    In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis

  14. Radio occultation based on BeiDou satellite navigation

    Science.gov (United States)

    Jiang, Hu; Hu, Haiying; Shen, Xue-min; Gong, Wenbin; Zhang, Yonghe

    2014-11-01

    With the development of GNSS systems, it has become a tendency that radio occultation is used to sense the Earth's atmosphere. By this means, the moisture, temperature, pressure, and total electron content can be derived. Based on the sensing results, more complicated models for atmosphere might come into being. Meteorology well benefits from this technology. As scheduled, the BD satellite navigation system will have a worldwide coverage by the end of 2020. Radio occultation studies in China have been highlighted in the recent decade. More and more feasibilities reports have been published in either domestic or international journals. Herein, some scenarios are proposed to assess the coverage of radio occultation based on two different phases of BD satellite navigation system. Phase one for BD is composed of GEO,IGSO and several MEO satellites. Phase two for BD consists mostly of 24 MEO satellites, some GEO and IGSO satellites. The characteristics of radio occultation based on these two phases are presented respectively.

  15. Using pan-sharpened high resolution satellite data to improve impervious surfaces estimation

    Science.gov (United States)

    Xu, Ru; Zhang, Hongsheng; Wang, Ting; Lin, Hui

    2017-05-01

    Impervious surface is an important environmental and socio-economic indicator for numerous urban studies. While a large number of researches have been conducted to estimate the area and distribution of impervious surface from satellite data, the accuracy for impervious surface estimation (ISE) is insufficient due to high diversity of urban land cover types. This study evaluated the use of panchromatic (PAN) data in very high resolution satellite image for improving the accuracy of ISE by various pan-sharpening approaches, with a further comprehensive analysis of its scale effects. Three benchmark pan-sharpening approaches, Gram-Schmidt (GS), PANSHARP and principal component analysis (PCA) were applied to WorldView-2 in three spots of Hong Kong. The on-screen digitization were carried out based on Google Map and the results were viewed as referenced impervious surfaces. The referenced impervious surfaces and the ISE results were then re-scaled to various spatial resolutions to obtain the percentage of impervious surfaces. The correlation coefficient (CC) and root mean square error (RMSE) were adopted as the quantitative indicator to assess the accuracy. The accuracy differences between three research areas were further illustrated by the average local variance (ALV) which was used for landscape pattern analysis. The experimental results suggested that 1) three research regions have various landscape patterns; 2) ISE accuracy extracted from pan-sharpened data was better than ISE from original multispectral (MS) data; and 3) this improvement has a noticeable scale effects with various resolutions. The improvement was reduced slightly as the resolution became coarser.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    modeling to develop procedures and best practices for satellite based wind resource assessment offshore. All existing satellite images from the Envisat Advanced SAR sensor by the European Space Agency (2002-12) have been collected over a domain in the South China Sea. Wind speed is first retrieved from...

  17. Lower satellite-gravimetry estimates of Antarctic sea-level contribution.

    Science.gov (United States)

    King, Matt A; Bingham, Rory J; Moore, Phil; Whitehouse, Pippa L; Bentley, Michael J; Milne, Glenn A

    2012-11-22

    Recent estimates of Antarctica's present-day rate of ice-mass contribution to changes in sea level range from 31 gigatonnes a year (Gt yr(-1); ref. 1) to 246 Gt yr(-1) (ref. 2), a range that cannot be reconciled within formal errors. Time-varying rates of mass loss contribute to this, but substantial technique-specific systematic errors also exist. In particular, estimates of secular ice-mass change derived from Gravity Recovery and Climate Experiment (GRACE) satellite data are dominated by significant uncertainty in the accuracy of models of mass change due to glacial isostatic adjustment (GIA). Here we adopt a new model of GIA, developed from geological constraints, which produces GIA rates systematically lower than those of previous models, and an improved fit to independent uplift data. After applying the model to 99 months (from August 2002 to December 2010) of GRACE data, we estimate a continent-wide ice-mass change of -69 ± 18 Gt yr(-1) (+0.19 ± 0.05 mm yr(-1) sea-level equivalent). This is about a third to a half of the most recently published GRACE estimates, which cover a similar time period but are based on older GIA models. Plausible GIA model uncertainties, and errors relating to removing longitudinal GRACE artefacts ('destriping'), confine our estimate to the range -126 Gt yr(-1) to -29 Gt yr(-1) (0.08-0.35 mm yr(-1) sea-level equivalent). We resolve 26 independent drainage basins and find that Antarctic mass loss, and its acceleration, is concentrated in basins along the Amundsen Sea coast. Outside this region, we find that West Antarctica is nearly in balance and that East Antarctica is gaining substantial mass.

  18. Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

    Directory of Open Access Journals (Sweden)

    Mohammad Zahidul H. Bhuiyan

    2010-01-01

    Full Text Available Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS, such as the Global Positioning System (GPS or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s, phase(s, and delay(s of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK- and Sine Binary Offset Carrier- (SinBOC- modulated signals is also analyzed in closed loop model with the new Composite

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

    Science.gov (United States)

    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

  20. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    Science.gov (United States)

    Qayyum, A.; Malik, A. S.; Saad, M. N. M.; Iqbal, M.; Abdullah, F.; Rahseed, W.; Abdullah, T. A. R. B. T.; Ramli, A. Q.

    2015-04-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites' imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.

  1. Potential-field estimation from satellite data using scalar and vector Slepian functions

    CERN Document Server

    Plattner, Alain

    2013-01-01

    In the last few decades a series of increasingly sophisticated satellite missions has brought us gravity and magnetometry data of ever improving quality. To make optimal use of this rich source of information on the structure of Earth and other celestial bodies, our computational algorithms should be well matched to the specific properties of the data. In particular, inversion methods require specialized adaptation if the data are only locally available, their quality varies spatially, or if we are interested in model recovery only for a specific spatial region. Here, we present two approaches to estimate potential fields on a spherical Earth, from gradient data collected at satellite altitude. Our context is that of the estimation of the gravitational or magnetic potential from vector-valued measurements. Both of our approaches utilize spherical Slepian functions to produce an approximation of local data at satellite altitude, which is subsequently transformed to the Earth's spherical reference surface. The ...

  2. Uncertainty Estimates of NASA Satellite LST over the Greenland and Antarctic Plateau: 2003-2015

    Science.gov (United States)

    Knuteson, R.; Borbas, E. E.; Burgess, G.

    2015-12-01

    Jin and Dickinson (2010) identify three reasons why LST has not been adopted as a climate variable. Paraphrasing the authors, the three roadblocks for use of satellite LST products in climate studies are; 1) unknown accuracy (What are surface emissivity and atmospheric correction uncertainties?)2) spatial scale ambiguity (Are satellite footprints too large to be physically meaningful?)3) lack of consistency over decadal time scales (How far backward/forward can we go in time?). These issues apply particularly to the cryosphere where the lack of surface measurement sites make the proper use of satellite observations critical for monitoring climate change. This paper will address each of these three issues but with a focus on the high and dry Greenland and Antarctic plateaus and the contrast in trends between the two. Recent comparisons of MODIS LST products with AIRS version 6 LST products show large differences over Greenland (Lee et al. 2014). In this paper we take the logical next step of creating a bottoms up uncertainty budget for a new synergistic AIRS/MODIS LST product for ice and snow conditions. This new product will address the issue of unknown accuracy by providing a local LST uncertainty along with each estimate of surface temperature. The combination of the high spatial resolution of the MODIS and the high spectral resolution of the AIRS observations of radiance allow the combination of the two sensors to provide information with lower uncertainty than what is possible from the current separate operational products. The issue of surface emissivity and atmospheric correction uncertainties will be addressed explicitly using spectrally resolved models that cover the infrared region. The issue of spatial scale ambiguity is overcome by creating a classification of the results based on the spatial homogenity of surface temperatures. The issue of lack of consistency over long time scales is addressed by demonstrating an algorithm using collocated NASA MODIS

  3. Global trends in satellite-based emergency mapping.

    Science.gov (United States)

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

    2016-07-15

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

  4. Global trends in satellite-based emergency mapping

    Science.gov (United States)

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

    2016-01-01

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

  5. Global trends in satellite-based emergency mapping

    Science.gov (United States)

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

    2016-07-01

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

  6. Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data

    NARCIS (Netherlands)

    Shen, F.; Verhoef, W.; Zhou, Y.; Salama, M.S.; Liu, X.

    2010-01-01

    The Changjiang (Yangtze) estuarine and coastal waters are characterized by suspended sediments over a wide range of concentrations from 20 to 2,500 mg l-1. Suspended sediment plays important roles in the estuarine and coastal system and environment. Previous algorithms for satellite estimates of sus

  7. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

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

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  8. Stochastic estimation of dynamically changing object orientation parameters using satellite measurements

    OpenAIRE

    Lukasevich, V. I.; Kramarov, S. O.; Sokolov, Sergey V.

    2015-01-01

    It is solved a problem of a posteriori estimation of dynamically modified parameters of angular movement of the object by satellite measurements. There are shown advantages of application of the methods of stochastic non-linear dynamic filtration before single-stage measurements. It is represented an example, showing efficiency of proposed approach.

  9. Combining satellite altimetry and gravimetry data to improve Antarctic mass balance and gia estimates

    NARCIS (Netherlands)

    Gunter, B.C.; Didova, O.; Riva, R.E.M.; van den Broeke, M.R.; Ligtenberg, S.R.M.; Lenaerts, J.T.M.; King, M.; Urban, T.

    2012-01-01

    This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating reprocessed data sets over a longer period of t

  10. Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data

    NARCIS (Netherlands)

    Shen, F.; Verhoef, W.; Zhou, Y.; Salama, M.S.; Liu, X.

    2010-01-01

    The Changjiang (Yangtze) estuarine and coastal waters are characterized by suspended sediments over a wide range of concentrations from 20 to 2,500 mg l-1. Suspended sediment plays important roles in the estuarine and coastal system and environment. Previous algorithms for satellite estimates of

  11. Combining satellite altimetry and gravimetry data to improve Antarctic mass balance and gia estimates

    NARCIS (Netherlands)

    Gunter, B.C.; Didova, O.; Riva, R.E.M.; van den Broeke, M.R.; Ligtenberg, S.R.M.; Lenaerts, J.T.M.; King, M.; Urban, T.

    2012-01-01

    This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating reprocessed data sets over a longer period of

  12. Robust double gain unscented Kalman filter for small satellite attitude estimation

    Science.gov (United States)

    Cao, Lu; Yang, Weiwei; Li, Hengnian; Zhang, Zhidong; Shi, Jianjun

    2017-08-01

    Limited by the low precision of small satellite sensors, the estimation theories with high performance remains the most popular research topic for the attitude estimation. The Kalman filter (KF) and its extensions have been widely applied in the satellite attitude estimation and achieved plenty of achievements. However, most of the existing methods just take use of the current time-step's priori measurement residuals to complete the measurement update and state estimation, which always ignores the extraction and utilization of the previous time-step's posteriori measurement residuals. In addition, the uncertainty model errors always exist in the attitude dynamic system, which also put forward the higher performance requirements for the classical KF in attitude estimation problem. Therefore, the novel robust double gain unscented Kalman filter (RDG-UKF) is presented in this paper to satisfy the above requirements for the small satellite attitude estimation with the low precision sensors. It is assumed that the system state estimation errors can be exhibited in the measurement residual; therefore, the new method is to derive the second Kalman gain Kk2 for making full use of the previous time-step's measurement residual to improve the utilization efficiency of the measurement data. Moreover, the sequence orthogonal principle and unscented transform (UT) strategy are introduced to robust and enhance the performance of the novel Kalman Filter in order to reduce the influence of existing uncertainty model errors. Numerical simulations show that the proposed RDG-UKF is more effective and robustness in dealing with the model errors and low precision sensors for the attitude estimation of small satellite by comparing with the classical unscented Kalman Filter (UKF).

  13. Assessing Satellite-Based Fire Data for use in the National Emissions Inventory

    Science.gov (United States)

    Soja, Amber J.; Al-Saadi, Jassim; Giglio, Louis; Randall, Dave; Kittaka, Chieko; Pouliot, George; Kordzi, Joseph J.; Raffuse, Sean; Pace, Thompson G.; Pierce, Thomas E.; Moore, Tom; Biswadev, Roy; Pierce, R. Bradley; Szykman, James J.

    2009-01-01

    Biomass burning is significant to emission estimates because: (1) it can be a major contributor of particulate matter and other pollutants; (2) it is one of the most poorly documented of all sources; (3) it can adversely affect human health; and (4) it has been identified as a significant contributor to climate change through feedbacks with the radiation budget. Additionally, biomass burning can be a significant contributor to a regions inability to achieve the National Ambient Air Quality Standards for PM 2.5 and ozone, particularly on the top 20% worst air quality days. The United States does not have a standard methodology to track fire occurrence or area burned, which are essential components to estimating fire emissions. Satellite imagery is available almost instantaneously and has great potential to enhance emission estimates and their timeliness. This investigation compares satellite-derived fire data to ground-based data to assign statistical error and helps provide confidence in these data. The largest fires are identified by all satellites and their spatial domain is accurately sensed. MODIS provides enhanced spatial and temporal information, and GOES ABBA data are able to capture more small agricultural fires. A methodology is presented that combines these satellite data in Near-Real-Time to produce a product that captures 81 to 92% of the total area burned by wildfire, prescribed, agricultural and rangeland burning. Each satellite possesses distinct temporal and spatial capabilities that permit the detection of unique fires that could be omitted if using data from only one satellite.

  14. Digital, Satellite-Based Aeronautical Communication

    Science.gov (United States)

    Davarian, F.

    1989-01-01

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

  15. Model-based satellite image fusion

    DEFF Research Database (Denmark)

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

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...

  16. Delivery of satellite based broadband services

    Science.gov (United States)

    Chandrasekhar, M. G.; Venugopal, D.

    2007-06-01

    Availability of speedy communication links to individuals and organizations is essential to keep pace with the business and social requirements of this modern age. While the PCs have been continuously growing in processing speed and memory capabilities, the availability of broadband communication links still has not been satisfactory in many parts of the world. Recognizing the need to give fillip to the growth of broadband services and improve the broadband penetration, the telecom policies of different counties have placed special emphasis on the same. While emphasis is on the use of fiber optic and copper in local loop, satellite communications systems will play an important role in quickly establishing these services in areas where fiber and other communication systems are not available and are not likely to be available for a long time to come. To make satellite communication systems attractive for the wide spread of these services in a cost effective way special emphasis has to be given on factors affecting the cost of the bandwidth and the equipment. As broadband services are bandwidth demanding, use of bandwidth efficient modulation technique and suitable system architecture are some of the important aspects that need to be examined. Further there is a need to re-look on how information services are provided keeping in view the user requirements and broadcast capability of satellite systems over wide areas. This paper addresses some of the aspects of delivering broadband services via satellite taking Indian requirement as an example.

  17. Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

    Directory of Open Access Journals (Sweden)

    E. Delogu

    2012-08-01

    Full Text Available Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

  18. Use of satellite images in snow water equivalent (SWE) estimation in the Upper Vistula drainage basin in southern Poland

    Science.gov (United States)

    Kasina, M.; Chamerlinska, A.; Lasek, J.; Przeniczny, P.

    2013-12-01

    Snow-water equivalent (SWE) and snow depth are the two most important parameters used in hydrological forecasting offices to estimate the amount of water stored in the form of snow. These two parameters are essential during snowmelt periods when rapid snowmelt (often combined with rainfall) causes slow-onset floods. In this case, the water equivalent can be used as an indicator of the amount of water expected in runoff. So far the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB) produces this estimate based only on SWE and snow depth data obtained from meteorological stations at five day intervals. The two measurements are performed at shorter intervals either when heavy snowfall occurs or when the mean daily air temperature exceeds 0οC. The main aim of this project is to improve the existing method of snow water equivalent estimation by using satellite-derived data. Snow-water equivalent data and the extent of snow cover were derived from satellite products prepared within the H-SAF Project, which is the EUMETSAT Network of Satellite Application Facility dedicated to support Operational Hydrology and Water Management. Both H10 - Snow mask by VIS/IR radiometry and H11 - Snow water equivalent by MW radiometry products are derived in a daily time step. It then becomes possible to compare and further assimilate ground-truth data. Other analyses included Bayesian Kriging spatial interpolation, which is suitable for non-stationary data. The method described in this paper - same as other methods based on satellite derived data - is weather dependent and it is limited to cloud-free periods. A comparison of results obtained using this method and results obtained using ground-based data calculations proved its applicability in lowland areas. In mountainous regions, where differences in SWE values strongly depend on elevation, the obtained SWE values were underestimated.

  19. Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction. M.S. Thesis

    Science.gov (United States)

    Davis, John H.

    1993-01-01

    Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons.

  20. Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

    Directory of Open Access Journals (Sweden)

    Boluwaji M. Olomiyesan

    2016-01-01

    Full Text Available In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005 of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE, mean percentage error (MPE, root mean square error (RMSE, and coefficient of determination (R2. Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

  1. Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

    Directory of Open Access Journals (Sweden)

    Jochen Zschau

    2012-05-01

    Full Text Available Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types. At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.

  2. Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

    Science.gov (United States)

    Wang, Shifeng; So, Emily; Smith, Pete

    2015-04-01

    Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.

  3. Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2006-01-01

    Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal

  4. Co-Channel Interference Mitigation Using Satellite Based Receivers

    Science.gov (United States)

    2014-12-01

    While there is some phase noise present in the continuous time-shifted signal, it is important to recognize that this signal is plotted over the [−π...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RECEIVERS by John E. Patterson...07-02-2012 to 12-19-2014 4. TITLE AND SUBTITLE CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RE- CEIVERS 5. FUNDING NUMBERS 6. AUTHOR(S

  5. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    Science.gov (United States)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  6. Reusable Reentry Satellite (RRS) system design study: System cost estimates document

    Science.gov (United States)

    1991-01-01

    The Reusable Reentry Satellite (RRS) program was initiated to provide life science investigators relatively inexpensive, frequent access to space for extended periods of time with eventual satellite recovery on earth. The RRS will provide an on-orbit laboratory for research on biological and material processes, be launched from a number of expendable launch vehicles, and operate in Low-Altitude Earth Orbit (LEO) as a free-flying unmanned laboratory. SAIC's design will provide independent atmospheric reentry and soft landing in the continental U.S., orbit for a maximum of 60 days, and will sustain three flights per year for 10 years. The Reusable Reentry Vehicle (RRV) will be 3-axis stabilized with artificial gravity up to 1.5g's, be rugged and easily maintainable, and have a modular design to accommodate a satellite bus and separate modular payloads (e.g., rodent module, general biological module, ESA microgravity botany facility, general botany module). The purpose of this System Cost Estimate Document is to provide a Life Cycle Cost Estimate (LCCE) for a NASA RRS Program using SAIC's RRS design. The estimate includes development, procurement, and 10 years of operations and support (O&S) costs for NASA's RRS program. The estimate does not include costs for other agencies which may track or interface with the RRS program (e.g., Air Force tracking agencies or individual RRS experimenters involved with special payload modules (PM's)). The life cycle cost estimate extends over the 10 year operation and support period FY99-2008.

  7. Efficient chaotic based satellite power supply subsystem

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-10-15

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

  8. Discharge estimation in arid areas with the help of optical satellite data

    Science.gov (United States)

    Mett, M.; Aufleger, M.

    2009-04-01

    The MENA region is facing severe water scarcity. Overexploitation of groundwater resources leads to an ongoing drawdown of the water tables, salinisation and desertification of vast areas. To make matters worse enormous birth-rates, economic growth and refugees from conflict areas let the need for water explode. In the context of climate change this situation will even worsen and armed conflicts are within the bounds of possibility. To ease water scarcity many innovative techniques like artificial groundwater recharge are being developed or already state of the art. But missing hydrological information (for instance discharge data) often prevents design and efficient operation of such measures. Especially in poor countries hydrological measuring devices like gage stations are often missing, in a bad status or professionals of the water sector are absent. This leads to the paradox situation that in many arid regions water resources are indeed available but they cannot be utilised because they are not known. Nowadays different approaches are being designed to obtain hydrological information from perennial river systems with the help of satellite techniques. Mostly they are based on hydraulic parameters like river dimensions, roughness and water levels which can be derived from satellite data. By using conventional flow formulas and additional field investigations the discharge can be estimated. Another methodology derived information about maximum flow depth and flow width from optical sensors of high resolution to calculate discharge of the rivers whilst the flood. Attempts to derive discharge information from structural components of the river and fluviomorphologic changes due to changing flow regimes are in the focus of recent research. One attempt used Synthetic Aperture Radar (SAR) data to estimate discharge in braided river systems. Other attempts used airborne SAR imagery to obtain information about sinuosity and total river width of perennial braided river

  9. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2012-08-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase.

    The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick

  10. Estimation of differential code biases for Beidou navigation system using multi-GNSS observations: How stable are the differential satellite and receiver code biases?

    Science.gov (United States)

    Xue, Junchen; Song, Shuli; Zhu, Wenyao

    2016-04-01

    Differential code biases (DCBs) are important parameters that must be estimated accurately and reliably for high-precision GNSS applications. For optimal operational service performance of the Beidou navigation system (BDS), continuous monitoring and constant quality assessment of the BDS satellite DCBs are crucial. In this study, a global ionospheric model was constructed based on a dual system BDS/GPS combination. Daily BDS DCBs were estimated together with the total electron content from 23 months' multi-GNSS observations. The stability of the resulting BDS DCB estimates was analyzed in detail. It was found that over a long period, the standard deviations (STDs) for all satellite B1-B2 DCBs were within 0.3 ns (average: 0.19 ns) and for all satellite B1-B3 DCBs, the STDs were within 0.36 ns (average: 0.22 ns). For BDS receivers, the STDs were greater than for the satellites, with most values BDS satellite DCBs between two consecutive days was BDS DCBs, they only require occasional estimation or calibration. Furthermore, the 30-day averaged satellite DCBs can be used reliably for the most demanding BDS applications.

  11. Unscented predictive variable structure filter for satellite attitude estimation with model errors when using low precision sensors

    Science.gov (United States)

    Cao, Lu; Li, Hengnian

    2016-10-01

    For the satellite attitude estimation problem, the serious model errors always exist and hider the estimation performance of the Attitude Determination and Control System (ACDS), especially for a small satellite with low precision sensors. To deal with this problem, a new algorithm for the attitude estimation, referred to as the unscented predictive variable structure filter (UPVSF) is presented. This strategy is proposed based on the variable structure control concept and unscented transform (UT) sampling method. It can be implemented in real time with an ability to estimate the model errors on-line, in order to improve the state estimation precision. In addition, the model errors in this filter are not restricted only to the Gaussian noises; therefore, it has the advantages to deal with the various kinds of model errors or noises. It is anticipated that the UT sampling strategy can further enhance the robustness and accuracy of the novel UPVSF. Numerical simulations show that the proposed UPVSF is more effective and robustness in dealing with the model errors and low precision sensors compared with the traditional unscented Kalman filter (UKF).

  12. Testing estimation of water surface in Italian rice district from MODIS satellite data

    Science.gov (United States)

    Ranghetti, Luigi; Busetto, Lorenzo; Crema, Alberto; Fasola, Mauro; Cardarelli, Elisa; Boschetti, Mirco

    2016-10-01

    Recent changes in rice crop management within Northern Italy rice district led to a reduction of seeding in flooding condition, which may have an impact on reservoir water management and on the animal and plant communities that depend on the flooded paddies. Therefore, monitoring and quantifying the spatial and temporal variability of water presence in paddy fields is becoming important. In this study we present a method to estimate dynamics of presence of standing water (i.e. fraction of flooded area) in rice fields using MODIS data. First, we produced high resolution water presence maps from Landsat by thresholding the Normalised Difference Flood Index (NDFI) made: we made it by comparing five Landsat 8 images with field-obtained information about rice field status and water presence. Using these data we developed an empirical model to estimate the flooding fraction of each MODIS cell. Finally we validated the MODIS-based flooding maps with both Landsat and ground information. Results showed a good predictability of water surface from Landsat (OA = 92%) and a robust usability of MODIS data to predict water fraction (R2 = 0.73, EF = 0.57, RMSE = 0.13 at 1 × 1 km resolution). Analysis showed that the predictive ability of the model decreases with the greening up of rice, so we used NDVI to automatically discriminate estimations for inaccurate cells in order to provide the water maps with a reliability flag. Results demonstrate that it is possible to monitor water dynamics in rice paddies using moderate resolution multispectral satellite data. The achievement is a proof of concept for the analysis of MODIS archives to investigate irrigation dynamics in the last 15 years to retrieve information for ecological and hydrological studies.

  13. Multi-technique combination of space geodesy observations: Impact of the Jason-2 satellite on the GPS satellite orbits estimation

    Science.gov (United States)

    Zoulida, Myriam; Pollet, Arnaud; Coulot, David; Perosanz, Félix; Loyer, Sylvain; Biancale, Richard; Rebischung, Paul

    2016-10-01

    In order to improve the Precise Orbit Determination (POD) of the GPS constellation and the Jason-2 Low Earth Orbiter (LEO), we carry out a simultaneous estimation of GPS satellite orbits along with Jason-2 orbits, using GINS software. Along with GPS station observations, we use Jason-2 GPS, SLR and DORIS observations, over a data span of 6 months (28/05/2011-03/12/2011). We use the Geophysical Data Records-D (GDR-D) orbit estimation standards for the Jason-2 satellite. A GPS-only solution is computed as well, where only the GPS station observations are used. It appears that adding the LEO GPS observations results in an increase of about 0.7% of ambiguities fixed, with respect to the GPS-only solution. The resulting GPS orbits from both solutions are of equivalent quality, agreeing with each other at about 7 mm on Root Mean Square (RMS). Comparisons of the resulting GPS orbits to the International GNSS Service (IGS) final orbits show the same level of agreement for both the GPS-only orbits, at 1.38 cm in RMS, and the GPS + Jason2 orbits at 1.33 cm in RMS. We also compare the resulting Jason-2 orbits with the 3-technique Segment Sol multi-missions d'ALTimétrie, d'orbitographie et de localisation précise (SSALTO) POD products. The orbits show good agreement, with 2.02 cm of orbit differences global RMS, and 0.98 cm of orbit differences RMS on the radial component.

  14. A Comparison of Satellite and Emnpirical Formula Techniques for Estimating Insolation over the Oceans.

    Science.gov (United States)

    Frouin, Robert; Gautier, Catherine; Katsaros, Kristina B.; Lind, Richard J.

    1988-09-01

    Surface insulation data collected during the Mixed Layer Dynamiccs Experiment are used to intercompare the satellite technique of Gautier et al. (1980) and five commonly referenced empirical formulas for estimating daily insulation over the oceans. The results demonstrate the superiority of the satellite technique, which exhibits a 0.97 correlation coefficient, a 12.0 W m M2 error of estimate, and a 4.9 W m2 bias error, and which is also able to account for water vapor, ozone, and dust amount variations in the atmosphere and monitor quasi-instantaneously vast extents of ocean. Among the empirical formulas, Mosby's (1936) yields the best predictions with a 0.84 correlation coefficient, a 19.1 W m2 standard error of estimate, and a 3.4 W m2 bias. Kimball'(1928) and Reed's (1977) formulas however, perform nearly as well. The largest biases are obtained with Berliand's (1960) and Laevastu' (1960) formulas, which overestimate insolation by 15.2 and 24.5 W m2, respectively. It is suggested the empirical formulas, even though established from visual cloud cover observations, would provide useful insolation estimates if employed with satellite-derived cloud cover.

  15. Environmental evaluation of the forest of Mt. Fuji, based on multiple satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Shiosaka, K.; Konta, F.; Nishikawa, H. (The Inst. of Regional Environ. Planning, Shizuoka (Japan) Shizuoka Univ., Shizuoka (Japan) Nippon Univ., Narashino (Japan))

    1994-03-01

    Evaluation of environmental roles of the forest of Mt. Fuji and estimation of deposition of sulfur dioxide on the leaves of Japanese cypress (Chamaecyparis obtusa) were done based on satellite data. The evaluation suggests that artificial Japanese cypress forests, which occupy the largest area among vegetations of Mt. Fuji, have problems concerning environmental role of storing of soil water, and that the result of the estimation indicates an uneven distribution of sulfur dioxide deposition.

  16. Environmental evaluation of the forest of MT Fuji, based on multiple satellite data

    Science.gov (United States)

    Shiosaka, K.; Konta, F.; Nishikawa, H.

    1994-03-01

    Evaluation of environmental roles of the forest of Mt. Fuji and estimation of deposition of sulfur dioxide on the leaves of Japanese cypress (Chamaecyparis obtusa) weere done based on satellite data. The evaluation suggests that artificial Japanese cypress forests, which occupy the largest area among vegetations of Mt. Fuji have problems concerning environmental role of storing of soil water, and that the result of the estimation indicates an uneven distribution of sulfur dioxide deposition.

  17. Autonomous sensor-based dual-arm satellite grappling

    Science.gov (United States)

    Wilcox, Brian; Tso, Kam; Litwin, Todd; Hayati, Samad; Bon, Bruce

    1989-01-01

    Dual-arm satellite grappling involves the integration of technologies developed in the Sensing and Perception (S&P) Subsystem for object acquisition and tracking, and the Manipulator Control and Mechanization (MCM) Subsystem for dual-arm control. S&P acquires and tracks the position, orientation, velocity, and angular velocity of a slowly spinning satellite, and sends tracking data to the MCM subsystem. MCM grapples the satellite and brings it to rest, controlling the arms so that no excessive forces or torques are exerted on the satellite or arms. A 350-pound satellite mockup which can spin freely on a gimbal for several minutes, closely simulating the dynamics of a real satellite is demonstrated. The satellite mockup is fitted with a panel under which may be mounted various elements such as line replacement modules and electrical connectors that will be used to demonstrate servicing tasks once the satellite is docked. The subsystems are housed in three MicroVAX II microcomputers. The hardware of the S&P Subsystem includes CCD cameras, video digitizers, frame buffers, IMFEX (a custom pipelined video processor), a time-code generator with millisecond precision, and a MicroVAX II computer. Its software is written in Pascal and is based on a locally written vision software library. The hardware of the MCM Subsystem includes PUMA 560 robot arms, Lord force/torque sensors, two MicroVAX II computers, and unimation pneumatic parallel grippers. Its software is written in C, and is based on a robot language called RCCL. The two subsystems are described and test results on the grappling of the satellite mockup with rotational rates of up to 2 rpm are provided.

  18. Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget

    Science.gov (United States)

    Rodell, Matthew; McWilliams, Eric B.; Famiglietti, James S.; Beaudoing, Hiroko K.; Nigro, Joseph

    2011-01-01

    Evapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground-based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation-based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment satellite mission. We demonstrate that while uncertainty in the water budget-based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget-based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite-based ET retrieval optimization.

  19. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu

    2015-03-01

    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  20. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  1. A comparative study of satellite and ground-based phenology.

    Science.gov (United States)

    Studer, S; Stöckli, R; Appenzeller, C; Vidale, P L

    2007-05-01

    Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

  2. The Role of Satellite Imagery to Improve Pastureland Estimates in South America

    Science.gov (United States)

    Graesser, J.

    2015-12-01

    Agriculture has changed substantially across the globe over the past half century. While much work has been done to improve spatial-temporal estimates of agricultural changes, we still know more about the extent of row-crop agriculture than livestock-grazed land. The gap between cropland and pastureland estimates exists largely because it is challenging to characterize natural versus grazed grasslands from a remote sensing perspective. However, the impasse of pastureland estimates is set to break, with an increasing number of spaceborne sensors and freely available satellite data. The Landsat satellite archive in particular provides researchers with immense amounts of data to improve pastureland information. Here we focus on South America, where pastureland expansion has been scrutinized for the past few decades. We explore the challenges of estimating pastureland using temporal Landsat imagery and focus on key agricultural countries, regions, and ecosystems. We focus on the suggested shift of pastureland from the Argentine Pampas to northern Argentina, and the mixing of small-scale and large-scale ranching in eastern Paraguay and how it could impact the Chaco forest to the west. Further, the Beni Savannahs of northern Bolivia and the Colombian Llanos—both grassland and savannah regions historically used for livestock grazing—have been hinted at as future areas for cropland expansion. There are certainly environmental concerns with pastureland expansion into forests; but what are the environmental implications when well-managed pasture systems are converted to intensive soybean or palm oil plantation? Tropical, grazed grasslands are important habitats for biodiversity, and pasturelands can mitigate soil erosion when well managed. Thus, we must improve estimates of grazed land before we can make informed policy and conservation decisions. This talk presents insights into pastureland estimates in South America and discusses the feasibility to improve current

  3. DIGITAL VIDEO BROADCAST RETURN CHANNEL VIA SATELLITE (DVB-RCS HUB FOR SATELLITE BASED E-LEARNING

    Directory of Open Access Journals (Sweden)

    N.G.Vasantha Kumar

    2011-02-01

    Full Text Available This paper discusses in-house designed and developed scale-down DVB-RCS hub along with the performance of the realized hub. This development is intended to support the Satellite Based e-Learning initiative in India. The scale-down DVB-RCS HUB is implemented around a single PC with other subsystems making it very cost effective and unique of its kind. This realization will drastically reduce the total cost of Satellite based Education Networks as very low cost commercially available Satellite Interactive Terminals (SITs complying to open standard could be used at remote locations. The system is successfully tested to work with a commercial SIT using a GEO satellite EDUSAT which is especially dedicated for satellite based e-Learning. The internal detail of the DVB-RCS Forward and Return Link Organization and how it manages the Satellite Interactive Terminals access to the satellite channel using MF-TDMA approach has been described.

  4. Satellite-based assessment of yield variation and its determinants in smallholder African systems

    Science.gov (United States)

    Lobell, David B.

    2017-01-01

    The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

  5. A quantitative method for estimating cloud cover over tropical cyclones from satellite data

    OpenAIRE

    BALOGUN, E. E.

    2011-01-01

    A photometric method for quantifying cloud cover over tropical cyclones as observed from satellite photographs is presented. Two gridded photographs of tropical cyclones are analyzed by this method. On each photograph, nine concentric circles are drawn. The observed or reported centre of the cyclones is used as the centre for each set of concentric circles. Photometric estimates of cloud cover are made along the nine concentric circles. The principle of harmonic analysis is applied to the cl...

  6. Technology status of HNF-based monopropellants for satellite propulsion

    NARCIS (Netherlands)

    Marée, A.G.M.; Moerel, J.L.P.A.; Weiland-Veltmans, W.H.M.; Wierkx, F.J.M.; Zevenbergen, J.

    2004-01-01

    This paper reports on significant technological progress made over the last few years in determining the feasibility of HNF-based monopropellants. An HNF-based monopropellant is an interesting alternative for hydrazine as monopropellant for satellite propulsion. New non-toxic monopropellants based o

  7. Technology status of HNF-based monopropellants for satellite propulsion

    NARCIS (Netherlands)

    Marée, A.G.M.; Moerel, J.L.P.A.; Weiland-Veltmans, W.H.M.; Wierkx, F.J.M.; Zevenbergen, J.

    2004-01-01

    This paper reports on significant technological progress made over the last few years in determining the feasibility of HNF-based monopropellants. An HNF-based monopropellant is an interesting alternative for hydrazine as monopropellant for satellite propulsion. New non-toxic monopropellants based o

  8. Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers

    Directory of Open Access Journals (Sweden)

    O. Jakubov

    2013-09-01

    Full Text Available Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity.

  9. Estimation of snow cover distribution in Beas basin, Indian Himalaya using satellite data and ground measurements

    Indian Academy of Sciences (India)

    H S Negi; A V Kulkarni; B S Semwal

    2009-10-01

    In the present paper,a methodology has been developed for the mapping of snow cover in Beas basin,Indian Himalaya using AWiFS (IRS-P6)satellite data.The complexities in the mapping of snow cover in the study area are snow under vegetation,contaminated snow and patchy snow. To overcome these problems,field measurements using spectroradiometer were carried out and reflectance/snow indices trend were studied.By evaluation and validation of different topographic correction models,it was observed that,the normalized difference snow index (NDSI)values remain constant with the variations in slope and aspect and thus NDSI can take care of topography effects.Different snow cover mapping methods using snow indices are compared to find the suitable mapping technique.The proposed methodology for snow cover mapping uses the NDSI (estimated using planetary re flectance),NIR band reflectance and forest/vegetation cover information.The satellite estimated snow or non-snow pixel information using proposed methodology was validated with the snow cover information collected at three observatory locations and it was found that the algorithm classify all the sample points correctly,once that pixel is cloud free.The snow cover distribution was estimated using one year (2004 –05)cloud free satellite data and good correlation was observed between increase/decrease areal extent of seasonal snow cover and ground observed fresh snowfall and standing snow data.

  10. Antenna pointing system for satellite tracking based on Kalman filtering and model predictive control techniques

    Science.gov (United States)

    Souza, André L. G.; Ishihara, João Y.; Ferreira, Henrique C.; Borges, Renato A.; Borges, Geovany A.

    2016-12-01

    The present work proposes a new approach for an antenna pointing system for satellite tracking. Such a system uses the received signal to estimate the beam pointing deviation and then adjusts the antenna pointing. The present work has two contributions. First, the estimation is performed by a Kalman filter based conical scan technique. This technique uses the Kalman filter avoiding the batch estimator and applies a mathematical manipulation avoiding the linearization approximations. Secondly, a control technique based on the model predictive control together with an explicit state feedback solution are obtained in order to reduce the computational burden. Numerical examples illustrate the results.

  11. Solar radiation estimation using images form geostationary satellites; Estimacao de radiacao solar usando imagens de satelites geoestacionarios

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Cicero Barbosa dos [Centro Federal de Educacao Tecnologica do Parana, PR (Brazil); Zuern, Hans Helmut [Santa Catarina Univ., Florianopolis, SC (Brazil). LABSPOT

    1996-12-31

    The opportunity of potential measurement Photovoltaic through of studies of solar radiation maximum incidence, aimed the generation of electrical energy, contained in either radial systems or stand-alone or even grid-connected to conventional system, preceded by a study of solar radiation estimation technique, which is the main fuel the Photovoltaic generation. This work presents a technique of solar radiation estimation, using images from satellite geo-stationary in a visible field. The city of Curitiba was an implementation and the results are compared to the estimation made by researches from INPE - National Institute Space Research, whose observations were based on the solar shine duration, obtained in a network of 187 meteorological station for period of 10 years (1961-1970). (author) 24 refs., 2 figs., 2 tabs.; e-mail: cicero at labspot.ufsc.br; eellhh at ibm.ufsc.br

  12. Monte-Carlo Estimation of the Inflight Performance of the GEMS Satellite X-Ray Polarimeter

    Science.gov (United States)

    Kitaguchi, Takao; Tamagawa, Toru; Hayato, Asami; Enoto, Teruaki; Yoshikawa, Akifumi; Kaneko, Kenta; Takeuchi, Yoko; Black, Kevin; Hill, Joanne; Jahoda, Keith; Krizmanic, John; Sturner, Steve; Griffiths, Scott; Kaaret, Philip; Marlowe, Hannah

    2014-01-01

    We report a Monte-Carlo estimation of the in-orbit performance of a cosmic X-ray polarimeter designed to be installed on the focal plane of a small satellite. The simulation uses GEANT for the transport of photons and energetic particles and results from Magboltz for the transport of secondary electrons in the detector gas. We validated the simulation by comparing spectra and modulation curves with actual data taken with radioactive sources and an X-ray generator. We also estimated the in-orbit background induced by cosmic radiation in low Earth orbit.

  13. On the scale estimation using truncated swath measurements from low Earth orbiting satellites

    Science.gov (United States)

    Liu, Qi

    2013-05-01

    Truncation effect caused by limited swath width of low Earth orbiting (LEO) satellites results in inevitable underestimation of object scale when using pixel-counting methods. A new approach is proposed to obtain more accurate object scale through truncated measurements. The approach is based upon the mean object area fraction (MOAF), which depicts the relative population of object points in a varying-size domain and proves to be less sensitive to truncation effect. The MOAF-equivalent radius (MER) is deduced by comparing the actual MOAF with the standard one inferred from a circle object. Numerical simulations are implemented to demonstrate the MER characteristics. In contrast to area-equivalent radius (AER) that is merely determined by the absolute amount of object points, MER relies on the overall spatial structure of the object. For objects with irregular shapes, the MER value is generally smaller than AER in the absence of truncation. Nevertheless, taking the actual AER as true scale, MER has significantly reduced biases compared to AER once the object is truncated. This advantage can be reinforced when focusing on size statistics of analogous objects, because negative and positive biases associated with various truncation situations coexist in MER, against the uniform negative biases of AER. When applied to MODIS cloud mask data that are restricted in individual granules, MER has consistently larger values than AER for most truncated clouds. Compared with the explicitly problematic estimation from AER due to truncation, MER offers a notable elevation on the estimated cloud size and gets closer to the truth.

  14. Evaluation of Satellite and Ground Based Precipitation Products for Flood Forecasting

    Science.gov (United States)

    Chintalapudi, S.; Sharif, H.; Yeggina, S.

    2012-04-01

    The development in satellite-derived rainfall estimates encouraged the hydrological modeling in sparse gauged basins or ungauged basins. Especially, physically-based distributed hydrological models can benefit from the good spatial and temporal coverage of satellite precipitation products. In this study, three satellite derived precipitation datasets (TRMM, CMORPH, and PERSIANN), NEXRAD, and rain gauge precipitation datasets were used to drive the hydrological model. The physically-based, distributed hydrological model Gridded Surface Subsurface Hydrological Analysis (GSSHA) was used in this study. Focus will be on the results from the Guadalupe River Basin above Canyon Lake and below Comfort, Texas. The Guadalupe River Basin above Canyon Lake and below Comfort Texas drains an area of 1232 km2. Different storm events will be used in these simulations. August 2007 event was used as calibration and June 2007 event was used as validation. Results are discussed interms of accuracy of satellite precipitation estimates with the ground based precipitation estimates, predicting peak discharges, runoff volumes, time lag, and spatial distribution. The initial results showed that, model was able to predict the peak discharges and runoff volumes when using NEXRAD MPE data, and TRMM 3B42 precipitation product. The results also showed that there was time lag in hydrographs driven by both PERSIANN and CMORPH data sets.

  15. Simultaneous state and actuator fault estimation for satellite attitude control systems

    Institute of Scientific and Technical Information of China (English)

    Cheng Yao; Wang Rixin; Xu Minqiang; Li Yuqing

    2016-01-01

    In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.

  16. Evapotranspiration Estimation over Yangtze River Basin from GRACE satellite measurement and in situ data

    Science.gov (United States)

    Li, Qiong; Luo, Zhicai; Zhong, Bo; Wang, Haihong; Zhou, Zebing

    2016-04-01

    As the critical component of hydrologic cycle, evapotranspiration (ET) plays an important role in global water exchanges and energy flow across the hydrosphere, atmosphere and biosphere. Influenced by the Asian monsoon, the Yangtze River Basin (YRB) suffer from the several severe floods and droughts over the last decades due to the significant difference between temporal and spatial distribution terrestrial water storages. As an indispensable part, it is practically important to assessment ET in the YRB accompany with increased population and rapid economic and agriculture development. Average ET over the YRB is computed as the residual of terrestrial water budget using the Gravity Recovery and Climate Experiment (GRACE) satellite-based measurements and the ground-based observations. The GRACE-based ET were well coincidence with the ET from MODIS, with the correlation coefficient of 0.853, and the correlation coefficient is 0.696 while comparing with the ET ground-based observation. The mean monthly average of ET from these various estimates is 56.9 mm/month over the whole YRB, and peak between June and August. Monthly variations of ET reach a maximum in Wujiang with 69.11 mm/month and a minimum in Jinshajiang with 39.01 mm/month. Based on the correlation between ET and independent estimates of near-surface temperature and soil moisture, it is showed that as the temperature increased, the ET of the seven sub-catchment were rising except for the Poyang Lake and Donting Lake. And we also can infer that the midstream of YRB is significant correlated with ESON especially in the Hanjiang basin. The Surface Humidity Index over the YRB was gradually decreased and its variations in each sub-catchment showed a significant decreasing trend in Jinshajiang and Mingjiang. This research has important potential for use in large-scale water budget assessments and intercomparison studies. Acknowledgements: This research is supported by the National Natural Science Foundation of

  17. Inversion Technique for Estimating Emissions of Volcanic Ash from Satellite Imagery

    Science.gov (United States)

    Pelley, Rachel; Cooke, Michael; Manning, Alistair; Thomson, David; Witham, Claire; Hort, Matthew

    2014-05-01

    When using dispersion models such as NAME (Numerical Atmospheric-dispersion Modelling Environment) to predict the dispersion of volcanic ash, a source term defining the mass release rate of ash is required. Inversion modelling using observations of the ash plume provides a method of estimating the source term for use in NAME. Our inversion technique makes use of satellite retrievals, calculated using data from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument on-board the MSG (Meteosat Second Generation) satellite, as the ash observations. InTEM (Inversion Technique for Emission Modelling) is the UK Met Office's inversion modelling system. Recently the capability to estimate time and height varying source terms has been implemented and applied to volcanic ash. InTEM uses a probabilistic approach to fit NAME model concentrations to satellite retrievals. This is achieved by applying Bayes Theorem to give a cost function for the source term. Source term profiles with lower costs generate model concentrations that better fit the satellite retrievals. InTEM uses the global optimisation technique, simulated annealing, to find the minimum of the cost function. The use of a probabilistic approach allows the uncertainty in the satellite retrievals to be incorporated into the inversion technique. InTEM makes use of satellite retrievals of both ash column loadings and of cloud free regions. We present a system that allows InTEM to be used during an eruption. The system is automated and can produce source term updates up to four times a day. To allow automation hourly satellite retrievals of ash are routinely produced using conservative detection limits. The conservative detection limits provide good detection of the ash plume while limiting the number of false alarms. Regions which are flagged as ash contaminated or free from cloud (both meteorological and ash) are used in the InTEM system. This approach is shown to improve the concentrations in the

  18. Fast emission estimates in China and South Africa constrained by satellite observations

    Science.gov (United States)

    Mijling, Bas; van der A, Ronald

    2013-04-01

    Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for emerging economies such as China and South Africa, where rapid economic growth change emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. However, constraining emissions from observations of concentrations is computationally challenging. Within the GlobEmission project (part of the Data User Element programme of ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China and South Africa, using the CHIMERE chemical transport model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e

  19. A satellite based telemetry link for a UAV application

    Science.gov (United States)

    Bloise, Anthony

    1995-01-01

    The requirements for a satellite based communication facility to service the needs of the Geographical Information System (GIS) data collection community are addressed in this paper. GIS data is supplied in the form of video imagery at sub-television rates in one or more spectral bands / polarizations laced with a position correlated data stream. The limitations and vicissitudes of using a terrestrial based telecommunications link to collect GIS data are illustrated from actual mission scenarios. The expectations from a satellite based communications link by the geophysical data collection community concerning satellite architecture, operating bands, bandwidth, footprint agility, up link and down link hardware configurations on the UAV, the Mobile Control Vehicle and at the Central Command and Data Collection Facility comprise the principle issues discussed in the first section of this paper. The final section of the paper discusses satellite based communication links would have an increased volume and scope of services the GIS data collection community could make available to the GIS user community, and the price the data collection community could afford to pay for access to the communication satellite described in the paper.

  20. Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

    DEFF Research Database (Denmark)

    Lunde, Asger; Brix, Anne Floor

    In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared to the p......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from...

  1. REKF and RUKF for pico satellite attitude estimation in the presence of measurement faults

    Institute of Scientific and Technical Information of China (English)

    Halil Ersin Söken; Chingiz Hajiyev

    2014-01-01

    When a pico satel ite is under normal operational condi-tions, whether it is extended or unscented, a conventional Kalman filter gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunc-tions in the estimation system, the Kalman filter gives inaccurate results and diverges by time. This study compares two different robust Kalman filtering algorithms, robust extended Kalman filter (REKF) and robust unscented Kalman filter (RUKF), for the case of measurement malfunctions. In both filters, by the use of de-fined variables named as the measurement noise scale factor, the faulty measurements are taken into the consideration with a smal weight, and the estimations are corrected without affecting the characteristic of the accurate ones. The proposed robust Kalman filters are applied for the attitude estimation process of a pico satel-lite, and the results are compared.

  2. Estimates of radiative flux divergence in the atmosphere from satellite data

    Science.gov (United States)

    Smith, G. L.; Charlock, Thomas P.; Bess, T. D.; Gupta, Shashi; Rutan, David; Rose, Fred G.

    1990-01-01

    Several options for the inference of the atmospheric radiative flux divergence (ARD) on the basis of satellite data are discussed. Attention is given to the clear-sky case and the cloudy-sky case. LW ARD profiles for different climatological regimes are presented and the effect of cloud base height on LW ARD divergence at various heights is illustrated.

  3. Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

    Directory of Open Access Journals (Sweden)

    S.A. Margulis

    2001-01-01

    Full Text Available Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc., it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error. Keywords: precipitation, temporal disaggregation, hydrological modelling, error propagation

  4. Model of a neural network inertial satellite navigation system capable of estimating the earth's gravitational field gradient

    Science.gov (United States)

    Devyatisil'nyi, A. S.

    2016-09-01

    A model for recognizing inertial and satellite data on an object's motion that are delivered by a set of distributed onboard sensors (newtonmeters, gyros, satellite receivers) has been described. Specifically, the model is capable of estimating the parameters of the gravitational field.

  5. An improved technique for global daily sunshine duration estimation using satellite imagery

    Institute of Scientific and Technical Information of China (English)

    Muhammad Ali SHAMIM; Renji REMESAN; Da-wei HAN; Naeem EJAZ; Ayub ELAHI

    2012-01-01

    This paper presents an improved model for global sunshine duration estimation.The methodology incorporates geostationary satellite images by including snow cover information,sun and satellite angles and a trend correction factor for seasons,for the determination of cloud cover index.The effectiveness of the proposed methodology has been tested using Meteosat geostationary satellite images in the visible band with a temporal resolution of 1 h and spatial resolution of 2.5 km×2.5 km,for the Brue Catchment in the southwest of England.Validation results show a significant improvement in the estimation of global sunshine duration by the proposed method as compared to its predecessor (R2 is improved from 0.68 to 0.83,root mean squared error (RMSE) from 2.37 h/d to 1.19 h/d and the mean biased error (MBE) from 0.21 h/d to 0.08 h/d).Further studies are needed to test this method in other parts of the world with different climate and geographical conditions.

  6. A preliminary estimate of geoid-induced variations in repeat orbit satellite altimeter observations

    Science.gov (United States)

    Brenner, Anita C.; Beckley, B. D.; Koblinsky, C. J.

    1990-01-01

    Altimeter satellites are often maintained in a repeating orbit to facilitate the separation of sea-height variations from the geoid. However, atmospheric drag and solar radiation pressure cause a satellite orbit to drift. For Geosat this drift causes the ground track to vary by + or - 1 km about the nominal repeat path. This misalignment leads to an error in the estimates of sea surface height variations because of the local slope in the geoid. This error has been estimated globally for the Geosat Exact Repeat Mission using a mean sea surface constructed from Geos 3 and Seasat altimeter data. Over most of the ocean the geoid gradient is small, and the repeat-track misalignment leads to errors of only 1 to 2 cm. However, in the vicinity of trenches, continental shelves, islands, and seamounts, errors can exceed 20 cm. The estimated error is compared with direct estimates from Geosat altimetry, and a strong correlation is found in the vicinity of the Tonga and Aleutian trenches. This correlation increases as the orbit error is reduced because of the increased signal-to-noise ratio.

  7. A preliminary estimate of geoid-induced variations in repeat orbit satellite altimeter observations

    Science.gov (United States)

    Brenner, Anita C.; Beckley, B. D.; Koblinsky, C. J.

    1990-01-01

    Altimeter satellites are often maintained in a repeating orbit to facilitate the separation of sea-height variations from the geoid. However, atmospheric drag and solar radiation pressure cause a satellite orbit to drift. For Geosat this drift causes the ground track to vary by + or - 1 km about the nominal repeat path. This misalignment leads to an error in the estimates of sea surface height variations because of the local slope in the geoid. This error has been estimated globally for the Geosat Exact Repeat Mission using a mean sea surface constructed from Geos 3 and Seasat altimeter data. Over most of the ocean the geoid gradient is small, and the repeat-track misalignment leads to errors of only 1 to 2 cm. However, in the vicinity of trenches, continental shelves, islands, and seamounts, errors can exceed 20 cm. The estimated error is compared with direct estimates from Geosat altimetry, and a strong correlation is found in the vicinity of the Tonga and Aleutian trenches. This correlation increases as the orbit error is reduced because of the increased signal-to-noise ratio.

  8. Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

    Science.gov (United States)

    Fisher, Brad; Wolff, David B.

    2010-01-01

    Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-10-14

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

  10. Validation of satellite-based noontime UVI with NDACC ground-based instruments: influence of topography, environment and satellite overpass time

    Science.gov (United States)

    Brogniez, Colette; Auriol, Frédérique; Deroo, Christine; Arola, Antti; Kujanpää, Jukka; Sauvage, Béatrice; Kalakoski, Niilo; Riku Aleksi Pitkänen, Mikko; Catalfamo, Maxime; Metzger, Jean-Marc; Tournois, Guy; Da Conceicao, Pierre

    2016-12-01

    Spectral solar UV radiation measurements are performed in France using three spectroradiometers located at very different sites. One is installed in Villeneuve d'Ascq, in the north of France (VDA). It is an urban site in a topographically flat region. Another instrument is installed in Observatoire de Haute-Provence, located in the southern French Alps (OHP). It is a rural mountainous site. The third instrument is installed in Saint-Denis, Réunion Island (SDR). It is a coastal urban site on a small mountainous island in the southern tropics. The three instruments are affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and carry out routine measurements to monitor the spectral solar UV radiation and enable derivation of UV index (UVI). The ground-based UVI values observed at solar noon are compared to similar quantities derived from the Ozone Monitoring Instrument (OMI, onboard the Aura satellite) and the second Global Ozone Monitoring Experiment (GOME-2, onboard the Metop-A satellite) measurements for validation of these satellite-based products. The present study concerns the period 2009-September 2012, date of the implementation of a new OMI processing tool. The new version (v1.3) introduces a correction for absorbing aerosols that were not considered in the old version (v1.2). Both versions of the OMI UVI products were available before September 2012 and are used to assess the improvement of the new processing tool. On average, estimates from satellite instruments always overestimate surface UVI at solar noon. Under cloudless conditions, the satellite-derived estimates of UVI compare satisfactorily with ground-based data: the median relative bias is less than 8 % at VDA and 4 % at SDR for both OMI v1.3 and GOME-2, and about 6 % for OMI v1.3 and 2 % for GOME-2 at OHP. The correlation between satellite-based and ground-based data is better at VDA and OHP (about 0.99) than at SDR (0.96) for both space-borne instruments. For all

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

    Science.gov (United States)

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

    2002-01-01

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

  12. The key role of Satellite Laser Ranging towards the integrated estimation of geometry, rotation and gravitational field of the Earth

    Science.gov (United States)

    Blossfeld, Mathis

    2015-01-01

    In 2007, the Global Geodetic Observing System (GGOS) was installed as a full component of the International Association of Geodesy (IAG). One primary goal of GGOS is the integration of geometric and gravimetric observation techniques to estimate consistent geodetic-geophysical parameters. Thereby, GGOS is based on the data and services of the IAG. Besides the combination of different geodetic techniques, also the common estimation of the station coordinates (TRF), Earth Orientation Parameters (EOP) and coefficients of the Earth's gravitational field (Stokes coefficients) is necessary in order to reach this goal. However, the combination of all geometric and gravimetric observation techniques is not yet fully realized. A major step towards the GGOS idea of parameter integration would be the understanding of the existing correlations between the above mentioned fundamental geodetic parameter groups. This topic is the major objective of this thesis. One possibility to study the interactions is the use of Satellite Laser Ranging (SLR) in an intertechnique combination with Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI) or the intra-technique combination of multiple SLR-tracked satellites. SLR plays a key role in this thesis since it is the unique technique which is sensitive to all parameter groups and allows an integrated parameter estimation with very high accuracy. The present work is based on five first-author publications which are supplemented by four co-author publications. In this framework, for the first time an extensive discussion of a refined global Terrestrial Reference Frame (TRF) estimation procedure, the estimation of so-called Epoch Reference Frames (ERFs) is presented. In contrast to the conventional linear station motion model, the ERFs provide frequently estimated station coordinates and Earth Orientation Parameters (EOP) which allow to approximate not modeled non-linear station motions very accurately

  13. Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique

    Science.gov (United States)

    Ronald E. McRoberts; Mark D. Nelson; Daniel G. Wendt

    2002-01-01

    For two large study areas in Minnesota, USA, stratified estimation using classified Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-stratum estimates. These measurements further...

  14. Validation of an Innovative Satellite-Based UV Dosimeter

    Science.gov (United States)

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

    2016-08-01

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

  15. AATSR Based Volcanic Ash Plume Top Height Estimation

    Science.gov (United States)

    Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Sundstrom, Anu-Maija; Rodriguez, Edith; de Leeuw, Gerrit

    2015-11-01

    The AATSR Correlation Method (ACM) height estimation algorithm is presented. The algorithm uses Advanced Along Track Scanning Radiometer (AATSR) satellite data to detect volcanic ash plumes and to estimate the plume top height. The height estimate is based on the stereo-viewing capability of the AATSR instrument, which allows to determine the parallax between the satellite's nadir and 55◦ forward views, and thus the corresponding height. AATSR provides an advantage compared to other stereo-view satellite instruments: with AATSR it is possible to detect ash plumes using brightness temperature difference between thermal infrared (TIR) channels centered at 11 and 12 μm. The automatic ash detection makes the algorithm efficient in processing large quantities of data: the height estimate is calculated only for the ash-flagged pixels. Besides ash plumes, the algorithm can be applied to any elevated feature with sufficient contrast to the background, such as smoke and dust plumes and clouds. The ACM algorithm can be applied to the Sea and Land Surface Temperature Radiometer (SLSTR), scheduled for launch at the end of 2015.

  16. Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

    Institute of Scientific and Technical Information of China (English)

    REN Lin; MAO Zhihua; HUANG Haiqing; GONG Fang

    2010-01-01

    Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360~. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.

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

    CERN Document Server

    Betz, J

    2016-01-01

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

  18. Satellite-based monitoring of particulate matter pollution at very high resolution: the HOTBAR method

    Science.gov (United States)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Particulate matter air pollution is a major health risk, and is responsible for millions of premature deaths each year. Concentrations tend to be highest in urban areas - particularly in the mega-cities of rapidly industrialising countries, where there are limited ground monitoring networks. Satellite-based monitoring has been used for many years to assess regional-scale trends in air quality, but currently available satellite products produce data at 1-10km resolution: too coarse to discern the small-scale patterns of sources and sinks seen in urban areas. Higher-resolution satellite products are required to provide accurate assessments of particulate matter concentrations in these areas, and to allow analysis of localised air quality effects on health. The Haze Optimized Transform-based Aerosol Retrieval (HOTBAR) method is a novel method which provides estimates of PM2.5 concentrations from high-resolution (approximately 30m) satellite imagery. This method is designed to work over a wide range of land covers and performs well over the complex land-cover mosaic found in urban areas. It requires only standard visible and near-infrared data, making it applicable to a range of data from sensors such as Landsat, SPOT and Sentinel-2. The method is based upon an extension of the Haze Optimized Transform (HOT), which was originally designed for assessing areas of thick haze in satellite imagery. This was done by calculating a 'haziness' value for each pixel in an image as the distance from a 'Clear Line' in feature space, defined by the high correlation between visible bands. Here, we adapt the HOT method and use it to estimate Aerosol Optical Thickness (a measure of the column-integrated haziness of the atmosphere) instead, from which PM2.5 concentrations can then be estimated. Significant extensions to the original HOT method include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values

  19. GPS/Magnetometer Based Satellite Navigation and Attitude Determination

    Science.gov (United States)

    Deutschmann, Julie; Bar-Itzhack, Itzhack; Harman, Rick; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    In recent years algorithms were developed for orbit, attitude and angular-rate determination of Low Earth Orbiting (LEO) satellites. Those algorithms rely on measurements of magnetometers, which are standard, relatively inexpensive, sensors that are normally installed on every LEO satellite. Although magnetometers alone are sufficient for obtaining the desired information, the convergence of the algorithms to the correct values of the satellite orbital parameters, position, attitude and angular velocity is very slow. The addition of sun sensors reduces the convergence time considerably. However, for many LEO satellites the sun data is not available during portions of the orbit when the spacecraft (SC) is in the earth shadow. It is here where the GPS space vehicles (SV) can provide valuable support. This is clearly demonstrated in the present paper. Although GPS measurements alone can be used to obtain SC position, velocity, attitude and angular-rate, the use of magnetometers improve the results due to the synergistic effect of sensor fusion. Moreover, it is possible to obtain these results with less than three SVs. In this paper we introduce an estimation algorithm, which is a combination of an Extended Kalman Filter (EKF) and a Pseudo Linear Kalman Filter (PSELIKA).

  20. Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Genovese Vanessa

    2007-10-01

    Full Text Available Abstract Background A simulation model that relies on satellite observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (MODIS was used to estimate net primary productivity (NPP of forest stands at the Bartlett Experiment Forest (BEF in the White Mountains of New Hampshire. Results Net primary production (NPP predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape. Comparison of the model-predicted annual NPP to the plot-estimated values showed a significant correlation of R2 = 0.5. Stepwise addition of 30-meter resolution elevation data values explained no more than 20% of the residual variation in measured NPP patterns at BEF. Both the Landsat 7 and the 250-meter resolution MODIS derived mean annual NPP predictions for the BEF plot locations were within ± 2.5% of the mean of plot estimates for annual NPP. Conclusion Although MODIS imagery cannot capture the spatial details of NPP across the network of closely spaced plot locations as well as Landsat, the MODIS satellite data as inputs to the NASA-CASA model does accurately predict the average annual productivity of a site like the BEF.

  1. Minimum Number of Observation Points for LEO Satellite Orbit Estimation by OWL Network

    Science.gov (United States)

    Park, Maru; Jo, Jung Hyun; Cho, Sungki; Choi, Jin; Kim, Chun-Hwey; Park, Jang-Hyun; Yim, Hong-Suh; Choi, Young-Jun; Moon, Hong-Kyu; Bae, Young-Ho; Park, Sun-Youp; Kim, Ji-Hye; Roh, Dong-Goo; Jang, Hyun-Jung; Park, Young-Sik; Jeong, Min-Ji

    2015-12-01

    By using the Optical Wide-field Patrol (OWL) network developed by the Korea Astronomy and Space Science Institute (KASI) we generated the right ascension and declination angle data from optical observation of Low Earth Orbit (LEO) satellites. We performed an analysis to verify the optimum number of observations needed per arc for successful estimation of orbit. The currently functioning OWL observatories are located in Daejeon (South Korea), Songino (Mongolia), and Oukaïmeden (Morocco). The Daejeon Observatory is functioning as a test bed. In this study, the observed targets were Gravity Probe B, COSMOS 1455, COSMOS 1726, COSMOS 2428, SEASAT 1, ATV-5, and CryoSat-2 (all in LEO). These satellites were observed from the test bed and the Songino Observatory of the OWL network during 21 nights in 2014 and 2015. After we estimated the orbit from systematically selected sets of observation points (20, 50, 100, and 150) for each pass, we compared the difference between the orbit estimates for each case, and the Two Line Element set (TLE) from the Joint Space Operation Center (JSpOC). Then, we determined the average of the difference and selected the optimal observation points by comparing the average values.

  2. Solar resources estimation combining digital terrain models and satellite images techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)

    2010-12-15

    One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

  3. A Satellite Based Fog Study of the Korean Peninsula

    Science.gov (United States)

    2007-06-01

    total number of fog and fog likely days detected from the two MODIS satellites, Aqua and Tera , respectively. Results from all nine areas of...trends in fog detection based on the satellite differences. 46 0 20 40 60 80 100 120 N um be r o f D ay s 1 2 3 4 5 6 7 8 9 Areas Four Month Tera vs...Aqua Fog Totals Tera Fog Tera Fog Likely Aqua Fog Aqua Fog Likely Figure 29. Comparisons of the four month total number of fog and fog likely days

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

    Science.gov (United States)

    Abrishamkar, Farrokh; Biglieri, Ezio

    1988-01-01

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

  5. Ionospheric TEC Estimations with the Signals of Various Geostationary Navigational Satellites

    Science.gov (United States)

    Kurbatov, G. A.; Padokhin, A. M.; Kunitsyn, V.; Yasyukevich, Y.

    2015-12-01

    The development of GNSS and SBAS systems provides the possibility to retrieve ionospheric TEC from the dual frequency observations from a number of geostationary satellites using the same approach as for dual frequency GPS/GLONASS observations. In this connection, the quality of geostationary data, first of all the level of noise in TEC estimations is of great interest and importance. In this work we present the results of the comparison of the noise patterns in TEC estimations using signals of geostationary satellites of augumentation systems - indian GAGAN, european EGNOS and american WAAS, as well as the signals of chinees COMPASS/Beidou navigational system. We show that among above mentioned systems geostationary COMPASS/Beidou satellites provide best noise level in TEC estimations (RMS~0.1TECU), which corresponds to those of GPS/GLONASS, while GAGAN and WAAS TEC RMS could reach up to 1.5 TECU with typical values of 0.25-0.5 TECU which is up to one order greater than for common GPS/GLONASS observations. EGNOS TEC estimations being even more noisy (TEC RMS up to 10TECU) than WAAS and GAGAN ones at present time are not suitable for ionospheric studies. We also present geostationary TEC response to increasing solar X-Ray and EUV ionizing radiation during several recent X-class flares. Good correlation was found between TEC and EUV flux for the stations at the sunlit hemisphere. We also present geostationary TEC response to geomagnetic field variations during strong and moderate geomagnetic storms (including G4 St. Patricks Day Storm of 2015) showing examples of both positive and negative TEC anomalies of order of tens of TECU during main storm phase. Our results show the capability of geostationary GNSS and SBAS observations for continuous monitoring of ionospheric TEC. Intensively growing networks of dedicated receivers (for example MGEX network) and increasing number of dual-frequency geostationary satellites in SBAS and GNSS constellations potentially make it a

  6. Error analysis for satellite gravity field determination based on two-dimensional Fourier methods

    CERN Document Server

    Cai, Lin; Hsu, Houtse; Gao, Fang; Zhu, Zhu; Luo, Jun

    2012-01-01

    The time-wise and space-wise approaches are generally applied to data processing and error analysis for satellite gravimetry missions. But both the approaches, which are based on least-squares collocation, address the whole effect of measurement errors and estimate the resolution of gravity field models mainly from a numerical point of indirect view. Moreover, requirement for higher accuracy and resolution gravity field models could make the computation more difficult, and serious numerical instabilities arise. In order to overcome the problems, this study focuses on constructing a direct relationship between power spectral density of the satellite gravimetry measurements and coefficients of the Earth's gravity potential. Based on two-dimensional Fourier transform, the relationship is analytically concluded. By taking advantage of the analytical expression, it is efficient and distinct for parameter estimation and error analysis of missions. From the relationship and the simulations, it is analytically confir...

  7. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization

    Science.gov (United States)

    Smith, W. Kolby; Reed, Sasha C.; Cleveland, Cory C.; Ballantyne, Ashley P; Anderegg, William R. L.; Wieder, William R.; Liu, Yi Y; Running, Steven W.

    2015-01-01

    Atmospheric mass balance analyses suggest that terrestrial carbon (C) storage is increasing, partially abating the atmospheric [CO2] growth rate, although the continued strength of this important ecosystem service remains uncertain. Some evidence suggests that these increases will persist owing to positive responses of vegetation growth (net primary productivity; NPP) to rising atmospheric [CO2] (that is, ‘CO2 fertilization’). Here, we present a new satellite-derived global terrestrial NPP data set, which shows a significant increase in NPP from 1982 to 2011. However, comparison against Earth system model (ESM) NPP estimates reveals a significant divergence, with satellite-derived increases (2.8 ± 1.50%) less than half of ESM-derived increases (7.6  ±  1.67%) over the 30-year period. By isolating the CO2 fertilization effect in each NPP time series and comparing it against a synthesis of available free-air CO2 enrichment data, we provide evidence that much of the discrepancy may be due to an over-sensitivity of ESMs to atmospheric [CO2], potentially reflecting an under-representation of climatic feedbacks and/or a lack of representation of nutrient constraints. Our understanding of CO2 fertilization effects on NPP needs rapid improvement to enable more accurate projections of future C cycle–climate feedbacks; we contend that better integration of modelling, satellite and experimental approaches offers a promising way forward.

  8. Exploiting the power law distribution properties of satellite fire radiative power retrievals: A method to estimate fire radiative energy and biomass burned from sparse satellite observations

    Science.gov (United States)

    Kumar, S. S.; Roy, D. P.; Boschetti, L.; Kremens, R.

    2011-10-01

    Instantaneous estimates of the power released by fire (fire radiative power, FRP) are available with satellite active fire detection products. The temporal integral of FRP provides an estimate of the fire radiative energy (FRE) that is related linearly to the amount of biomass burned needed by the atmospheric emissions modeling community. The FRE, however, is sensitive to satellite temporal and spatial FRP undersampling due to infrequent satellite overpasses, cloud and smoke obscuration, and failure to detect cool and/or small fires. Satellite FRPs derived over individual burned areas and fires have been observed to exhibit power law distributions. This property is exploited to develop a new way to derive FRE, as the product of the fire duration and the expected FRP value derived from the FRP power law probability distribution function. The method is demonstrated and validated by the use of FRP data measured with a dual-band radiometer over prescribed fires in the United States and by the use of FRP data retrieved from moderate resolution imaging spectroradiometer (MODIS) active-fire detections over Brazilian deforestation and Australian savanna fires. The biomass burned derived using the conventional FRP temporal integration and power law FRE estimation methods is compared with biomass burned measurements (prescribed fires) and available fuel load information reported in the literature (Australian and Brazilian fires). The results indicate that the FRE power law derivation method may provide more reliable burned biomass estimates under sparse satellite FRP sampling conditions and correct for satellite active-fire detection omission errors if the FRP power law distribution parameters and the fire duration are known.

  9. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  10. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li

    2009-01-01

    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  11. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    Science.gov (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  12. Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

    Science.gov (United States)

    Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

    2010-12-01

    The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture

  13. Satellite-based assessment of climate controls on US burned area

    OpenAIRE

    D. C. Morton; G. J. Collatz; Wang, D.; Randerson, J. T.; Giglio, L.; Chen, Y.

    2013-01-01

    Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate–fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burne...

  14. Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

    OpenAIRE

    HASIRCI, Z.; Cavdar, I. H.; Ozturk, M

    2016-01-01

    Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ...

  15. The principle of the positioning system based on communication satellites

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    It is a long dream to realize the communication and navigation functionality in a satellite system in the world. This paper introduces how to establish the system, a positioning system based on communication satellites called Chinese Area Positioning System (CAPS). Instead of the typical navigation satellites, the communication satellites are configured firstly to transfer navigation signals from ground stations, and can be used to obtain service of the positioning, velocity and time, and to achieve the function of navigation and positioning. Some key technique issues should be first solved; they include the accuracy position determination and orbit prediction of the communication satellites, the measur- ing and calculation of transfer time of the signals, the carrier frequency drift in communication satellite signal transfer, how to improve the geometrical configuration of the constellation in the system, and the integration of navigation & communication. Several innovative methods are developed to make the new system have full functions of navigation and communication. Based on the development of crucial techniques and methods, the CAPS demonstration system has been designed and developed. Four communication satellites in the geosynchronous orbit (GEO) located at 87.5°E, 110.5°E, 134°E, 142°E and barometric altimetry are used in the CAPS system. The GEO satellites located at 134°E and 142°E are decommissioned GEO (DGEO) satellites. C-band is used as the navigation band. Dual frequency at C1=4143.15 MHz and C2=3826.02 MHz as well as dual codes with standard code (CA code and precision code (P code)) are adopted. The ground segment consists of five ground stations; the master station is in Lintong, Xi’an. The ground stations take a lot of responsibilities, including monitor and management of the operation of all system components, determination of the satellite position and prediction of the satellite orbit, accomplishment of the virtual atomic clock

  16. Dust indicator maps for improving solar radiation estimation from satellite data

    Science.gov (United States)

    Marpu, P. R.; Eissa, Y.; Al Meqbali, N.; Ghedira, H.

    2012-12-01

    Measurement of solar radiation from ground-based sensors is an expensive process as it requires large number of ground measurement stations to account for the spatial variability. Moreover, the instruments require regular maintenance. Satellite data can be used to model solar radiation and produce maps in regular intervals, which can be used for solar resource assessment. The models can either be empirical, physics-based or statistical models. However, in environments such as the United Arab Emirates (UAE) which are characterized by heavy dust, the results obtained by the models will lead to lower accuracies. In this study, we build on the model developed in [1], where ensembles of ANNs are used separately for cloudy and cloud-free pixels to derive solar radiation maps using the data acquired in the thermal channels of the Meteosat SEVIRI instrument. The model showed good accuracies for the estimation of direct normal irradiance (DNI), diffuse horizontal irradiance (DHI) and global horizontal irradiance (GHI); where the relative root mean square error (rRMSE) values for the DNI, DHI and GHI were 15.7, 23.6 and 7.2%, respectively, while the relative mean bias error (rMBE) values were +0.8, +8.3 and +1.9%, respectively. However, an analysis of the results on different dusty days showed varying accuracy. To further improve the model, we propose to use the dust indicator maps as inputs to the model. An interception index was proposed in [2] to detect dust over desert regions using visible channels of the SEVIRI instrument. The index has a range of 0 to 1 where the value of 1 corresponds to heavy dust and 0 corresponds to clear conditions. There is ongoing work to use the measurements from AERONET stations to derive dust indicator maps based on canonical correlation analysis, which relates the thermal channels to the aerosol optical depth (AOD) derived at different wavelengths from the AERONET measurements. There is also an ongoing work to analyze the time series of the

  17. Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

    Science.gov (United States)

    Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  18. Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

    Directory of Open Access Journals (Sweden)

    Carolien Toté

    2015-02-01

    Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  19. Possible satellite-based observations of the 1997 Leonid meteoroids

    Energy Technology Data Exchange (ETDEWEB)

    Pongratz, M.B.; Carlos, R.C.; Cayton, T.

    1998-12-01

    The Block IIA GPS satellites are equipped with a sensor designed to detect electromagnetic transients. Several phenomena will produce triggers in this sensor. They include earth-based electromagnetic transients such as lightning and two space-based phenomena--deep dielectric discharge and meteoroid or hyper-velocity micro-gram particle impact (HMPI). Energetic electrons in the GPS environment cause the deep dielectric charging. HMPIs cause triggers through the transient electric fields generated by the ejecta plasma. During the 1997 Leonid passage the energetic particle fluxes were very low. In the presence of such low fluxes the typical median trigger rate is 20 per minute with a standard deviation of about 20 per minute. Between 0800 UT and 1200 UT on November 17, 1997, the sensor on a specially configured satellite observed trigger rates more than 10 sigma above the nominal median rate. Sensors on other Block IIA GPS satellites also observed excess triggers during November. Detection is enhanced when the sensor antenna is oriented into the Leonid radiant. While many questions persist the authors feel that it is likely that the excess events during the November interval were caused by the close approach of the satellites to the Leonid meteoroid path.

  20. An Ontology Based Methodology for Satellite Data Semantic Interoperability

    Directory of Open Access Journals (Sweden)

    ABBURU, S.

    2015-08-01

    Full Text Available Satellites and ocean based observing system consists of various sensors and configurations. These observing systems transmit data in heterogeneous file formats and heterogeneous vocabulary from various data centers. These data centers maintain a centralized data management system that disseminates the observations to various research communities. Currently, different data naming conventions are being used by existing observing systems, thus leading to semantic heterogeneity. In this work, sensor data interoperability and semantics of the data are being addressed through ontologies. The present work provides an effective technical solution to address semantic heterogeneity through semantic technologies. These technologies provide interoperability, capability to build knowledge base, and framework for semantic information retrieval by developing an effective concept vocabulary through domain ontologies. The paper aims at a new methodology to interlink the multidisciplinary and heterogeneous sensor data products. A four phase methodology has been implemented to address satellite data semantic interoperability. The paper concludes with the evaluation of the methodology by linking and interfacing multiple ontologies to arrive at ontology vocabulary for sensor observations. Data from Indian Meteorological satellite INSAT-3D satellite have been used as a typical example to illustrate the concepts. This work on similar lines can also be extended to other sensor observations.

  1. Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

    2012-01-01

    Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

  2. Tracking and Data Relay Satellite (TDRS) Orbit Estimation Using an Extended Kalman Filter

    Science.gov (United States)

    Ward, Douglas T.; Dang, Ket D.; Slojkowski, Steve; Blizzard, Mike; Jenkins, Greg

    2007-01-01

    Alternatives to the Tracking and Data Relay Satellite (TDRS) orbit estimation procedure were studied to develop a technique that both produces more reliable results and is more amenable to automation than the prior procedure. The Earth Observing System (EOS) Terra mission has TDRS ephemeris prediction 3(sigma) requirements of 75 meters in position and 5.5 millimeters per second in velocity over a 1.5-day prediction span. Meeting these requirements sometimes required reruns of the prior orbit determination (OD) process, with manual editing of tracking data to get an acceptable solution. After a study of the available alternatives, the Flight Dynamics Facility (FDF) began using the Real-Time Orbit Determination (RTOD(Registered TradeMark)) Kalman filter program for operational support of TDRSs in February 2007. This extended Kalman filter (EKF) is used for daily support, including within hours after most thrusting, to estimate the spacecraft position, velocity, and solar radiation coefficient of reflectivity (C(sub R)). The tracking data used are from the Bilateration Ranging Transponder System (BRTS), selected TDRS System (TDRSS) User satellite tracking data, and Telemetry, Tracking, and Command (TT&C) data. Degraded filter results right after maneuvers and some momentum unloads provided incentive for a hybrid OD technique. The results of combining EKF strengths with the Goddard Trajectory Determination System (GTDS) Differential Correction (DC) program batch-least-squares solutions, as recommended in a 2005 paper on the chain-bias technique, are also presented.

  3. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  4. The principle of the positioning system based on communication satellites

    Institute of Scientific and Technical Information of China (English)

    AI GuoXiang; SHI HuLi; WU HaiTao; LI ZhiGang; GUO Ji

    2009-01-01

    It is a long dream to realize the communication and navigation functionality in a satellite system in the world.This paper introduces how to establish the system,a positioning system based on communication satellites called Chinese Area Positioning System (CAPS).Instead of the typical navigation satelIites,the communication satellites are configured firstly to transfer navigation signals from ground stations,and can be used to obtain service of the positioning,velocity and time,and to achieve the function of navigation and positioning.Some key technique issues should be first solved; they include the accuracy position determination and orbit prediction of the communication satellites,the measuring and calculation of transfer time of the signals,the carrier frequency drift in communication satellite ignal transfer,how to improve the geometrical configuration of the constellation in the system,and the integration of navigation & communication.Several innovative methods are developed to make the new system have full functions of navigation and communication.Based on the development of crucial techniques and methods,the CAPS demonstration system has been designed and developed.Four communication satellites in the geosynchronous orbit (GEO) located at 87.5°E,110.5°E,134°E,142°E and barometric altimetry are used in the CAPS system.The GEO satellites located at 134°E and 142°E re decommissioned GEO (DGEO) satellites.C-band is used as the navigation band.Dual frequency at C1=4143.15 MHz and C2=3826.02 MHz as well as dual codes with standard code (CA code and precision code (P code)) are adopted.The ground segment consists of five ground stations; the master station is in Lintong,Xi'an.The ground stations take a lot of responsibilities,including monitor and management of the operation of all system components,determination of the satellite position and prediction of the satellite orbit,accomplishment of the virtual atomic clock measurement,transmission and receiving

  5. Satellite microwave estimates of soil moisture and applications for desertification studies

    Science.gov (United States)

    Owe, Manfred; Van de Griend, Adriaan A.; de Jeu, Richard A.; de Vries, Jorrit; Seyhan, E.

    1998-12-01

    Based on a series of studies conducted in Botswana and preliminary results from an ongoing study in Spain, developments in microwave remote sensing by satellite which can be used to monitor near real-time surface moisture and also study long term soil moisture climatology are described. A progression of methodologies beginning with single polarization studies and leading to both dual polarization and multiple frequency techniques are described. Continuing analysis of a nine year data set of satellite-derived surface moisture in Spain is ongoing. Preliminary results from this study appear to provide some evidence of long term decertification in certain parts of this region. The methodologies developed during these investigations can be applied to other regions, and have the potential for providing modelers with extended data sets of independently derived surface moisture for simulation and validation studies, and climate change studies at the global scale.

  6. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

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

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

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

  8. Growth in NOx emissions from power plants in China: bottom-up estimates and satellite observations

    Directory of Open Access Journals (Sweden)

    Y. Lei

    2012-01-01

    Full Text Available Using OMI (Ozone Monitoring Instrument tropospheric NO2 columns and a nested-grid 3-D global chemical transport model (GEOS-Chem, we investigated the growth in NOx emissions from coal-fired power plants and their contributions to the growth in NO2 columns in 2005–2007 in China. We first developed a unit-based power plant NOx emission inventory for 2005–2007 to support this investigation. The total capacities of coal-fired power generation have increased by 48.8% in 2005–2007, with 92.2% of the total capacity additions coming from generator units with size ≥300 MW. The annual NOx emissions from coal-fired power plants were estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg NO2 for 2007, respectively. The modeled summer average tropospheric NO2 columns were highly correlated (R2 = 0.79–0.82 with OMI measurements over grids dominated by power plant emissions, with only 7–14% low bias, lending support to the high accuracy of the unit-based power plant NOx emission inventory. The ratios of OMI-derived annual and summer average tropospheric NO2 columns between 2007 and 2005 indicated that most of the grids with significant NO2 increases were related to power plant construction activities. OMI had the capability to trace the changes of NOx emissions from individual large power plants in cases where there is less interference from other NOx sources. Scenario runs from GEOS-Chem model suggested that the new power plants contributed 18.5% and 10% to the annual average NO2 columns in 2007 in Inner Mongolia and North China, respectively. The massive new power plant NOx emissions significantly changed the local NO2 profiles, especially in less polluted areas. A sensitivity study found that changes of NO2 shape factors due to including new power plant emissions increased the summer average OMI tropospheric NO2 columns by 3.8–17.2% for six selected locations, indicating that the updated emission information could help to improve the satellite

  9. Growth in NOx emissions from power plants in China: bottom-up estimates and satellite observations

    Directory of Open Access Journals (Sweden)

    Y. Lei

    2012-05-01

    Full Text Available Using OMI (Ozone Monitoring Instrument tropospheric NO2 columns and a nested-grid 3-D global chemical transport model (GEOS-Chem, we investigated the growth in NOx emissions from coal-fired power plants and their contributions to the growth in NO2 columns in 2005–2007 in China. We first developed a unit-based power plant NOx emission inventory for 2005–2007 to support this investigation. The total capacities of coal-fired power generation have increased by 48.8% in 2005–2007, with 92.2% of the total capacity additions coming from generator units with size ≥300 MW. The annual NOx emissions from coal-fired power plants were estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg NO2 for 2007, respectively. The modeled summer average tropospheric NO2 columns were highly correlated (R2 = 0.79–0.82 with OMI measurements over grids dominated by power plant emissions, with only 7–14% low bias, lending support to the high accuracy of the unit-based power plant NOx emission inventory. The ratios of OMI-derived annual and summer average tropospheric NO2 columns between 2007 and 2005 indicated that most of the grids with significant NO2 increases were related to power plant construction activities. OMI had the capability to trace the changes of NOx emissions from individual large power plants in cases where there is less interference from other NOx sources. Scenario runs from GEOS-Chem model suggested that the new power plants contributed 18.5% and 10% to the annual average NO2 columns in 2007 in Inner Mongolia and North China, respectively. The massive new power plant NOx emissions significantly changed the local NO2 profiles, especially in less polluted areas. A sensitivity study found that changes of NO2 shape factors due to including new power plant emissions increased the summer average OMI tropospheric NO2 columns by 3.8–17.2% for six selected locations, indicating that the updated emission information could help to improve the satellite

  10. MITRA Virtual laboratory for operative application of satellite time series for land degradation risk estimation

    Science.gov (United States)

    Nole, Gabriele; Scorza, Francesco; Lanorte, Antonio; Manzi, Teresa; Lasaponara, Rosa

    2015-04-01

    This paper aims to present the development of a tool to integrate time series from active and passive satellite sensors (such as of MODIS, Vegetation, Landsat, ASTER, COSMO, Sentinel) into a virtual laboratory to support studies on landscape and archaeological landscape, investigation on environmental changes, estimation and monitoring of natural and anthropogenic risks. The virtual laboratory is composed by both data and open source tools specifically developed for the above mentioned applications. Results obtained for investigations carried out using the implemented tools for monitoring land degradation issues and subtle changes ongoing on forestry and natural areas are herein presented. In detail MODIS, SPOT Vegetation and Landsat time series were analyzed comparing results of different statistical analyses and the results integrated with ancillary data and evaluated with field survey. The comparison of the outputs we obtained for the Basilicata Region from satellite data analyses and independent data sets clearly pointed out the reliability for the diverse change analyses we performed, at the pixel level, using MODIS, SPOT Vegetation and Landsat TM data. Next steps are going to be implemented to further advance the current Virtual Laboratory tools, by extending current facilities adding new computational algorithms and applying to other geographic regions. Acknowledgement This research was performed within the framework of the project PO FESR Basilicata 2007/2013 - Progetto di cooperazione internazionale MITRA "Remote Sensing tecnologies for Natural and Cultural heritage Degradation Monitoring for Preservation and valorization" funded by Basilicata Region Reference 1. A. Lanorte, 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 disturbance International Journal of Applied Earth Observation and

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

    Science.gov (United States)

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

    2010-05-01

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

  12. Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycle.In this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory data.The resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf forests.These models were used to estimate biomass for all GLAS footprints of forest located in the study area.All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data.Biomass data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t ha-1.The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area.It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to

  13. Galileo satellite antenna modeling

    Science.gov (United States)

    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.

  14. UKF-based attitude determination method for gyroless satellite

    Institute of Scientific and Technical Information of China (English)

    张红梅; 邓正隆

    2004-01-01

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

  15. Periodic material-based vibration isolation for satellites

    Directory of Open Access Journals (Sweden)

    Xinnan Liu

    2016-01-01

    Full Text Available The vibration environment of a satellite is very severe during launch. Isolating the satellitevibrations during launch will significantly enhance reliability and lifespan, and reduce the weight of satellite structure and manufacturing cost. Guided by the recent advances in solid-state physics research, a new type of satellite vibration isolator is proposed by usingperiodic material that is hence called periodic isolator. The periodic isolator possesses a unique dynamic property, i.e., frequency band gaps. External vibrations with frequencies falling in the frequency band gaps of the periodic isolator are to be isolated. Using the elastodynamics and the Bloch-Floquet theorem, the frequency band gaps of periodic isolators are determined. A parametric study is conducted to provide guidelines for the design of periodic isolators. Based on these analytical results, a finite element model of a micro-satellite with a set of designed periodic isolators is built to show the feasibility of vibration isolation. The periodic isolator is found to be a multi-directional isolator that provides vibration isolation in the three directions.

  16. Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

    Science.gov (United States)

    Lacagnina, Carlo; Hasekamp, Otto P.; Torres, Omar

    2017-01-01

    Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is -4.6 +/- 1.5 W/sq m for cloud-free and -2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

  17. Direct radiative effect of aerosols based on PARASOL and OMI satellite observations

    Science.gov (United States)

    Lacagnina, Carlo; Hasekamp, Otto P.; Torres, Omar

    2017-02-01

    Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is -4.6 ± 1.5 W/m2 for cloud-free and -2.1 ± 0.7 W/m2 for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

  18. Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

    Science.gov (United States)

    Lacagnina, Carlo; Hasekamp, Otto P.; Torres, Omar

    2017-01-01

    Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is -4.6 +/- 1.5 W/sq m for cloud-free and -2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

  19. Global Fine Particulate Matter Concentrations and Trends Inferred from Satellite Observations, Modeling, and Ground-Based Measurements

    Science.gov (United States)

    Martin, Randall; van Donkelaar, Aaron; Boys, Brian; Philip, Sajeev; Lee, Colin; Snider, Graydon; Weagle, Crystal

    2014-05-01

    Outdoor fine particulate matter (PM2.5) is a leading environmentally-related cause of premature mortality worldwide. However, ground-level PM2.5 monitors remain sparse in many regions of the world. Satellite remote sensing from MODIS, MISR, and SeaWiFS yields a powerful global data source to address this issue. Global modeling (GEOS-Chem) plays a critical role in relating these observations to ground-level concentrations. The resultant satellite-based estimates of PM2.5 indicate dramatic variation around the world, with implications for global public health. A new ground-based aerosol network (SPARTAN) offers valuable measurements to understand the relationship between satellite observations of aerosol optical depth and ground-level PM2.5 concentrations. This talk will highlight recent advances in combining satellite remote sensing, global modeling, and ground-based measurements to improve understanding of global population exposure to outdoor fine particulate matter.

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

    Science.gov (United States)

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

    2017-10-01

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

  1. How reliable are satellite precipitation estimates for driving hydrological models: a verification study over the Mediterranean area

    Science.gov (United States)

    Camici, Stefania; Ciabatta, Luca; Massari, Christian; Brocca, Luca

    2017-04-01

    Floods are one of the most common and dangerous natural hazards, causing every year thousands of casualties and damages worldwide. The main tool for assessing flood risk and reducing damages is represented by hydrologic early warning systems that allow to forecast flood events by using real time data obtained through ground monitoring networks (e.g., raingauges and radars). However, the use of such data, mainly rainfall, presents some issues firstly related to the network density and to the limited spatial representativeness of local measurements. A way to overcome these issues may be the use of satellite-based rainfall products (SRPs) that nowadays are available on a global scale at ever increasing spatial/temporal resolution and accuracy. However, despite the large availability and increased accuracy of SRPs (e.g., the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA); the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF); and the recent Global Precipitation Measurement (GPM) mission), remotely sensed rainfall data are scarcely used in hydrological modeling and only a small number of studies have been carried out to outline some guidelines for using satellite data as input for hydrological modelling. Reasons may be related to: 1) the large bias characterizing satellite precipitation estimates, which is dependent on rainfall intensity and season, 2) the spatial/temporal resolution, 3) the timeliness, which is often insufficient for operational purposes, and 4) a general (often not justified) skepticism of the hydrological community in the use of satellite products for land applications. The objective of this study is to explore the feasibility of using SRPs in a lumped hydrologic model (MISDc, "Modello Idrologico Semi-Distribuito in continuo", Masseroni et al., 2017) over 10 basins in the Mediterranean area with different sizes and physiographic characteristics. Specifically

  2. The satellite based augmentation system – EGNOS for non-precision approach global navigation satellite system

    Directory of Open Access Journals (Sweden)

    Andrzej FELLNER

    2012-01-01

    Full Text Available First in the Poland tests of the EGNOS SIS (Signal in Space were conducted on 5th October 2007 on the flight inspection with SPAN (The Synchronized Position Attitude Navigation technology at the Mielec airfield. This was an introduction to a test campaign of the EGNOS-based satellite navigation system for air traffic. The advanced studies will be performed within the framework of the EGNOS-APV project in 2011. The implementation of the EGNOS system to APV-I precision approach operations, is conducted according to ICAO requirements in Annex 10. Definition of usefulness and certification of EGNOS as SBAS (Satellite Based Augmentation System in aviation requires thorough analyses of accuracy, integrity, continuity and availability of SIS. Also, the project will try to exploit the excellent accuracy performance of EGNOS to analyze the implementation of GLS (GNSS Landing System approaches (Cat I-like approached using SBAS, with a decision height of 200 ft. Location of the EGNOS monitoring station Rzeszów, located near Polish-Ukrainian border, being also at the east border of planned EGNOS coverage for ECAC states is very useful for SIS tests in this area. According to current EGNOS programmed schedule, the project activities will be carried out with EGNOS system v2.2, which is the version released for civil aviation certification. Therefore, the project will allow demonstrating the feasibility of the EGNOS certifiable version for civil applications.

  3. Coastal water quality estimation from Geostationary Ocean Color Imager (GOCI) satellite data using machine learning approaches

    Science.gov (United States)

    Im, Jungho; Ha, Sunghyun; Kim, Yong Hoon; Ha, Hokyung; Choi, Jongkuk; Kim, Miae

    2014-05-01

    It is important to monitor coastal water quality using key parameters such as chlorophyll-a concentration and suspended sediment to better manage coastal areas as well as to better understand the nature of biophysical processes in coastal seawater. Remote sensing technology has been commonly used to monitor coastal water quality due to its ability of covering vast areas at high temporal resolution. While it is relatively straightforward to estimate water quality in open ocean (i.e., Case I water) using remote sensing, coastal water quality estimation is still challenging as many factors can influence water quality, including various materials coming from inland water systems and tidal circulation. There are continued efforts to accurately estimate water quality parameters in coastal seawater from remote sensing data in a timely manner. In this study, two major water quality indicators, chlorophyll-a concentration and the amount of suspended sediment, were estimated using Geostationary Ocean Color Imager (GOCI) satellite data. GOCI, launched in June 2010, is the first geostationary ocean color observation satellite in the world. GOCI collects data hourly for 8 hours a day at 6 visible and 2 near-infrared bands at a 500 m resolution with 2,500 x 2,500 km square around Korean peninsula. Along with conventional statistical methods (i.e., various linear and non-linear regression), three machine learning approaches such as random forest, Cubist, and support vector regression were evaluated for coastal water quality estimation. In situ measurements (63 samples; including location, two water quality parameters, and the spectra of surface water using a hand-held spectroradiometer) collected during four days between 2011 and 2012 were used as reference data. Due to the small sample size, leave-one-out cross validation was used to assess the performance of the water quality estimation models. Atmospherically corrected radiance data and selected band-ratioed images were used

  4. EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

    Directory of Open Access Journals (Sweden)

    J. C. Bergès

    2010-01-01

    Full Text Available This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

  5. Operational Testing of Satellite based Hydrological Model (SHM)

    Science.gov (United States)

    Gaur, Srishti; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.

    2017-04-01

    Incorporation of the concept of transposability in model testing is one of the prominent ways to check the credibility of a hydrological model. Successful testing ensures ability of hydrological models to deal with changing conditions, along with its extrapolation capacity. For a newly developed model, a number of contradictions arises regarding its applicability, therefore testing of credibility of model is essential to proficiently assess its strength and limitations. This concept emphasizes to perform 'Hierarchical Operational Testing' of Satellite based Hydrological Model (SHM), a newly developed surface water-groundwater coupled model, under PRACRITI-2 program initiated by Space Application Centre (SAC), Ahmedabad. SHM aims at sustainable water resources management using remote sensing data from Indian satellites. It consists of grid cells of 5km x 5km resolution and comprises of five modules namely: Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU). SW module (functions in the grid cells with land cover other than forest and snow) deals with estimation of surface runoff, soil moisture and evapotranspiration by using NRCS-CN method, water balance and Hragreaves method, respectively. The hydrology of F module is dependent entirely on sub-surface processes and water balance is calculated based on it. GW module generates baseflow (depending on water table variation with the level of water in streams) using Boussinesq equation. ROU module is grounded on a cell-to-cell routing technique based on the principle of Time Variant Spatially Distributed Direct Runoff Hydrograph (SDDH) to route the generated runoff and baseflow by different modules up to the outlet. For this study Subarnarekha river basin, flood prone zone of eastern India, has been chosen for hierarchical operational testing scheme which includes tests under stationary as well as transitory conditions. For this the basin has been divided into three sub-basins using three flow

  6. Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the volcanically unperturbed lower stratosphere

    Directory of Open Access Journals (Sweden)

    T. Deshler

    2010-05-01

    Full Text Available Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003. An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities, even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal size

  7. Estimativa de parâmetros biofísicos de plantios de café a partir de imagens orbitais de alta resolução espacial Estimation of biophysical parameters of coffee fields based on high-resolution satellite images

    Directory of Open Access Journals (Sweden)

    Gláucia M. Ramirez

    2010-06-01

    , SAVI and RVI based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

  8. Satellite Formation Design for Space Based Radar Applications

    Science.gov (United States)

    2007-07-30

    Practical Guidance Methodology for Relative Motion of LEO Spacecraft Based on the Clohessy-Wiltshire Equations,” AAS Paper 04-252, AAS/AIAA Space...Non- Circular Reference Orbit," AAS Paper 01-222, AAS/AIAA Space Flight Mechanics Meeting, Santa Barbara, CA, Feb 11-16, 2001. 11. D. Brouwer ...Small Eccentricities or Inclinations in the Brouwer Theory of the Artificial Satellite,” The Astronomical Journal, Vol. 68, October 1963, pp. 555

  9. Estimate Landslide Volume with Genetic Algorithms and Image Similarity Method from Single Satellite Image

    Science.gov (United States)

    Yu, Ting-To

    2013-04-01

    It is important to acquire the volume of landslide in short period of time. For hazard mitigation and also emergency response purpose, the traditional method takes much longer time than expected. Due to the weather limit, traffic accessibility and many regulations of law, it take months to handle these process before the actual carry out of filed work. Remote sensing imagery can get the data as long as the visibility allowed, which happened only few day after the event. While traditional photometry requires a stereo pairs images to produce the post event DEM for calculating the change of volume. Usually have to wait weeks or even months for gathering such data, LiDAR or ground GPS measurement might take even longer period of time with much higher cost. In this study we use one post event satellite image and pre-event DTM to compare the similarity between these by alter the DTM with genetic algorithms. The outcome of smartest guess from GAs shall remove or add exact values of height at each location, which been converted into shadow relief viewgraph to compare with satellite image. Once the similarity threshold been make then the guessing work stop. It takes only few hours to finish the entire task, the computed accuracy is around 70% by comparing to the high resolution LiDAR survey at a landslide, southern Taiwan. With extra GCPs, the estimate accuracy can improve to 85% and also within few hours after the receiving of satellite image. Data of this demonstration case is a 5 m DTM at 2005, 2M resolution FormoSat optical image at 2009 and 5M LiDAR at 2010. The GAs and image similarity code is developed on Matlab at windows PC.

  10. Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

    Science.gov (United States)

    Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

    2016-04-01

    Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico

  11. Efficient enhancing scheme for TCP performance over satellite-based internet

    Institute of Scientific and Technical Information of China (English)

    Wang Lina; Gu Xuemai

    2007-01-01

    Satellite link characteristics drastically degrade transport control protocol (TCP) performance. An efficient performance enhancing scheme is proposed. The improvement of TCP performance over satellite-based Intemet is accomplished by protocol transition gateways at each end ora satellite link. The protocol which runs over a satellite link executes the receiver-driven flow control and acknowledgements- and timeouts-based error control strategies. The validity of this TCP performance enhancing scheme is verified by a series of simulation experiments. Results show that the proposed scheme can efficiently enhance the TCP performance over satellite-based Intemet and ensure that the available bandwidth resources of the satellite link are fully utilized.

  12. Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

    Science.gov (United States)

    Smith, Paul L.; VonderHaar, Thomas H.

    1996-01-01

    The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

  13. On event based state estimation

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.

    2009-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper

  14. On event based state estimation

    NARCIS (Netherlands)

    Sijs, J.; Lazar, M.

    2009-01-01

    To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper

  15. Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

    Science.gov (United States)

    Fisher, B. L.; Wolff, D. B.

    2008-12-01

    Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor

  16. Biomass prediction model in maize based on satellite images

    Science.gov (United States)

    Mihai, Herbei; Florin, Sala

    2016-06-01

    Monitoring of crops by satellite techniques is very useful in the context of precision agriculture, regarding crops management and agricultural production. The present study has evaluated the interrelationship between maize biomass production and satellite indices (NDVI and NDBR) during five development stages (BBCH code), highlighting different levels of correlation. Biomass production recorded was between 2.39±0.005 t ha-1 (12-13 BBCH code) and 51.92±0.028 t ha-1 (83-85 BBCH code), in relation to vegetation stages studied. Values of chlorophyll content ranged from 24.1±0.25 SPAD unit (12-13 BBCH code) to 58.63±0.47 SPAD unit (71-73 BBCH code), and the obtained satellite indices ranged from 0.035641±0.002 and 0.320839±0.002 for NDVI indices respectively 0.035095±0.034 and 0.491038±0.018 in the case of NDBR indices. By regression analysis it was possible to obtain predictive models of biomass in maize based on the satellite indices, in statistical accurate conditions. The most accurate prediction was possible based on NDBR index (R2 = 0.986, F = 144.23, p<0.001, RMSE = 1.446), then based on chlorophyll content (R2 = 0.834, F = 16.14, p = 0.012, RMSE = 6.927) and NDVI index (R2 = 0.682, F = 3.869, p = 0.116, RMSE = 12.178).

  17. Heavy precipitation retrieval from combined satellite observations and ground-based lightning measurements

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Casella, D.; di Paola, F.; Formenton, M.; Sanò, P.

    2010-09-01

    We have developed a series of algorithms for the retrieval of precipitation (especially, heavy precipitation) over the Mediterranean area using satellite observations from the available microwave (MW) radiometers onboard low Earth orbit (LEO) satellites and from the visible-infrared (VIS-IR) SEVIRI radiometer onboard the European geosynchronous (GEO) satellite Meteosat Second Generation (MSG), in conjunction with lightning data from ground-based networks - such as ZEUS and LINET. These are: • A new approach for precipitation retrieval from space (which we call the Cloud Dynamics and Radiation Database approach, CDRD) that incorporates lightning and environmental/dynamical information in addition to the upwelling microwave brightness temperatures (TB’s) so as to reduce the retrieval uncertainty and improve the retrieval performance; • A new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique), that uses passive-microwave (PM) retrievals in conjunction with lightning information and the Global Convection Detection (GCD) technique to discriminate deep convective clouds within the GEO observations; • A new morphing approach (which we call the Lightning-based Precipitation Evolving Technique, L-PET) that uses the available lightning measurements for propagating the rainfall estimates from satellite-borne MW radiometers to a much higher time resolution than the MW observations. We will present and discuss our combined MW/IR/lightning precipitation algorithms and analyses with special reference to some case studies over the western Mediterranean.

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

    Science.gov (United States)

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

    2016-04-01

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

  19. Dynamics modeling for sugar cane sucrose estimation using time series satellite imagery

    Science.gov (United States)

    Zhao, Yu; Justina, Diego Della; Kazama, Yoriko; Rocha, Jansle Vieira; Graziano, Paulo Sergio; Lamparelli, Rubens Augusto Camargo

    2016-10-01

    Sugarcane, as one of the most mainstay crop in Brazil, plays an essential role in ethanol production. To monitor sugarcane crop growth and predict sugarcane sucrose content, remote sensing technology plays an essential role while accurate and timely crop growth information is significant, in particularly for large scale farming. We focused on the issues of sugarcane sucrose content estimation using time-series satellite image. Firstly, we calculated the spectral features and vegetation indices to make them be correspondence to the sucrose accumulation biological mechanism. Secondly, we improved the statistical regression model considering more other factors. The evaluation was performed and we got precision of 90% which is about 20% higher than the conventional method. The validation results showed that prediction accuracy using our sugarcane growth modeling and improved mix model is satisfied.

  20. Efficient estimation algorithms for a satellite-aided search and rescue mission

    Science.gov (United States)

    Argentiero, P.; Garza-Robles, R.

    1977-01-01

    It has been suggested to establish a search and rescue orbiting satellite system as a means for locating distress signals from downed aircraft, small boats, and overland expeditions. Emissions from Emergency Locator Transmitters (ELT), now available in most U.S. aircraft are to be utilized in the positioning procedure. A description is presented of a set of Doppler navigation algorithms for extracting ELT position coordinates from Doppler data. The algorithms have been programmed for a small computing machine and the resulting system has successfully processed both real and simulated Doppler data. A software system for solving the Doppler navigation problem must include an orbit propagator, a first guess algorithm, and an algorithm for estimating longitude and latitude from Doppler data. Each of these components is considered.

  1. Estimate solar contribution to the global surface warming using the ACRIM TSI satellite composite.

    Science.gov (United States)

    Scafetta, N.; West, B. J.

    2005-12-01

    We study, by using a wavelet decomposition methodology, the solar signature on global surface temperature data using the ACRIM total solar irradiance satellite composite by Willson and Mordvinov. These data present a +0.047% per decade trend between minima during solar cycles 21-23 (1980-2002). By using the phenomenological climate sensitivity to a 22-year cycle, we estimate that the ACRIM upward trend might have contributed 10-30% of the global surface temperature warming over the period 1980-2002. Moreover, by comparing the phenomenological climate sensitivity to the 11-year solar cycle with those hypothesized by some energy balance models we conclude that the former is 1.5-3 times stronger than the latter. Finally, we study the climate sensitivity in different regions of the Earth.

  2. Estimating Zenith Tropospheric Delays from BeiDou Navigation Satellite System Observations

    Directory of Open Access Journals (Sweden)

    Xin Sui

    2013-04-01

    Full Text Available The GNSS derived Zenith Tropospheric Delay (ZTD plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS. The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

  3. Estimating zenith tropospheric delays from BeiDou navigation satellite system observations.

    Science.gov (United States)

    Xu, Aigong; Xu, Zongqiu; Ge, Maorong; Xu, Xinchao; Zhu, Huizhong; Sui, Xin

    2013-04-03

    The GNSS derived Zenith Tropospheric Delay (ZTD) plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS) was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS). The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

  4. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena

    2015-04-01

    The method has been elaborated to evaluate the water and heat regime characteristics of the territory on a regional scale for the vegetation season based on a physical-mathematical model of water and heat exchange between vegetation covered land surface and atmosphere (LSM, Land Surface Model) appropriate for using satellite information on land surface and meteorological conditions. The developed model is intended for calculating soil water content, evapotranspiration (evaporation from bare soil and transpiration by vegetation), vertical water and heat fluxes as well as land surface and vegetation cover temperatures and vertical distributions of temperature and moisture in the active soil layer. Parameters of the model are soil and vegetation characteristics and input variables are meteorological characteristics. Their values have been obtained from ground-based observations at agricultural meteorological stations and satellite-based measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua and SEVIRI (geostationary satellites Meteosat-9, -10). The AVHRR data have been used to build the estimates of three types of land surface temperature (LST): land skin temperature Tsg, air temperature at a level of vegetation cover Ta and efficient radiation temperature Tseff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, and precipitation. The set of estimates derived from MODIS data has comprised values of LST Tls, E, NDVI and LAI. The SEVIRI-based retrievals have included Tls, Ta, Е at daylight and nighttime, LAI (daily) and precipitation. The case study has been carried out for agricultural Central Black Earth region of the European Russia of 227,300 sq.km containing 7 regions of the Russian Federation for years 2009-2013 vegetation seasons. Estimates of described characteristics have been built with the help of the developed original and improved pre-existing methods and technologies of thematic processing

  5. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  6. Covariance analysis of differential drag-based satellite cluster flight

    Science.gov (United States)

    Ben-Yaacov, Ohad; Ivantsov, Anatoly; Gurfil, Pini

    2016-06-01

    One possibility for satellite cluster flight is to control relative distances using differential drag. The idea is to increase or decrease the drag acceleration on each satellite by changing its attitude, and use the resulting small differential acceleration as a controller. The most significant advantage of the differential drag concept is that it enables cluster flight without consuming fuel. However, any drag-based control algorithm must cope with significant aerodynamical and mechanical uncertainties. The goal of the current paper is to develop a method for examination of the differential drag-based cluster flight performance in the presence of noise and uncertainties. In particular, the differential drag control law is examined under measurement noise, drag uncertainties, and initial condition-related uncertainties. The method used for uncertainty quantification is the Linear Covariance Analysis, which enables us to propagate the augmented state and filter covariance without propagating the state itself. Validation using a Monte-Carlo simulation is provided. The results show that all uncertainties have relatively small effect on the inter-satellite distance, even in the long term, which validates the robustness of the used differential drag controller.

  7. Satellite Imagery Assisted Road-Based Visual Navigation System

    Science.gov (United States)

    Volkova, A.; Gibbens, P. W.

    2016-06-01

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

  8. Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

    Directory of Open Access Journals (Sweden)

    C. A. Poulsen

    2011-04-01

    Full Text Available Clouds play an important role in balancing the Earth's radiation budget. Clouds reflect sunlight which cools the Earth, and also trap infrared radiation in the same manner as greenhouse gases. Changes in cloud cover and cloud properties over time can have important consequences for climate. The Intergovernmental Panel for Climate Change (IPCC has identified current gaps in the understanding of clouds and related climate feedback processes as a leading cause of uncertainty in forecasting climate change. In this paper we present an algorithm that uses optimal estimation to retrieve cloud parameters from satellite multi-spectral imager data, in particular the Along-Track Scanning Radiometers ATSR-2 and AATSR. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. Importantly, the technique also provides estimated errors along with the retrieved values and quantifies the consistency between retrieval representation of cloud and satellite radiances. This should enable the effective use of the products for comparison with climate models or for exploitation via data assimilation. The technique is evaluated by performing retrieval simulations for a variety of simulated single layer and multi-layer conditions. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed. This algorithm has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation project to produce a 14 year consistent record for climate research (Sayer et al., 2010.

  9. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

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

  10. Chaos Based Secure IP Communications over Satellite DVB

    Science.gov (United States)

    Caragata, Daniel; El Assad, Safwan; Tutanescu, Ion; Sofron, Emil

    2010-06-01

    The Digital Video Broadcasting—Satellite (DVB-S) standard was originally conceived for TV and radio broadcasting. Later, it became possible to send IP packets using encapsulation methods such as Multi Protocol Encapsulation, MPE, or Unidirectional Lightweight Encapsulation, ULE. This paper proposes a chaos based security system for IP communications over DVB-S with ULE encapsulation. The proposed security system satisfies all the security requirements while respecting the characteristics of satellite links, such as the importance of efficient bandwidth utilization and high latency time. It uses chaotic functions to generate the keys and to encrypt the data. The key management is realized using a multi-layer architecture. A theoretical analysis of the system and a simulation of FTP and HTTP traffic are presented and discussed to show the cost of the security enhancement and to provide the necessary tools for security parameters setup.

  11. River discharge estimation at daily resolution from satellite altimetry over an entire river basin

    Science.gov (United States)

    Tourian, M. J.; Schwatke, C.; Sneeuw, N.

    2017-03-01

    One of the main challenges of hydrological modeling is the poor spatiotemporal coverage of in situ discharge databases which have steadily been declining over the past few decades. It has been demonstrated that water heights over rivers from satellite altimetry can sensibly be used to deal with the growing lack of in situ discharge data. However, the altimetric discharge is often estimated from a single virtual station suffering from coarse temporal resolution, sometimes with data outages, poor modeling and inconsistent sampling. In this study, we propose a method to estimate daily river discharge using altimetric time series of an entire river basin including its tributaries. Here, we implement a linear dynamic model to (1) provide a scheme for data assimilation of multiple altimetric discharge along a river; (2) estimate daily discharge; (3) deal with data outages, and (4) smooth the estimated discharge. The model consists of a stochastic process model that benefits from the cyclostationary behavior of discharge. Our process model comprises the covariance and cross-covariance information of river discharge at different gauges. Combined with altimetric discharge time series, we solve the linear dynamic system using the Kalman filter and smoother providing unbiased discharge with minimum variance. We evaluate our method over the Niger basin, where we generate altimetric discharge using water level time series derived from missions ENVISAT, SARAL/AltiKa, and Jason-2. Validation against in situ discharge shows that our method provides daily river discharge with an average correlation of 0.95, relative RMS error of 12%, relative bias of 10% and NSE coefficient of 0.7. Using a modified NSE-metric, that assesses the non-cyclostationary behavior, we show that our estimated discharge outperforms available legacy mean daily discharge.

  12. Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China

    Directory of Open Access Journals (Sweden)

    Shanyu Huang

    2015-08-01

    Full Text Available Rice farming in Northeast China is crucially important for China’s food security and sustainable development. A key challenge is how to optimize nitrogen (N management to ensure high yield production while improving N use efficiency and protecting the environment. Handheld chlorophyll meter (CM and active crop canopy sensors have been used to improve rice N management in this region. However, these technologies are still time consuming for large-scale applications. Satellite remote sensing provides a promising technology for large-scale crop growth monitoring and precision management. The objective of this study was to evaluate the potential of using FORMOSAT-2 satellite images to diagnose rice N status for guiding topdressing N application at the stem elongation stage in Northeast China. Five farmers’ fields (three in 2011 and two in 2012 were selected from the Qixing Farm in Heilongjiang Province of Northeast China. FORMOSAT-2 satellite images were collected in late June. Simultaneously, 92 field samples were collected and six agronomic variables, including aboveground biomass, leaf area index (LAI, plant N concentration (PNC, plant N uptake (PNU, CM readings and N nutrition index (NNI defined as the ratio of actual PNC and critical PNC, were determined. Based on the FORMOSAT-2 imagery, a total of 50 vegetation indices (VIs were computed and correlated with the field-based agronomic variables. Results indicated that 45% of NNI variability could be explained using Ratio Vegetation Index 3 (RVI3 directly across years. A more practical and promising approach was proposed by using satellite remote sensing to estimate aboveground biomass and PNU at the panicle initiation stage and then using these two variables to estimate NNI indirectly (R2 = 0.52 across years. Further, the difference between the estimated PNU and the critical PNU can be used to guide the topdressing N application rate adjustments.

  13. Combined Use of Satellite Observations with Urban Surface Characteristics to Estimate PM Concentrations by Employing Mixed-Effects Models

    Science.gov (United States)

    Beloconi, Anton; Benas, Nikolaos; Chrysoulakis, Nektarios; Kamarianakis, Yiannis

    2008-11-01

    Linear mixed effects models were developed for the estimation of the average daily Particulate Matter (PM) concentration spatial distribution over the area of Greater London (UK). Both fine (PM2.5) and coarse (PM10) concentrations were predicted for the 2002- 2012 time period, based on satellite data. The latter included Aerosol Optical Thickness (AOT) at 3×3 km spatial resolution, as well as the Surface Relative Humidity, Surface Temperature and K-Index derived from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. For a meaningful interpretation of the association among these variables, all data were homogenized with regard to spatial support and geographic projection, thus addressing the change of support problem and leading to a valid statistical inference. To this end, spatial (2D) and spatio- temporal (3D) kriging techniques were applied to in-situ particulate matter concentrations and the leave-one- station-out cross-validation was performed on a daily level to gauge the quality of the predictions. Satellite- derived covariates displayed clear seasonal patterns; in order to work with data which is stationary in mean, for each covariate, deviations from its estimated annual profiles were computed using nonlinear least squares and nonlinear absolute deviations. High-resolution land- cover and morphology static datasets were additionally incorporated in the analysis in order to catch the effects of nearby emission sources and sequestration sites. For pairwise comparisons of the particulate matter concentration means at distinct land-cover classes, the pairwise comparisons method for unequal sample sizes, known as Tukey's method, was performed. The use of satellite-derived products allowed better assessment of space-time interactions of PM, since these daily spatial measurements were able to capture differences in PM concentrations between grid cells, while the use of high- resolution land-cover and morphology static datasets allowed accounting for

  14. Contribution of MODIS Derived Snow Cover Satellite Data into Artificial Neural Network for Streamflow Estimation

    Science.gov (United States)

    Uysal, Gokcen; Arda Sorman, Ali; Sensoy, Aynur

    2014-05-01

    Contribution of snowmelt and correspondingly snow observations are highly important in mountainous basins for modelers who deal with conceptual, physical or soft computing models in terms of effective water resources management. Long term archived continuous data are needed for appropriate training and testing of data driven approaches like artificial neural networks (ANN). Data is scarce at the upper elevations due to the difficulty of installing sufficient automated SNOTEL stations; thus in literatures many attempts are made on the rainfall dominated basins for streamflow estimation studies. On the other hand, optical satellites can easily detect snow because of its high reflectance property. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite that has two platforms (Terra and Aqua) provides daily and 8-daily snow images for different time periods since 2000, therefore snow cover data (SCA) may be useful as an input layer for ANN applications. In this study, a multi-layer perceptron (MLP) model is trained and tested with precipitation, temperature, radiation, previous day discharges as well as MODIS daily SCA data. The weights and biases are optimized with fastest and robust Levenberg-Marquardt backpropagation algorithm. MODIS snow cover images are removed from cloud coverage using certain filtering techniques. The Upper Euphrates River Basin in eastern part of Turkey (10 250 km2) is selected as the application area since it is fed by snowmelt approximately 2/3 of total annual volume during spring and early summer. Several input models and ANN structures are investigated to see the effect of the contributions using 10 years of data (2001-2010) for training and validation. The accuracy of the streamflow estimations is checked with statistical criteria (coefficient of determination, Nash-Sutcliffe model efficiency, root mean square error, mean absolute error) and the results seem to improve when SCA data is introduced. Furthermore, a forecast study is

  15. Developing a Near-Continuous Estimation of Volumetric Fluctuations in Tropical Lakes and Reservoirs Using Satellite Remote Sensing

    Science.gov (United States)

    Keys, T.; Scott, D.

    2015-12-01

    Lakes and reservoirs play an integral role in water resources management by storing large quantities of water commonly used for irrigation, hydroelectric power, water supply, and flood mitigation. Knowing the exact quantity of stored water and necessary water for each of these usages is a critical component of sustainable water resources management. However, limited amounts of hydrologic data in developing nations, most of which are located in the tropics, hinders the accurate monitoring of water storage and allocation. Recent improvements in remote sensing have greatly enhanced the ability to calculate volumetric fluctuations of lakes and reservoirs at given points through time but are limited by temporal resolution as well as the computational time required for image processing. This study utilizes the newly developed MODISTools package for the programming language R in conjunction with satellite altimetry from three different altimetry databases to estimate lake and reservoir volumes at eight day intervals over a 15 year period. The study specifically examines three large lakes and reservoirs: Balbina Reservoir in the Amazon River Basin, Lake Tana in the Nile River Basin, and Tonle Sap Lake in the Mekong River Basin. Altimetry-based water level estimations are validated by in situ water level data from monitoring stations while surface area estimations are validated by Sound Navigation and Ranging (SONAR) generated bathymetric maps with corresponding stage-area relationships. Preliminary results indicate that both remotely sensed water levels and surface areas agree well with in situ measurements, supporting the appropriateness of this methodology.

  16. Estimation of an eartquake focal mechanism from a satellite radar interferogram:Application to the December 4, 1992 Landers aftershock

    Science.gov (United States)

    Feigl, Kurt L.; Sergent, Arnaud; Jacq, Dominique

    1995-05-01

    Interferometric fringes generated by the phase difference between a pair of synthetic-aperture radar images acquired by the ERS-1 satellite were used to estimate the focal mechanism of a small, shallow thrust earthquake. The inversion procedure is an iterative, linerarized least-squares algorithm based on a standard elastic dislocation formulation for coseismic displacements. The preferred estimate is a thrust focal mechanism with its hypocenter at (N34.35 deg +/- 0.4 km, W 116.91 deg +/- 0.2 km, 2.6 +/- 0.3 km depth) on a plane dipping southward beneath the San Bernardino Mountains, with a moment magnitude of 5.4. The strike, dip and rake are N106 deg E +/- 7 deg, 28 deg +/- 4 deg, and 93 deg +/- 4deg, respectively on a fault 3.1 +/- 0.5 km wide and 2.9 +/- 0.4 km long. The precision of these estimates is competitive with seismological determinations.

  17. Interoperability of satellite-based augmentation systems for aircraft navigation

    Science.gov (United States)

    Dai, Donghai

    The Federal Aviation Administration (FAA) is pioneering a transformation of the national airspace system from its present ground based navigation and landing systems to a satellite based system using the Global Positioning System (GPS). To meet the critical safety-of-life aviation positioning requirements, a Satellite-Based Augmentation System (SBAS), the Wide Area Augmentation System (WAAS), is being implemented to support navigation for all phases of flight, including Category I precision approach. The system is designed to be used as a primary means of navigation, capable of meeting the Required Navigation Performance (RNP), and therefore must satisfy the accuracy, integrity, continuity and availability requirements. In recent years there has been international acceptance of Global Navigation Satellite Systems (GNSS), spurring widespread growth in the independent development of SBASs. Besides the FAA's WAAS, the European Geostationary Navigation Overlay Service System (EGNOS) and the Japan Civil Aviation Bureau's MTSAT-Satellite Augmentation System (MSAS) are also being actively developed. Although all of these SBASs can operate as stand-alone, regional systems, there is increasing interest in linking these SBASs together to reduce costs while improving service coverage. This research investigated the coverage and availability improvements due to cooperative efforts among regional SBAS networks. The primary goal was to identify the optimal interoperation strategies in terms of performance, complexity and practicality. The core algorithms associated with the most promising concepts were developed and demonstrated. Experimental verification of the most promising concepts was conducted using data collected from a joint international test between the National Satellite Test Bed (NSTB) and the EGNOS System Test Bed (ESTB). This research clearly shows that a simple switch between SBASs made by the airborne equipment is the most effective choice for achieving the

  18. Ionospheric Slant Total Electron Content Analysis Using Global Positioning System Based Estimation

    Science.gov (United States)

    Sparks, Lawrence C. (Inventor); Mannucci, Anthony J. (Inventor); Komjathy, Attila (Inventor)

    2017-01-01

    A method, system, apparatus, and computer program product provide the ability to analyze ionospheric slant total electron content (TEC) using global navigation satellite systems (GNSS)-based estimation. Slant TEC is estimated for a given set of raypath geometries by fitting historical GNSS data to a specified delay model. The accuracy of the specified delay model is estimated by computing delay estimate residuals and plotting a behavior of the delay estimate residuals. An ionospheric threat model is computed based on the specified delay model. Ionospheric grid delays (IGDs) and grid ionospheric vertical errors (GIVEs) are computed based on the ionospheric threat model.

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

    Science.gov (United States)

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

    2016-07-01

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

  20. Estimation of hydraulic conductivity of a coastal aquifer using satellite imagery

    Science.gov (United States)

    Rebolledo-Vieyra, M.; Iglesias-Prieto, R.; Marino-Tapia, I.

    2012-12-01

    The northern Yucatan Peninsula is characterized by a young and dynamic karstic system that yields very high secondary porosity and permeability. However, we have little, if none, knowledge about the hydraulic conductivity and the amount of groundwater being discharged in to ocean. Here we present and estimation of the hydraulic conductivity and quantity of groundwater being discharged by the northern Yucatan Peninsula coastal aquifer into the Gulf of Mexico, using the Sea Surface Temperature (SST) Images offshore the Yucatan coast, where we have detected a thermal anomaly that appears few hours after heavy rainfall in northern Yucatan. We associated these thermal anomalies of the SST to the groundwater being discharged into the ocean. To test our hypothesis we conducted a review of extreme rainfall events in the last 10 years; in parallel we used data from pressure and flow direction gauges installed in a known submarine groundwater discharge (SGD) to estimate the hydraulic conductivity and the quantity of groundwater being discharged. The satellite imagery and the rainfall data, allowed us to estimate the time lag between the rainfall and the SGD beginning, along with the hydraulic data from the gauges we have estimated the hydrogeological parameters of the coastal aquifer. This data is very important to contribute to the understanding the hydrogeological setting of the Yucatan coastal aquifer and its implications of the impact of human activities on the water quality. July 29th, 2005, NOAA's Sea Surface Temperature (SST) image of the Gulf of Mexico taken a week after hurricane Emily (2005). A thermal low is present offshore northern Yucatan.

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

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

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

  2. Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

    Science.gov (United States)

    di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

    2009-04-01

    Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is

  3. Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation

    Science.gov (United States)

    Yang, Qinghua; Losch, Martin; Losa, Svetlana N.; Jung, Thomas; Nerger, Lars; Lavergne, Thomas

    2016-04-01

    Data assimilation experiments that aim at improving summer ice concentration and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect of using sea ice concentration satellite data products with appropriate uncertainty estimates is assessed by three different experiments using sea ice concentration data of the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI) which are provided with a per-grid-cell physically based sea ice concentration uncertainty estimate. The first experiment uses the constant uncertainty, the second one imposes the provided SICCI uncertainty estimate, while the third experiment employs an elevated minimum uncertainty to account for a representation error. Using the observation uncertainties that are provided with the data improves the ensemble mean forecast of ice concentration compared to using constant data errors, but the thickness forecast, based on the sparsely available data, appears to be degraded. Further investigating this lack of positive impact on the sea ice thicknesses leads us to a fundamental mismatch between the satellite-based radiometric concentration and the modeled physical ice concentration in summer: the passive microwave sensors used for deriving the vast majority of the sea ice concentration satellite-based observations cannot distinguish ocean water (in leads) from melt water (in ponds). New data assimilation methodologies that fully account or mitigate this mismatch must be designed for successful assimilation of sea ice concentration satellite data in summer melt conditions. In our study, thickness forecasts can be slightly improved by adopting the pragmatic solution of raising the minimum observation uncertainty to inflate the data error and ensemble spread.

  4. Estimating water storage changes and sink terms in Volta Basin from satellite missions

    Directory of Open Access Journals (Sweden)

    Vagner G. FERREIRA

    2014-01-01

    Full Text Available The insufficiency of distributed in situ hydrological measurements is a major challenge for hydrological studies in many regions of the world. Satellite missions such as the Gravity Recovery and Climate Experiment (GRACE and the Tropical Rainfall Measurement Mission (TRMM can be used to improve our understanding of water resources beyond surface water in poorly gauged basins. In this study we combined GRACE and TRMM to investigate monthly estimates of evaporation plus runoff (sink terms using the water balance equation for the period from January 2005 to December 2010 within the Volta Basin. These estimates have been validated by comparison with time series of sink terms (evaporation plus surface and subsurface runoff from the Global Land Data Assimilation System (GLDAS. The results, for the period under consideration, show strong agreement between both time series, with a root mean square error (RMSE of 20.2 mm/month (0.67 mm/d and a correlation coefficient of 0.85. T