WorldWideScience

Sample records for satellite land surface

  1. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  2. MEaSUREs Land Surface Temperature from GOES Satellites

    Science.gov (United States)

    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  3. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    Science.gov (United States)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  4. Use of satellite land surface temperatures in the EUSTACE global surface air temperature analysis

    Science.gov (United States)

    Ghent, D.; Good, E.; Rayner, N. A.

    2015-12-01

    EUSTACE (EU Surface Temperatures for All Corners of Earth) is a Horizon2020 project that will produce a spatially complete, near-surface air temperature (NSAT) analysis for the globe for every day since 1850. The analysis will be based on both satellite and in situ surface temperature observations over land, sea, ice and lakes, which will be combined using state-of-the-art statistical methods. The use of satellite data will enable the EUSTACE analysis to offer improved estimates of NSAT in regions that are poorly observed in situ, compared with existing in-situ based analyses. This presentation illustrates how satellite land surface temperature (LST) data - sourced from the European Space Agency (ESA) Data User Element (DUE) GlobTemperature project - will be used in EUSTACE. Satellite LSTs represent the temperature of the Earth's skin, which can differ from the corresponding NSAT by several degrees or more, particularly during the hottest part of the day. Therefore the first challenge is to develop an approach to estimate global NSAT from satellite observations. Two methods will be trialled in EUSTACE, both of which are summarised here: an established empirical regression-based approach for predicting NSAT from satellite data, and a new method whereby NSAT is calculated from LST and other parameters using a physics-based model. The second challenge is in estimating the uncertainties for the satellite NSAT estimates, which will determine how these data are used in the final blended satellite-in situ analysis. This is also important as a key component of EUSTACE is in delivering accurate uncertainty information to users. An overview of the methods to estimate the satellite NSATs is also included in this presentation.

  5. Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

    Science.gov (United States)

    Xian, George

    2008-01-01

    By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.

  6. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  7. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  8. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; Velde, van der R.; Vekerdy, Z.; Su, Z.

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  9. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park

  10. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  11. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  12. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  13. The Global Land Surface Satellite (GLASS Remote Sensing Data Processing System and Products

    Directory of Open Access Journals (Sweden)

    Gongqi Zhou

    2013-05-01

    Full Text Available Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computing system and massive volumes of multi-sensor and multi-temporal remotely sensed data. This manuscript describes the ground Global LAnd Surface Satellite (GLASS product generation system that can be used to generate long-sequence time series of global land surface data products based on various remotely sensed data. To ensure stabilization and efficiency in running the system, we used the methods of task management, parallelization, and multi I/O channels. An array of GLASS remote sensing products related to global land surface parameters are currently being produced and distributed by the Center for Global Change Data Processing and Analysis at Beijing Normal University in Beijing, China. These products include Leaf Area Index (LAI, land surface albedo, and broadband emissivity (BBE from the years 1981 to 2010, downward shortwave radiation (DSR and photosynthetically active radiation (PAR from the years 2008 to 2010.

  14. Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2015-12-01

    Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  15. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  16. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  17. The long-term Global LAnd Surface Satellite (GLASS) product suite and applications

    Science.gov (United States)

    Liang, S.

    2015-12-01

    Our Earth's environment is experiencing rapid changes due to natural variability and human activities. To monitor, understand and predict environment changes to meet the economic, social and environmental needs, use of long-term high-quality satellite data products is critical. The Global LAnd Surface Satellite (GLASS) product suite, generated at Beijing Normal University, currently includes 12 products, including leaf area index (LAI), broadband shortwave albedo, broadband longwave emissivity, downwelling shortwave radiation and photosynthetically active radiation, land surface skin temperature, longwave net radiation, daytime all-wave net radiation, fraction of absorbed photosynetically active radiation absorbed by green vegetation (FAPAR), fraction of green vegetation coverage, gross primary productivity (GPP), and evapotranspiration (ET). Most products span from 1981-2014. The algorithms for producing these products have been published in the top remote sensing related journals and books. More and more applications have being reported in the scientific literature. The GLASS products are freely available at the Center for Global Change Data Processing and Analysis of Beijing Normal University (http://www.bnu-datacenter.com/), and the University of Maryland Global Land Cover Facility (http://glcf.umd.edu). After briefly introducing the basic characteristics of GLASS products, we will present some applications on the long-term environmental changes detected from GLASS products at both global and local scales. Detailed analysis of regional hotspots, such as Greenland, Tibetan plateau, and northern China, will be emphasized, where environmental changes have been mainly associated with climate warming, drought, land-atmosphere interactions, and human activities.

  18. Towards a protocol for validating satellite-based Land Surface Temperature: Application to AATSR data

    Science.gov (United States)

    Ghent, Darren; Schneider, Philipp; Remedios, John

    2013-04-01

    Land surface temperature (LST) retrieval accuracy can be challenging as a result of emissivity variability and atmospheric effects. Surface emissivities can be highly variable owing to the heterogeneity of the land; a problem which is amplified in regions of high topographic variance or for larger viewing angles. Atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. Combined, atmospheric effects and emissivity variability can result in retrieval errors of several degrees. If though these are appropriately handled satellite-derived LST products can be used to improve our ability to monitor and to understand land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. Here we present validation of an improved LST data record from the Advanced Along-Track Scanning Radiometer (AATSR) and illustrate the improvements in accuracy and precision compared with the standard ESA LST product. Validation is a critical part of developing any satellite product, although over the land heterogeneity ensures this is a challenging undertaking. A substantial amount of previous effort has gone into the area of structuring and standardizing calibration and validation approaches within the field of Earth Observation. However, no unified approach for accomplishing this for LST has yet to be practised by the LST community. Recent work has attempted to address this situation with the development of a protocol for validating LST (Schneider et al., 2012) under the auspices of ESA and the support of the wider LST community. We report here on a first application of this protocol to satellite LST data. The approach can briefly be summarised thus: in situ validation is performed where ground-based observations are available - being predominantly homogeneous sites; heterogeneous pixels are validated by way of established radiometric-based techniques (Wan and Li

  19. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  20. Cross-validation of satellite products over France through their integration into a land surface model

    Science.gov (United States)

    Calvet, Jean-Christophe; Barbu, Alina; Carrer, Dominique; Meurey, Catherine

    2014-05-01

    Long (more than 30 years) time series of satellite-derived products over land are now available. They concern Essential Climate Variables (ECV) such as LAI, FAPAR, surface albedo, and soil moisture. The direct validation of such Climate Data Records (CDR) is not easy, as in situ observations are limited in space and time. Therefore, indirect validation has a key role. It consists in comparing the products with similar preexisting products derived from satellite observations or from land surface model (LSM) simulations. The most advanced indirect validation technique consists in integrating the products into a LSM using a data assimilation scheme. The obtained reanalysis accounts for the synergies of the various upstream products and provides statistics which can be used to monitor the quality of the assimilated observations. Meteo-France develops the ISBA-A-gs generic LSM able to represent the diurnal cycle of the surface fluxes together with the seasonal, interannual and decadal variability of the vegetation biomass. The LSM is embedded in the SURFEX modeling platform together with a simplified extended Kalman filter. These tools form a Land Data Assimilation System (LDAS). The current version of the LDAS assimilates SPOT-VGT LAI and ASCAT surface soil moisture (SSM) products over France (8km x 8km), and a passive monitoring of albedo, FAPAR and Land Surface temperature (LST) is performed (i.e., the simulated values are compared with the satellite products). The LDAS-France system is used in the European Copernicus Global Land Service (http://land.copernicus.eu/global/) to monitor the quality of upstream products. The LDAS generates statistics whose trends can be analyzed in order to detect possible drifts in the quality of the products: (1) for LAI and SSM, metrics derived from the active monitoring (i.e. assimilation) such as innovations (observations vs. model forecast), residuals (observations vs. analysis), and increments (analysis vs. model forecast) ; (2

  1. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  2. The Water Cycle from Space: Use of Satellite Data in Land Surface Hydrology and Water Resource Management

    Science.gov (United States)

    Laymon, Charles; Blankenship, Clay; Khan, Maudood; Limaye, Ashutosh; Hornbuckle, Brian; Rowlandson, Tracy

    2010-01-01

    This slide presentation reviews how our understanding of the water cycle is enhanced by our use of satellite data, and how this informs land surface hydrology and water resource management. It reviews how NASA's current and future satellite missions will provide Earth system data of unprecedented breadth, accuracy and utility for hydrologic analysis.

  3. Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa

    Directory of Open Access Journals (Sweden)

    Ronald A. Harris

    2014-12-01

    Full Text Available Wind farms (WFs are believed to have an impact on lower boundary layer meteorology. A recent study examined satellite-measured land surface temperature data (LST and found a local nighttime warming effect attributable to a group of four large WFs in Texas. This study furthers their work by investigating the impacts of five individual WFs in Iowa, where the land surface properties and climate conditions are different from those in Texas. Two methods are used to assess WF impacts: first, compare the spatial coupling between the LST changes (after turbine construction versus before and the geographic layouts of the WFs; second, quantify the LST difference between the WFs and their immediate surroundings (non-WF areas. Each WF shows an irrefutable nighttime warming signal relative to the surrounding areas after their turbines were installed, and these warming signals are generally coupled with the geographic layouts of the wind turbines, especially in summer. This study provides further observational evidence that WFs can cause surface warming at nighttime, and that such a signal can be detected by satellite-based sensors.

  4. Validation of Satellite-Derived Land Surface Temperature Products - Methods and Good Practice

    Science.gov (United States)

    Guillevic, P. C.; Hulley, G. C.; Hook, S. J.; Biard, J.; Ghent, D.

    2014-12-01

    Land Surface Temperature (LST) is a key variable for surface water and energy budget calculations that can be obtained globally and operationally from satellite observations. LST is used for many applications, including weather forecasting, short-term climate prediction, extreme weather monitoring, and irrigation and water resource management. In order to maximize the usefulness of LST for research and studies it is necessary to know the uncertainty in the LST measurement. Multiple validation methods and activities are necessary to assess LST compliance with the quality specifications of operational users. This work presents four different validation methods that have been widely used to determine the uncertainties in LST products derived from satellite measurements. 1) The temperature based validation method involves comparisons with ground-based measurements of LST. The method is strongly limited by the number and quality of available field stations. 2) Scene-based comparisons involve comparing a new satellite LST product with a heritage LST product. This method is not an absolute validation and satellite LST inter-comparisons alone do not provide an independent validation measurement. 3) The radiance-based validation method does not require ground-based measurements and is usually used for large scale validation effort or for LST products with coarser spatial resolution (> 1km). 4) Time series comparisons are used to detect problems that can occur during the instrument's life, e.g. calibration drift, or unrealistic outliers due to cloud coverage. This study enumerates the sources of errors associated with each method. The four different approaches are complementary and provide different levels of information about the quality of the retrieved LST. The challenges in retrieving the LST from satellite measurements are discussed using results obtained for MODIS and VIIRS. This work contributes to the objective of the Land Product Validation (LPV) sub-group of the

  5. Land surface thermal characterization of Asian-pacific region with Japanese geostationary satellite

    Science.gov (United States)

    Oyoshi, K.; Tamura, M.

    2010-12-01

    Land Surface Temperature (LST) is a significant indicator of energy balance at the Earth's surface. It is required for a wide variety of climate, hydrological, ecological, and biogeochemical studies. Although LST is highly variable both temporally and spatially, it is impossible for polar-orbiting satellite to detect hourly changes in LST, because the satellite is able to only collect data of the same area at most twice a day. On the other hand, geostationary satellite is able to collect hourly data and has a possibility to monitor hourly changes in LST, therefore hourly measurements of geostationary satellite enables us to characterize detailed thermal conditions of the Earth's surface and improve our understanding of the surface energy balance. Multi-functional Transport Satellite (MTSAT) is a Japanese geostationary satellite launched in 2005 and covers Asia-Pacific region. MTSAT provides hourly data with 5 bands including two thermal infrared (TIR) bands in the 10.5-12.5 micron region. In this research, we have developed a methodology to retrieve hourly LST from thermal infrared data of MTSAT. We applied Generalized Split-window (GSW) equation to estimate LST from TIR data. First, the brightness temperatures measured at sensor on MTSAT was simulated by radiative transfer code (MODTRAN), and the numerical coefficients of GSW equation were optimized based on the simulation results with non-linear minimization algorithm. The standard deviation of derived GSW equation was less than or equal to 1.09K in the case of viewing zenith angle lower than 40 degree and 1.73K in 60 degree. Then, spatial distributions of LST have been mapped optimized GSW equation with brightness temperatures of MTSAT IR1 and IR2 and emissivity map from MODIS product. Finally, these maps were validated with MODIS LST product (MOD11A1) over four Asian-pacific regions such as Bangkok, Tokyo, UlanBator and Jakarta , It is found that RMSE of these regions were 4.57K, 2.22K, 2.71K and 3.92K

  6. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  7. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    Science.gov (United States)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  8. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  9. Spatial heterogeneity of satellite derived land surface parameters and energy flux densities for LITFASS-area

    Directory of Open Access Journals (Sweden)

    A. Tittebrand

    2009-03-01

    Full Text Available Based on satellite data in different temporal and spatial resolution, the current use of frequency distribution functions (PDF for surface parameters and energy fluxes is one of the most promising ways to describe subgrid heterogeneity of a landscape. Objective of this study is to find typical distribution patterns of parameters (albedo, NDVI for the determination of the actual latent heat flux (L.E determined from highly resolved satellite data within pixel on coarser scale.

    Landsat ETM+, Terra MODIS and NOAA-AVHRR surface temperature and spectral reflectance were used to infer further surface parameters and radiant- and energy flux densities for LITFASS-area, a 20×20 km2 heterogeneous area in Eastern Germany, mainly characterised by the land use types forest, crop, grass and water. Based on the Penman-Monteith-approach L.E, as key quantity of the hydrological cycle, is determined for each sensor in the accordant spatial resolution with an improved parametrisation. However, using three sensors, significant discrepancies between the inferred parameters can cause flux distinctions resultant from differences of the sensor filter response functions or atmospheric correction methods. The approximation of MODIS- and AVHRR- derived surface parameters to the reference parameters of ETM (via regression lines and histogram stretching, respectively, further the use of accurate land use classifications (CORINE and a new Landsat-classification, and a consistent parametrisation for the three sensors were realized to obtain a uniform base for investigations of the spatial variability.

    The analyses for 4 scenes in 2002 and 2003 showed that for forest clear distribution-patterns for NDVI and albedo are found. Grass and crop distributions show higher variability and differ significantly to each other in NDVI but only marginal in albedo. Regarding NDVI-distribution functions NDVI was found to be the key variable for L.E-determination.

  10. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

    Science.gov (United States)

    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  11. Study of land surface temperature and spectral emissivity using multi-sensor satellite data

    Indian Academy of Sciences (India)

    P K Srivastava; T J Majumdar; Amit K Bhattacharya

    2010-02-01

    In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km2, is a part of Singhbhum–Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show

  12. 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

  13. 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

  14. Can satellite land surface temperature data be used similarly to ground discharge measurements for distributed hydrological model calibration?

    NARCIS (Netherlands)

    Corbari, C.; Mancini, M.; Li, J.; Su, Zhongbo

    2015-01-01

    This study proposes a new methodology for the calibration of distributed hydrological models at basin scale by constraining an internal model variable using satellite data of land surface temperature. The model algorithm solves the system of energy and mass balances in terms of a representative equi

  15. Land Surface Temperature- Comparing Data from Polar Orbiting and Geostationary Satellites

    Science.gov (United States)

    Comyn-Platt, E.; Remedios, J. J.; Good, E. J.; Ghent, D.; Saunders, R.

    2012-04-01

    Land Surface Temperature (LST) is a vital parameter in Earth climate science, driving long-wave radiation exchanges that control the surface energy budget and carbon fluxes, which are important factors in Numerical Weather Prediction (NWP) and the monitoring of climate change. Satellites offer a convenient way to observe LST consistently and regularly over large areas. A comparison between LST retrieved from a Geostationary Instrument, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and a Polar Orbiting Instrument, the Advanced Along Track Scanning Radiometer (AATSR) is presented. Both sensors offer differing benefits. AATSR offers superior precision and spatial resolution with global coverage but given its sun-synchronous platform only observes at two local times, ~10am and ~10pm. SEVIRI provides the high-temporal resolution (every 15 minutes) required for observing diurnal variability of surface temperatures but given its geostationary platform has a poorer resolution, 3km at nadir, which declines at higher latitudes. A number of retrieval methods are applied to the raw satellite data: First order coefficient based algorithms provided on an operational basis by the LandSAF (for SEVIRI) and the University of Leicester (for AATSR); Second order coefficient based algorithms put forward by the University of Valencia; and an optimal estimation method using the 1DVar software provided by the NWP SAF. Optimal estimation is an iterative technique based upon inverse theory, thus is very useful for expanding into data assimilation systems. The retrievals are assessed and compared on both a fine scale using in-situ data from recognised validation sites and on a broad scale using two 100x100 regions such that biases can be better understood. Overall, the importance of LST lies in monitoring daily temperature extremes, e.g. for estimating permafrost thawing depth or risk of crop damage due to frost, hence the ideal dataset would use a combination of observations

  16. 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

  17. Estimation of land surface evapotranspiration with A satellite remote sensing procedure

    Science.gov (United States)

    Irmak, A.; Ratcliffe, I.; Ranade, P.; Hubbard, K.G.; Singh, R.K.; Kamble, B.; Kjaersgaard, J.

    2011-01-01

    There are various methods available for estimating magnitude and trends of evapotranspiration. Bowen ratio energy balance system and eddy correlation techniques offer powerful alternatives for measuring land surface evapotranspiration. In spite of the elegance, high accuracy, and theoretical attractions of these techniques for measuring evapotranspiration, their practical use over large areas can be limited due to the number of sites needed and the related expense. Application of evapotranspiration mapping from satellite measurements can overcome the limitations. The objective of this study was to utilize the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) model in Great Plains environmental settings to understand water use in managed ecosystems on a regional scale. We investigated spatiotemporal distribution of a fraction of reference evapotranspiration (ETrF) using eight Landsat 5 images during the 2005 and 2006 growing season for path 29, row 32. The ETrF maps generated by METRICTM allowed us to follow the magnitude and trend in ETrF for major land-use classes during the growing season. The ETrF was lower early in the growing season for agricultural crops and gradually increased as the normalized difference vegetation index of crops increased, thus presenting more surface area over which water could transpire toward the midseason. Comparison of predictions with Bowen ratio energy balance system measurements at Clay Center, NE, showed that METRICTM performed well at the field scale for predicting evapotranspiration from a cornfield. If calibrated properly, the model could be a viable tool to estimate water use in managed ecosystems in subhumid climates at a large scale.

  18. Global Flood Response Using Satellite Rainfall Information Coupled with Land Surface and Routing Models

    Science.gov (United States)

    Adler, R. F.; Wu, H.

    2016-12-01

    The Global Flood Monitoring System (GFMS) (http://flood.umd.edu) has been developed and used in recent years to provide real-time flood detection, streamflow estimates and inundation calculations for most of the globe. The GFMS is driven by satellite-based precipitation, with the accuracy of the flood estimates being primarily dependent on the accuracy of the precipitation analyses and the land surface and routing models used. The routing calculations are done at both 12 km and 1 km resolution. Users of GFMS results include international and national flood response organizations. The devastating floods in October 2015 in South Carolina are analyzed indicating that the GFMS estimated streamflow is accurate and useful indicating significant flooding in the upstream basins. Further downstream the GFMS streamflow underestimates due to the presence of dams which are not accounted for in GFMS. Other examples are given for Yemen and Somalia and for Sri Lanka and southern India. A forecast flood event associated with a typhoon hitting Taiwan is also examined. One-kilometer resolution inundation mapping from GFMS holds the promise of highly useful information for flood disaster response. The algorithm is briefly described and examples are shown for recent cases where inundation estimates available from optical and Synthetic Aperture Radar (SAR) satellite sensors are available. For a case of significant flooding in Texas in May and June along the Brazos River the GFMS calculated streamflow compares favorably with the observed. Available Landsat-based (May 28) and MODIS-based (June 2) inundation analyses from U. of Colorado shows generally good agreement with the GFMS inundation calculation in most of the area where skies were clear and the optical techniques could be applied. The GFMS provides very useful disaster response information on a timely basis. However, there is still significant room for improvement, including improved precipitation information from NASA's Global

  19. Cross-satellite comparison of operational land surface temperature products derived from MODIS and ASTER data over bare soil surfaces

    Science.gov (United States)

    Duan, Si-Bo; Li, Zhao-Liang; Cheng, Jie; Leng, Pei

    2017-04-01

    The collection 6 (C6) MODIS land surface temperature (LST) product is publicly available for the user community. Compared to the collection 5 (C5) MODIS LST product, the C6 MODIS LST product has been refined over bare soil pixels. Assessing the accuracy of the C6 MODIS LST product will help to facilitate the use of the LST product in various applications. In this study, we present a cross-satellite comparison to evaluate the accuracy of the C6 MODIS LST product (MOD11_L2) over bare soil surfaces under various atmospheric and surface conditions using the ASTER LST product as a reference. For comparison, the C5 MODIS LST product was also used in the analysis. The absolute biases (0.2-1.5 K) of the differences between the C6 MODIS LST and ASTER LST over bare soil surfaces are approximately two times less than those (0.6-3.8 K) of the differences between the C5 MODIS LST and ASTER LST. Furthermore, the RMSEs (0.7-2.3 K) over bare soil surfaces for the C6 MODIS LST are significantly smaller than those (0.9-4.2 K) for the C5 MODIS LST. These results indicate that the accuracy of the C6 MODIS LST product is much better than that of the C5 MODIS LST product. We recommend that the user community employs the C6 MODIS LST product in their applications.

  20. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  1. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Science.gov (United States)

    Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

    2015-01-01

    Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of

  2. Maximizing the Use of Satellite Thermal Infrared Data for Advancing Land Surface Temperature Analysis

    Science.gov (United States)

    Weng, Q.; Fu, P.; Gao, F.

    2014-12-01

    Land surface temperature (LST) is a crucial parameter in investigating environmental, ecological processes and climate change at various scales, and is also valuable in the studies of evapotranspiration, soil moisture conditions, surface energy balance, and urban heat islands. These studies require thermal infrared (TIR) images at both high temporal and spatial resolution to retrieve LST. However, currently, no single satellite sensors can deliver TIR data at both high temporal and spatial resolution. Thus, various algorithms/models have been developed to enhance the spatial or the temporal resolution of TIR data, but rare of those can enhance both spatial and temporal details. This paper presents a new data fusion algorithm for producing Landsat-like LST data by blending daily MODIS and periodic Landsat TM datasets. The original Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was improved and modified for predicting thermal radiance and LST data by considering annual temperature cycle (ATC) and urban thermal landscape heterogeneity. The technique of linear spectral mixture analysis was employed to relate the Landsat radiance with the MODIS one, so that the temporal changes in radiance can be incorporated in the fusion model. This paper details the theoretical basis and the implementation procedures of the proposed data fusion algorithm, Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT). A case study was conducted that predicted LSTs of five dates in 2005 from July to October in Los Angeles County, California. The results indicate that the prediction accuracy for the whole study area ranged from 1.3 K to 2 K. Like existing spatio-temporal data fusion models, the SADFAT method has a limitation in predicting LST changes that were not recorded in the MODIS and/or Landsat pixels due to the model assumption.

  3. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  4. An inter-comparison of soil moisture data products from satellite remote sensing and a land surface model

    Science.gov (United States)

    Fang, Li; Hain, Christopher R.; Zhan, Xiwu; Anderson, Martha C.

    2016-06-01

    Significant advances have been achieved in generating soil moisture (SM) products from satellite remote sensing and/or land surface modeling with reasonably good accuracy in recent years. However, the discrepancies among the different SM data products can be considerably large, which hampers their usage in various applications. The bias of one SM product from another is well recognized in the literature. Bias estimation and spatial correction methods have been documented for assimilating satellite SM product into land surface and hydrologic models. Nevertheless, understanding the characteristics of each of these SM data products is required for many applications where the most accurate data products are desirable. This study inter-compares five SM data products from three different sources with each other, and evaluates them against in situ SM measurements over 14-year period from 2000 to 2013. Specifically, three microwave (MW) satellite based data sets provided by ESA's Climate Change Initiative (CCI) (CCI-merged, -active and -passive products), one thermal infrared (TIR) satellite based product (ALEXI), and the Noah land surface model (LSM) simulations. The in-situ SM measurements are collected from the North American Soil Moisture Database (NASMD), which involves more than 600 ground sites from a variety of networks. They are used to evaluate the accuracies of these five SM data products. In general, each of the five SM products is capable of capturing the dry/wet patterns over the study period. However, the absolute SM values among the five products vary significantly. SM simulations from Noah LSM are more stable relative to the satellite-based products. All TIR and MW satellite based products are relatively noisier than the Noah LSM simulations. Even though MW satellite based SM retrievals have been predominantly used in the past years, SM retrievals of the ALEXI model based on TIR satellite observations demonstrate skills equivalent to all the MW satellite

  5. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard

    2010-01-01

    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetat......Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence...... on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions...

  6. Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

    Science.gov (United States)

    Anand, Jasdeep S.; Monks, Paul S.

    2017-07-01

    Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

  7. Parameterizing atmosphere-land surface exchange for climate models with satellite data: A case study for the Southern Great Plains CART site

    Science.gov (United States)

    Gao, W.

    High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, researchers examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surface contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 x 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy's Atmospheric Radiation Measurement (ARM) Program.

  8. Inferring past land use-induced changes in surface albedo from satellite observations: a useful tool to evaluate model simulations

    Directory of Open Access Journals (Sweden)

    J. P. Boisier

    2013-03-01

    Full Text Available Regional cooling resulting from increases in surface albedo has been identified in several studies as the main biogeophysical effect of past land use-induced land cover changes (LCC on climate. However, the amplitude of this effect remains quite uncertain due to, among other factors, (a uncertainties in the extent of historical LCC and, (b differences in the way various models simulate surface albedo and more specifically its dependency on vegetation type and snow cover. We derived monthly albedo climatologies for croplands and four other land cover types from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite observations. We then reconstructed the changes in surface albedo between preindustrial times and present-day by combining these climatologies with the land cover maps of 1870 and 1992 used by seven land surface models (LSMs in the context of the LUCID ("Land Use and Climate: identification of robust Impacts" intercomparison project. These reconstructions show surface albedo increases larger than 10% (absolute in winter, and larger than 2% in summer between 1870 and 1992 over areas that experienced intense deforestation in the northern temperate regions. The historical surface albedo changes estimated with MODIS data were then compared to those simulated by the various climate models participating in LUCID. The inter-model mean albedo response to LCC shows a similar spatial and seasonal pattern to the one resulting from the MODIS-based reconstructions, that is, larger albedo increases in winter than in summer, driven by the presence of snow. However, individual models show significant differences between the simulated albedo changes and the corresponding reconstructions, despite the fact that land cover change maps are the same. Our analyses suggest that the primary reason for those discrepancies is how LSMs parameterize albedo. Another reason, of secondary importance, results from differences in their simulated snow extent

  9. Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

    Science.gov (United States)

    Broich, M.; Huete, A.; Tulbure, M. G.; Ma, X.; Xin, Q.; Paget, M.; Restrepo-Coupe, N.; Davies, K.; Devadas, R.; Held, A.

    2014-05-01

    Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray-Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in the interior of the

  10. Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

    Directory of Open Access Journals (Sweden)

    M. Broich

    2014-05-01

    Full Text Available Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI. We based our analysis on Enhanced Vegetation Index (EVI data from the MODerate Resolution Imaging Spectroradiometer (MODIS from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB, the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month in

  11. Spatial Downscaling Research of Satellite Land Surface Temperature Based on Spectral Normalization Index

    Directory of Open Access Journals (Sweden)

    LI Xiaojun

    2017-03-01

    Full Text Available Aiming at the problem that the spatial and temporal resolution of land surface temperature (LST have the contradiction with each other, a new downscaling model was put forward, based on the TsHARP(an algorithm for sharpening thermal imagery downscaling method, this research makes improvements by selecting the better correlation of spectral index(normalized difference vegetation index, NDVI; normalized difference build-up index, NDBI; modified normalized difference water index, MNDWI; enhanced bare soil index, EBSI with LST, i.e., replaces the original NDVI with new spectral index according to the different surface land-cover types, to assess the accuracy of each downscaling method based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results show that both models could effectively enhance the spatial resolution while simultaneously preserving the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image, both models were proved to be effective and applicable in our study area; global scale analysis shows that the new model (RMSE:1.635℃ is better than the TsHARP method (RMSE:2.736℃ in terms of the spatial variability and accuracy of the results; the different land-cover types of downscaling statistical analysis shows that the TsHARP method has poor downscaling results in the low vegetation coverage area, especially for the bare land and building-up area(|MBE|>3℃, the new model has obvious advantages in the description of the low vegetation coverage area. Seasonal analysis shows that the downscaling results of two models in summer and autumn are superior to those in spring and winter, the new model downscaling results are better than the TsHARP method in the four seasons, in which the spring and winter downscaling improvement is better than summer and autumn.

  12. Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

    Science.gov (United States)

    Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

  13. How well do we characterize the biophysical effects of vegetation cover change? Benchmarking land surface models against satellite observations.

    Science.gov (United States)

    Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

    2017-04-01

    Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and

  14. Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

    Science.gov (United States)

    Lisenko, S. A.

    2017-05-01

    An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

  15. Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations

    Directory of Open Access Journals (Sweden)

    Miriam Pablos

    2016-07-01

    Full Text Available Soil moisture (SM is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST and evapotranspiration (ET. Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS and NASA’s Soil Moisture Active Passive (SMAP. LST is remotely sensed using thermal infrared (TIR sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014 of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R ≈ − 0.6 to −0.8, and between SMOS SM and MODIS LST Terra/Aqua day (R ≈ − 0.7. At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R ≈ − 0.5 to −0.7; satellite R ≈ − 0.4 to −0.7 indicating SM–LST coupling, than in winter (in situ R ≈ +0.3; satellite R ≈ − 0.3 indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ∼0

  16. Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature

    Science.gov (United States)

    Marques da Silva, J. R.; Damásio, C. V.; Sousa, A. M. O.; Bugalho, L.; Pessanha, L.; Quaresma, P.

    2015-06-01

    Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 × 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: "thermal integral over air temperature (accumulated degree-days)". The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.

  17. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Science.gov (United States)

    Naha, Shaini; Thakur, Praveen K.; Aggarwal, S. P.

    2016-06-01

    The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed

  18. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Directory of Open Access Journals (Sweden)

    S. Naha

    2016-06-01

    Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

  19. Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.

    Science.gov (United States)

    Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

    2014-12-01

    This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring.

  20. 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.

  1. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    to imperfect model forecasts. It remains a crucial challenge to account for system uncertainty, so as to provide model outputs accompanied by a quantified confidence interval. Properly characterizing and reducing uncertainty opens-up the opportunity for risk-based decision-making and more effective emergency...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...... temperature are explored in a multi-objective calibration experiment to optimize the parameters in a SVAT model in the Sahel. The two satellite derived variables were effective at constraining most land-surface and soil parameters. A data assimilation framework is developed and implemented with an integrated...

  2. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

  3. Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

    2009-01-01

    An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

  4. Assessment of the interannual variability of agricultural yields in France using satellite data and a generic land surface model

    Science.gov (United States)

    Canal, Nicolas; Calvet, Jean-Christophe; Szczypta, Camille

    2013-04-01

    The generic ISBA-A-gs Land Surface Model (LSM) is used to simulate the interannual variability of the maximum above-ground biomass (Bagm) of cereals and grasslands in France. Agricultural statistics are used to optimize the maximal available soil water content (MaxAWC) of the model. For a number of administrative units, significant correlations between the simulated Bagm and the agricultural yield statistics are found over the 1994-2010 period. It is shown that the interannual variability of Bagm and of the simulated soil moisture correlate at given key periods. Significant correlations are found between ten-daily averaged simulated soil moisture and the simulated (observed) Bagm (yields). The corresponding plant growth stage is determined through the Leaf Area Index (LAI). Moreover, it is shown that the interannual variability of the modelled LAI and of the new satellite-derived GEOLAND2 LAI are consistent. The predictive value of both simulated and observed LAI on the agricultural yield (10 to 40 days before harvest) is investigated. The scores are used to benchmark different configurations of the model. In particular two contrasting representations of the soil moisture profile are considered: (1) one root-zone layer, (2) several soil layers with an explicit representation of diffusion processes and an exponential root density profile, with or without a deep soil layer below the root-zone.

  5. Geostatistical improvements of evapotranspiration spatial information using satellite land surface and weather stations data

    Science.gov (United States)

    de Carvalho Alves, Marcelo; de Carvalho, Luiz Gonsaga; Vianello, Rubens Leite; Sediyama, Gilberto C.; de Oliveira, Marcelo Silva; de Sá Junior, Arionaldo

    2013-07-01

    The objective of the present study was to use the simple cokriging methodology to characterize the spatial variability of Penman-Monteith reference evapotranspiration and Thornthwaite potential evapotranspiration methods based on Moderate Resolution Imaging Spetroradiometer (MODIS) global evapotranspiration products and high-resolution surfaces of WordClim temperature and precipitation data. The climatic element data referred to 39 National Institute of Meteorology climatic stations located in Minas Gerais state, Brazil and surrounding states. The use of geostatistics and simple cokriging technique enabled the characterization of the spatial variability of the evapotranspiration providing uncertainty information on the spatial prediction pattern. Evapotranspiration and precipitation surfaces were implemented for the climatic classification in Minas Gerais. Multivariate geostatistical determined improvements of evapotranspiration spatial information. The regions in the south of Minas Gerais derived from the moisture index estimated with the MODIS evapotranspiration (2000-2010), presented divergence of humid conditions when compared to the moisture index derived from the simple kriged and cokriged evapotranspiration (1961-1990), indicating climate change in this region. There was stronger pattern of crossed covariance between evapotranspiration and precipitation rather than temperature, indicating that trends in precipitation could be one of the main external drivers of the evapotranspiration in Minas Gerais state, Brazil.

  6. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    varying magnitude and sign on both diurnal and seasonal scales, which will have implications if using LST products in downstream applications like hydrological or soil vegetation atmosphere transfer (SVAT) models. The directional effects will cause uncertainties in LST estimates that are different...... in terms of timing than the uncertainties in data from polar orbiting sensors, which will cause discrepancies between measurements from the two types of sensors. An assessment of the performance of current LST algorithms from MSG SEVIRI for semi-arid West Africa was carried out, using data from two field...... the illumination geometry changes both over the course of the day and with the seasons. In the present study, the directional effects are assessed at different scales using a modeling approach. The model applied, the Modified Geometry Projection (MGP) model, represents the surface as a composite of four components...

  7. Aircraft-Based Satellite Navigation Augmentation to Enable Automated Landing and Movement on the Airport Surface

    Science.gov (United States)

    Obeidat, Qasem Turki

    A brain-computer interface (BCI) enables a paralyzed user to interact with an external device through brain signals. A BCI measures identifies patterns within these measured signals, translating such patterns into commands. The P300 is a pattern of a scalp potentials elicited by a luminance increment of an attended target rather than a non-target character of an alphanumeric matrix. The Row-Column Paradigm (RCP) can utilize responses to series of illuminations of matrix target and non-target characters to spell out alphanumeric strings of P300-eliciting target characters, yet this popular RCP speller faces three challenges. Theadjacent problem concerns the proximity of neighboring characters, the crowding problem concerns their number. Both adjacent and crowding problems concern how these factors impede BCI performance. The fatigue problem concerns how RCP use is tiring. This dissertation addressed these challenges for both desktop and mobile platforms. A new P300 speller interface, the Zigzag Paradigm (ZP), reduced the adjacent problem by increasing the distance between adjacent characters, as well as the crowding problem, by reducing the number neighboring characters. In desktop study, the classification accuracy was significantly improved 91% with the ZP VS 80.6% with the RCP. Since the ZP is not suitable for mobile P300 spellers with a small screen size, a new P300 speller interface was developed in this study, the Edges Paradigm (EP). The EP reduced the adjacent and crowding problems by adding flashing squares located upon the outer edges of the character matrix in the EP. The classification accuracy of the EP (i.e., 93.3%) was significantly higher than the RCP (i.e., 82.1%). We further compared three speller paradigms (i.e., RCP, ZP, and EP), and the result indicated that the EP produced the highest accuracy and caused less fatigue. Later, the EP is implemented in a simulator of a Samsung galaxy smart phone on the Microsoft Surface Pro 2. The mobile EP was

  8. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale

    Directory of Open Access Journals (Sweden)

    Christiane Schmullius

    2013-05-01

    Full Text Available Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Very High Resolution Radiometer (AVHRR and (Advanced Along Track Scanning Radiometer ((AATSR are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude. Within this study, we compared land surface temperature products from (AATSR, MODIS and AVHRR with an in situ air temperature (Tair database provided by the National Climate Data Center (NCDC. Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST and air temperature for the overlapping time period of the remote sensing data (2000–2005. In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (AATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

  9. 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

  10. Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

    DEFF Research Database (Denmark)

    Moyano, Carmen; Garcia, Monica; Tornos, Lucia

    2015-01-01

    consumption trends in the area. The results showed that the thermal-PT-JPL model is a suitable and simple tool requiring only air temperature and incoming solar radiation apart from standard satellites-products freely available. Our results show that in comparison with the hydrological model conceptual...... to estimate soil surface conductance based on an apparent thermal inertia index. A process-based model was applied to estimate surface energy fluxes including daily ET based on a modified version of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model at 1km pixel resolution during a chrono......-sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

  11. A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

    Directory of Open Access Journals (Sweden)

    Robert M. Parinussa

    2016-10-01

    Full Text Available Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth’s surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1–2 GHz. Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E, as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM, and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm and descending (01:30 am paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for

  12. An investigation of current and future satellite and in-situ data for the remote sensing of the land surface energy balance

    Science.gov (United States)

    Diak, George R.

    1994-01-01

    This final report from the University of Wisconsin-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) summarizes a research program designed to improve our knowledge of the water and energy balance of the land surface through the application of remote sensing and in-situ data sources. The remote sensing data source investigations to be detailed involve surface radiometric ('skin') temperatures and also high-spectral-resolution infrared radiance data from atmospheric sounding instruments projected to be available at the end of the decade, which have shown promising results for evaluating the land-surface water and energy budget. The in-situ data types to be discussed are measurements of the temporal changes of the height of the planetary boundary layer and measurements of air temperature within the planetary boundary layer. Physical models of the land surface, planetary boundary layer and free atmosphere have been used as important tools to interpret the in-situ and remote sensing signals of the surface energy balance. A prototype 'optimal' system for combining multiple data sources into a three-dimensional estimate of the surface energy balance was developed and first results from this system will be detailed. Potential new sources of data for this system and suggested continuation research will also be discussed.

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

    Science.gov (United States)

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

    2011-01-01

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

  14. Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

    Directory of Open Access Journals (Sweden)

    K. Atlaskina

    2015-05-01

    Full Text Available Thirteen years of MODIS surface albedo data for the Northern Hemisphere during the spring months (March–May were analysed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analysed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF has a strong influence on the albedo in the study area and can explain 56% of variation of albedo in March, 76% in April and 92% in May. Therefore the effects of other parameters were investigated only for areas with 100% SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds −15 °C. At monthly mean air temperatures below this value no albedo changes are observed. Enhanced vegetation index (EVI and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100% SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in Eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

  15. Comparison of Satellite-Derived TOA Shortwave Clear-Sky Fluxes to Estimates from GCM Simulations Constrained by Satellite Observations of Land Surface Characteristics

    Science.gov (United States)

    Anantharaj, Valentine G.; Nair, Udaysankar S.; Lawrence, Peter; Chase, Thomas N.; Christopher, Sundar; Jones, Thomas

    2010-01-01

    Clear-sky, upwelling shortwave flux at the top of the atmosphere (S(sub TOA raised arrow)), simulated using the atmospheric and land model components of the Community Climate System Model 3 (CCSM3), is compared to corresponding observational estimates from the Clouds and Earth's Radiant Energy System (CERES) sensor. Improvements resulting from the use of land surface albedo derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to constrain the simulations are also examined. Compared to CERES observations, CCSM3 overestimates global, annual averaged S(sub TOA raised arrow) over both land and oceans. However, regionally, CCSM3 overestimates S(sub TOA raised arrow) over some land and ocean areas while underestimating it over other sites. CCSM3 underestimates S(sub TOA raised arrow) over the Saharan and Arabian Deserts and substantial differences exist between CERES observations and CCSM3 over agricultural areas. Over selected sites, after using groundbased observations to remove systematic biases that exist in CCSM computation of S(sub TOA raised arrow), it is found that use of MODIS albedo improves the simulation of S(sub TOA raised arrow). Inability of coarse resolution CCSM3 simulation to resolve spatial heterogeneity of snowfall over high altitude sites such as the Tibetan Plateau causes overestimation of S(sub TOA raised arrow) in these areas. Discrepancies also exist in the simulation of S(sub TOA raised arrow) over ocean areas as CCSM3 does not account for the effect of wind speed on ocean surface albedo. This study shows that the radiative energy budget at the TOA is improved through the use of MODIS albedo in Global Climate Models.

  16. Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

    Science.gov (United States)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

    2012-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

  17. Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

    2017-04-01

    Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM

  18. GLORI (GLObal navigation satellite system Reflectometry Instrument): A New Airborne GNSS-R receiver for land surface applications

    Science.gov (United States)

    Motte, Erwan; Zribi, Mehrez; Fanise, Pascal

    2015-04-01

    GLORI (GLObal navigation satellite system Reflectometry Instrument) is a new receiver dedicated to the airborne measurement of surface parameters such as soil moisture and biomass above ground and sea state (wave height and direction) above oceans. The instrument is based on the PARIS concept [Martin-Neira, 1993] using both the direct and surface-reflected L-band signals from the GPS constellation as a multistatic radar source. The receiver is based on one up-looking and one down-looking dual polarization hemispherical active antennas feeding a low-cost 4-channel SDR direct down-conversion receiver tuned to the GPS L1 frequency. The raw measurements are sampled at 16.368MHz and stored as 2-bit, IQ binary files. In post-processing, GPS acquisition and tracking are performed on the direct up-looking signal while the down-looking signal is processed blindly using tracking parameters from the direct signal. The obtained direct and reflected code-correlation waveforms are the basic observables for geophysical parameters inversion. The instrument was designed to be installed aboard the ATR42 experimental aircraft from the French SAFIRE fleet as a permanent payload. The long term goal of the project is to provide real-time continuous surface information for every flight performed. The aircraft records attitude information through its Inertial Measurement Unit and a commercial GPS receiver records additional information such as estimated doppler and code phase, receiver location, satellites azimuth and elevation. A series of test flights were performed over both the Toulouse and Gulf of Lion (Mediterranean Sea) regions during the period 17-21 Nov 2014 together with the KuROS radar [Hauser et al., 2014]. Using processing methods from the literature [Egido et al., 2014], preliminary results demonstrate the instrument sensitivity to both ground and ocean surface parameters estimation. A dedicated scientific flight campaign is planned at the end of second quarter 2015 with

  19. Distributed land surface modeling with utilization of multi-sensor satellite data: application for the vast agricultural terrain in cold region

    Science.gov (United States)

    Muzylev, E.; Uspensky, A.; Gelfan, A.; Startseva, Z.; Volkova, E.; Kukharsky, A.; Romanov, P.; Alexandrovich, M.

    2012-04-01

    A technique for satellite-data-based modeling water and heat regimes of a large scale area has been developed and applied for the 227,300 km2 agricultural region in the European Russia. The core component of the technique is the physically based distributed Remote Sensing Based Land Surface Model (RSBLSM) intended for simulating transpiration by vegetation and evaporation from bare soil, vertical transfer of water and heat within soil and vegetation covers during a vegetation season as well as hydrothermal processes in soil and snow covers during a cold season, including snow accumulation and melt, dynamics of soil moisture and temperature during soil freezing and thawing, infiltration into frozen soil. Processes in the "atmosphere-snow-frozen soil" system are critical for cold region agriculture, as they control crop development in early spring before the vegetation season beginning. For assigning the model parameters as well as for preliminary calibrating and validating the model, available multi-year data sets of soil moisture/temperature profiles, evaporation, snow and soil freezing depth measured at the meteorological stations located within the study region have been utilized. To provide an appropriate parametrization of the model for the areas where ground-based measurements are unavailable, estimates have been utilized for vegetation, meteorological and snow characteristics derived from the multispectral measurements of AVHRR/NOAA (1999-2010), MODIS/EOS Terra & Aqua (2002-2010), AMSR-E/Aqua (2003-2004; 2008-2010), and SEVIRI/Meteosat-9 (2009-2010). The technologies of thematic processing the listed satellite data have been developed and applied to estimate the land surface and snow cover characteristics for the study area. The developed technologies of AVHRR data processing have been adapted to retrieve land surface temperature (LST) and emissivity (E), surface-air temperature at a level of vegetation cover (TA), normalized vegetation index (NDVI), leaf

  20. Comparison of Total Water Storage Anomalies from Global Hydrologic and Land Surface Models and New GRACE Satellite Solutions

    Science.gov (United States)

    Scanlon, B. R.; Zhang, Z.; Sun, A.; Save, H.; Mueller Schmied, H.; Wada, Y.; Doll, P. M.; Eisner, S.

    2016-12-01

    There is Increasing interest in global hydrology based on modeling and remote sensing, highlighting the need to compare output from modeling and remote sensing approaches. Here we evaluate simulated terrestrial Total Water Storage anomalies (TWSA) from global hydrologic models (GHMs: WGHM and PRC-GLOBWB) and global land surface models (LSMs, such as GLDAS NOAH, MOSAIC, VIC, and CLM) using newly released GRACE mascons solutions from the Univ. of Texas Center for Space Research. The comparisons are based on monthly TWS anomalies over 13 years (April 2002 - April 2015) for 176 basins globally. Performance metrics include scatter plots of simulated and GRACE observed TWSA by basin with median slopes for different models indicating bias, correlations (shape and timing of TWS time series), and variability ratio (standard deviation of model TWSA/std. dev. GRACE observed TWSA), with optimal values of 1 indicating perfect agreement. The GRACE data were also disaggregated into long-term trends and seasonal amplitudes. Modeled TWS anomalies are biased low by 20 - 30% relative to GRACE TWSA with similar bias levels for basins in different size classes but greater bias with increasing basin aridity. Discrepancies between models and GRACE TWSA are greatest for long-term trends in TWSA with 60 - 95% underestimation of GRACE TWSA by models. There is good agreement in seasonal amplitudes from models and GRACE ( 0.9 for models with little impact of basin size or climate for most models. These comparisons highlight reliable model performance in terms of seasonal amplitudes in TWSA and underestimation of long-term trends in TWSA and in arid basins.

  1. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Directory of Open Access Journals (Sweden)

    Wenquan Zhu

    Full Text Available Carbon Flux Phenology (CFP can affect the interannual variation in Net Ecosystem Exchange (NEE of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands, using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU by more than 70% and End of Carbon Uptake (ECU by more than 60%. The Root Mean Square Error (RMSE of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

  2. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Science.gov (United States)

    Zhu, Wenquan; Chen, Guangsheng; Jiang, Nan; Liu, Jianhong; Mou, Minjie

    2013-01-01

    Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptake (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

  3. Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale

    NARCIS (Netherlands)

    Urban, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M.

    2013-01-01

    Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are pr

  4. Prognostic land surface albedo from a dynamic global vegetation model clumped canopy radiative transfer scheme and satellite-derived geographic forest heights

    Science.gov (United States)

    Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Aleinov, I. D.; Jonas, J.

    2014-12-01

    Vegetation cover was introduced into general circulations models (GCMs) in the 1980's to account for the effect of land surface albedo and water vapor conductance on the Earth's climate. Schemes assigning canopy albedoes by broad biome type have been superceded in 1990's by canopy radiative transfer schemes for homogeneous canopies obeying Beer's Law extinction as a function of leaf area index (LAI). Leaf albedo and often canopy height are prescribed by plant functional type (PFT). It is recognized that this approach does not effectively describe geographic variation in the radiative transfer of vegetated cover, particularly for mixed and sparse canopies. GCM-coupled dynamic global vegetation models (DGVMs) have retained these simple canopy representations, with little further evaluation of their albedos. With the emergence lidar-derived canopy vertical structure data, DGVM modelers are now revisiting albedo simulation. We present preliminary prognostic global land surface albedo produced by the Ent Terrestrial Biosphere Model (TBM), a DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. The Ent TBM is a next generation DGVM designed to incorporate variation in canopy heights, and mixed and sparse canopies. For such dynamically varying canopy structure, it uses the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer model, which is derived from gap probability theory for canopies of tree cohorts with ellipsoidal crowns, and accounts for soil, snow, and bare stems. We have developed a first-order global vegetation structure data set (GVSD), which gives a year of satellite-derived geographic variation in canopy height, maximum canopy leaf area, and seasonal LAI. Combined with Ent allometric relations, this data set provides population density and foliage clumping within crowns. We compare the Ent prognostic albedoes to those of the previous GISS GCM scheme, and to satellite estimates. The impact of albedo differences on surface

  5. Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C Data

    Directory of Open Access Journals (Sweden)

    Jun Xia

    2008-02-01

    Full Text Available On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m , using the Generalized Split-Window (GSWalgorithm proposed by Wan and Dozier (1996. The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC, and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities(LSEs are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006; and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.’ method (2003. The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give

  6. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...... hydrological and tested by assimilating synthetic hydraulic head observations in a catchment in Denmark. Assimilation led to a substantial reduction of model prediction error, and better model forecasts. Also, a new assimilation scheme is developed to downscale and bias-correct coarse satellite derived soil...

  7. A new digital land mobile satellite system

    Science.gov (United States)

    Schneider, Philip

    A description is given of the different digital services planned to be carried over existing and planned mobile satellite systems. These systems are then compared with analog services in terms of bandwidth and power efficiency. This comparison provides the rationale for the establishment of a digital land mobile satellite service (DLMSS) to use frequencies that are currently available but not yet assigned to a domestic mobile satellite system in the United States. The focus here is on the expected advantages of digital transmission techniques in accommodating additional mobile satellite systems in this portion of the spectrum, and how such techniques can fully satisfy voice, data and facsimile mobile communications requirements in a cost effective manner. A description is given of the system architecture of the DMLSS service proposed by the Geostar Messaging Corporation (GMC) and the market potential of DLMSS.

  8. TOWARD CALIBRATED MODULAR WIRELESS SYSTEM BASED AD HOC SENSORS FOR IN SITU LAND SURFACE TEMPERATURE MEASUREMENTS AS SUPPORT TO SATELLITE REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    ASAAD CHAHBOUN

    2011-06-01

    Full Text Available This paper presents a new method for in situ Land Surface Temperature (LST measurements' campaigns for satellite algorithms validations. The proposed method based on Wireless Sensor Network (WSN is constituted by modules of node arrays. Each of which is constituted by 25 smart nodes scattered throughout a target field. Every node represents a Thermal Infra Red (TIR radiation sensor and keeps a minimum size while ensuring the functions of communication, sensing, and processing. This Wireless-LST (Wi-LST system is convenient to beinstalled on a field pointing to any type of targets (e.g. bare soil, grass, water, etc.. Ad hoc topology is adopted among the TIR nodes with multi-hop mesh routing protocol for communication, acquisition data are transmitted to the client tier wirelessly. Using these emergent technologies, we propose a practical method for Wi-LSTsystem calibration. TIR sensor (i.e. OSM101 from OMEGA society measures temperature, which is conditioned and amplified by an AD595 within a precision of 0.1 °C. Assessed LST is transmitted over thedeveloped ad hoc WSN modules (i.e. MICA2DOT from CROSSBOW society, and collected at in situ base station (i.e. PANASONIC CF19 laptop using an integrated database. LST is evaluated with a polynomialalgorithm structure as part of developed software. Finally, the comparison of the mean values of LST(Wi-LST in each site with the Moderate Resolution Imaging Spectro-radiometer (MODIS sensor, obtained from the daily LST product (MOD11C1 developed by the MODIS-NASA Science Team, on board TERRA satellite during the campaign period is provided.

  9. Numerical modeling and remote sensing of global water management systems: Applications for land surface modeling, satellite missions, and sustainable water resources

    Science.gov (United States)

    Solander, Kurt C.

    The ability to accurately quantify water storages and fluxes in water management systems through observations or models is of increasing importance due to the expected impacts from climate change and population growth worldwide. Here, I describe three innovative techniques developed to better understand this problem. First, a model was created to represent reservoir storage and outflow with the objective of integration into a Land Surface Model (LSM) to simulate the impacts of reservoir management on the climate system. Given this goal, storage capacity represented the lone model input required that is not already available to an LSM user. Model parameterization was linked to air temperature to allow future simulations to adapt to a changing climate, making it the first such model to mimic the potential response of a reservoir operator to climate change. Second, spatial and temporal error properties of future NASA Surface Water and Ocean Topography (SWOT) satellite reservoir operations were quantified. This work invoked the use of the SWOTsim instrument simulator, which was run over a number of synthetic and actual reservoirs so the resulting error properties could be extrapolated to the global scale. The results provide eventual users of SWOT data with a blueprint of expected reservoir error properties so such characteristics can be determined a priori for a reservoir given knowledge about its topology and anticipated repeat orbit pass over its location. Finally, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission was used in conjunction with in-situ water use records to evaluate sustainable water use at the two-digit HUC basin scale over the contiguous United States. Results indicate that the least sustainable water management region is centered in the southwest, where consumptive water use exceeded water availability by over 100% on average for some of these basins. This work represents the first attempt at evaluating sustainable

  10. National Spatiotemporal Exposure Surface for NO2: Monthly Scaling of a Satellite-Derived Land-Use Regression, 2000-2010.

    Science.gov (United States)

    Bechle, Matthew J; Millet, Dylan B; Marshall, Julian D

    2015-10-20

    Land-use regression (LUR) is widely used for estimating within-urban variability in air pollution. While LUR has recently been extended to national and continental scales, these models are typically for long-term averages. Here we present NO2 surfaces for the continental United States with excellent spatial resolution (∼100 m) and monthly average concentrations for one decade. We investigate multiple potential data sources (e.g., satellite column and surface estimates, high- and standard-resolution satellite data, and a mechanistic model [WRF-Chem]), approaches to model building (e.g., one model for the whole country versus having separate models for urban and rural areas, monthly LURs versus temporal scaling of a spatial LUR), and spatial interpolation methods for temporal scaling factors (e.g., kriging versus inverse distance weighted). Our core approach uses NO2 measurements from U.S. EPA monitors (2000-2010) to build a spatial LUR and to calculate spatially varying temporal scaling factors. The model captures 82% of the spatial and 76% of the temporal variability (population-weighted average) of monthly mean NO2 concentrations from U.S. EPA monitors with low average bias (21%) and error (2.4 ppb). Model performance in absolute terms is similar near versus far from monitors, and in urban, suburban, and rural locations (mean absolute error 2-3 ppb); since low-density locations generally experience lower concentrations, model performance in relative terms is better near monitors than far from monitors (mean bias 3% versus 40%) and is better for urban and suburban locations (1-6%) than for rural locations (78%, reflecting the relatively clean conditions in many rural areas). During 2000-2010, population-weighted mean NO2 exposure decreased 42% (1.0 ppb [∼5.2%] per year), from 23.2 ppb (year 2000) to 13.5 ppb (year 2010). We apply our approach to all U.S. Census blocks in the contiguous United States to provide 132 months of publicly available, high

  11. DISAGGREGATION OF GOES LAND SURFACE TEMPERATURES USING SURFACE EMISSIVITY

    Science.gov (United States)

    Accurate temporal and spatial estimation of land surface temperatures (LST) is important for modeling the hydrological cycle at field to global scales because LSTs can improve estimates of soil moisture and evapotranspiration. Using remote sensing satellites, accurate LSTs could be routine, but unfo...

  12. Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

    Science.gov (United States)

    Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

    2013-05-01

    Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987-2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

  13. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar operational environmental satellite data for land surface monitoring in Africa

    DEFF Research Database (Denmark)

    Fensholt, Rasmus; Anyamba, Assaf; Huber Gharib, Silvia

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth’s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which oft...

  14. Meteosat SEVIRI Fire Radiative Power (FRP products from the Land Surface Analysis Satellite Applications Facility (LSA SAF – Part 1: Algorithms, product contents and analysis

    Directory of Open Access Journals (Sweden)

    M. J. Wooster

    2015-06-01

    Full Text Available Characterising changes in landscape scale fire activity at very high temporal resolution is best achieved using thermal observations of actively burning fires made from geostationary Earth observation (EO satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from these types of geostationary observations, often with the aim of supporting the generation of data related to biomass burning fuel consumption and trace gas and aerosol emission fields. The Fire Radiative Power (FRP products generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF from data collected by the Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI are one such set of products, and are freely available in both near real-time and archived form. Every 15 min, the algorithms used to generate these products identify and map the location of new SEVIRI observations containing actively burning fires, and characterise their individual rates of radiative energy release (fire radiative power; FRP that is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the highest spatial resolution FRP dataset, delivered for all of Europe, northern and southern Africa, and part of South America at a spatial resolution of 3 km (decreasing away from the west African sub-satellite point at the full 15 min temporal resolution. The FRP-GRID product is an hourly summary of the FRP-PIXEL data, produced at a 5° grid cell size and including simple bias adjustments for meteorological cloud cover and for the regional underestimation of FRP caused, primarily, by the non-detection of low FRP fire pixels at SEVIRI's relatively coarse pixel size. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA algorithm used to detect the SEVIRI active fire pixels, and detail methods used to deliver atmospherically corrected FRP

  15. An Estimation of Land Surface Temperatures from Landsat ETM+ ...

    African Journals Online (AJOL)

    Dr-Adeline

    2 National Authority for Remote Sensing and Space Sciences, Cairo, Egypt. 3University of ... Keywords: Urban growth, urban heat Island, land surface temperatures, satellite remote sensing .... observed target includes green vegetation or not.

  16. Determination of Land Surface Temperature (LST) and Potential ...

    African Journals Online (AJOL)

    Determination of Land Surface Temperature (LST) and Potential Urban Heat Island Effect in Parts of Lagos State using Satellite ... Changes in temperature appear to be closely related to concentrations of atmospheric carbon dioxide.

  17. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2014-09-01

    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

  18. Modeling Land Surface Phenology Using Earthlight

    Science.gov (United States)

    Henebry, G. M.

    2005-12-01

    Microwave radiometers have long been used in earth observation, but the coarse spatial resolution of the data has discouraged its use in investigations of the vegetated land surface. The Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite acquires multifrequency observations twice daily (1:30 and 13:30). From these brightness temperatures come two data products relevant to land surface phenology: soil moisture and vegetation water content. Although the nominal spatial resolution of these products is coarse (25 km), the fine temporal sampling allows characterization of the diel variation in surface moisture as contained in the uppermost soil layer and bound in the vegetation canopy. The ephermal dynamics of surficial soil moisture are difficult to validate due to the scale discrepancy between the 625 sq km coverage of a single pixel and the sparse network of weather stations. In contrast, canopy dynamics are more readily validated using finer spatial resolution data products and/or ecoregionalizations. For sites in the North American Great Plains and Northern Eurasia dominated by herbaceous vegetation, I will present land surface phenologies modeled using emitted earthlight and compare them with land surface phenologies modeled using reflected sunlight. I will also explore whether some key climate modes have a significant effect on the microwave-retrieved land surface phenologies.

  19. Greenland surface albedo changes 1981-2012 from satellite observations

    Science.gov (United States)

    Significant melt over Greenland has been observed during the last several decades associated with extreme warming events over the northern Atlantic Ocean. An analysis of surface albedo change over Greenland is presented, using a 32-year consistent satellite albedo product from the Global Land Surfac...

  20. An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model

    Science.gov (United States)

    Hain, Christopher R.; Crow, Wade T.; Anderson, Martha C.; Mecikalski, John R.

    2012-11-01

    Studies that have assimilated remotely sensed soil moisture (SM) into land surface models (LSMs) have generally focused on retrievals from microwave (MW) sensors. However, retrievals from thermal infrared (TIR) sensors have also been shown to add unique information, especially where MW sensors are not able to provide accurate retrievals (due to, e.g., dense vegetation). In this study, we examine the assimilation of a TIR product based on surface evaporative flux estimates from the Atmosphere Land Exchange Inverse (ALEXI) model and the MW-based VU Amsterdam NASA surface SM product generated with the Land Parameter Retrieval Model (LPRM). A set of data assimilation experiments using an ensemble Kalman filter are performed over the contiguous United States to assess the impact of assimilating ALEXI and LPRM SM retrievals in isolation and together in a dual-assimilation case. The relative skill of each assimilation case is assessed through a data denial approach where a LSM is forced with an inferior precipitation data set. The ability of each assimilation case to correct for precipitation errors is quantified by comparing with a simulation forced with a higher-quality precipitation data set. All three assimilation cases (ALEXI, LPRM, and Dual assimilation) show relative improvements versus the open loop (i.e., reduced RMSD) for surface and root zone SM. In the surface zone, the dual assimilation case provides the largest improvements, followed by the LPRM case. However, the ALEXI case performs best in the root zone. Results from the data denial experiment are supported by comparisons between assimilation results and ground-based SM observations from the Soil Climate Analysis Network.

  1. Determining Land Surface Temperature Relations with Land Use-Land Cover and Air Pollution

    Science.gov (United States)

    Kahya, Ceyhan; Bektas Balcik, Filiz; Burak Oztaner, Yasar; Guney, Burcu

    2016-04-01

    Rapid population growth in conjunction with unplanned urbanization, expansion, and encroachment into the limited agricultural fields and green areas have negative impacts on vegetated areas. Land Surface Temperature (LST), Urban Heat Islands (UHI) and air pollution are the most important environmental problems that the extensive part of the world suffers from. The main objective of this research is to investigate the relationship between LST, air pollution and Land Use-Land Cover (LULC) in Istanbul, using Landsat 8 OLI satellite image. Mono-window algorithm is used to compute LST from Landsat 8 TIR data. In order to determine the air pollution, in-situ measurements of particulate matter (PM10) of the same day as the Landsat 8 OLI satellite image are obtained. The results of this data are interpolated using the Inverse Distance Weighted (IDW) method and LULC categories of Istanbul were determined by using remote sensing indices. Error matrix was created for accuracy assessment. The relationship between LST, air pollution and LULC categories are determined by using regression analysis method. Keywords: Land Surface Temperature (LST), air pollution, Land Use-Land Cover (LULC), Istanbul

  2. The L-band PBMR measurements of surface soil moisture in FIFE. [First International satellite land surface climatology project Field Experiment

    Science.gov (United States)

    Wang, James R.; Shiue, James C.; Schmugge, Thomas J.; Engman, Edwin T.

    1990-01-01

    The NASA Langley Research Center's L-band pushbroom microwave radiometer (PBMR) aboard the NASA C-130 aircraft was used to map surface soil moisture at and around the Konza Prairie Natural Research Area in Kansas during the four intensive field campaigns of FIFE in May-October 1987. There was a total of 11 measurements was made when soils were known to be saturated. This measurement was used for the calibration of the vegetation effect on the microwave absorption. Based on this calibration, the data from other measurements on other days were inverted to generate the soil moisture maps. Good agreement was found when the estimated soil moisture values were compared to those independently measured on the ground at a number of widely separated locations. There was a slight bias between the estimated and measured values, the estimated soil moisture on the average being lower by about 1.8 percent. This small bias, however, was accounted for by the difference in time of the radiometric measurements and the soil moisture ground sampling.

  3. Land Surface Weather Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — METAR is the international standard code format for hourly surface weather observations. The acronym roughly translates from French as Aviation Routine Weather...

  4. China Land Observation Satellite Third User Conference Promotes The Applications Of Domestic Satellite Data

    Institute of Scientific and Technical Information of China (English)

    Zong He

    2009-01-01

    @@ China Land Observation Satellite Third User Conference with the theme of "Strengthening cooperation,enlarging sharing and promoting the application of domestic satellite data" was held on July 16,2009 in Beijing. The conference was hosted by China Centre for Resources Satellite Data and Applications(CRESDA),a subsidiary of China Aerospace Science and Technology Corporation (CASC).

  5. Observations of land-atmosphere interactions using satellite data

    Science.gov (United States)

    Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

    2016-04-01

    Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of

  6. 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.

  7. Improvement of NCEP Numerical Weather Prediction with Use of Satellite Land Measurements

    Science.gov (United States)

    Zheng, W.; Ek, M. B.; Wei, H.; Meng, J.; Dong, J.; Wu, Y.; Zhan, X.; Liu, J.; Jiang, Z.; Vargas, M.

    2014-12-01

    Over the past two decades, satellite measurements are being increasingly used in weather and climate prediction systems and have made a considerable progress in accurate numerical weather and climate predictions. However, it is noticed that the utilization of satellite measurements over land is far less than over ocean, because of the high land surface inhomogeneity and the high emissivity variabilities in time and space of surface characteristics. In this presentation, we will discuss the application efforts of satellite land observations in the National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS) in order to improve the global numerical weather prediction (NWP). Our study focuses on use of satellite data sets such as vegetation type and green vegetation fraction, assimilation of satellite products such as soil moisture retrieval, and direct radiance assimilation. Global soil moisture data products could be used for initialization of soil moisture state variables in numerical weather, climate and hydrological forecast models. A global Soil Moisture Operational Product System (SMOPS) has been developed at NOAA-NESDIS to continuously provide global soil moisture data products to meet NOAA-NCEP's soil moisture data needs. The impact of the soil moisture data products on numerical weather forecast is assessed using the NCEP GFS in which the Ensemble Kalman Filter (EnKF) data assimilation algorithm has been implemented. In terms of radiance assimilation, satellite radiance measurements in various spectral channels are assimilated through the JCSDA Community Radiative Transfer Model (CRTM) on the NCEP Gridpoint Statistical Interpolation (GSI) system, which requires the CRTM to calculate model brightness temperature (Tb) with input of model atmosphere profiles and surface parameters. Particularly, for surface sensitive channels (window channels), Tb largely depends on surface parameters such as land surface skin temperature, soil

  8. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    related to inaccurate land surface modelling, e.g. enhanced warm bias in warm dry summer months. Coupling the regional climate model to a hydrological model shows the potential of improving the surface flux simulations in dry periods and the 2 m air temperature in general. In the dry periods......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation...

  9. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  10. Land vehicle antennas for satellite mobile communications

    Science.gov (United States)

    Haddad, H. A.; Pieper, B. V.; Mckenna, D. B.

    1985-01-01

    The RF performance, size, pointing system, and cost were investigated concepts are: for a mechanically steered 1 x 4 tilted microstrip array, a mechanically steered fixed-beam conformal array, and an electronically steered conformal phased array. Emphasis is on the RF performance of the tilted 1 x 4 antenna array and methods for pointing the various antennas studied to a geosynchronous satellite. An updated version of satellite isolations in a two-satellite system is presented. Cost estimates for the antennas in quantities of 10,000 and 100,000 unites are summarized.

  11. ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

    Directory of Open Access Journals (Sweden)

    S. Faroux

    2013-04-01

    Full Text Available The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo. Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover and GLC2000 (Global Land Cover by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography. The leaf area index (LAI from MODIS and normalized difference vegetation index (NDVI from SPOT/Vegetation (a global monitoring system of vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas and, inside the nature tile, fractions of 12 plant functional types (PFTs representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of

  12. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    OpenAIRE

    Ruescas, Ana Belen; Danne, Olaf; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temp...

  13. Analysis of Anomaly in Land Surface Temperature Using MODIS Products

    Science.gov (United States)

    Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

    2011-12-01

    Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

  14. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    Science.gov (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  15. Urban Land Use Change Detection Using Multisensor Satellite Images

    Institute of Scientific and Technical Information of China (English)

    DENG Jin-Song; WANG Ke; LI Jun; DENG Yan-Hua

    2009-01-01

    Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multiseusor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 muttispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into bnilt-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.

  16. Detection of land cover change using an Artificial Neural Network on a time-series of MODIS satellite data

    CSIR Research Space (South Africa)

    Olivier, JC

    2007-11-01

    Full Text Available An Artificial Neural Network (ANN) is proposed to detect human-induced land cover change using a sliding window through a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite surface reflectance pixel values. Training...

  17. Land mobile satellite propagation measurements in Japan using ETS-V satellite

    Science.gov (United States)

    Obara, Noriaki; Tanaka, Kenji; Yamamoto, Shin-Ichi; Wakana, Hiromitsu

    1993-01-01

    Propagation characteristics of land mobile satellite communications channels have been investigated actively in recent years. Information of propagation characteristics associated with multipath fading and shadowing is required to design commercial land mobile satellite communications systems, including protocol and error correction method. CRL (Communications Research Laboratory) has carried out propagation measurements using the Engineering Test Satellite-V (ETS-V) at L band (1.5 GHz) through main roads in Japan by a medium gain antenna with an autotracking capability. This paper presents the propagation statistics obtained in this campaign.

  18. Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

    2014-01-01

    Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

  19. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  20. Land mobile satellite services in Europe

    Science.gov (United States)

    Bartholome, P.; Rogard, R.; Berretta, G.

    1988-10-01

    The potential role of satellite communication as a complement to the pan-European cellular telephone network being developed to replace the current national or regional networks in the mid 1990s is discussed. The design concept and capabilities of the all-digital cellular network are reviewed; the requirements not covered by the network are listed; market-survey results indicating business interest in these additional services are summarized; and particular attention is given to the ESA demonstration system PRODAT. PRODAT uses the Marecs satellite to provide low-rate two-way data transmission for mobile terminals; the CDMA technique is used for the return links from mobile unit to hub station.

  1. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed s

  2. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed s

  3. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed

  4. Derived Land Surface Emissivity From Suomi NPP CrIS

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

    2012-01-01

    Presented here is the land surface IR spectral emissivity retrieved from the Cross-track Infrared Sounder (CrIS) measurements. The CrIS is aboard the Suomi National Polar-orbiting Partnership (NPP) satellite launched on October 28, 2011. We describe the retrieval algorithm, demonstrate the surface emissivity retrieved with CrIS measurements, and inter-comparison with the Infrared Atmospheric Sounding Interferometer (IASI) emissivity. We also demonstrate that surface emissivity from satellite measurements can be used in assistance of monitoring global surface climate change, as a long-term measurement of IASI and CrIS will be provided by the series of EUMETSAT MetOp and US Joint Polar Satellite System (JPSS) satellites. Monthly mean surface properties are produced using last 5-year IASI measurements. A temporal variation indicates seasonal diversity and El Nino/La Nina effects not only shown on the water but also on the land. Surface spectral emissivity and skin temperature from current and future operational satellites can be utilized as a means of long-term monitoring of the Earth's environment. CrIS spectral emissivity are retrieved and compared with IASI. The difference is small and could be within expected retrieval error; however it is under investigation.

  5. Determination of atmospheric aerosol properties over land using satellite measurements

    NARCIS (Netherlands)

    Kokhanovsky, A.A.; Leeuw, G. de

    2009-01-01

    Mostly, aerosol properties are poorly understood because the aerosol properties are very sparse. The first workshop on the determination of atmospheric aerosol properties over land using satellite measurements is convened in Bremen, Germany. In this workshop, the topics of discussions included a var

  6. Effect of land use/cover change on land surface temperatures - The Nile Delta, Egypt

    Science.gov (United States)

    Hereher, Mohamed E.

    2017-02-01

    In this study remote sensing techniques were employed to investigate the impact of land use/cover change on land surface temperatures (LST) for a highly dynamic landscape, i.e. the Nile Delta. Land use change was determined from analyzing a 15 years of bi-monthly normalized difference vegetation index (NDVI) dataset acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite along with a synchronized 13 years of bi-monthly LST dataset retrieved from MODIS Aqua satellite. Time series analysis for NDVI and LST data was carried out at selected locations experiencing land use change. Mean LST change was determined for each location before and after the land use change. Results indicate that NDVI composite data for 15 years proved sufficient for delineating land use change. Significant spatial changes include the transformation from agriculture to urban land, which increased the LST by 1.7 °C during the 13 years and the transformation of bare land to agriculture, which decreased the LST by 0.52 °C for the same period. Due to the explosive population growth in the Nile Delta, urban encroachment upon agricultural land could, hence, promote a prolonged regional warming by modifying the micro-climate and other climate-related phenomena.

  7. The Land Surface Temperature Impact to Land Cover Types

    Science.gov (United States)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  8. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

    2012-01-01

    Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  9. The experience of land cover change detection by satellite data

    Institute of Scientific and Technical Information of China (English)

    Lev SPIVAK; Irina VITKOVSKAYA; Madina BATYRBAYEVA; Alexey TEREKHOV

    2012-01-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan.As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan.The major process of desertification takes place in the arid and semi-arid areas.To allocate spots of stable degradation of vegetation,the transition zone was first identified.Productivity of vegetation in transfer zone is slightly dependent on climate conditions.Multi-year digital maps of vegetation index were generated with NOAA satellite images.According to the result,the territory of the republic was zoned by means of vegetation productivity criterion.All the arable lands in Kazakhstan are in the risky agriculture zone.Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture,where natural factors,such as wind and water erosion,can significantly change land quality in a relatively short time period.We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from lowresolution satellite data for all of Kazakhstan.This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  10. Improving arable land heterogeneity information in available land cover products for land surface modelling using MERIS NDVI data

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2010-10-01

    Full Text Available Regionalization of physical land surface models requires the supply of detailed land cover information. Numerous global and regional land cover maps already exist but generally, they do not resolve arable land into different crop types. However, arable land comprises a huge variety of different crops with characteristic phenological behaviour, demonstrated in this paper with Leaf Area Index (LAI measurements exemplarily for maize and winter wheat. This affects the mass and energy fluxes on the land surface and thus its hydrology. The objective of this study is the generation of a land cover map for central Europe based on CORINE Land Cover (CLC 2000, merged with CORINE Switzerland, but distinguishing different crop types. Accordingly, an approach was developed, subdividing the land cover class arable land into the regionally most relevant subclasses for central Europe using multiseasonal MERIS Normalized Difference Vegetation Index (NDVI data. The satellite data were used for the separation of spring and summer crops due to their different phenological behaviour. Subsequently, the generated phenological classes were subdivided following statistical data from EUROSTAT. This database was analysed concerning the acreage of different crop types. The impact of the improved land use/cover map on evapotranspiration was modelled exemplarily for the Upper Danube catchment with the hydrological model PROMET. Simulations based on the newly developed land cover approach showed a more detailed evapotranspiration pattern compared to model results using the traditional CLC map, which is ignorant of most arable subdivisions. Due to the improved temporal behaviour and spatial allocation of evapotranspiration processes in the new land cover approach, the simulated water balance more closely matches the measured gauge.

  11. Surface Emissivity Derived From Multispectral Satellite Data

    Science.gov (United States)

    Minnis, P.; Smith, W. L., Jr.; Young, D. F.

    1998-01-01

    Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a surface at a given skin temperature. Surface emissivity is difficult to determine because skin temperature is an ill-defined parameter. The surface-emitted radiation may arise from a range of surface depths depending on many factors including soil moisture, vegetation, surface porosity, and heat capacity. Emissivity can be measured in the laboratory for pure surfaces. Transfer of laboratory measurements to actual Earth surfaces, however, is fraught with uncertainties because of their complex nature. This paper describes a new empirical approach for estimating surface skin temperature from a combination of brightness temperatures measured at different infrared wavelengths with satellite imagers. The method uses data from the new Geostationary Operational Environmental Satellite (GOES) imager to determine multispectral emissivities from the skin temperatures derived over the ARM Southern Great Plains domain.

  12. Real Time Land-Surface Hydrologic Modeling Over Continental US

    Science.gov (United States)

    Houser, Paul R.

    1998-01-01

    The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

  13. Land Surface Temperature at Night

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  14. Improved in-situ methods for determining land surface emissivity

    Science.gov (United States)

    Göttsche, Frank; Olesen, Folke; Hulley, Glynn

    2014-05-01

    The accurate validation of LST satellite products, such as the operational LST retrieved by the Land Surface Analysis - Satellite Application Facility (LSA-SAF), requires accurate knowledge of emissivity for the areas observed by the ground radiometers as well as for the area observed by the satellite sensor. Especially over arid regions, the relatively high uncertainty in land surface emissivity (LSE) limits the accuracy with which land surface temperature (LST) can be retrieved from thermal infrared (TIR) radiance measurements. LSE uncertainty affects LST obtained from satellite measurements and in-situ radiance measurements alike. Furthermore, direct comparisons between satellite sensors and ground based sensors are complicated by spatial scale mismatch: ground radiometers usually observe some 10 m2, whereas satellite sensors typically observe between 1 km2 and 100 km2. Therefore, validation sites have to be carefully selected and need to be characterised on the scale of the ground radiometer as well as on the scale of the satellite pixel. The permanent stations near Gobabeb (Namibia; hyper-arid desert climate) and Dahra (Senegal; hot-arid steppe-prairie climate) are two of KIT's four dedicated LST validation stations. Gobabeb station is located on vast and flat gravel plains (several 100 km2), which are mainly covered by coarse gravel, sand, and desiccated grass. The gravel plains are highly homogeneous in space and time, which makes them ideal for validating a broad range of satellite-derived products. Dahra station is located in so called 'tiger bush' and is covered by strongly seasonal grass (95%) and sparse, evergreen trees (dominantly acacia trees) with a background of reddish sand. The strong seasonality is caused by a pronounced rainy season, during which LST retrieval is highly challenging. Outside the rainy season, both sites have relatively large fractions of bare ground and desiccated vegetation: therefore, they are particularly prone to be

  15. Monitoring the hydrologic and vegetation dynamics of arid land with satellite remote sensing and mathematic modeling

    Science.gov (United States)

    Zhan, Xiwu; Gao, Wei; Pan, Xiaoling; Ma, Yingjun

    2003-07-01

    Terrestrial ecosystems, in which carbon is retained in live biomass, play an important role in the global carbon cycling. Among these ecological systems, vegetation and soils in deserts and semi deserts control significant proportions in the total carbon stocks on the land surface and the carbon fluxes between the land surface and the atmosphere (IPCC special report: Land Use, Land Use Change and Forestry, June 2000). Therefore, accurate assessment of the carbon stocks and fluxes of the desert and semi desert areas at regional scales is required in global carbon cycle studies. In addition, vegetative ecosystem in semi-arid and arid land is strongly dependent on the water resources. Monitoring the hydrologic processes of the land is thus also required. This work explores the methodology for the sequential continuous estimation of the carbon stocks, CO2 flux, evapotranspiration, and sensible heat fluxes over desert and semidesert area using data from the Jornada desert in New Mexico, USA. A CO2 and energy flux coupled model is used to estimate CO2, water vapor and sensible heat fluxes over the desert area. The model is driven by the observed meteorological data. Its input land surface parameters are derived from satellite images. Simulated energy fluxes are validated for specific sites with eddy covariance observations. Based on the output of spatially distributed CO2 fluxes, carbon accumulations over the desert area during a period of time is calculated and the contribution of the desert ecosystem to the atmospheric carbon pool is discussed.

  16. Satellite dynamics on the Laplace surface

    CERN Document Server

    Tremaine, Scott; Namouni, Fathi

    2008-01-01

    The orbital dynamics of most planetary satellites is governed by the quadrupole moment from the equatorial bulge of the host planet and the tidal field from the Sun. On the Laplace surface, the long-term orbital evolution driven by the combined effects of these forces is zero, so that orbits have a fixed orientation and shape. The "classical" Laplace surface is defined for circular orbits, and coincides with the planet's equator at small planetocentric distances and with its orbital plane at large distances. A dissipative circumplanetary disk should settle to this surface, and hence satellites formed from such a disk are likely to orbit in or near the classical Laplace surface. This paper studies the properties of Laplace surfaces. Our principal results are: (i) if the planetary obliquity exceeds 68.875 deg there is a range of semimajor axes in which the classical Laplace surface is unstable; (ii) at some obliquities and planetocentric distances there is a distinct Laplace surface consisting of nested eccentr...

  17. Determination of regional surface heat fluxes over heterogeneous landscapes by integrating satellite remote sensing with boundary layer observations

    NARCIS (Netherlands)

    Ma, Y.M.

    2006-01-01

    Keywords: satellite remote sensing, surface layer observations, atmospheric boundary layer observations, land surface variables, vegetation variables, land surface heat fluxes, validation, heterogeneous landscape, GAME/Tibet

  18. LAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    P. Nalina

    2014-01-01

    Full Text Available Land use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. The Nilgiris district of Tamilnadu state in India is the first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by frequent landslides. Therefore in this present study land use land cover dynamics of Nilgiri district has been studied from 1990 to 2010 using Satellite Remote Sensing Technique. The temporal changes of land use and land cover changes of Nilgiris district over the period of 1990 to 2010 were monitored using LISS I and LISS III of IRS 1A and IRS-P6 satellites. Land use dynamics were identified using Maximum likelihood classification under supervised classification technique. From the remote sensing study, it is found that during the study period of 1990 to 2010, area of dense forest increased by 27.17%, forest plantation area decreased by 54.64%. Conversion of forest plantation, Range land and open forest by agriculture and settlement leading to soil erosion and landslides. Tea plantation increased by 33.95% and agricultural area for plantation of vegetables increased rapidly to 217.56% in the mountain steep area. The accuracy of classification has been assessed by forming confusion matrix and evaluating kappa coefficient. The overall accuracy has been obtained as 83.7 and 89.48% for the years 1990 and 2010 respectively. The kappa coefficients were reported as 0.80 and 0.88 respectively for the years 1990 and 2010.

  19. evaluation of land surface temperature parameterization ...

    African Journals Online (AJOL)

    user

    1 DEPARTMENT OF PHYSICS, ADEYEMI COLLEGE OF EDUCATION, ONDO, ... Surface temperature (Ts) is vital to the study of land-atmosphere interactions and climate variabilities. .... value = 0.167 m3m-3), and very low for dry days (mean.

  20. Heavy rainfall prediction applying satellite-based cloud data assimilation over land

    Science.gov (United States)

    Seto, Rie; Koike, Toshio; Rasmy, Mohamed

    2016-08-01

    To optimize flood management, it is crucial to determine whether rain will fall within a river basin. This requires very fine precision in prediction of rainfall areas. Cloud data assimilation has great potential to improve the prediction of precipitation area because it can directly obtain information on locations of rain systems. Clouds can be observed globally by satellite-based microwave remote sensing. Microwave observation also includes information of latent heat and water vapor associated with cloud amount, which enables the assimilation of not only cloud itself but also the cloud-affected atmosphere. However, it is difficult to observe clouds over land using satellite microwave remote sensing, because their emissivity is much lower than that of the land surface. To overcome this challenge, we need appropriate representation of heterogeneous land emissivity. We developed a coupled atmosphere and land data assimilation system with the Weather Research and Forecasting Model (CALDAS-WRF), which can assimilate soil moisture, vertically integrated cloud water content over land, and heat and moisture within clouds simultaneously. We applied this system to heavy rain events in Japan. Results show that the system effectively assimilated cloud signals and produced very accurate cloud and precipitation distributions. The system also accurately formed a consistent atmospheric field around the cloud. Precipitation intensity was also substantially improved by appropriately representing the local atmospheric field. Furthermore, combination of the method and operationally analyzed dynamical and moisture fields improved prediction of precipitation duration. The results demonstrate the method's promise in dramatically improving predictions of heavy rain and consequent flooding.

  1. Ocean surface currents from satellite data

    Science.gov (United States)

    Dohan, Kathleen

    2017-04-01

    The atmosphere drives entire ocean motions, and yet the exchange of momentum between the atmosphere and ocean occurs in the thin layer where they meet, involving the smallest scales of turbulence. The Ocean Surface Current Analyses Real-time (OSCAR) project attempts to better understand this exchange using satellite observations with simplified physics to calculate global ocean currents. The goal is to continually improve the physics in OSCAR and more accurately model the currents. The theoretical study will help coupled ocean-atmosphere modeling efforts whereas the societal benefits of measuring ocean currents are broad, e.g., fish larval dispersion, heat transport, commercial shipping, and search and rescue.

  2. A protocol for validating Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2015-12-01

    One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of

  3. Spatial assessment of land surface temperature and land use/land cover in Langkawi Island

    Science.gov (United States)

    Abu Bakar, Suzana Binti; Pradhan, Biswajeet; Salihu Lay, Usman; Abdullahi, Saleh

    2016-06-01

    This study investigates the relationship between Land Surface Temperature and Land Use/Land Cover in Langkawi Island by using Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI) and Modified Normalized Difference Water Index (MNDWI) qualitatively by using Landsat 7 ETM+ and Landsat 8 (OLI/TIRS) over the period 2002 and 2015. Pixel-based classifiers Maximum Likelihood (MLC) and Support Vector Machine (SVM), has been performed to prepare the Land Use/ Land Cover map (LU/LC) and the result shows that Support Vector Machine (SVM) achieved maximum accuracy with 90% and 90.46% compared to Maximum Likelihood (MLC) classifier with 86.62% and 86.98% respectively. The result revealed that as the impervious surface (built-up /roads) increases, the surface temperature of the area increased. However, land surface temperature decreased in the vegetated areas. Based from the linear regression between LST and NDVI, NDBI and MNDWI, these indices can be used as an indicator to monitor the impact of Land Use/Land Cover on Land Surface Temperature.

  4. Linking oil production to surface subsidence from satellite radar interferometry

    Science.gov (United States)

    Xu, Haibin; Dvorkin, Jack; Nur, Amos

    Land subsidence over the Belridge and Lost Hills oil fields, Southern California, was measured using spaceborne interferometric synthetic aperture radar (InSAR). During the 105-day period between 11/5/95 and 2/17/96, the subsidence in the center of the Lost Hills field reached 15 cm. We assume that this surface subsidence resulted from the vertical shrinkage of the reservoir, which in turn was due to oil production and the resulting pore pressure drop. We model this mechanical effect using an elastic deformation theoretical solution with input constants taken from relevant experiments. The modeled surface deformation matches the InSAR measured values. This result indicates that it is possible, in principle, to monitor hydrocarbon production using satellite-based measurements of earth deformation.

  5. Satellite Sensed Skin Sea Surface Temperature

    Science.gov (United States)

    Donlon, Craig

    1997-01-01

    Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to

  6. Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands

    KAUST Repository

    Rosas, Jorge

    2014-12-01

    Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.

  7. Satellite Monitoring of the Surface Water and Energy Budget in the Central Tibetan Plateau

    Institute of Scientific and Technical Information of China (English)

    YANG Kun; Toshio KOIKE

    2008-01-01

    The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP (Coordinated Enhanced Observing Period)-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system (LDAS-UT) to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.

  8. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, J.F.

    2014-01-01

    Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

  9. Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

  10. Evaluation of BAER surface model for aerosol optical thickness retrieval over land surface

    Directory of Open Access Journals (Sweden)

    Y. S. Chiang

    2012-04-01

    Full Text Available Estimation of surface reflectance is essential for an accurate retrieval of aerosol optical thickness (AOT by satellite remote sensing approach. Due to the variability of surface reflectance over land surfaces, a surface model is required to take into account the crucial factor controlling this variability. In the present study, we attempted to simulate surface reflectance in the short-wave channels with two methods, namely the land cover type dependent method and a two-source linear model. In the two-source linear model, we assumed that the spectral property can be described by a mixture of vegetated and non-vegetated area, and both the normalized difference vegetation index (NDVI, and the vegetation continuous field (VCF was applied to summarize this surface characteristic. By comparing our estimation with surface reflectance data derived from Moderate Resolution Imaging Spectroradiometer (MODIS, it indicated that the land cover type approach did not provide a better estimation because of inhomogeneous land cover pattern and the mixing pixel properties. For the two-source linear method, the study suggested that the use of NDVI as parameterization for vegetation fraction can reflect the spectral behavior of shortwave surface reflectance, despite of some deviation due to the averaging characteristics in our linear combination process. A channel-dependent offset and scalar factor could enhance reflectance estimation and further improve AOT retrieval by the current Bremen AErosol Retrieval (BAER approach.

  11. Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite

    Science.gov (United States)

    Ebtehaj, A. M.; Kummerow, C. D.

    2017-06-01

    Satellites are playing an ever-increasing role in estimating precipitation over remote areas. Improving satellite retrievals of precipitation requires increased understanding of its passive microwave signatures over different land surfaces. Snow-covered surfaces are notoriously difficult to interpret because they exhibit both emission from the land below and scattering from the ice crystals. Using data from the Global Precipitation Measurement (GPM) satellite, we demonstrate that microwave brightness temperatures of rain and snowfall transition from a scattering to an emission regime from summer to winter, due to expansion of less emissive snow cover. Evidence suggests that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The results demonstrate that, using a multifrequency matching method, the probability of snowfall detection can even be higher than rainfall—chiefly because of the information content of the low-frequency channels that respond to the (near) surface temperature.

  12. A comparison of all-weather land surface temperature products

    Science.gov (United States)

    Martins, Joao; Trigo, Isabel F.; Ghilain, Nicolas; Goettche, Frank-M.; Ermida, Sofia; Olesen, Folke-S.; Gellens-Meulenberghs, Françoise; Arboleda, Alirio

    2017-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF, http://landsaf.ipma.pt) has been providing land surface temperature (LST) estimates using SEVIRI/MSG on an operational basis since 2006. The LSA-SAF service has since been extended to provide a wide range of satellite-based quantities over land surfaces, such as emissivity, albedo, radiative fluxes, vegetation state, evapotranspiration, and fire-related variables. Being based on infra-red measurements, the SEVIRI/MSG LST product is limited to clear-sky pixels only. Several all-weather LST products have been proposed by the scientific community either based on microwave observations or using Soil-Vegetation-Atmosphere Transfer models to fill the gaps caused by clouds. The goal of this work is to provide a nearly gap-free operational all-weather LST product and compare these approaches. In order to estimate evapotranspiration and turbulent energy fluxes, the LSA-SAF solves the surface energy budget for each SEVIRI pixel, taking into account the physical and physiological processes occurring in vegetation canopies. This task is accomplished with an adapted SVAT model, which adopts some formulations and parameters of the Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) model operated at the European Center for Medium-range Weather Forecasts (ECMWF), and using: 1) radiative inputs also derived by LSA-SAF, which includes surface albedo, down-welling fluxes and fire radiative power; 2) a land-surface characterization obtained by combining the ECOCLIMAP database with both LSA-SAF vegetation products and the H(ydrology)-SAF snow mask; 3) meteorological fields from ECMWF forecasts interpolated to SEVIRI pixels, and 4) soil moisture derived by the H-SAF and LST from LSA-SAF. A byproduct of the SVAT model is surface skin temperature, which is needed to close the surface energy balance. The model skin temperature corresponds to the radiative temperature of the interface between soil and atmosphere

  13. Evaluation and Monitoring of Jpss Land Surface Temperature Data

    Science.gov (United States)

    Yu, Y.; Yu, P.; Liu, Y.; Csiszar, I. A.

    2016-12-01

    Land Surface Temperature (LST) is one of environmental data records (EDRs) produced operationally through the U.S. Joint Polar Satellite System (JPSS) mission. LST is an important parameter for understanding climate change, modeling the hydrological and biogeochemical cycles, and is a prime candidate for Numerical Weather Prediction (NWP) assimilation models. Recently, the international LST and Emissivity Working Ggroup (ILSTE-WG) is promoting to the inclusion of the LST as essential climate variable (ECV) in the Global Climate Observation System (GCOS) of the Word Meteorological Organization (WMO). At the Center for Satellite Applications and Research (STAR) of National Atmospheric and Oceanic Administration (NOAA), we, are as a science team, are responsible to for the science of JPSS LST production. In this work, we present our activities and accomplishments on the JPSS LST evaluation and monitoring since the launch of the first JPSS satellite, i.e. S-NPP, satellite. Beta version, provisional version, and validated stage 1 version of the S-NPP LST products which were announced in May 2013, July 2014, and March 2015, respectively. Evaluation of the LST products have been performed versus ground measurements and other polar-orbiting satellite LST data (e,g. MODIS LSTs); some results will be illustrated. A daily monitoring system of the JPSS LST production has been developed, which presents daily, weekly and monthly global LST maps and inter-comparison results on the STAR JPSS program website. Further, evaluation of the enterprise LST algorithm for JPSS mission which is in development at STAR currently are presented in this work. Finally, evaluation and monitoring plan of the LST production for the JPSS-1 satellite are also presented.

  14. Land use changes and its impact on land surface temperature of Yancheng City from 2000 to 2009 analysis

    Science.gov (United States)

    Wang, Xinghan

    2014-02-01

    In the paper, based on the technology of remote sensing and geographic information system, and according to the Landsat TM images obtained the land use database and land surface temperature of Yancheng city in the year of 2000 and 2009. Five land use types were identified, namely: farmland, building site, forest and grassland, water, and beach wetland. And then analysis of the urban expansion model based on the Defense Meteorological satellite data. The results show that: (1) In the five kinds of land use types, the largest rate of land use change is beach wetland, which is -8.23, followed by water as -5.17, forest and grassland is 3.27, building site is 2.24, farmland is 0.69. (2) During the 2000-2009, the towns of Yancheng city continuous outward expansion. In the old town, the expansion model is similar to the concentric circles spread to the periphery, but in the new district, which mainly concentrated in the northeast and southeast, the expansion model is re-planning, development and construction. (3) The land use structure change, especially the changes of beach wetland have a largest influence on the land surface temperature of Yancheng city. Among them, the average land surface temperature has increased over 8 degrees. However, the farmland change due to the overall land surface temperature decreased. And the increase of building site, making the urban heat island effect has been enhanced, while the town where the land surface temperature increases in value added in 0 to 5 degrees. At the same time, the water changes, this due to the land surface temperature increases and the added value in the range of 5 to 8 degrees.

  15. Seasonal evaluation of the land surface sheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian regions in Hungary

    NARCIS (Netherlands)

    Wipfler, E.L.; Metselaar, K.; Dam, van J.C.; Feddes, R.A.; Meijgaard, van E.; Ulft, van L.H.; Hurk, van den B.; Zwart, S.J.; Bastiaanssen, W.G.M.

    2011-01-01

    The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of

  16. Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

    2012-01-01

    Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 14% (312 K) over desert and 17% (320 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.52% (26 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 1017 K under the most severe conditions.

  17. Satellite discrimination of snow/cloud surfaces

    Science.gov (United States)

    Crane, R. G.; Anderson, M. R.

    1984-01-01

    Differentiation between cloud cover and snow surfaces using remotely sensed data is complicated by the similarity of their radiative temperatures, and also by their similar reflectances at visible wavelengths. A method of cloud analysis over snow-covered regions is presented, using 1.51-1.63 micron data from an experimental sensor on board a U.S. Air Force Defense Meteorological Satellite Program platform. At these wavelengths, snow appears relatively 'black' while clouds are highly reflective. The spatial structure of the 1.51-1.63 micron reflectivity fields over a continuous snow surface are examined. Plots of mean reflectance against coefficients of variation for 4 x 4 pixel areas reveals a cluster of points have low reflectivity and low variability, corresponding to snow-covered (cloud free) areas, and a similar cluster with high reflectances corresponding to 100 per cent cloud cover. For the case of a single layered cloud, the radiances associated with partially filled fields of view are also inferred.

  18. Land surface processes and Sahel climate

    Science.gov (United States)

    Nicholson, Sharon

    2000-02-01

    This paper examines the question of land surface-atmosphere interactions in the West African Sahel and their role in the interannual variability of rainfall. In the Sahel, mean rainfall decreased by 25-40% between 1931-1960 and 1968-1997; every year in the 1950s was wet, and nearly every year since 1970 has been anomalously dry. Thus the intensity and multiyear persistence of drought conditions are unusual and perhaps unique features of Sahel climate. This article presents arguments for the role of land surface feedback in producing these features and reviews research relevant to land surface processes in the region, such as results from the 1992 Hydrologic Atmospheric Pilot Experiment (HAPEX)-Sahel experiment and recent studies on aerosols and on the issue of desertification in the region, a factor implicated by some as a cause of the changes in rainfall. Included also is a summary of evidence of feedback on meteorological processes, presented from both model results and observations. The reviewed studies demonstrate numerous ways in which the state of the land surface can influence interactions with the atmosphere. Surface hydrology essentially acts to delay and prolong the effects of meteorological drought. Each evaporative component of the surface water balance has its own timescale, with the presence of vegetation affecting the process both by delaying and prolonging the return of soil moisture to the atmosphere but at the same time accelerating the process through the evaporation of canopy-intercepted water. Hence the vegetation structure, including rooting depth, can modulate the land-atmosphere interaction. Such processes take on particular significance in the Sahel, where there is a high degree of recycling of atmospheric moisture and where the meteorological processes from the scale of boundary layer development to mesoscale disturbance generation are strongly influenced by moisture. Simple models of these feedback processes and their various timescales

  19. Inexpensive land-use maps extracted from satellite data

    Science.gov (United States)

    Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.

    1979-01-01

    Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.

  20. Detection of land use and land cover change and land surface temperature in English Bazar urban centre

    Directory of Open Access Journals (Sweden)

    Swades Pal

    2017-06-01

    Full Text Available Present paper tends to capture the impact of land use land cover (LULC on land surface temperature (LST in English Bazar Municipality of Malda District using multi spectral and multi temporal satellite data. Seasonal and temporal LST is extracted in three phases e.g. in 1991, 2010 and 2014. Results show that LST increases 0.070 °C/year and 0.114 °C/year during winter and summer periods respectively and significant LST difference exist over different LULC units. Built up area retains maximum LST in all selected phases. Correlation coefficient among different deriving factors of LST with LST reveals that impervious land maximally control LST (r = 0.62 followed by water bodies and vegetation cover. Even a single land use unit like impervious land water body and vegetation also create differences in LST (R2 of NDBI vs. LST ranges from 0.47 to 0.607; NDVI vs. LST ranges from 0.441 to 0.62. LST is almost co linear with aerial temperature as indicated by significant correlation value (0.44604 for January and 0.658 for April 2014 at 0.01 level of significance and the temperature gap between them ranges from 3.5 °C to 6.5 °C. Such co linearity validates the LST models. The estimated temperature gap is also strongly controlled by LULC. As the LULC pattern is getting changed, its imprint is reflected on LST and air temperature. So, immediate thinking about new urbanism should be adopted, started and implement to arrest the rising temperature and effect of urban heat island.

  1. Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

    Directory of Open Access Journals (Sweden)

    Bayes Ahmed

    2013-11-01

    Full Text Available Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth on LST and consequently to devise appropriate policy measures.

  2. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, ......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed....

  3. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed....

  4. Land cover change impacts on surface ozone: an observation-based study

    Science.gov (United States)

    Zhang, Yi; Lin, Jintai

    2016-04-01

    Ozone air quality is a critical global environmental issue. Although it is clear that industrialization and urbanization has increased surface ozone through enhanced emissions of its precursors, much less is known about the role of changes in land cover and land use. Human activities have substantially altered the global land cover and land use through agriculture, urbanization, deforestation, and afforestation. Changes in Land cover and land use affect the ozone levels by altering soil emissions of nitrogen oxides (NOx), biogenic emissions of volatile organic compounds (VOCs), and dry deposition of ozone itself. This study performs a series of experiments with a chemical transport model based on satellite observation of land types to analyze the influences of changes in land cover/land use and their impact on surface ozone concentration. Our results indicate that land cover change explains 1-2 ppbv of summertime surface ozone increase in the Western United States and 1-6 ppbv of increase in Southern China between 2001 and 2012. This is largely driven by enhanced isoprene emissions and soil NOx emissions. It is also found that land cover change itself elevates summertime surface zone in Canadian coniferous forests by up to 4 ppbv mainly through substantial decreases in ozone dry deposition associated with increased vegetation density in a warmer climate.

  5. Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

    Science.gov (United States)

    Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

    2016-07-01

    Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after

  6. Seasonal variation of surface temperature based on land cover in Ankara

    Directory of Open Access Journals (Sweden)

    İhsan Çiçek

    2013-03-01

    Full Text Available In this study, the seasonal variation of the surface temperature of Ankara urban area and its enviroment have been analyzed by using Landsat 7 image. The Landsat 7 images of each month from 2007 to 2011 have been used to analyze the annually changes of the surface temperature. The land cover of the research area was defined with supervised classification method on the basis of the satellite image belonging to 2008 July. After determining the surface temperatures from 6-1 bands of satellite images, the monthly mean surface temperatures were calculated for land cover classification for the period between 2007 and 2011. Accordşng to the results obtained, the surface temperatures are high in summer and low in winter from the air temperatures. all satellite images were taken at 10:00 am, it is found that urban areas are cooler than rural areas at 10:00 am. Regarding the land cover classification, the water surfaces are the coolest surfaces during the whole year. The warmest areas are the grasslands and dry farming areas. While the parks are warmer than the urban areas during the winter, during the summer they are cooler than artificial land covers. The urban areas with higher building density are the cooler surfaces after water bodies.

  7. Land surface phenology from SPOT VEGETATION time series

    Directory of Open Access Journals (Sweden)

    A. Verger

    2016-12-01

    Full Text Available Land surface phenology from time series of satellite data are expected to contribute to improve the representation of vegetation phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from GEOCLIM-LAI, a global climatology of leaf area index (LAI derived from 1-km SPOT VEGETATION time series for 1999-2010. The calibration with ground measurements showed that the start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The satellite-derived phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests in Europe, cherry in Asia and lilac shrubs in North America showed an overall root mean square error lower than 19 days for the start, end and length of season, and good agreement between the latitudinal gradients of VEGETATION LAI phenology and ground data.

  8. Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey (USGS) has generated land surface form classes for the contiguous United States. These land surface form classes were created as part of...

  9. Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

    2011-01-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  10. Land surface Verification Toolkit (LVT – a generalized framework for land surface model evaluation

    Directory of Open Access Journals (Sweden)

    S. V. Kumar

    2012-02-01

    Full Text Available Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS, it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  11. Land surface Verification Toolkit (LVT – a generalized framework for land surface model evaluation

    Directory of Open Access Journals (Sweden)

    S. V. Kumar

    2012-06-01

    Full Text Available Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS, it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  12. Attitude guidance and simulation with animation of a land-survey satellite motion

    Science.gov (United States)

    Somova, Tatyana

    2017-01-01

    We consider problems of synthesis of the vector spline attitude guidance laws for a land-survey satellite and an in-flight support of the satellite attitude control system with the use of computer animation of its motion. We have presented the results on the efficiency of the developed algorithms.

  13. Land surface phenological responses to land use and climate variation in a changing Central Asia

    Science.gov (United States)

    Kariyeva, Jahan

    During the last few decades Central Asia has experienced widespread changes in land cover and land use following the socio-economic and institutional transformations of the region catalyzed by the USSR collapse in 1991. The decade-long drought events and steadily increasing temperature regimes in the region came on top of these institutional transformations, affecting the long term and landscape scale vegetation responses. This research is based on the need to better understand the potential ecological and policy implications of climate variation and land use practices in the contexts of landscape-scale changes dynamics and variability patterns of land surface phenology responses in Central Asia. The land surface phenology responses -- the spatio-temporal dynamics of terrestrial vegetation derived from the remotely sensed data -- provide measurements linked to the timing of vegetation growth cycles (e.g., start of growing season) and total vegetation productivity over the growing season, which are used as a proxy for the assessment of effects of variations in environmental settings. Local and regional scale assessment of the before and after the USSR collapse vegetation response patterns in the natural and agricultural systems of the Central Asian drylands was conducted to characterize newly emerging links (since 1991) between coupled human and natural systems, e.g., socio-economic and policy drivers of altered land and water use and distribution patterns. Spatio-temporal patterns of bioclimatic responses were examined to determine how phenology is associated with temperature and precipitation in different land use types, including rainfed and irrigated agricultural types. Phenological models were developed to examine relationship between environmental drivers and effect of their altitudinal and latitudinal gradients on the broad-scale vegetation response patterns in non-cropland ecosystems of the desert, steppe, and mountainous regional landscapes of Central Asia

  14. 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.

  15. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the di

  16. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the

  17. Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

    Science.gov (United States)

    Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

    2004-01-01

    Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

  18. Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

    2013-01-01

    Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

  19. Complex land surface phenologies of moisture status

    Science.gov (United States)

    Henebry, G. M.; Doubkova, M.

    2006-12-01

    Making cross-scale linkages from experimental plots or flux tower footprints to regional and continental extents is made difficult by disparate spatial and temporal scales between process and observation. While exchanges between the vegetated land surface and the atmospheric boundary layer are continual, sampling and observations are typically intermittent in time and limited across space. Remote sensing of reflected sunlight has proven useful to track ecological dynamics. These observations are, however, restricted to daytime and often obscured by cloud cover, necessitating production of multi-date composites. The current generation of passive microwave radiometers can observe the land surface both day and night regardless of cloudiness, albeit at a spatial resolution coarser than typically used in ecological remote sensing. Datastreams from the AMSR-E (Advanced Microwave Scanning Radiometer-EOS) onboard NASA's Aqua platform are processed daily at the National Snow and Ice Data Center (NSIDC) into various products, including global retrievals of surficial soil moisture and vegetation water content based on microwave brightness temperatures observed at multiple frequencies. Due to sensor orbit and swath width, gaps occur at the lower latitudes in daily products. We have further processed the product-streams from the descending (01:30) and ascending (13:30) orbits into separate smoothed daily composites using an 8-day retrospective moving average. Of particular interest for synoptic ecology is the diel difference in vegetation water content. When the difference between the pre-dawn and the early afternoon values is positive, it suggests that the supply of moisture from the root zone is not able to keep pace with evapotranspiration during the day, but the soil and canopy moisture equalize overnight. Time series of the diel difference show rapid changes in moisture status in response to precipitation events and dry spells. What constitutes the appropriate baseline

  20. Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

    Directory of Open Access Journals (Sweden)

    Ying Qu

    2015-01-01

    Full Text Available Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces, gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

  1. Integrative inversion of land surface component temperature

    Institute of Scientific and Technical Information of China (English)

    FAN Wenjie; XU Xiru

    2005-01-01

    In this paper, the row winter wheat was selected as the example to study the component temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evidently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field experiment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inversion stability of components temperature. Just two parameters were sufficient for accurate atmospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric transmittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

  2. The development of a land use inventory for regional planning using satellite imagery

    Science.gov (United States)

    Hessling, A. H.; Mara, T. G.

    1975-01-01

    Water quality planning in Ohio, Kentucky, and Indiana is reviewed in terms of use of land use data and satellite imagery. A land use inventory applicable to water quality planning and developed through computer processing of LANDSAT-1 imagery is described.

  3. Mapping land cover from satellite images: A basic, low cost approach

    Science.gov (United States)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

    1978-01-01

    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  4. Forecasting distributions of large federal-lands fires utilizing satellite and gridded weather information

    Science.gov (United States)

    Preisler, H.K.; Burgan, R.E.; Eidenshink, J.C.; Klaver, Jacqueline M.; Klaver, R.W.

    2009-01-01

    The current study presents a statistical model for assessing the skill of fire danger indices and for forecasting the distribution of the expected numbers of large fires over a given region and for the upcoming week. The procedure permits development of daily maps that forecast, for the forthcoming week and within federal lands, percentiles of the distributions of (i) number of ignitions; (ii) number of fires above a given size; (iii) conditional probabilities of fires greater than a specified size, given ignition. As an illustration, we used the methods to study the skill of the Fire Potential Index an index that incorporates satellite and surface observations to map fire potential at a national scale in forecasting distributions of large fires. ?? 2009 IAWF.

  5. Exploring Land use and Land cover change in the mining areas of Wa East District, Ghana using Satellite Imagery

    Science.gov (United States)

    Basommi, Prosper Laari; Guan, Qingfeng; Cheng, Dandan

    2015-11-01

    Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index valueswere used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

  6. AATSR Land Surface Temperature Product Validation Using Ground Measurements in China and Implications for SLSTR

    Science.gov (United States)

    Zhou, Ji; Zmuda, Andy; Desnos, Yves-Louis; Ma, Jin

    2016-08-01

    Land surface temperature (LST) is one of the most important parameters at the interface between the earth's surface and the atmosphere. It acts as a sensitive indicator of climate change and is an essential input parameter for land surface models. Because of the intense variability at different spatial and temporal scales, satellite remote sensing provides the sole opportunity to acquire LSTs over large regions. Validation of the LST products is an necessary step before their applications conducted by scientific community and it is essential for the developers to improve the LST products.

  7. Toward Transfer Functions for Land Surface Phenologies

    Science.gov (United States)

    Henebry, G. M.

    2010-12-01

    A key problem in projecting future landscapes is simulating the associated land surface phenologies (or LSPs). A recent study of land surface models concluded that the representations of crop phenologies among the models diverged sufficiently to impede a useful intercomparison of simulation results from their associated climate models. Grassland phenologies are far more complicated than cropland phenologies due to multiple forcing factors, photosynthetic pathways (C3 vs C4), and spatial heterogeneities in both resource availabilities and land management practices. Furthermore, many tallgrass species (such as switchgrass) are widely distributed across temperature, but not moisture, gradients, resulting in significant ecotypic variation across the species' geographic range. Thus, how feasible is "transplanting" tallgrass LSPs across isotherms—but along isohyets—to simulate a shift in cultivation from maize-soy to switchgrass? Prior work has shown a quadratic model can provide a parsimonious link between a Normalized Difference Vegetation Index (or NDVI) time series and thermal time, measured in terms of accumulated growing degree-days (or AGDD). Moreover, the thermal time to peak NDVI (or TTP) is a simple function of the parameter coefficients of fitted model. I fitted quadratic models to MODIS NDVI and weather station data at multiple sites across the Northern Great Plains over ten growing seasons, 2000-2009. There is a strong latitudinal gradient in TTP that results in part from a quasi-linear gradient in accumulated daylight hours (or ADH) between 30 and 50 degrees north. However, AGDD improves upon ADH by providing sensitivity to the variability of growing season weather. In the quadratic parameter coefficients there is a geographic pattern apparent as a function of TTP, although it is more variable at shorter TTPs. Using these patterns, an LSP transfer function was implemented along a latitudinal transect to simulate switchgrass cultivation in areas now

  8. Need for, and financial feasibility of, satellite-aided land mobile communications

    Science.gov (United States)

    Castruccio, P. A.; Marantz, C. S.; Freibaum, J.

    Questions regarding the role of a mobile-satellite system in augmenting the terrestrial communications system are considered, and a market assessment study is discussed. Aspects of an investment analysis are examined, taking into account a three phase financial study of four postulated land Mobile Satellite Service (LMSS) systems, project profitability evaluation methods, risk analysis methods, financial projections, potential investor acceptance standards, and a risk analysis. It is concluded that a satellite augmented terrestrial mobile service appears to be economically and technically superior to a service depending exclusively on terrestrial systems. The interest in the Mobile Satellite Service is found to be worldwide, and the ground equipment market is potentially large.

  9. Assessing the Impacts of Urbanization-Associated Land Use/Cover Change on Land Surface Temperature and Surface Moisture: A Case Study in the Midwestern United States

    Directory of Open Access Journals (Sweden)

    Yitong Jiang

    2015-04-01

    Full Text Available Urbanization-associated land use and land cover (LULC changes lead to modifications of surface microclimatic and hydrological conditions, including the formation of urban heat islands and changes in surface runoff pattern. The goal of the paper is to investigate the changes of biophysical variables due to urbanization induced LULC changes in Indianapolis, USA, from 2001 to 2006. The biophysical parameters analyzed included Land Surface Temperature (LST, fractional vegetation cover, Normalized Difference Water Index (NDWI, impervious fractions evaporative fraction, and soil moisture. Land cover classification and changes and impervious fractions were obtained from the National Land Cover Database of 2001 and 2006. The Temperature-Vegetation Index (TVX space was created to analyze how these satellite-derived biophysical parameters change during urbanization. The results showed that the general trend of pixel migration in response to the LULC changes was from the areas of low temperature, dense vegetation cover, and high surface moisture conditions to the areas of high temperature, sparse vegetation cover, and low surface moisture condition in the TVX space. Analyses of the T-soil moisture and T-NDWI spaces revealed similar changed patterns. The rate of change in LST, vegetation cover, and moisture varied with LULC type and percent imperviousness. Compared to conversion from cultivated to residential land, the change from forest to commercial land altered LST and moisture more intensively. Compared to the area changed from cultivated to residential, the area changed from forest to commercial altered 48% more in fractional vegetation cover, 71% more in LST, and 15% more in soil moisture Soil moisture and NDWI were both tested as measures of surface moisture in the urban areas. NDWI was proven to be a useful measure of vegetation liquid water and was more sensitive to the land cover changes comparing to soil moisture. From a change forest to

  10. Towards the Consideration of Surface and Environment variables for a Microwave Precipitation Algorithm Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.; Guch, I.

    2014-12-01

    Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperatures characteristics similar to precipitation Ongoing work by NASA's GPM microwave radiometer team is constructing databases for the GPROF algorithm through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The at-launch database focuses on stratification by emissivity class, surface temperature and total precipitable water (TPW). We'll perform sensitivity studies to determine the potential role of environmental factors such as land surface temperature, surface elevation, and relative humidity and storm morphology such as storm vertical structure, height, and ice thickness to improve precipitation estimation over land, including rain and snow. In other words, what information outside of the satellite radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate

  11. Production of a combined land surface data set and its use to assess land-atmosphere coupling in China

    Science.gov (United States)

    Li, Mingxing; Ma, Zhuguo; Gu, Hongping; Yang, Qing; Zheng, Ziyan

    2017-01-01

    Land-atmosphere interactions play an important role in shaping regional climate and its variability. In land-atmosphere coupling study, a fundamental challenge is data limitation, such as the sparsity of long-term land observations and uncertainty in individual model simulations. This study produces a multisource combined land surface data set using a Bayesian model averaging method, for the assessment of land-atmosphere coupling across China. We employ the newly produced soil moisture and evapotranspiration, together with satellite-derived soil moisture and observation-based evapotranspiration to assess spatiotemporal characteristics of the coupling with observed precipitation and temperature. We also define a coupling index to identify region-specific regimes. The results have shown that strong coupling occurs over northern China, particularly in the transition zone between dry and wet climate. Here summer coupling is dominated by land evaporative water storage. Over the southern humid regions and regions at high altitudes, land-atmosphere coupling in summer is characterized by an energy-limited regime. Estimated coupling strengths vary with season and variable used. Precipitation-related couplings are generally stronger in summer; temperature-related couplings are stronger in summer in dry areas but stronger in winter in humid areas. These findings provide a multisource combined representation and cross validation of spatial and temporal characteristics of land-atmosphere coupling across China. The implications are that northern China is a critical region for climate change/variability impact and adaptation assessment.

  12. LDAS-Monde: Global scale satellite driven Land Data Assimilation System based on SURFEX modelling platform

    Science.gov (United States)

    Munier, Simon; Albergel, Clément; Leroux, Delphine; Calvet, Jean-Christophe

    2017-04-01

    In the past decades, large efforts have been made to improve our understanding of the dynamics of the terrestrial water cycle, including vertical and horizontal water fluxes as well as water stored in the biosphere. The soil water content is closely related to the development of the vegetation, which is in turn closely related to the water and energy exchanges with the atmosphere (through evapotranspiration) as well as to carbon fluxes. Land Surface Models (LSMs) are usually designed to represent biogeophysical variables, such as Surface and Root Zone Soil Moisture (SSM, RZSM) or Leaf Area Index (LAI), in order to simulate water, energy and carbon fluxes at the interface between land and atmosphere. With the recent increase of satellite missions and derived products, LSMs can benefit from Earth Observations via Data Assimilation systems to improve their representation of different biogeophysical variables. This study, which is part of the eartH2Observe European project (http://www.earth2observe.eu), presents LDAS-Monde, a global Land Data Assimilation System using an implementation of the Simplified Extended Kalman Filter (SEKF) in the Météo-France's modelling platform (SURFEX). SURFEX is based on the coupling of the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (CTRIP). Two global operational datasets derived from satellite observations are assimilated simultaneously: (i) SSM from the ESA Climate Change Initiative and (ii) LAI from the Copernicus Global Land Service project. Atmospheric forcing used in SURFEX are derived from the ERA-Interim reanalysis and corrected from GPCC precipitations. The simulations are conducted at the global scale at a 1 degree spatial resolution over the period 2000-2014. An analysis of the model sensitivity to the assimilated observations is performed over

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

    Science.gov (United States)

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

    2016-09-01

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

  14. eMODIS Global Land Surface Temperature Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) Aqua Land Surface Temperature (LST) product is similar to the Land Processes Distributed Active...

  15. A parsimonious land data assimilation system for the SMAP/GPM satellite era

    Science.gov (United States)

    Land data assimilation systems typically require complex parameterizations in order to: define required observation operators, quantify observing/forecasting errors and calibrate a land surface assimilation model. These parameters are commonly defined in an arbitrary manner and, if poorly specified,...

  16. Human-induced greening of the northern extratropical land surface

    Science.gov (United States)

    Mao, Jiafu; Ribes, Aurélien; Yan, Binyan; Shi, Xiaoying; Thornton, Peter E.; Séférian, Roland; Ciais, Philippe; Myneni, Ranga B.; Douville, Hervé; Piao, Shilong; Zhu, Zaichun; Dickinson, Robert E.; Dai, Yongjiu; Ricciuto, Daniel M.; Jin, Mingzhou; Hoffman, Forrest M.; Wang, Bin; Huang, Mengtian; Lian, Xu

    2016-10-01

    Significant land greening in the northern extratropical latitudes (NEL) has been documented through satellite observations during the past three decades. This enhanced vegetation growth has broad implications for surface energy, water and carbon budgets, and ecosystem services across multiple scales. Discernible human impacts on the Earth's climate system have been revealed by using statistical frameworks of detection-attribution. These impacts, however, were not previously identified on the NEL greening signal, owing to the lack of long-term observational records, possible bias of satellite data, different algorithms used to calculate vegetation greenness, and the lack of suitable simulations from coupled Earth system models (ESMs). Here we have overcome these challenges to attribute recent changes in NEL vegetation activity. We used two 30-year-long remote-sensing-based leaf area index (LAI) data sets, simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm. Our findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. These results provide the first clear evidence of a discernible human fingerprint on physiological vegetation changes other than phenology and range shifts.

  17. Spatial Aggregation of Land Surface Characteristics: Impact of resolution of remote sensing data on land surface modelling

    NARCIS (Netherlands)

    Pelgrum, H.

    2000-01-01

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo, surface te

  18. Bureau of Land Management Surface Land Ownership (2014)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — These data were collected by the U.S. Bureau of Land Management (BLM) in New Mexico at both the New Mexico State Office and at the various field offices. This...

  19. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data.

    Science.gov (United States)

    Soffianian, Alireza; Madanian, Maliheh

    2015-08-01

    Changes in land cover and land use reveal the effects of natural and human processes on the Earth's surface. These changes are predicted to exert the greatest environmental impacts in the upcoming decades. The purpose of the present study was to monitor land cover changes using Multispectral Scanner Sensor (MSS) and multitemporal Landsat Thematic Mapper (TM) data from the counties of Isfahan Province, Iran, during 1975, 1990, and 2010. The maximum likelihood supervised classification method was applied to map land cover. Postclassification change detection technique was also used to produce change images through cross-tabulation. Classification results were improved using ancillary data, visual interpretation, and local knowledge about the area. The overall accuracy of land cover change maps ranged from 88 to 90.6%. Kappa coefficients associated with the classification were 0.81 for 1975, 0.84 for 1990, and 0.85 for 2010 images. This study monitored changes related to conversion of agricultural land to impervious surfaces, undeveloped land to agricultural land, agricultural land to impervious surfaces, and undeveloped land to impervious surfaces. The analyses of land cover changes during the study period revealed the significant development of impervious surfaces in counties of Isfahan Province as a result of population growth, traffic conditions, and industrialization. The image classification indicated that agricultural lands increased from 2520.96 km(2) in 1975 to 4103.85 km(2) in 2010. These land cover changes were evaluated in different counties of Isfahan Province.

  20. Analysis of the Effects of Different Land Use and Land Cover Classification on Surface Meteorological Variables using WRF Model

    Science.gov (United States)

    Sati, A. P.

    2015-12-01

    The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes across the globe. Most of the urban areas being developed today are on the expense of agricultural or barren lands and the changes result from various practices such as deforestation, changing agriculture practices, rapid expansion of urban centers etc.For modeling applications, classification of land use is important and periodic updates of land cover are necessary to capture change due to LULC changes.Updated land cover and land use data derived from satellites offer the possibility of consistent and regularly collected information on LULC. In this study we explore the application of Landsat based LULC classification inWeather Research and Forecasting (WRF) model in predicting the meteorology over Delhi, India. The supervised classification of Landsat 8 imagery over Delhi region is performed which update the urban extent as well as other Land use for the region. WRF model simulations are performed using LULC classification from Landsat data, United States Geological Survey (USGS) and Moderate Resolution Imaging Spectroradiometer (MODIS) for various meteorological parameters. Modifications in LULC showed a significant effect on various surface meteorological parameters such as temperature, humidity, wind circulations and other underlying surface parameters. There is a considerable improvement in the spatial distribution of the surface meteorological parameters with correction in input LULC. The study demonstrates the improved LULC classification from Landsat data than currently in vogue and their potential to improve numerical weather simulations especially for expanding urban areas.The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes

  1. The international surface temperature initiative's global land surface databank

    Science.gov (United States)

    Lawrimore, J. H.; Rennie, J.; Gambi de Almeida, W.; Christy, J.; Flannery, M.; Gleason, B.; Klein-Tank, A.; Mhanda, A.; Ishihara, K.; Lister, D.; Menne, M. J.; Razuvaev, V.; Renom, M.; Rusticucci, M.; Tandy, J.; Thorne, P. W.; Worley, S.

    2013-09-01

    The International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.

  2. Global mobile satellite communications theory for maritime, land and aeronautical applications

    CERN Document Server

    Ilčev, Stojče Dimov

    2017-01-01

    This book discusses current theory regarding global mobile satellite communications (GMSC) for maritime, land (road and rail), and aeronautical applications. It covers how these can enable connections between moving objects such as ships, road and rail vehicles and aircrafts on one hand, and on the other ground telecommunications subscribers through the medium of communications satellites, ground earth stations, Terrestrial Telecommunication Networks (TTN), Internet Service Providers (ISP) and other wireless and landline telecommunications providers. This new edition covers new developments and initiatives that have resulted in land and aeronautical applications and the introduction of new satellite constellations in non-geostationary orbits and projects of new hybrid satellite constellations. The book presents current GMSC trends, mobile system concepts and network architecture using a simple mode of style with understandable technical information, characteristics, graphics, illustrations and mathematics equ...

  3. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  4. Impact of sea surface temperature on satellite retrieval of sea surface salinity

    Science.gov (United States)

    Jin, Xuchen; Zhu, Qiankun; He, Xianqiang; Chen, Peng; Wang, Difeng; Hao, Zengzhou; Huang, Haiqing

    2016-10-01

    Currently, global sea surface salinity (SSS) can be retrieved by the satellite microwave radiometer onboard the satellite, such as the Soil Moisture and Ocean Salinity(SMOS) and the Aqurius. SMOS is an Earth Explorer Opportunity Mission from the European Space Agency(ESA). It was launched at a sun-synchronous orbit in 2009 and one of the payloads is called MIRAS(Microwave Imaging Radiometer using Aperture Synthesis), which is the first interferometric microwave radiometer designed for observing SSS at L-band(1.41 GHz).The foundation of the salinity retrieval by microwave radiometer is that the sea surface radiance at L-band has the most suitable sensitivity with the variation of the salinity. It is well known that the sensitivity of brightness temperatures(TB) to SSS depends on the sea surface temperature (SST), but the quantitative impact of the SST on the satellite retrieval of the SSS is still poorly known. In this study, we investigate the impact of the SST on the accuracy of salinity retrieval from the SMOS. First of all, The dielectric constant model proposed by Klein and Swift has been used to estimate the vertically and horizontally polarized brightness temperatures(TV and TH) of a smooth sea water surface at L-band and derive the derivatives of TV and TH as a function of SSS to show the relative sensitivity at 45° incident angle. Then, we use the GAM(generalized additive model) method to evaluate the association between the satellite-measured brightness temperature and in-situ SSS at different SST. Moreover, the satellite-derived SSS from the SMOS is validated using the ARGO data to assess the RMSE(root mean squared error). We compare the SMOS SSS and ARGO SSS over two regions of Pacific ocean far from land and ice under different SST. The RMSE of retrieved SSS at different SST have been estimated. Our results showed that SST is one of the most significant factors affecting the accuracy of SSS retrieval. The satellite-measured brightness temperature has a

  5. Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

    Science.gov (United States)

    Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

    1997-01-01

    variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

  6. Visual interpretation of ASTER satellite data, Part II: Land use mapping in Mpumalanga,South Africa

    Directory of Open Access Journals (Sweden)

    Elna van Niekerk

    2007-09-01

    Full Text Available Since the initiation in 1960 of the era of satellite remote sensing to detect the different characteristics of the earth, a powerful tool was created to aid researchers. Many land-use studies were undertaken using Landsat MSS, Landsat TM and ETM, as well as SPOT satellite data. The application of these data to the mapping of land use and land cover at smaller scales was constrained by the limited spectral and/or spatial resolution of the data provided by these satellite sensors. In view of the relatively high cost of SPOT data, and uncertainty regarding the future continuation of the Landsat series, alternative data sources need to be investigated. In the absence of published previous research on this issue in South Africa, the purpose of this article is to investigate the value of visual interpretation of ASTER satellite images for the identification and mapping of land-use in an area in South Africa. The study area is situated in Mpumalanga, in the area of Witbank, around the Witbank and Doorndraai dams. This area is characterised by a variety of urban, rural and industrial land uses. Digital image processing of one Landsat 5 TM, one Landsat 7 ETM and one ASTER satellite image was undertaken, including atmospheric correction and georeferencing, natural colour composites, photo infrared colour composites (or false colour satellite images, band ratios, Normalised Difference Indices, as well as the Brightness, Greenness and Wetness Indices. The efficacy with which land use could be identified through the visual interpretation of the processed Landsat 5 TM, Landsat 7 TM and ASTER satellite images was compared. The published 1:50 000 topographical maps of the area were used for the purpose of initial verification. Findings of the visual interpretation process were verified by field visits to the study area. The study found that the ASTER satellite data produced clearer results and therefore have a higher mapping ability and capacity than the

  7. Enhancing the representation of subgrid land surface characteristics in land surface models

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2013-03-01

    Full Text Available Land surface heterogeneity has long been recognized as important to represent in the land surface models. In most existing land surface models, the spatial variability of surface cover is represented as subgrid composition of multiple surface cover types. In this study, we developed a new subgrid classification method (SGC that accounts for the topographic variability of the vegetation cover. Each model grid cell was represented with a number of elevation classes and each elevation class was further described by a number of vegetation types. The numbers of elevation classes and vegetation types were variable and optimized for each model grid so that the spatial variability of both elevation and vegetation can be reasonably explained given a pre-determined total number of classes. The subgrid structure of the Community Land Model (CLM was used as an example to illustrate the newly developed method in this study. With similar computational burden as the current subgrid vegetation representation in CLM, the new method is able to explain at least 80% of the total subgrid Plant Functional Types (PFTs and greatly reduced the variations of elevation within each subgrid class compared to the baseline method where a single elevation class is assigned to each subgrid PFT. The new method was also evaluated against two other subgrid methods (SGC1 and SGC2 that assigned fixed numbers of elevation and vegetation classes for each model grid with different perspectives of surface cover classification. Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0° and 2.0° with three maximum-allowed total number of classes Nclass of 24, 18 and 12 representing different computational burdens over the North America (NA continent, the new method showed variable performances compared to the SGC1 and SGC2 methods. However, the advantage of the SGC method over the other two methods clearly emerged at coarser model resolutions and with moderate computational

  8. Land-mobile-satellite fade measurements in Australia

    Science.gov (United States)

    Vogel, Wolfhard J.; Goldhirsh, Julius; Hase, Yoshihiro

    1992-01-01

    Attenuation measurements were implemented at L-band (1.5 GHz) in southeastern Australia during an 11-day period in October 1988 as part of a continuing examination of the propagation effects due to roadside trees and terrain for mobile-satellite service. Beacon transmissions from the geostationary ETS-V and IPORS satellites were observed. The Australian campaign expanded to another continent our Mobile Satellite Service data base of measurements executed in the eastern and southwestern United States regions. An empirical fade distribution model based on U.S. data predicted the Australian results with errors generally less than 1 dB in the 1-20 percent probability region. Directive antennas are shown to suffer deeper fades under severe shadowing conditions (3 dB excess at 4 percent), the equal-probability isolation between co- and cross-polarized transmissions deteriorated to 10 dB at the 5 dB fade level, and antenna diversity reception may reduce unavailability of the system by a factor of 2-8.

  9. Revising Hydrology of a Land Surface Model

    Science.gov (United States)

    Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

    2015-04-01

    Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

  10. Mycorrhizal fungi and global land surface models?

    Science.gov (United States)

    Brzostek, E. R.; Fisher, J. B.; Shi, M.; Phillips, R.

    2013-12-01

    In the current generation of Land Surface Models (LSMs), the representation of coupled carbon (C) and nutrient cycles does not account for allocation of C by plants to mycorrhizal fungi in exchange for limiting nutrients. Given that the amount of C transferred to mycorrhizae can exceed 20% of net primary production (NPP), mycorrhizae can supply over half of the nitrogen (N) needed to support NPP, and that large majority of plants form associations with mycorrhizae; integrating these mechanisms into LSMs may significantly alter our understanding of the role of the terrestrial biosphere in mitigating climate change. Here, we present results from the integration of a mycorrhizal framework into a cutting-edge global plant nitrogen model -- Fixation & Uptake of Nitrogen (FUN; Fisher et al., 2010) -- that can be coupled into existing LSMs. In this mycorrhizal framework, the C cost of N acquisition varies as a function of mycorrhizal type with: (1) plants that support arbuscular mycorrhizae (AM) benefiting when N is plentiful and (2) plants that support ectomycorrhizae (ECM) benefiting when N is limiting. At the plot scale (15 x 15m), the My-FUN model improved predictions of retranslocation, N uptake, and the amount of C transferred into the soil relative to the base model across 45 plots that vary in mycorrhizal type in Indiana, USA. At the ecosystem scale, when we coupled this new framework into the Community Land Model (CLM-CN), the model estimated lower C uptake than the base model and more accurately predicted C uptake at the Morgan Monroe State Forest AmeriFlux site. These results suggest that the inclusion of a mycorrhizal framework into LSMs will enhance our ability to predict feedbacks between global change and the terrestrial biosphere.

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

    Science.gov (United States)

    Arcidiancono, Antonio

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

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

    Science.gov (United States)

    Arcidiancono, Antonio

    1990-01-01

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

  13. Monitoring Surface Climate With its Emissivity Derived From Satellite Measurements

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

    2012-01-01

    Satellite thermal infrared (IR) spectral emissivity data have been shown to be significant for atmospheric research and monitoring the Earth fs environment. Long-term and large-scale observations needed for global monitoring and research can be supplied by satellite-based remote sensing. Presented here is the global surface IR emissivity data retrieved from the last 5 years of Infrared Atmospheric Sounding Interferometer (IASI) measurements observed from the MetOp-A satellite. Monthly mean surface properties (i.e., skin temperature T(sub s) and emissivity spectra epsilon(sub v) with a spatial resolution of 0.5x0.5-degrees latitude-longitude are produced to monitor seasonal and inter-annual variations. We demonstrate that surface epsilon(sub v) and T(sub s) retrieved with IASI measurements can be used to assist in monitoring surface weather and surface climate change. Surface epsilon(sub v) together with T(sub s) from current and future operational satellites can be utilized as a means of long-term and large-scale monitoring of Earth 's surface weather environment and associated changes.

  14. Characterizing the relationship between land use land cover change and land surface temperature

    Science.gov (United States)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  15. Bureau of Land Management Surface Land Ownership (2012)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — These data was collected by the U.S. Bureau of Land Management (BLM) in New Mexico at both the New Mexico State Office and at the various field offices. This dataset...

  16. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land

    Directory of Open Access Journals (Sweden)

    Feng Gao

    2012-10-01

    Full Text Available Thermal infrared (TIR imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST and Normalized Difference Vegetation Index (NDVI developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that

  17. Improving land surface models with FLUXNET data

    Directory of Open Access Journals (Sweden)

    Y. -P. Wang

    2009-07-01

    Full Text Available There is a growing consensus that land surface models (LSMs that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for "fusing" (i.e. linking LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF. MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent and orthogonal data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs from MDF can be used to interpret model validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT – we would expect similar parameter

  18. Improving land surface models with FLUXNET data

    Directory of Open Access Journals (Sweden)

    M. Williams

    2009-03-01

    Full Text Available There is a growing consensus that land surface models (LSMs that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for fusing LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF. MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs from MDF can be used to interpret model process validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT – we would expect similar parameter estimates among sites

  19. Detecting surface geostrophic currents using wavelet filter from satellite geodesy

    Institute of Scientific and Technical Information of China (English)

    HSU; HouTse

    2007-01-01

    According to the features of spatial spectrum of the dynamic ocean topography (DOT),wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96),combining an altimetry-derived mean sea surface height model (KMSS04),two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter,and the DOT models asso-ciated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global,Kuroshio and equatorial Pacific regions with that from oceanography,and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale,the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography,which indicates that ocean currents detected by satellite measurement have reached relatively high precision.

  20. Detecting surface geostrophic currents using wavelet filter from satellite geodesy

    Institute of Scientific and Technical Information of China (English)

    ZHANG ZiZhan; LU Yang; HSU HouTse

    2007-01-01

    According to the features of spatial spectrum of the dynamic ocean topography (DOT), wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96), combining an altimetry-derived mean sea surface height model (KMSS04), two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter, and the DOT models associated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global, Kuroshio and equatorial Pacific regions with that from oceanography, and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale, the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography, which indicates that ocean currents detected by satellite measurement have reached relatively high precision.

  1. On the sensitivity of Land Surface Temperature estimates in arid irrigated lands using MODTRAN

    KAUST Repository

    Rosas, Jorge

    2015-11-29

    Land surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of evapotranspiration (ET) and surface moisture status. However, in order to retrieve the ET with an accuracy approaching 10%, LST should be retrieved to within 1 ◦C or better, disregarding other elements of uncertainty. The removal of atmospheric effects is key towards achieving a precise estimation of LST and it requires detailed information on water vapor. The Thermal Infrared Sensor (TIRS) onboard Landsat 8 captures data in two long wave thermal bands with 100-meter resolution. However, the US Geological Survey has reported a calibration problem of TIRS bands caused by stray light, resulting in a higher bias in one of its two bands (4% in band 11, 2% in band 10). Therefore, split-window algorithms for the estimation of LST might not be reliable. Our work will focus on the impact of using different atmospheric profiles (e.g. weather prediction models, satellite) for the estimation of LST derived from MODTRAN by using one of the TIRS bands onboard Landsat 8 (band 10). Sites with in-situ measurements of LST are used as evaluation sources. Comparisons between the measured LST and LST derived based on different atmospheric profile inputs to MODTRAN are carried out from 2 Landsat-overpass days (DOY 153 and 160 2015). Preliminary results show a mean absolute error of around 3 ◦C between in-situ and estimated LST over two different crops (alfalfa and carrot) and bare soil.

  2. Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model

    Science.gov (United States)

    Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.

    2017-03-01

    This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.

  3. Afforestation in China cools local land surface temperature.

    Science.gov (United States)

    Peng, Shu-Shi; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Zhou, Liming; Li, Laurent Z X; Myneni, Ranga B; Yin, Yi; Zeng, Hui

    2014-02-25

    China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.

  4. CARBON SEQUESTRATION ON SURFACE MINE LANDS

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2003-10-30

    The 2002-2003 Department of Energy plantings amounted to 164 acres containing 111,520 tree seedlings in eastern and western Kentucky. Data gathered on these trees included an inventory to determine survival of all planted species. A sub-sample of seedlings was selected to assess the height and diameter of individual species of seedlings established. Additional efforts involved collection of soil sample and litter samples, analysis of herbaceous ground cover from vegetation clip plots and leaf area on each tree species, and development of tissue collections. All areas were sampled for penetration resistance, penetration depth (or depth to refusal), and bulk density at various depths. Rain fall events and flow rates were recorded. The water quality of runoff samples involved the determination of total and settleable solids and particle size distribution. A study was initiated that will focus on the colonization of small mammals from forest edges to various areas located on reclaimed surface mines. This effort will provide a better understanding of the role small mammals and birds have in the establishment of plant communities on mine lands that will be useful in developing and improving reclamation techniques.

  5. Satellite remote sensing of ultraviolet irradiance on the ocean surface

    Institute of Scientific and Technical Information of China (English)

    LI Teng; PAN Delu; BAI Yan; LI Gang; HE Xianqiang; CHEN Chen-Tung Arthur; GAO Kunshan; LIU Dong; LEI Hui

    2015-01-01

    Ultraviolet (UV) radiation has a significant influence on marine biological processes and primary productivity;however, the existing ocean color satellite sensors seldom contain UV bands. A look-up table of wavelength-integrated UV irradiance (280–400 nm) on the sea surface is established using the coupled ocean atmosphere radiative transfer (COART) model. On the basis of the look-up table, the distributions of the UV irradiance at middle and low latitudes are inversed by using the satellite-derived atmospheric products from the Aqua satellite, including aerosol optical thickness at 550 nm, ozone content, liquid water path, and the total precipitable water. The validation results show that the mean relative difference of the 10 d rolling averaged UV irradiance between the satellite retrieval and field observations is 8.20% at the time of satellite passing and 13.95% for the daily dose of UV. The monthly-averaged UV irradiance and daily dose of UV retrieved by satellite data show a good correlation with thein situ data, with mean relative differences of 6.87% and 8.43%, respectively. The sensitivity analysis of satellite inputs is conducted. The liquid water path representing the condition of cloud has the highest effect on the retrieval of the UV irradiance, while ozone and aerosol have relatively lesser effect. The influence of the total precipitable water is not significant. On the basis of the satellite-derived UV irradiance on the sea surface, a preliminary simple estimation of ultraviolet radiation’s effects on the global marine primary productivity is presented, and the results reveal that ultraviolet radiation has a non-negligible effect on the estimation of the marine primary productivity.

  6. Satellite monitoring of sea surface pollution

    Science.gov (United States)

    Fielder, G.; Telfer, D. J. (Principal Investigator)

    1979-01-01

    The author has identified the following significant results. Image processing techniques developed are well adapted to the exploration and isolation of local areas which exhibit small temperature differences between themselves and their surroundings. In the worst case of imagery of small areal extent of sea surface having no coastal boundary in the area, there is yet no method of distinguishing unambiguously an oil spill from fog, cloud, the effect produced by shallow sediments, or the effects of naturally occuring thermal fronts. In the case of uniform slicks of liquid North Sea oil in still air, laboratory simulation experiments show that, for oil thicknesses in excess of 1 or 2 mm, there is, under equilibrium conditions, little dependence of oil surface temperature on the thickness of the oil layer. The surface temperature of oil is consistently higher than that of water, the difference being about 1 K at low values of relative humidity, but tending to increase as the relative humidity increases.

  7. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    CERN Document Server

    Ruescas, Ana Belen; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). In this paper we explain the implementation in the Basic ENVISAT Toolbox for (A)ATSR and MERIS (BEAM) and the use of one LST algorithm developed in the framework of the Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project. The LST algorithm is based on the split-window technique with an explicit dependence on the surface emissivity. Performance of the methodology is assessed by using MEdium Resolution Imaging Spectrometer/Advanced Alo...

  8. Low gain and steerable vehicle antennas for communications with land mobile satellite

    Science.gov (United States)

    Woo, K.

    1982-01-01

    Current development activities at JPL for ground mobile vehicle antennas to be used with the Land Mobile Satellite Service (LMSS) system are described. Both low gain and electronically steerable high gain type antennas are discussed in terms of their design concept and RF performance. For the low gain type, three classes of antennas are under various stages of development. These are the crossed-drooping dipole, quadrifilar helix, and microstrip patch designs. The antennas are intended to provide circularly-polarized radiation with a minimum of 3-dB gain in the angular region from 19 degrees to 60 deg from the horizon in elevation plane and with an omnidirectional pattern in azimuthal plane. For the electronically steerable high gain type, circularly-polarized microstrip patch phased arrays formed on a planar surface and on the surface of a truncated cone are under study. The arrays are intended to provide a minimum of 12 dB gain in the same angular region in elevation plane at all azimuthal angles. This coverage is accomplished by scanning the high gain pencil beam in both elevation and azimuthal directions. Both types of antennas are to transmit at 821-831 MHz band and to receive at 866-876 MHz band. They must be of low cost design and reasonably conformal to the vehicle.

  9. Merged Land and Ocean Surface Temperature, Version 3.5

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The historical Merged Land-Ocean Surface Temperature Analysis (MLOST) is derived from two independent analyses, an Extended Reconstructed Sea Surface Temperature...

  10. 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.

  11. A data mining approach for sharpening satellite thermal imagery over land

    Science.gov (United States)

    Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

  12. On evaluation of ShARP passive rainfall retrievals over snow-covered land surfaces and coastal zones

    CERN Document Server

    Ebtehaj, Ardeshir M; Foufoula-Georgiou, Efi

    2015-01-01

    For precipitation retrievals over land, using satellite measurements in microwave bands, it is important to properly discriminate the weak rainfall signals from strong and highly variable background surface emission. Traditionally, land rainfall retrieval methods often rely on a weak signal of rainfall scattering on high-frequency channels (85 GHz) and make use of empirical thresholding and regression-based techniques. Due to the increased ground surface signal interference, precipitation retrieval over radiometrically complex land surfaces, especially over snow-covered lands, deserts and coastal areas, is of particular challenge for this class of retrieval techniques. This paper evaluates the results by the recently proposed Shrunken locally linear embedding Algorithm for Retrieval of Precipitation (ShARP), over a radiometrically complex terrain and coastal areas using the data provided by the Tropical Rainfall Measuring Mission (TRMM) satellite. To this end, the ShARP retrieval experiments are performed ove...

  13. Reforesting unused surface mined lands by replanting with native trees

    Science.gov (United States)

    Patrick N. Angel; James A. Burger; Carl E. Zipper; Scott Eggerud

    2012-01-01

    More than 600,000 ha (1.5 million ac) of mostly forested land in the Appalachian region were surface mined for coal under the Surface Mining Control and Reclamation Act. Today, these lands are largely unmanaged and covered with persistent herbaceous species, such as fescue (Festuca spp.) and sericea lespedeza (Lespedeza cuneata [Dum. Cours.] G. Don,) and a mix of...

  14. Classes of land-surface form in the United States

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This digital dataset describes classes of land-surface form in the conterminous United States. The source of the data is the map of land-surface form in the 1970...

  15. Simulation of at-sensor radiance over land for proposed thermal channels of Imager payload onboard INSAT-3D satellite using MODTRAN model

    Indian Academy of Sciences (India)

    M R Pandya; D B Shah; H J Trivedi; S Panigrahy

    2011-02-01

    INSAT-3D is the new generation Indian satellite designed for improved Earth observations through two payloads – Imager and Sounder. Study was conducted with an aim of simulating satellite level signal over land in the infrared channels of the Imager payload using a radiative transfer model MODTRAN. Satellite level at-sensor radiance corresponding to all four infrared channels of INSAT-3D Imager payload is obtained using MODTRAN and sensitivity of at-sensor radiance was inferred as a function of input parameters namely, surface temperature, emissivity, view angle and atmospheric water vapour, which is helpful in understanding the signal simulation scheme needed for retrieving a very critical parameter namely, land surface temperature.

  16. Assimilation of neural network soil moisture in land surface models

    Science.gov (United States)

    Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

    2017-04-01

    In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

  17. Carbon Sequestration on Surface Mine Lands

    Energy Technology Data Exchange (ETDEWEB)

    Donald Graves; Christopher Barton; Richard Sweigard; Richard Warner; Carmen Agouridis

    2006-03-31

    Since the implementation of the federal Surface Mining Control and Reclamation Act of 1977 (SMCRA) in May of 1978, many opportunities have been lost for the reforestation of surface mines in the eastern United States. Research has shown that excessive compaction of spoil material in the backfilling and grading process is the biggest impediment to the establishment of productive forests as a post-mining land use (Ashby, 1998, Burger et al., 1994, Graves et al., 2000). Stability of mine sites was a prominent concern among regulators and mine operators in the years immediately following the implementation of SMCRA. These concerns resulted in the highly compacted, flatly graded, and consequently unproductive spoils of the early post-SMCRA era. However, there is nothing in the regulations that requires mine sites to be overly compacted as long as stability is achieved. It has been cultural barriers and not regulatory barriers that have contributed to the failure of reforestation efforts under the federal law over the past 27 years. Efforts to change the perception that the federal law and regulations impede effective reforestation techniques and interfere with bond release must be implemented. Demonstration of techniques that lead to the successful reforestation of surface mines is one such method that can be used to change perceptions and protect the forest ecosystems that were indigenous to these areas prior to mining. The University of Kentucky initiated a large-scale reforestation effort to address regulatory and cultural impediments to forest reclamation in 2003. During the three years of this project 383,000 trees were planted on over 556 acres in different physiographic areas of Kentucky (Table 1, Figure 1). Species used for the project were similar to those that existed on the sites before mining was initiated (Table 2). A monitoring program was undertaken to evaluate growth and survival of the planted species as a function of spoil characteristics and

  18. Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Schluessel, Peter

    2009-01-01

    Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

  19. Using satellite data to monitor land-use land-cover change in North-eastern Latvia.

    Science.gov (United States)

    Fonji, Simon Foteck; Taff, Gregory N

    2014-01-01

    Land-use and land-cover change (LULCC), especially those caused by human activities, is one of the most important components of global environmental change (Jessen 3(rd) edition: 1-526 2005). In this study the effects of geographic and demographic factors on LULCC are analyzed in northeastern Latvia using official estimates from census and vital statistics data, and using remotely sensed satellite imagery (Landsat Thematic Mapper) acquired from 1992 and 2007. The remote sensing images, elevation data, in-situ ground truth and ground control data (using GPS), census and vital statistics data were processed, integrated, and analyzed in a geographic information system (GIS). Changes in six categories of land-use and land-cover (wetland, water, agriculture, forest, bare field and urban/suburban) were studied to determine their relationship to demographic and geographic factors between 1992 and 2007. Supervised classifications were performed on the Landsat images. Analysis of land cover change based on "change-to" categories between the 1992 and 2007 images revealed that changes to forest were the most common type of change (17.1% of pixels), followed by changes to agriculture (8.6%) and the fewest were changes to urban/suburban (0.8%). Integration of population data and land-cover change data revealed key findings: areas near to roads underwent more LULCC and areas far away from Riga underwent less LULCC. Range in elevation was positively correlated with all LULCC categories. Population density was found to be associated with most LULCC categories but the direction of effect was scale dependent. This paper shows how socio-demographic data can be integrated with satellite image data and cartographic data to analyze drivers of LULCC at multiple spatial scales.

  20. Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences

    OpenAIRE

    José Luis Gómez-Dans; Philip Edward Lewis; Mathias Disney

    2016-01-01

    There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately ap...

  1. Development of high resolution land surface parameters for the Community Land Model

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2012-06-01

    Full Text Available There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0 are at 0.5° or coarser resolutions, released with the model from the National Center for Atmospheric Research (NCAR. Plant Functional Types (PFTs, vegetation properties such as Leaf Area Index (LAI, Stem Area Index (SAI, and non-vegetated land covers were developed using remotely-sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM applied to the western US to demonstrate their use in high-resolution modeling. Future work will include global offline CLMsimulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

  2. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    Science.gov (United States)

    Ban, Yifang; Gong, Peng; Giri, Chandra

    2015-05-01

    Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

  3. Spatial validation of large scale land surface models against monthly land surface temperature patterns using innovative performance metrics.

    Science.gov (United States)

    Koch, Julian; Siemann, Amanda; Stisen, Simon; Sheffield, Justin

    2016-04-01

    Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. This study features two innovative spatial performance metrics, namely EOF- and connectivity-analysis, to validate predicted LST patterns by three LSMs (Mosaic, Noah, VIC) over the contiguous USA. The LST validation dataset is derived from global High-Resolution-Infrared-Radiometric-Sounder (HIRS) retrievals for a 30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality, and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly driven by air temperature. The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings.

  4. Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

    Science.gov (United States)

    Wu, Yuling; Nair, Udaysankar S.; Pielke, Roger A., Sr.; McNider, Richard T.; Christopher, Sundar A.; Anantharaj, Valentine G.

    2009-01-01

    Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near- Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skillful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.

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

    Science.gov (United States)

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

    1990-01-01

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

  6. Development of a Landing Mechanism for Asteroids with Soft Surface

    Directory of Open Access Journals (Sweden)

    Zhijun Zhao

    2013-01-01

    Full Text Available A landing mechanism to an asteroid with soft surface is developed. It consists of three landing feet, landing legs, cardan element, damping element, equipment base, anchoring system, and so on. Static structural analysis and modal analysis are carried out to check the strength and natural frequency of the landing mechanism with FEA. Testing platform for the anchoring system is introduced, and then the penetrating and anchoring tests of the anchoring system are carried out in different media. It shows that cohesion of the media has large influence on the penetrating and anchoring performance of the anchoring system. Landing tests of the landing mechanism with different velocities under simulated microgravity environment are carried out on the air-floating platform, and the impact accelerations are measured by the sensors on the landing mechanism. At the same time, these impact accelerations are processed by spectrum analysis to find the natural frequency of the landing mechanism.

  7. Artificial Crater Formation on Satellite Surfaces Using an Orbiting Railgun

    Science.gov (United States)

    Dissly, R. W.; Miller, K. L.; Carlson, R. J.

    2003-01-01

    The specification of greater than 45kW of disposable power available on the JIMO spacecraft raises the possibility of a new class of instrumentation that has utility at such power levels. In this presentation we discuss the concept of an electromagnetic mass driver that can launch projectiles from orbit around one of the Galilean satellites directed on a trajectory that will impact the satellite surface. The resulting impact will create a crater that will provide information on the mechanical properties of surface and near-surface materials, expose subsurface materials for remote spectral identification, and form a vapor cloud that can be sensed for composition either remotely or in-situ. An analog for such a controlled cratering experiment is Deep Impact, a mission to observe the crater and ensuing ejecta cloud formed by a ballistic projectile into a comet surface in July, 2005.

  8. Artificial Crater Formation on Satellite Surfaces Using an Orbiting Railgun

    Science.gov (United States)

    Dissly, R. W.; Miller, K. L.; Carlson, R. J.

    2003-01-01

    The specification of greater than 45kW of disposable power available on the JIMO spacecraft raises the possibility of a new class of instrumentation that has utility at such power levels. In this presentation we discuss the concept of an electromagnetic mass driver that can launch projectiles from orbit around one of the Galilean satellites directed on a trajectory that will impact the satellite surface. The resulting impact will create a crater that will provide information on the mechanical properties of surface and near-surface materials, expose subsurface materials for remote spectral identification, and form a vapor cloud that can be sensed for composition either remotely or in-situ. An analog for such a controlled cratering experiment is Deep Impact, a mission to observe the crater and ensuing ejecta cloud formed by a ballistic projectile into a comet surface in July, 2005.

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

    Science.gov (United States)

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

    2015-12-01

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

  10. Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

    Science.gov (United States)

    Chen, Xuelong; Su, Bob

    2017-04-01

    Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

  11. Global observation-based diagnosis of soil moisture control on land surface flux partition

    Science.gov (United States)

    Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

    2016-04-01

    Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux

  12. Geocenter motion due to surface mass transport from GRACE satellite data

    Science.gov (United States)

    Riva, R. E. M.; van der Wal, W.; Lavallée, D. A.; Hashemi Farahani, H.; Ditmar, P.

    2012-04-01

    Measurements of mass redistribution from satellite gravimetry are insensitive to geocenter motions. However, geocenter motions can be constrained by satellite gravity data alone if we partition mass changes between land and oceans, under the assumption that the ocean is passive (i.e., in gravitational equilibrium with the land load and the solid earth). Here, we make use of 8 years (2003-2010) of optimally filtered monthly GRACE-based solutions produced at TU Delft to determine changes in the land load and the corresponding geocenter motion, through an iterative procedure. We pay particular attention to correcting for signal leakage caused by the limited spatial resolution of GRACE. We also investigate how the choice of a model of glacial isostatic adjustment (GIA) affects the estimated geocenter motion trend due to present-day surface mass transport. Finally, we separate the contribution of ice masses from that of land hydrology and show how they have a different sensitivity to the chosen GIA model and observational time-span.

  13. 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.

  14. Surface ages of mid-size Saturnian satellites

    CERN Document Server

    Di Sisto, Romina P

    2015-01-01

    The observations of the surfaces of the mid sized Saturnian satellites made by Cassini Huygens mission have shown a variety of features that allows study of the processes that took place and are taking place on those worlds. Research of the Saturnian satellite surfaces has clear implications for Saturn history and surroundings. In a recent paper, the production of craters on the mid sized Saturnian satellites by Centaur objects was calculated considering the current Solar System. We have compared our results with crater counts from Cassini images and we have noted that the number of observed small craters is less than our calculated number. In this paper we estimate the age of the surface for each observed terrain on each mid sized satellite of Saturn. We have noticed that since there are less observed small craters than calculated (except on Iapetus), this results in younger ages. This could be the result of efficient endogenous or exogenous process(es) for erasing small craters and or crater saturation at t...

  15. Daily monitoring of the land surface of the Earth

    Science.gov (United States)

    Mascaro, J.

    2016-12-01

    Planet is an integrated aerospace and data analytics company that operates the largest fleet of Earth-imaging satellites. With more than 140 cube-sats successfully launched to date, Planet is now collecting approximately 10 million square kilometers of imagery per day (3-5m per pixel, in red, green, blue and near infrared spectral bands). By early 2017, Planet's constellation will image the entire land surface of the Earth on a daily basis. Due to investments in cloud storage and computing, approximately 75% of imagery collected is available to Planet's partners within 24 hours of capture through an Application Program Interface. This unique dataset has enormous applications for monitoring the status of Earth's natural ecosystems, as well as human settlements and agricultural welfare. Through our Ambassadors Program, Planet has made data available for researchers in areas as disparate as human rights monitoring in refugee camps, to assessments of the impact of hydroelectric installations, to tracking illegal gold mining in Amazon forests, to assessing the status of the cryosphere. Here, we share early results from Planet's research partner network, including enhanced spatial and temporal resolution of NDVI data for agricultural health in Saudi Arabia, computation of rates of illegal deforestation in Southern Peru, estimates of tropical forest carbon stocks based on data integration with active sensors, and estimates of glacial flow rates. We synthesize the potentially enormous research and scientific value of Planet's persistent monitoring capability, and discuss methods by which the data will be disseminated into the scientific community.

  16. Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

    Science.gov (United States)

    Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

    2017-04-01

    The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to

  17. Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

    Science.gov (United States)

    Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

    2016-04-01

    Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover

  18. Validation of Land Surface Temperature products in arid climate regions with permanent in-situ measurements

    Science.gov (United States)

    Goettsche, F.; Olesen, F.; Trigo, I.; Hulley, G. C.

    2013-12-01

    Land Surface Temperature (LST) is operationally obtained from several space-borne sensors, e.g. from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) by the Land Surface Analysis - Satellite Application Facility (LSA-SAF) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-Terra by the MODIS Land Team. The relative accuracy of LST products can be assessed by cross-validating different products. Alternatively, the so-called 'radiance based validation' can be used to compare satellite-retrieved LST with results from radiative transfer models: however, this requires precise a priori knowledge of land surface emissivity (LSE) and atmospheric conditions. Ultimately, in-situ measurements (';ground truth') are needed for validating satellite LST&E products. Therefore, the LST product derived by LSA-SAF is validated with independent in-situ measurements (';temperature based validation') at permanent validation stations located in different climate regions on the SEVIRI disk. In-situ validation is largely complicated by the spatial scale mismatch between satellite sensors and ground based sensors, i.e. areas observed by ground radiometers usually cover about 10 m2, whereas satellite measurements in the thermal infrared typically cover between 1 km2 and 100 km2. Furthermore, an accurate characterization of the surface is critical for all validation approaches, but particularly over arid regions, as shown by in-situ measurements revealing that LSE products can be wrong by more than 3% [1]. The permanent stations near Gobabeb (Namibia; hyper-arid desert climate) and Dahra (Senegal; hot-arid steppe-prairie climate) are two of KIT's four dedicated LST validation stations. Gobabeb station is located on vast and flat gravel plains (several 100 km2), which are mainly covered by coarse gravel, sand, and desiccated grass. The gravel plains are highly homogeneous in space and time, which makes them ideal for

  19. An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

    Science.gov (United States)

    Kim, Edward J.; Tedesco, Marco

    2006-01-01

    Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

  20. Effects of Crop Growth and Development on Land Surface Fluxes

    Institute of Scientific and Technical Information of China (English)

    CHEN Feng; XIE Zhenghui

    2011-01-01

    In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS_CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 n2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes.For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS_CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

  1. Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

    Science.gov (United States)

    Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Bogena, Heye; Vereecken, Harry

    2017-04-01

    Land surface models describe biogeophysical and biogeochemical processes at the land surface, and represent the lower boundary condition of atmospheric circulation models. Their key role is the quantification of mass and energy fluxes between the land surface and the atmosphere. Predictions with land surface models are affected by many unknown parameters, uncertain meteorological forcings and incomplete process understanding. Measurement data (e.g., soil moisture) can help to improve land surface model predictions. However, soil moisture products obtained from satellite remote sensing are normally available at a very coarse resolution and give information on the upper few centimetres of the soil only. Therefore, the recently developed Cosmic Ray Neutron Sensors (CRNS) are of high interest for predictions by land surface models, because they measure neutron count intensity, which is related to integral soil moisture content at the field scale (about 20 hectares). High resolution land surface models are also able to provide solutions at the same scale. In this study, we investigated whether the assimilation of soil moisture retrievals from CRNS data measured by a network of nine CRNS located in the Rur catchment in Germany (2354 km2) can improve land surface model prediction. The assimilation of soil moisture retrievals from neutron count intensity data was used to update model states and parameters of the land surface model CLM 4.5 over a two year time period, followed by a one year evaluation period without updates. This updating was done with the local ensemble transform Kalman filter. The real world experiment tested the value of CRNS using jackknifing experiments and three different initial soil maps. During the assimilation period, soil moisture predictions generally improved, for a biased soil map from an RMSE of 0.11 cm3/cm3 in the open loop run to 0.03 cm3/cm3 while during the evaluation period soil moisture predictions improved from 0.12 cm3/cm3 to 0.06 cm3

  2. 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.

  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. An advanced generation land mobile satellite system and its critical technologies

    Science.gov (United States)

    Naderi, F.

    1982-01-01

    A conceptual design for a Land Mobile Satellite System (LMSS) for the 1990s is presented. LMSS involves small tranceivers accessing satellites directly, with ground reception through small car-top antennas. The satellite would have a large antenna and blanket coverage areas in the UHF. The call may originate from a home, be carried by wire to a gateway, transmitted to satellite on the S-band, converted to UHF on the satellite, and transmitted to the vehicle. The system design is constrained by the number of users in an area during the busiest hours, Shuttle storage, controllability factors, and the total area served. A 55-m antenna has been selected, with 87 spot beams and two 10 MHz UHF bands in the 806-890 MHz band. A 17 dB interbeam isolation level is required, implying that sufficient sub-bands can be generated to assure 8265 total channels. The mobile satellite (MSAT) would have an 83 m mast lower segment, a 34 m upper segment, and a second, 10 m antenna made of a deployable mesh. Various antenna function modes are considered.

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

    Directory of Open Access Journals (Sweden)

    Xueke Li

    2016-05-01

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

  6. Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery

    Science.gov (United States)

    Pervez, Wasim; Uddin, Vali; Khan, Shoab Ahmad; Khan, Junaid Aziz

    2016-04-01

    Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

  7. System architecture and market aspects of an European Land Mobile Satellite System via EMS

    Science.gov (United States)

    Ananasso, F.; Mistretta, I.

    1992-03-01

    The paper describes an implementation scenario of a Land Mobile Satellite System via the EMS (European Mobile System) payload embarked on Italsat F-2. Some emphasis is given on market issues aiming at singling out business niches of Land Mobile Satellite Services (LMSS) in Europe. Other crucial issues exist such as: the alternate/competitive systems, the problems of interworking with other existing and/or planned systems, the definition of network architecture that better fits the user requirements, the marketing strategy and, last but not least, the financial evaluation of the project. The paper, on the basis of a study performed by Telespazio on behalf of ESA, discusses some of these issues with emphasis on competitive market aspects.

  8. Estimation of Land Surface Temperature for the Quantitative Analysis of Land Cover of Lower Areas of Sindh to Assess the Impacts of Climate Variability

    Science.gov (United States)

    Qaisar, Maha

    2016-07-01

    Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded

  9. Operational high latitude surface irradiance products from polar orbiting satellites

    Science.gov (United States)

    Godøy, Øystein

    2016-12-01

    It remains a challenge to find an adequate approach for operational estimation of surface incoming short- and longwave irradiance at high latitudes using polar orbiting meteorological satellite data. In this presentation validation results at a number of North Atlantic and Arctic Ocean high latitude stations are presented and discussed. The validation results have revealed that although the method works well and normally fulfil the operational requirements, there is room for improvement. A number of issues that can improve the estimates at high latitudes have been identified. These improvements are partly related to improved cloud classification using satellite data and partly related to improved handling of multiple reflections over bright surfaces (snow and sea ice), especially in broken cloud conditions. Furthermore, the availability of validation sites over open ocean and sea ice is a challenge.

  10. Using ARM Data to Evaluate Satellite Surface Solar Flux Retrievals

    Energy Technology Data Exchange (ETDEWEB)

    Hinkelman, L.M.; Stackhouse, P.W.; Young, D.F.; Long, C.N.; Rutan, D.

    2005-03-18

    The accurate, long-term radiometric data collected by Atmospheric Radiation Measurement (ARM) has become essential to the evaluation of surface radiation budget data from satellites. Since the spatial and temporal characteristics of data from these two sources are very different, the comparisons are typically made for long-term average values. While such studies provide a general indication of the quality of satellite flux products, more detailed analysis is required to understand specific retrieval algorithm weaknesses. Here we show how data from the ARM shortwave flux analysis (SFA) value added product (VAP) are being used to assess solar fluxes in the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB), release 2.5.

  11. Effect of surface BRDF of various land cover types on geostationary observations of tropospheric NO2

    Science.gov (United States)

    Noguchi, K.; Richter, A.; Rozanov, V.; Rozanov, A.; Burrows, J. P.; Irie, H.; Kita, K.

    2014-10-01

    We investigated the effect of surface reflectance anisotropy, bidirectional reflectance distribution function (BRDF), on satellite retrievals of tropospheric NO2. We assume the geometry of geostationary measurements over Tokyo, which is one of the worst air-polluted regions in East Asia. We calculated air mass factors (AMF) and box AMFs (BAMF) for tropospheric NO2 to evaluate the effect of BRDF by using the radiative transfer model SCIATRAN. To model the BRDF effect, we utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) products (MOD43B1 and MOD43B2), which provide three coefficients to express the RossThick-LiSparse reciprocal model, a semi-empirical and kernel-based model of BRDF. Because BRDF depends on the land cover type, we also utilized the High Resolution Land-Use and Land-Cover Map of the Advanced Land Observing Satellite (ALOS)/Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), which classifies the ground pixels over Tokyo into six main types: water, urban, paddy, crop, deciduous forest, and evergreen forest. We first develop an empirical model of the three BRDF coefficients for each land cover type over Tokyo and then apply the model to the calculation of land-cover-type-dependent AMFs and BAMFs. Results show that the variability of AMF among the land types is up to several tens of percent, and if we neglect the reflectance anisotropy, the difference with AMFs based on BRDF reaches 10% or more. The evaluation of the BAMFs calculated shows that not considering BRDF will cause large errors if the concentration of NO2 is high close to the surface, although the importance of BRDF for AMFs decreases for large aerosol optical depth (AOD).

  12. Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

    2016-12-01

    This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

  13. Handover aspects for a Low Earth Orbit (LEO) CDMA Land Mobile Satellite (LMS) system

    Science.gov (United States)

    Carter, P.; Beach, M. A.

    1993-01-01

    This paper addresses the problem of handoff in a land mobile satellite (LMS) system between adjacent satellites in a low earth orbit (LEO) constellation. In particular, emphasis is placed on the application of soft handoff in a direct sequence code division multiple access (DS-CDMA) LMS system. Soft handoff is explained in terms of terrestrial macroscopic diversity, in which signals transmitted via several independent fading paths are combined to enhance the link quality. This concept is then reconsidered in the context of a LEO LMS system. A two-state Markov channel model is used to simulate the effects of shadowing on the communications path from the mobile to each satellite during handoff. The results of the channel simulation form a platform for discussion regarding soft handoff, highlighting the potential merits of the scheme when applied in a LEO LMS environment.

  14. Fully automated extraction and analysis of surface Urban Heat Island patterns from moderate resolution satellite images

    Science.gov (United States)

    Keramitsoglou, I.; Kiranoudis, C. T.

    2012-04-01

    Comparison of thermal patterns across different cities is hampered by the lack of an appropriate methodology to extract the patterns and characterize them. What is more, increased attention by the urban climate community has been expressed to assess the magnitude and dynamics of the surface Urban Heat Island effect and to identify environmental impacts of large cities and "megacities". Motivated by this need, we propose an innovative object-based image analysis procedure to extract thermal patterns for the quantitative analysis of satellite-derived land surface temperature maps. The spatial and thermal attributes associated with these objects are then calculated and used for the analyses of the intensity, the position and the spatial extent of SUHIs. The output eventually builds up and populates a database with comparable and consistent attributes, allowing comparisons between cities as well as urban climate studies. The methodology is demonstrated over the Greater Athens Area, Greece, with more than 3000 LST images acquired by MODIS over a decade being analyzed. The approach can be potentially applied to current and future (e.g. Sentinel-3) level-2 satellite-derived land surface temperature maps of 1km spatial resolution acquired over continental and coastal cities.

  15. Impact of Land Use Changes on Surface Warming in China

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jingyong; DONG Wenjie; WU Lingyun; WEI Jiangfeng; CHEN Peiyan; Dong-Kyou LEE

    2005-01-01

    Land use changes such as urbanization, agriculture, pasturing, deforestation, desertification and irrigation can change the land surface heat flux directly, and also change the atmospheric circulation indirectly, and therefore affect the local temperature. But it is difficult to separate their effects from climate trends such as greenhouse-gas effects. Comparing the decadal trends of the observation station data with those of the NCEP/NCAR Reanalysis (NNR) data provides a good method to separate the effects because the NNR is insensitive to land surface changes. The effects of urbanization and other land use changes over China are estimated by using the difference between the station and the NNR surface temperature trends. Our results show that urbanization and other land use changes may contribute to the observed 0.12℃ (10 yr)- 1 increase for daily mean surface temperature, and the 0.20℃ (10 yr)- 1 and 0.03℃ (10 yr)-1 increases for the daily minimum and maximum surface temperatures, respectively. The urban heat island effect and the effects of other land-use changes mayalso play an important role in the diurnal temperature range change. The spatial pattern of the differences in trends shows a marked heterogeneity.The land surface degradation such as deforestation and desertification due to human activities over northern China, and rapidly-developed urbanization over southern China, may have mostly contributed to the increases at stations north of about 38°N and in Southeast China, respectively. Furthermore, the vegetation cover increase due to irrigation and fertilization may have contributed to the decreasing trend of surface temperature over the lower Yellow River Basin. The study illustrates the possible impacts of land use changes on surface temperature over China.

  16. Land surface temperature shaped by urban fractions in megacity region

    Science.gov (United States)

    Zhang, Xiaoxuan; Hu, Yonghong; Jia, Gensuo; Hou, Meiting; Fan, Yanguo; Sun, Zhongchang; Zhu, Yuxiang

    2017-02-01

    Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional warming trends. However, it is unclear how urban expansion contributes to local temperature change. In this study, we investigated the relationship between land surface temperature (LST) change and the increase of urban land signals. The megacity of Tianjin was chosen for the case study because it is representative of the urbanization process in northern China. A combined analysis of LST and urban land information was conducted based on an urban-rural transect derived from Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectrometer (MODIS), and QuickBird images. The results indicated that the density of urban land signals has intensified within a 1-km2 grid in the urban center with an impervious land fraction >60 %. However, the construction on urban land is quite different with low-/mid-rise buildings outnumbering high-rise buildings in the urban-rural transect. Based on a statistical moving window analysis, positive correlation ( R 2 > 0.9) is found between LST and urban land signals. Surface temperature change (ΔLST) increases by 0.062 °C, which was probably caused by the 1 % increase of urbanized land (ΔIF) in this case region.

  17. Integrated use of satellite images, DEMs, soil and substrate data in studying mountainous lands

    Science.gov (United States)

    Giannetti, Fabio; Montanarella, Luca; Salandin, Roberto

    A method based on the integration into a GIS of satellite images of different spatial resolution (Landsat TM and SPOT), Digital Elevation Models, geo-lithological maps and some soil-landscape data was developed and applied to a test area on a sector of the Italian northwestern Alps in the Piemonte region (Pellice, Po, Varaita and Maira valleys southwest of Torino). The main working steps performed (using GIS software) in this area were: (1) acquisition of geo-lithological and geomorphological maps available and a first definition of homogeneous zones obtained by joining different classes with pedogenic criteria; (2) processing and classification of satellite images to define homogeneous areas with reference to prevailing land cover, land use pattern, relief shape and spectral characters; (3) integration of the previous two layers to obtain a first set of cartographic units showing a distinctive and often repetitive pattern of land form, land cover and parent material; and (4) processing DEMs (slope and aspect), soil or soil-landscape data in order to refine data and characterise the units. The resulting cartographic units were superimposed on a soil-landscape map realised by means of stereoscopic interpretation of aerial photographs by IPLA at the same scale (1:250,000). This comparison was used to verify the correctness of the satellite image processing steps and consistency with the map scale used. A larger scale application was also developed for grassland at 1:50,000 scale to demonstrate the practical use of remote sensing and GIS data in assisting mountainous land development.

  18. Satellite remote sensing of surface energy balance: Success, failures, and unresolved issues in FIFE

    Science.gov (United States)

    Hall, Forrest G.; Huemmrich, Karl F.; Goetz, Scott J.; Sellers, Piers J.; Nickeson, Jaime E.

    1992-11-01

    The FIFE staff science group, consisting of the authors, developed and evaluated process models relating surface energy and mass flux, that is, surface rates, to boundary layer and surface biophysical characteristics, that is, surface states. In addition, we developed and evaluated remote sensing algorithms for inferring surface state characteristics. In this paper we report the results of our efforts. We also look in detail at the sensor and satellite platform requirements (spatial resolution and orbital requirements) as driven by surface energy balance dynamics and spatial variability. We examine also the scale invariance of the process models and remote sensing algorithms, that is, to what degree do the remotely sensed parameters and energy balance relations translate from the patch level where they were developed to the mesoscale level where they are required? Finally, we examine the atmospheric correction and calibration issues involved in extending the remotely sensed observations within a season and between years. From these investigations we conclude that (1) existing formulations for the radiation balance and latent heat components of the surface energy balance equation are valid at the patch level. (2) Many of the surface physiological characteristics that parameterize these formulations can be estimated using satellite remote sensing at both local and regional scales; a few important ones cannot. (3) The mathematical structures relating radiation and surface energy flux to remote sensing parameters are, for the most part, scale invariant over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) study area. The conditions for scale invariance are derived. (4) The precision of satellite remote sensing estimates of surface reflectance, calibrated and corrected for atmospheric effects, is no worse than about 1% absolute. The errors may actually be smaller, but an upper bound of 1% results from sampling variance

  19. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    MAO KeBiao; SHI JianCheng; LI ZhaoLiang; QIN ZhiHao; LI ManChun; XU Bin

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface temperature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM, the difference of different frequencies can eliminate the influence of water in soil and atmosphere, and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface should be at least classified into three types: water covered surface, snow covered surface, and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm, we built different equations for different ranges of temperature. The average land surface temperature error is about 2-3℃ relative to the MODIS LST product.

  20. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface tem-perature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM,the difference of different frequen-cies can eliminate the influence of water in soil and atmosphere,and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately,the land surface should be at least classified into three types:water covered surface,snow covered surface,and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm,we built different equations for different ranges of temperature. The average land surface temperature er-ror is about 2―3℃ relative to the MODIS LST product.

  1. Satellite monitoring of land-use and land-cover changes in northern Togo protected areas

    Institute of Scientific and Technical Information of China (English)

    Fousseni Folega; Chun-yu Zhang; Xiu-hai Zhao; Kperkouma Wala; Komlan Batawila; Hua-guo Huang; Marra Dourma; Koffi Akpagana

    2014-01-01

    Remote-sensing data for protected areas in northern Togo, obtained in three different years (2007, 2000, and 1987), were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index (NDVI) was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images. Maximum likelihood classification was applied to the 2007 image (ETM+2007) using a supervised classification process. Seven vegetation classes were defined from training data sets. The seven classes included the following biomes:riparian forest, dry forest, flooded vegetation, wooded savanna, fallows, parkland, and water. For these classes, the overall accuracy and the overall kappa statistic for the classi-fied map were 72.5% and 0.67, respectively. Data analyses indicated a great change in land resources;especially between 1987 and 2000 proba-bly due to the impact of democratization process social, economic, and political disorder from 1990. Wide-scale loss of vegetation occurred during this period. However, areas of vegetation clearing and regrowth were more visible between 2000 and 2007. The main source of confusion in the contingency matrix was due to heterogeneity within certain classes. It could also be due to spectral homogeneity among the classes. This research provides a baseline for future ecological landscape research and for the next management program in the area.

  2. Development of high resolution land surface parameters for the Community Land Model

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2012-11-01

    Full Text Available There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0 are at 0.5° or coarser resolutions, released with the Community Earth System Model (CESM. Plant Functional Types (PFTs, vegetation properties such as Leaf Area Index (LAI, Stem Area Index (SAI, and non-vegetated land covers were developed using remotely sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. Advantages and disadvantages of each dataset were discussed in order to provide guidance on the use of the data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM applied to the western US to demonstrate their use in high-resolution modeling. A remapping method from the latitude/longitude grid of the CLM data to the WRF grids with map projection was also demonstrated. Future work will include global offline CLM simulations to examine the impacts of source data resolution and subsequent land

  3. On The Reproducibility of Seasonal Land-surface Climate

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J

    2004-10-22

    The sensitivity of the continental seasonal climate to initial conditions is estimated from an ensemble of decadal simulations of an atmospheric general circulation model with the same specifications of radiative forcings and monthly ocean boundary conditions, but with different initial states of atmosphere and land. As measures of the ''reproducibility'' of continental climate for different initial conditions, spatio-temporal correlations are computed across paired realizations of eleven model land-surface variables in which the seasonal cycle is either included or excluded--the former case being pertinent to climate simulation, and the latter to seasonal anomaly prediction. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is substantially higher in the Tropics; its spatial reproducibility also markedly fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation. However, the overall degree of reproducibility depends strongly on the particular land-surface anomaly considered. It is also shown that the predictability of a land-surface anomaly implied by its reproducibility statistics is consistent with what is inferred from more conventional predictability metrics. Implications of these results for climate model intercomparison projects and for operational forecasts of seasonal continental climate also are elaborated.

  4. GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring.

    Science.gov (United States)

    Motte, Erwan; Zribi, Mehrez; Fanise, Pascal; Egido, Alejandro; Darrozes, José; Al-Yaari, Amen; Baghdadi, Nicolas; Baup, Frédéric; Dayau, Sylvia; Fieuzal, Remy; Frison, Pierre-Louis; Guyon, Dominique; Wigneron, Jean-Pierre

    2016-05-20

    Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than -15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than -30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics.

  5. GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

    Directory of Open Access Journals (Sweden)

    Erwan Motte

    2016-05-01

    Full Text Available Global Navigation Satellite System-Reflectometry (GNSS-R has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI, dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than −15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than −30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics.

  6. Algorithm Development for Land Surface Temperature Retrieval: Application to Chinese Gaofen-5 Data

    Directory of Open Access Journals (Sweden)

    Yuanyuan Chen

    2017-02-01

    Full Text Available Land surface temperature (LST is a key variable in the study of the energy exchange between the land surface and the atmosphere. Among the different methods proposed to estimate LST, the quadratic split-window (SW method has achieved considerable popularity. This method works well when the emissivities are high in both channels. Unfortunately, it performs poorly for low land surface emissivities (LSEs. To solve this problem, assuming that the LSE is known, the constant in the quadratic SW method was calculated by maintaining the other coefficients the same as those obtained for the black body condition. This procedure permits transfer of the emissivity effect to the constant. The result demonstrated that the constant was influenced by both atmospheric water vapour content (W and atmospheric temperature (T0 in the bottom layer. To parameterize the constant, an exponential approximation between W and T0 was used. A LST retrieval algorithm was proposed. The error for the proposed algorithm was RMSE = 0.70 K. Sensitivity analysis results showed that under the consideration of NEΔT = 0.2 K, 20% uncertainty in W and 1% uncertainties in the channel mean emissivity and the channel emissivity difference, the RMSE was 1.29 K. Compared with AST 08 product, the proposed algorithm underestimated LST by about 0.8 K for both study areas when ASTER L1B data was used as a proxy of Gaofen-5 (GF-5 satellite data. The GF-5 satellite is scheduled to be launched in 2017.

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

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

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

  8. Ice surface temperatures: seasonal cycle and daily variability from in-situ and satellite observations

    Science.gov (United States)

    Madsen, Kristine S.; Dybkjær, Gorm; Høyer, Jacob L.; Nielsen-Englyst, Pia; Rasmussen, Till A. S.; Tonboe, Rasmus T.

    2016-04-01

    Surface temperature is an important parameter for understanding the climate system, including the Polar Regions. Yet, in-situ temperature measurements over ice- and snow covered regions are sparse and unevenly distributed, and atmospheric circulation models estimating surface temperature may have large biases. To change this picture, we will analyse the seasonal cycle and daily variability of in-situ and satellite observations, and give an example of how to utilize the data in a sea ice model. We have compiled a data set of in-situ surface and 2 m air temperature observations over land ice, snow, sea ice, and from the marginal ice zone. 2523 time series of varying length from 14 data providers, with a total of more than 13 million observations, have been quality controlled and gathered in a uniform format. An overview of this data set will be presented. In addition, IST satellite observations have been processed from the Metop/AVHRR sensor and a merged analysis product has been constructed based upon the Metop/AVHRR, IASI and Modis IST observations. The satellite and in-situ observations of IST are analysed in parallel, to characterize the IST variability on diurnal and seasonal scales and its spatial patterns. The in-situ data are used to estimate sampling effects within the satellite observations and the good coverage of the satellite observations are used to complete the geographical variability. As an example of the application of satellite IST data, results will be shown from a coupled HYCOM-CICE ocean and sea ice model run, where the IST products have been ingested. The impact of using IST in models will be assessed. This work is a part of the EUSTACE project under Horizon 2020, where the ice surface temperatures form an important piece of the puzzle of creating an observationally based record of surface temperatures for all corners of the Earth, and of the ESA GlobTemperature project which aims at applying surface temperatures in models in order to

  9. Seasonal transition of precipitation characteristics associated with land surface conditions in and around Bangladesh

    Science.gov (United States)

    Ono, M.; Takahashi, H. G.

    2016-10-01

    This study examined the seasonal transition of precipitation characteristics and its association with land surface conditions in and around Bangladesh, where land surface conditions are predominantly wet. Hourly rain rate data from the Global Satellite Mapping of Precipitation Microwave-Infrared Combined Product and 10 day soil moisture data from the Advanced Microwave Scanning Radiometer Earth Observing System were used over the 7 years from 2003 to 2009. Area mean values of soil moisture, and precipitation amount, frequency, and intensity were calculated for each 10 day period. Results showed that higher precipitation amount and frequency were observed over the wet soil conditions, which indicates that soil moisture was influenced by previous precipitation events. However, the soil moisture could also control the precipitation characteristics. The seasonal and interannual variations in all regions suggested that precipitation amount and frequency increased in moist soil conditions, which is associated with an increase of water vapor supplied from the moist land surface. Over a flat plain (87°E-91°E, 23°N-25°N), a higher afternoon precipitation intensity was observed over drier land surfaces. This relationship was observed on seasonal and interannual variations. This suggests that the land surface conditions in this region can affect the afternoon precipitation intensity to some extent, although changes of atmospheric conditions can be a major factor particularly for the seasonal changes. However, this relationship was not observed in mountainous regions. This can be explained by other factors, such as thermally induced local circulations by the surrounding topography, being stronger than the impact of land surface conditions.

  10. CARBON SEQUESTRATION ON SURFACE MINE LANDS

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2005-06-22

    An area planted in 2004 on Bent Mountain in Pike County was shifted to the Department of Energy project to centralize an area to become a demonstration site. An additional 98.3 acres were planted on Peabody lands in western Kentucky and Bent Mountain to bring the total area under study by this project to 556.5 acres as indicated in Table 2. Major efforts this quarter include the implementation of new plots that will examine the influence of differing geologic material on tree growth and survival, water quality and quantity and carbon sequestration. Normal monitoring and maintenance was conducted and additional instrumentation was installed to monitor the new areas planted.

  11. Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

    Science.gov (United States)

    Famiglietti, J. S.; Wood, Eric F.

    1993-01-01

    A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

  12. Land management and land-cover change have impacts of similar magnitude on surface temperature

    DEFF Research Database (Denmark)

    Luyssaert, Sebastiaan; Jammet, Mathilde; Stoy, Paul C.

    2014-01-01

    Anthropogenic changes to land cover (LCC) remain common, but continuing land scarcity promotes the widespread intensification of land management changes (LMC) to better satisfy societal demand for food, fibre, fuel and shelter1. The biophysical effects of LCC on surface climate are largely...... understood2-5, particularly for the boreal6 and tropical zones7, but fewer studies have investigated the biophysical consequences of LMC; that is, anthropogenic modification without a change in land cover type. Harmonized analysis of ground measurements and remote sensing observations of both LCC and LMC...... revealed that, in the temperate zone, potential surface cooling from increased albedo is typically offset by warming from decreased sensible heat fluxes, with the net effect being a warming of the surface. Temperature changes from LMC and LCC were of the same magnitude, and averaged 2 K at the vegetation...

  13. Evaluating the strength of the land-atmosphere moisture feedback in Earth system models using satellite observations

    Science.gov (United States)

    Levine, Paul A.; Randerson, James T.; Swenson, Sean C.; Lawrence, David M.

    2016-12-01

    The relationship between terrestrial water storage (TWS) and atmospheric processes has important implications for predictability of climatic extremes and projection of future climate change. In places where moisture availability limits evapotranspiration (ET), variability in TWS has the potential to influence surface energy fluxes and atmospheric conditions. Where atmospheric conditions, in turn, influence moisture availability, a full feedback loop exists. Here we developed a novel approach for measuring the strength of both components of this feedback loop, i.e., the forcing of the atmosphere by variability in TWS and the response of TWS to atmospheric variability, using satellite observations of TWS, precipitation, solar radiation, and vapor pressure deficit during 2002-2014. Our approach defines metrics to quantify the relationship between TWS anomalies and climate globally on a seasonal to interannual timescale. Metrics derived from the satellite data were used to evaluate the strength of the feedback loop in 38 members of the Community Earth System Model (CESM) Large Ensemble (LENS) and in six models that contributed simulations to phase 5 of the Coupled Model Intercomparison Project (CMIP5). We found that both forcing and response limbs of the feedback loop in LENS were stronger than in the satellite observations in tropical and temperate regions. Feedbacks in the selected CMIP5 models were not as strong as those found in LENS, but were still generally stronger than those estimated from the satellite measurements. Consistent with previous studies conducted across different spatial and temporal scales, our analysis suggests that models may overestimate the strength of the feedbacks between the land surface and the atmosphere. We describe several possible mechanisms that may contribute to this bias, and discuss pathways through which models may overestimate ET or overestimate the sensitivity of ET to TWS.

  14. Widespread land surface wind decline in the Northern Hemisphere partly attributed to land surface changes

    Science.gov (United States)

    Thepaut, J.; Vautard, R.; Cattiaux, J.; Yiou, P.; Ciais, P.

    2010-12-01

    pressure gradients, and modeled winds from weather re-analyses do not exhibit any comparable stilling trends than at surface stations. For instance, large-scale circulation changes captured in the most recent European Centre for Medium Range Weather Forecast re-analysis (ERA-interim) can only explain only up to 10-50% of the wind stilling, depending on the region. In addition, a significant amount of the slow-down could originate from a generalized increase in surface roughness, due for instance to forest growth and expansion, and urbanization. This hypothesis, which could explain up to 60% of the decline, is supported by remote sensing observations and theoretical calculations combined with meso-scale model simulations. For future wind power energy resource, the part of wind decline due to land cover changes is easier to cope with than that due to global atmospheric circulation slow down.

  15. Satellite techniques for determining the geopotential of sea surface elevations

    Science.gov (United States)

    Pisacane, V. L.

    1986-01-01

    Spaceborne altimetry with measurement accuracies of a few centimeters which has the potential to determine sea surface elevations necessary to compute accurate three-dimensional geostrophic currents from traditional hydrographic observation is discussed. The limitation in this approach is the uncertainties in knowledge of the global and ocean geopotentials which produce satellite and height uncertainties about an order of magnitude larger than the goal of about 10 cm. The quantitative effects of geopotential uncertainties on processing altimetry data are described. Potential near term improvements, not requiring additional spacecraft, are discussed. Even though there is substantial improvements at the longer wavelengths, the oceanographic goal will be achieved. The geopotential research mission (GRM) is described which should produce geopotential models that are capable of defining the ocean geoid to 10 cm and near-earth satellite position. The state of the art and the potential of spaceborne gravimetry is described as an alternative approach to improve our knowledge of the geopotential.

  16. Climate Variability in Coastal Ecosystems - Use of MODIS Land Surface and Sea Surface Temperature Observations

    Science.gov (United States)

    Chintalapati, S.; Lakshmi, V.

    2007-12-01

    The intertidal zone, with its complex blend of marine and terrestrial environments, is one of the intensively studied ecosystems, in understanding the effects of climate change on species abundance and distribution. As climatic conditions change, the geographic limits of the intertidal species will likely move towards more tolerable coastal conditions. Traditionally, understanding climate change effects through species physiologic response have involved use of in situ measurements and thermal engineering models. But these approaches are constrained by their data intensive requirements and may not be suitable for predicting change patterns relevant to large scale species distributions. Satellite remote sensing provides an alternate approach, given the regular global coverage at moderate spatial resolutions. The present study uses six years of land surface temperature (LST) and sea surface temperature (SST) data from MODIS/Terra instrument along various coastlines around the globe - East and West Coast US, Southern Africa, Northern Japan and New Zealand. Apart from the dominant annual cycle in LST and SST, the other seasonal cycles vary from dominant semi-annual cycles in lower latitudes to 1.5 and 2 year cycles at higher latitudes. The monthly anomalies show strong spatial structure at lower latitudes when compared to higher latitudes, with the exception of US east coast, where the spatial structure extended almost along the whole coastline, indicating strong regulation from the Gulf Stream. The patterns along different coast lines are consistent with the atmospheric and ocean circulation patterns existing at those regions. These results suggest that the climatology at the coastal regions can be adequately represented using satellite-based temperature data, thus enabling further research in understanding the effects of climate change on species abundance and distribution at larger scales.

  17. Land Mobile Satellite Service (LMSS): A conceptual system design and identification of the critical technologies: Part 2: Technical report

    Science.gov (United States)

    Naderi, F. (Editor)

    1982-01-01

    A conceptual system design for a satellite-aided land mobile service is described. A geostationary satellite which employs a large (55-m) UHF reflector to communicate with small inexpensive user antennas on mobile vehicles is discussed. It is shown that such a satellite system through multiple beam antennas and frequency reuse can provide thousands of radiotelephone and dispatch channels serving hundreds of thousands of users throughout the U.S.

  18. Advanced microwave forward model for the land surface data assimilation

    Science.gov (United States)

    Park, Chang-Hwan; Pause, Marion; Gayler, Sebastian; Wollschlaeger, Ute; Jackson, Thomas J.; LeDrew, Ellsworth; Behrendt, Andreas; Wulfmeyer, Volker

    2015-04-01

    From local to global scales, microwave remote-sensing techniques can provide temporally and spatially highly resolved observations of land surface properties including soil moisture and temperature as well as the state of vegetation. These variables are critical for agricultural productivity and water resource management. Furthermore, having accurate information of these variables allows us to improve the performances of numerical weather forecasts and climate prediction models. However, it is challenging to translate a measured brightness temperature into the multiple land surface properties because of the inherent inversion problem. In this study, we introduce a novel forward model for microwave remote sensing to resolve this inversion problem and to close the gap between land surface modeling and observations. It is composed of the Noah-MP land surface model as well as new models for the dielectric mixing and the radiative transfer. For developing a realistic forward operator, the land surface model must simulate soil and vegetation processes properly. The Noah-MP land surface model provides an excellent starting point because it contains already a sophisticated soil texture and land cover data set. Soil moisture transport is derived using the Richards equation in combination with a set of soil hydraulic parameters. Vegetation properties are considered using several photosynthesis models with different complexity. The energy balance is closed for the top soil and the vegetation layers. The energy flux becomes more realistic due to including not only the volumetric ratio of land surface properties but also their surface fraction as sub-grid scale information (semitile approach). Dielectric constant is the fundamental link to quantify the land surface properties. Our physical based new dielectric-mixing model is superior to previous calibration and semi-empirical approaches. Furthermore, owing to the consideration of the oversaturated surface dielectric behaviour

  19. Effective UV surface albedo of seasonally snow-covered lands

    Science.gov (United States)

    Tanskanen, A.; Manninen, T.

    2007-05-01

    At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

  20. Path planning on satellite images for unmanned surface vehicles

    Directory of Open Access Journals (Sweden)

    Joe-Ming Yang

    2015-01-01

    Full Text Available In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A * algorithm (FAA *, an advanced A * algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV

  1. Remote Sensing Parameterization of Land Surface Heat Fluxes over Arid and Semi-arid Areas

    Institute of Scientific and Technical Information of China (English)

    马耀明; 王介民; 黄荣辉; 卫国安; MassimoMENENTI; 苏中波; 胡泽勇; 高峰; 文军

    2003-01-01

    Dealing with the regional land surfaces heat fluxes over inhomogeneous land surfaces in arid and semi-arid areas is an important but not an easy issue. In this study, one parameterization method based on satellite remote sensing and field observations is proposed and tested for deriving the regional land surface heat fluxes over inhomogeneous landscapes. As a case study, the method is applied to the Dunhuang experimental area and the HEIFE (Heihe River Field Experiment, 1988-1994) area. The Dunhuang area is selected as a basic experimental area for the Chinese National Key Programme for Developing Basic Sciences: Research on the Formation Mecbanism and Prediction Theory of Severe Climate Disaster in China (G1998040900, 1999-2003). The four scenes of Landsat TM data used in this study are 3 June 2000,22 August 2000, and 29 January 2001 for the Dunhuang area and 9 July 1991 for the HEIFE area. The regional distributions of land surface variables, vegetation variables, and heat fluxes over inhomogeneous landscapes in arid and semi-arid areas are obtained in this study.

  2. Combining Satellite Data and Models to Assess the Impacts of Urbanization on the Continental US Surface Climate

    Science.gov (United States)

    Bounoua, L.; Zhang, P.; Imhoff, M.; Santanello, J.; Kumar, S.; Shepherd, M.; Quattrochi, D.; Silva, J.; Rosenzweigh, C.; Gaffin, S.; Mostovoy, G.

    2013-01-01

    Urbanization is one of the most important and long lasting forms of land transformation. Urbanization affects the surface climate in different ways: (1) by reduction of the vegetation fraction causing subsequent reduction in photosynthesis and plant s water transpiration, (2) by alternation of surface runoff and infiltration and their impacts on soil moisture and the water table, (3) by change in the surface albedo and surface energy partitioning, and (4) by transformation of the surface roughness length and modification of surface fluxes. Land cover and land use change maps including urban areas have been developed and will be used in a suite of land surface models of different complexity to assess the impacts of urbanization on the continental US surface climate. These maps and datasets based on a full range of available satellite data and ground observations will be used to characterize distant-past (pre-urban), recent-past (2001), present (2010), and near future (2020) land cover and land use changes. The main objective of the project is to assess the impacts of these land transformation on past, current and near-future climate and the potential feedbacks from these changes on the atmospheric, hydrologic, biological, and socio-economic properties beyond the immediate metropolitan regions of cities and their near suburbs. The WRF modeling system will be used to explore the nature and the magnitude of the two-way interactions between urban lands and the atmosphere and assess the overall regional dynamic effect of urban expansion on the northeastern US weather and climate

  3. estimation of land surface temperature of kaduna metropolis, nigeria

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Understanding the spatial variation of Land Surface Temperature. (LST), will be ... positive correlation between mean of surface emissivity with date and ... deviation of 1.92 of LST and coefficient determinant R2 (0.46) show a ... (LST), as the prime and basic physical parameter of the earth's ..... thorough review of the paper.

  4. CARBON SEQUESTRATION OF SURFACE MINE LANDS

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2004-05-19

    The January-March 2004 Quarter was dedicated to tree planting activities in two locations in Kentucky. During year one of this project there was no available mine land to plant in the Hazard area so 107 acres were planted in the Martin county mine location. This year 120 acres was planted in the Hazard area to compensate for the prior year and an additional 57 acres was planted on Peabody properties in western Kentucky. An additional set of special plots were established on each of these areas that contained 4800 seedlings each for special carbon sequestration determinations. Plantings were also conducted to continue compaction and water quality studies on two newly established areas as well as confirmed measurements on the first years plantings. Total plantings on this project now amount to 357 acres containing 245,960 tree seedlings.

  5. Resolution and Content Improvements to MISR Aerosol and Land Surface Products

    Science.gov (United States)

    Garay, M. J.; Bull, M. A.; Diner, D. J.; Hansen, E. G.; Kalashnikova, O. V.

    2015-12-01

    Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing operational Level 2 (swath-based) aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution and atmospherically corrected land surface products at 1.1 km resolution. The performance of the aerosol product has been validated against ground-based Aerosol Robotic Network (AERONET) observations, model comparisons, and climatological assessments. This product has played a major role in studies of the impacts of aerosols on climate and air quality. The surface product has found a variety of uses, particularly at regional scales for assessing vegetation and land surface change. A major development effort has led to the release of an update to the operational (Version 22) MISR Level 2 aerosol and land surface retrieval products, which has been in production since December 2007. The new release is designated Version 23. The resolution of the aerosol product has been increased to 4.4 km, allowing more detailed characterization of aerosol spatial variability, especially near local sources and in urban areas. The product content has been simplified and updated to include more robust measures of retrieval uncertainty and other fields to benefit users. The land surface product has also been updated to incorporate the Version 23 aerosol product as input and to improve spatial coverage, particularly over mountainous terrain and snow/ice-covered surfaces. We will describe the major upgrades incorporated in Version 23 and present validation of the aerosol product against both the standard AERONET historical database, as well as high spatial density AERONET-DRAGON deployments. Comparisons will also be shown relative to the Version 22 aerosol and land surface products. Applications enabled by these product updates will be discussed.

  6. Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

    Science.gov (United States)

    DeColstoun, Eric Brown; Huang, Chengquan; Tan, Bin; Smith, Sarah Elizabeth; Phillips, Jacqueline; Wang, Panshi; Ling, Pui-Yu; Zhan, James; Li, Sike; Taylor, Michael P.; Wolfe, Robert E.; Tilton, James C.

    2013-01-01

    Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (approx. 2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

  7. Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

    Science.gov (United States)

    Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

    2013-12-01

    Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

  8. Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

    Science.gov (United States)

    Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

    2008-01-01

    The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

  9. IDENTIFYING THE LOCAL SURFACE URBAN HEAT ISLAND THROUGH THE MORPHOLOGY OF THE LAND SURFACE TEMPERATURE

    Directory of Open Access Journals (Sweden)

    J. Wang

    2016-06-01

    Full Text Available Current characterization of the Land Surface Temperature (LST at city scale insufficiently supports efficient mitigations and adaptations of the Surface Urban Heat Island (SUHI at local scale. This research intends to delineate the LST variation at local scale where mitigations and adaptations are more feasible. At the local scale, the research helps to identify the local SUHI (LSUHI at different levels. The concept complies with the planning and design conventions that urban problems are treated with respect to hierarchies or priorities. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. The continuous and smooth latent LST is first recovered from the raw images. The Multi-Scale Shape Index (MSSI is then applied to the latent LST to extract morphological indicators. The local scale variation of the LST is quantified by the indicators such that the LSUHI can be identified morphologically. The results are promising. It can potentially be extended to investigate the temporal dynamics of the LST and LSUHI. This research serves to the application of remote sensing, pattern analysis, urban microclimate study, and urban planning at least at 2 levels: (1 it extends the understanding of the SUHI to the local scale, and (2 the characterization at local scale facilitates problem identification and support mitigations and adaptations more efficiently.

  10. The influence of aerosols and land-use type on NO2 satellite retrieval over China

    Science.gov (United States)

    Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

    2017-04-01

    Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate

  11. Land Surface Albedos Computed from BRF Measurements with a Study of Conversion Formulae

    Directory of Open Access Journals (Sweden)

    Aku Riihelä

    2010-08-01

    Full Text Available Land surface hemispherical albedos of several targets have been resolved using the bidirectional reflectance factor (BRF library of the Finnish Geodetic Institute (FGI. The library contains BRF data measured by FGI during the years 2003–2009. Surface albedos are calculated using selected BRF datasets from the library. Polynomial interpolation and extrapolation have been used in computations. Several broadband conversion formulae generally used for satellite based surface albedo retrieval have been tested. The albedos were typically found to monotonically increase with increasing zenith angle of the Sun. The surface albedo variance was significant even within each target category / surface type. In general, the albedo estimates derived using diverse broadband conversion formulas and estimates obtained by direct integration of the measured spectra were in line.

  12. Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

    Science.gov (United States)

    Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

    2014-01-01

    ) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

  13. Climatic change due to land surface alterations

    Energy Technology Data Exchange (ETDEWEB)

    Franchito, S.H.; Rao, V.B.

    1992-01-01

    A primitive equations global zonally averaged climate model is developed. The model includes biofeedback mechanisms. For the Northern Hemisphere the parameterization of biofeedback mechanisms is similar to that used by Gutman et al. For the Southern Hemisphere new parameterizations are derived. The model simulates reasonably well the mean annual zonally averaged climate and geobotanic zones. Deforestation, desertification, and irrigation experiments are performed. In the case of deforestation and desertification there is a reduction in the surface net radiation, evaporation, and precipitation and an increase in the surface temperature. In the case of irrigation experiment opposite changes occurred. In all the cases considered the changes in evapotranspiration overcome the effect of surface albedo modification. In all the experiments changes are smaller in the Southern Hemisphere.

  14. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

    Directory of Open Access Journals (Sweden)

    Offer Rozenstein

    2014-03-01

    Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

  15. Global Land Data Assimilation System

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The goal of the Global Land Data Assimilation System (GLDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface...

  16. Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (Ts) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of Ts over the diurnal cycle in non-polar regions, while polar Ts retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed Ts, along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly Ts observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived Ts data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, Ts validation with established references is essential, as is proper evaluation of Ts sensitivity to atmospheric correction source.This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based Ts product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction

  17. Global Clear-Sky Surface Skin Temperature from Multiple Satellites Using a Single-Channel Algorithm with Angular Anisotropy Corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (T(sub s)) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T(sub s) over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T(sub s) over the diurnal cycle in non-polar regions, while polar T(sub s) retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T(sub s), along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T(sub s) observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T(sub s) data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T(sub s) validation with established references is essential, as is proper evaluation of T(sub s) sensitivity to atmospheric correction source. This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T(sub s) product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve

  18. Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa; Reichl, Rolf; Harrison, Kenneth; Santanello, Joseph

    2010-01-01

    Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

  19. Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

    Science.gov (United States)

    Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

    2011-01-01

    The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

  20. Carbon Sequestration on Surface Mine Lands

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Bon Jun Koo; Richard Sweigard; Richard Warner

    2004-11-30

    The first quarter of 2004 was dedicated to tree planting activities in two locations in Kentucky. During the first year of this project there was not available mine land to plant in the Hazard area, so 107 acres were planted in the Martin County mine location. This year 120 acres were planted in the Hazard area to compensate for the prior year and an additional 57 acres were planted on Peabody properties in western Kentucky. Additional sets of special plots were established on each of these areas that contained 4800 seedlings each for carbon sequestration demonstrations. Plantings were also conducted to continue compaction and water quality studies on the newly established areas as well as continual measurements of the first year's plantings. Total plantings on this project now amount to 357 acres containing 245,960 seedlings. During the second quarter of this year monitoring systems were established for all the new research areas. Weather data pertinent to the research as well as hydrology and water quality monitoring continues to be conducted on all areas. Studies established to assess specific questions pertaining to carbon flux and the invasion of the vegetation by small mammals are being quantified. Experimental practices initiated with this research project will eventually allow for the planting on long steep slopes with loose grading systems and allow mountain top removal areas to be constructed with loose spoil with no grading of the final layers of rooting material when establishing trees for the final land use designation. Monitoring systems have been installed to measure treatment effects on both above and below ground carbon and nitrogen pools in the planting areas. Soil and tissue samples were collected from both years planting and analyses were conducted in the laboratory. Examination of decomposition and heterotropic respiration on carbon cycling in the reforestation plots continued during the reporting period. Entire planted trees were

  1. Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

    Science.gov (United States)

    Liu, Yongqiang; Mamtimin, Ali; He, Qing

    2014-05-01

    Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

  2. Ice Surface Elevation Changes in East Antarctica from Satellite Altimetry

    Science.gov (United States)

    Zwally, H. Jay; Brenner, Anita C.; DiMarzio, John

    1998-01-01

    Estimates of the overall mass balance and seasonal and inter-annual variations in the surface mass balance are obtainable from time-series of ice surface elevations measured by satellite altimetry. Beginning in 2001, NASA's ICESat laser altimeter and lidar mission will significantly improve the range accuracy, the orbit accuracy, and the spatial coverage for measurement of ice sheet elevations (to 86 S) , as compared to previous radar altimeters designed for ocean measurements The radar altimeters on Seasat and Geosat provided ice sheet measurements to 72 S, and on ERS-1 and ERS-2 to 81 S. Although radar altimetry has significant limitations in coverage (due to loss of tracking) and accuracy over sloping surfaces, information on ice-sheet surface-elevation changes has been derived for parts of Antarctica. Recently, the accuracy of the ice measurements by Seasat (3 months of 1978) and Geosat (1985 to 1989) have been improved by new calculations of the satellite orbit heights and other altimeter corrections. Residual orbit errors and inter-satellite biases are evaluated by crossover analysis and by global adjustments to an ocean surface derived from altimeter data. The standard deviation of the orbit error is less than 9 cm, and the long-term trend in the error appears to be less than 1 cm/yr. Orbit errors can be further reduced by adjustment to the ocean surface, but false signals of several cm/yr may be also introduced by the adjustments. These false signals are caused mainly by residual errors in the altimeter corrections over the ocean, and secondary by real changes in the ocean surface elevation. Maps of ice sheet elevation changes north of 72 S are derived from Seasat-Geosat crossovers and from 4.5 years of Geosat crossovers. A notable ice thinning rate of about 50 cm/yr is found at elevations below 2200 meters between 70 and 72 S to the East of the Amery ice shelf, in both the Seasat-Geosat and Geosat-Geosat time intervals Above 2200 meters, to the ridge

  3. Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gensuo

    2013-01-01

    As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

  4. Satellite observations of surface temperature during the March 2015 total solar eclipse.

    Science.gov (United States)

    Good, Elizabeth

    2016-09-28

    The behaviour of remotely sensed land surface temperatures (LSTs) from the spinning-enhanced visible and infrared imager (SEVIRI) during the total solar eclipse of 20 March 2015 is analysed over Europe. LST is found to drop by up to several degrees Celcius during the eclipse, with the minimum LST occurring just after the eclipse mid-point (median=+1.5 min). The drop in LST is typically larger than the drop in near-surface air temperatures reported elsewhere, and correlates with solar obscuration (r=-0.47; larger obscuration = larger LST drop), eclipse duration (r=-0.62; longer duration = larger LST drop) and time (r=+0.37; earlier eclipse = larger LST drop). Locally, the LST drop is also correlated with vegetation (up to r=+0.6), with smaller LST drops occurring over more vegetated surfaces. The LSTs at locations near the coast and at higher elevation are also less affected by the eclipse. This study covers the largest area and uses the most observations of eclipse-induced surface temperature drops to date, and is the first full characterization of satellite LST during an eclipse (known to the author). The methods described could be applied to Geostationary Operational Environmental Satellite (GOES) LST data over North America during the August 2017 total solar eclipse.This article is part of the themed issue 'Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse'.

  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. Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

    2015-11-01

    Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

  7. Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

    2015-01-01

    Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

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

    Science.gov (United States)

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

    2016-10-01

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

  9. Concepts and cost trade-offs for land vehicle antennas in satellite mobile communications

    Science.gov (United States)

    Haddad, H. A.

    1948-01-01

    Several antenna design concepts, operating at UHF (821 to 825 MHz transmit and 866 to 870 MHz receive bands), with gain ranging between 6 and 12 dBic, that are suitable for land mobile vehicles are presented. The antennas may be used within CONUS and ALASKA to communicate to and from a geosynchronous satellite. Depending on the type of steering mechanism, the antennas are broken down into three categories; (1) electronically scanned arrays with phase shifters, (2) electronically switched arrays with switchable power dividers/combiners, and (3) mechanically steered arrays. The operating characteristics of two of these design concepts, one a conformal antenna with electronic beam steering and the other a nonconformal design with mechanical steering, were evaluated with regard to two and three satellite system. Cost estimates of various antenna concepts were made and plotted against their overall gain performance.

  10. Sea and Land Surface Temperature Radiometer detection assembly design and performance

    Science.gov (United States)

    Coppo, Peter; Mastrandrea, Carmine; Stagi, Moreno; Calamai, Luciano; Nieke, Jens

    2014-01-01

    The Sea and Land Surface Temperature Radiometers (SLSTRs) are high-accuracy radiometers selected for the Copernicus mission Sentinel-3 space component to provide sea surface temperature (SST) data continuity with respect to previous (Advanced) Along Track Scanning Radiometers [(A)ATSRs] for climatology. Many satellites are foreseen over a 20-year period, each with a 7.5-year lifetime. Sentinel-3A will be launched in 2015 and Sentinel-3B at least six months later, implying that two identical satellites will be maintained in the same orbit with a 180-deg phase delay. Each SLSTR has an improved design with respect to AATSR affording wider near-nadir and oblique view swaths (1400 and 740 km) for SST/land surface temperature global coverage at a 1-km spatial resolution (at SSP) with a daily revisit time (with two satellites), appropriate for both climate and meteorology. Cloud screening and other products are obtained with 0.5 km spatial resolution [at sub-satellite point (SSP)] in visible and short wave infrared (SWIR) bands, while two additional channels are included to monitor high temperature events such as forest fires. The two swaths are obtained with two conical scans and telescopes combined optically at a common focus, representing the input of a cooled focal plane assembly, where nine channels are separated with dichroic and are focalized on detectors with appropriate optical relays. IR and SWIR optics/detectors are cooled to 85 K by an active mechanical cryo-cooler with vibration compensation, while the VIS ones are maintained at a stable temperature. The opto-mechanical design and the expected electro-optical performance of the focal plane assembly are described and the model predictions at system level are compared with experimental data acquired in the vacuum chamber in flight representative thermal conditions or in the laboratory.

  11. A framework for global diurnally-resolved observations of Land Surface Temperature

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2014-05-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013

  12. Satellite remote sensing applications for surface soil moisture monitoring: A review

    Institute of Scientific and Technical Information of China (English)

    Lingli WANG; John J.QU

    2009-01-01

    Surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/ atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. Recent technological advances in satellite remote sensing have shown that soil moisture can be measured by a variety of remote sensing techniques,each with its own strengths and weaknesses. This paper presents a comprehensive review of the progress in remote sensing of soil moisture, with focus on technique approaches for soil moisture estimation from optical,thermal, passive microwave, and active microwave measurements. The physical principles and the status of current retrieval methods are summarized. Limitations existing in current soil moisture estimation algorithms and key issues that have to be addressed in the near future are also discussed.

  13. Determination of Land Use from Satellite Imagery for Input to Hydrologic Models.

    Science.gov (United States)

    1980-04-01

    Symposium on Remote Sensing of thieK Environment, 23-30 April 1980, San Jose, Costa Rica 19. KEY WORDS - C=Wm*. eO I.W. EII..e.wvm I*FS Week atfm...Fourteenth International Symposium on Remote Sensing of the Environment, 23-30 April 1980, San Jose, Costa Rica DETERMINATION OF LAND USE FROM SATELLITE...Factors in Small Hydropower Planning, Darryl W. Davis, February 1979, 38 pages. #62 Flood Hydrograph and Peak Flow Frequency Analysis, Arlen D. Feldman

  14. Development of the mechanical cryocooler system for the Sea Land Surface Temperature Radiometer

    Science.gov (United States)

    Camilletti, Adam; Burgess, Christopher; Donchev, Anton; Watson, Stuart; Weatherstone Akbar, Shane; Gamo-Albero, Victoria; Romero-Largacha, Victor; Caballero-Olmo, Gema

    2014-11-01

    The Sea Land Surface Temperature Radiometer is a dual view Earth observing instrument developed as part of the European Global Monitoring for Environment and Security programme. It is scheduled for launch on two satellites, Sentinel 3A and 3B in 2014. The instrument detectors are cooled to below 85 K by two split Stirling Cryocoolers running in hot redundancy. These coolers form part of a cryocooler system that includes a support structure and drive electronics. Aspects of the system design, including control and reduction of exported vibration are discussed; and results, including thermal performance and exported vibration from the Engineering Model Cryooler System test campaign are presented.

  15. SGP Cloud and Land Surface Interaction Campaign (CLASIC): Measurement Platforms

    Energy Technology Data Exchange (ETDEWEB)

    MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; TJ Jackson; B. Kustas; PJ Lamb; G McFarquhar; Q Min; B Schmid; MS Torn; DD Tuner

    2007-06-01

    The Cloud and Land Surface Interaction Campaign (CLASIC) will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of CLASIC includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the ACRF SGP site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations. An overview of the measurement platforms that will be used during the CLASIC are described in this report. The coordination of measurements, especially as it relates to aircraft flight plans, will be discussed in the CLASIC Implementation Plan.

  16. Advancing Coastal Climate Adaptation in Denmark by Land Subsidence Mapping using Sentinel-1 Satellite Imagery

    DEFF Research Database (Denmark)

    Sørensen, Carlo Sass; Broge, Niels H.; Mølgaard, Mads R.

    2016-01-01

    There are still large uncertainties in projections of climate change and sea level rise. Here, land subsidence is an additional factor that may adversely affect the vulnerability towards floods in low-lying coastal communities. The presented study performs an initial assessment of subsidence...... mapping using Sentinel-1 satellite imagery and leveling at two coastal locations in Denmark. Within both investigated areas current subsidence rates of 5-10 millimeters per year are found. This subsidence is related to the local geology, and challenges and potentials in bringing land subsidence mapping...... and geology into climate adaptation are discussed in relation to perspectives of a national subsidence monitoring system partly based on the findings from the two coastal locations. The current lack of subsidence data and a fragmentation of geotechnical information are considered as hindrances to optimal...

  17. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

    Directory of Open Access Journals (Sweden)

    Annett Bartsch

    2016-11-01

    Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

  18. Direct determination of surface albedos from satellite imagery

    Science.gov (United States)

    Mekler, Y.; Joseph, J. H.

    1983-01-01

    An empirical method to measure the spectral surface albedo of surfaces from Landsat imagery is presented and analyzed. The empiricism in the method is due only to the fact that three parameters of the solution must be determined for each spectral photograph of an image on the basis of independently known albedos at three points. The approach is otherwise based on exact solutions of the radiative transfer equation for upwelling intensity. Application of the method allows the routine construction of spectral albedo maps from satelite imagery, without requiring detailed knowledge of the atmospheric aerosol content, as long as the optical depth is less than 0.75, and of the calibration of the satellite sensor.

  19. Constraints from atmospheric CO2 and satellite-based vegetation activity observations on current land carbon cycle trends

    Directory of Open Access Journals (Sweden)

    S. Zaehle

    2012-11-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely-sensed vegetation activity to provide a firm set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration has to pass, to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI-Earth system model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite based vegetation activity data allows to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations.

  20. CARBON SEQUESTRATION ON SURFACE MINE LANDS

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2004-08-02

    The April-June 2004 quarter was dedicated to the establishment of monitoring systems for all the new research areas. Hydrology and water quality monitoring continues to be conducted on all areas as does weather data pertinent to the research. Studies assessing specific questions pertaining to carbon flux has been established and the invasion of the vegetation by small mammals is being quantified. The approval of two experimental practices associated with this research by the United States Office of Surface Mining was a major accomplishment during this period of time. These experimental practices will eventually allow for tree planting on long steep slopes with loose grading systems and for the use of loose dumped spoil on mountain top removal areas with no grading in the final layer of rooting material for tree establishment.

  1. Land mobile satellite communication system. Volume 2: Traffic analysis and market demand for the land mobile communications system in the European scenario

    Science.gov (United States)

    Carnebianca, C.; Pavesi, B.; Tuozzi, A.; Capone, R.

    1986-06-01

    The socioeconomic desirability in terms of market demand, technical economic feasibility, and price-performance for a Land Mobile Communication system ground based and/or satellite aided, able to satisfy the request of the traffic demand, foreseable in the 1995-2005 time frame, for the Western European countries was assessed. The criterion of economic value of the mobile system is considered as the driving element. The presence of gaps in the terrestrial system and reasonable traffic extrapolations suggest a very attractive role for a land mobile satellite communications mission.

  2. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  3. Complementing geotechnical slope stability and land movement analysis using satellite DInSAR

    Science.gov (United States)

    Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Papadaki, Eirini; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis

    2014-03-01

    This paper explores the potential of using satellite radar inteferometry to monitor time-varying land movement prior to any visible tension crack signs. The idea was developed during dedicated geotechnical studies at a large open-pit lignite mine, where large slope movements (10-20 mm/day) were monitored and large fissures were observed in the immediate area outside the current pit limits. In this work, differential interferometry (DInSAR), using Synthetic Aperture Radar (SAR) ALOS images, was applied to monitor the progression of land movement that could potentially thwart mine operations. Early signs of land movements were captured by this technique well before their visual observation. Moreover, a qualitative comparison of DInSAR and ground geodetic measurements indicates that the technique can be used for the identification of high risk areas and, subsequently, for the optimization of the spatial distribution of the available ground monitoring equipment. Finally, quantitative land movement results from DInSAR are shown to be in accordance with simultaneous measurements obtained by ground means.

  4. The impact of land and sea surface variations on the Delaware sea breeze at local scales

    Science.gov (United States)

    Hughes, Christopher P.

    The summertime climate of coastal Delaware is greatly influenced by the intensity, frequency, and location of the local sea breeze circulation. Sea breeze induced changes in temperature, humidity, wind speed, and precipitation influence many aspects of Delaware's economy by affecting tourism, farming, air pollution density, energy usage, and the strength, and persistence of Delaware's wind resource. The sea breeze front can develop offshore or along the coastline and often creates a near surface thermal gradient in excess of 5°C. The purpose of this dissertation is to investigate the dynamics of the Delaware sea breeze with a focus on the immediate coastline using observed and modeled components, both at high resolutions (~200m). The Weather Research and Forecasting model (version 3.5) was employed over southern Delaware with 5 domains (4 levels of nesting), with resolutions ranging from 18km to 222m, for June 2013 to investigate the sensitivity of the sea breeze to land and sea surface variations. The land surface was modified in the model to improve the resolution, which led to the addition of land surface along the coastline and accounted for recent urban development. Nine-day composites of satellite sea surface temperatures were ingested into the model and an in-house SST forcing dataset was developed to account for spatial SST variation within the inland bays. Simulations, which include the modified land surface, introduce a distinct secondary atmospheric circulation across the coastline of Rehoboth Bay when synoptic offshore wind flow is weak. Model runs using high spatial- and temporal-resolution satellite sea surface temperatures over the ocean indicate that the sea breeze landfall time is sensitive to the SST when the circulation develops offshore. During the summer of 2013 a field campaign was conducted in the coastal locations of Rehoboth Beach, DE and Cape Henlopen, DE. At each location, a series of eleven small, autonomous thermo-sensors (i

  5. Satellite-Supported Modeling of the Relationships between Urban Heat Island and Land Use/Cover Changes

    Science.gov (United States)

    Vahmani, P.; Ban-Weiss, G. A.

    2015-12-01

    Reliable assessment of the primary causes of urban heat island (UHI) and the efficiency of various heat mitigation strategies requires accurate prediction of urban temperatures and realistic representation of land surface physical characteristics in models. In this study, we expand the capabilities of the Weather Research and Forecasting (WRF) model and the Urban Canopy Model (UCM) by implementing high-resolution real-time satellite observations of green vegetation fraction (GVF), leaf area index (LAI), and albedo. We use MODIS-based GVF, LAI, and albedo to replace constant values that are assumed for urban pixels and climatological values that are used for non-urban pixels in the default WRF-UCM. Utilizing the improved model, summertime climate of Los Angeles is simulated over the span of three years (2010-2012). Next, thermal sensitivity of urban climate to anthropogenic land use/cover is assessed via replacing current urban cover with pre-development vegetation cover, consisting of shrubland and grassland. Surrounding undeveloped areas and inverse distance weighting method are utilized to estimate GVF and LAI of pre-development vegetation cover. Our analysis of diurnal and nocturnal surface and air temperatures shows cooling effects of urbanization in neighborhoods with high fractions of irrigated vegetation. However, urban warming is consistently detected over industrial/commercial and high-intensity residential areas. In addition to well-known mechanisms such as a shift in surface energy partitioning, high heat storage in urban material, and inefficiency of urban surfaces in transferring convective heat from the surface to the boundary layer, our results show decreased wind speed and sea breeze also contribute to the UHI intensity. We further evaluate the interactions between UHI and replacing irrigated and imported vegetation with non-irrigated native vegetation as a water conservation strategy in water-stressed Los Angeles metropolitan area.

  6. Simulation Experiments of Land Surface Physical Processes and Ecological Effect over Different Underlying Surface

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    Based on the existing Land Surface Physical Process Models(Deardorff, Dickinson, LIU, Noilhan, Seller, ZHAO), a Comprehensive Land Surface Physical Process Model (CLSPPM) is developed by considering the different physical processes of the earth's surface-vegetation-atmosphere system more completely. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feas...

  7. Carbon Sequestration on Surface Mine Lands

    Energy Technology Data Exchange (ETDEWEB)

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2005-10-02

    During this quarter a general forest monitoring program was conducted to measure treatment effects on above ground and below ground carbon C and Nitrogen (N) pools for the tree planting areas. Detailed studies to address specific questions pertaining to Carbon cycling was initiated with the development of plots to examine the influence of mycorrhizae, spoil chemical and mineralogical properties, and use of amendment on forest establishment and carbon sequestration. Efforts continued during this period to examine decomposition and heterotrophic respiration on C cycling in the reforestation plots. Projected climate change resulting from elevated atmospheric carbon dioxide has given rise to various strategies to sequester carbon in various terrestrial ecosystems. Reclaimed surface mine soils present one such potential carbon sink where traditional reclamation objectives can complement carbon sequestration. New plantings required the modification and design and installation on monitoring equipment. Maintenance and data monitoring on past and present installations are a continuing operation. The Department of Mining Engineering continued the collection of penetration resistance, penetration depth, and bulk density on both old and new treatment areas. Data processing and analysis is in process for these variables. Project scientists and graduate students continue to present results at scientific meetings, tours and field days presentations of the research areas are being conducted on a request basis.

  8. Land Surface Temperature retrieval from Sentinel 2 and 3 Missions: a conceptual framework

    Science.gov (United States)

    Sobrino, J. A.; Jimenez-Muñoz, J. C.; Ruescas, A.; Brockmann, C.; Heckel, A.; North, P. R. J.; Remedios, J. J.; Darren, G.; Merchant, C.; Berger, M.; Soria, G.; Danne, O.

    2012-04-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all the surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. Because of the strong heterogeneity in land surface characteristics such as vegetation, topography and soil physical properties, LST changes rapidly in space as well as in time. An adequate characterization of LST distribution and its temporal evolution, therefore, requires measurements with detailed spatial and temporal frequencies. With the advent of the ESA's Sentinel 2 and 3 series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVISAT satellite. For this purpose, the high spatial resolution data from Sentinel2/MSI will be used for a good characterization of the land surface sub-pixel heterogeneity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual-view available in the SLTSR instrument, will allow a better atmospheric correction through improved aerosol/water vapor content retrievals and the implementation of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accurate LST retrievals using the SLTSR thermal bands by developing a synergistic split-window/dual-angle algorithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as a benchmark for the future OLCI

  9. High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

    Science.gov (United States)

    Shin, S.; Pokhrel, Y. N.

    2016-12-01

    Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

  10. Improved meteorology and ozone air quality simulations using MODIS land surface parameters in the Yangtze River Delta urban cluster, China

    Science.gov (United States)

    Li, Mengmeng; Wang, Tijian; Xie, Min; Zhuang, Bingliang; Li, Shu; Han, Yong; Song, Yu; Cheng, Nianliang

    2017-03-01

    Land surface parameters play an important role in the land-atmosphere coupling and thus are critical to the weather and dispersion of pollutants in the atmosphere. This work aims at improving the meteorology and air quality simulations for a high-ozone (O3) event in the Yangtze River Delta urban cluster of China, through incorporation of satellite-derived land surface parameters. Using Moderate Resolution Imaging Spectroradiometer (MODIS) input to specify the land cover type, green vegetation fraction, leaf area index, albedo, emissivity, and deep soil temperature provides a more realistic representation of surface characteristics. Preliminary evaluations reveal clearly improved meteorological simulation with MODIS input compared with that using default parameters, particularly for temperature (from -2.5 to -1.7°C for mean bias) and humidity (from 9.7% to 4.3% for mean bias). The improved meteorology propagates through the air quality system, which results in better estimates for surface NO2 (from 11.5 to 8.0 ppb for mean bias) and nocturnal O3 low-end concentration values (from -18.8 to -13.6 ppb for mean bias). Modifications of the urban land surface parameters are the main reason for model improvement. The deeper urban boundary layer and intense updraft induced by the urban heat island are favorable for pollutant dilution, thus contributing to lower NO2 and elevated nocturnal O3. Furthermore, the intensified sea-land breeze circulation may exacerbate O3 pollution at coastal cities through pollutant recirculation. Improvement of mesoscale meteorology and air quality simulations with satellite-derived land surface parameters will be useful for air pollution monitoring and forecasting in urban areas.

  11. Evaluation of ESTARFM based algorithm for generating land surface temperature products by fusing ASTER and MODIS data during the HiWATER-MUSOEXE

    Science.gov (United States)

    Land surface temperature (LST) is an important parameter that is highly responsive to surface energy fluxes and has become valuable to many disciplines. However, it is difficult to acquire satellite LSTs with both high spatial and temporal resolutions due to tradeoffs between them. Thus, various alg...

  12. Evaluation of Development and Changes in Land Use using Different Satellite Image Processing and Remote Sensing Techniques (Case Study: Kermanshah, Iran

    Directory of Open Access Journals (Sweden)

    Mohammad Maleky

    2013-10-01

    Full Text Available Currently the largest city in the western Iran, Kermanshah enjoys fast growing trend because of its strategic location. Remote sensing and satellite imagery are well suited for assessing the changes in land use over different time periods. In this study, satellite images from Landsat TM sensor and ETM sensor have been prepared during 1987 and 2007 as geometric and radiometric corrections have been made to them. The process was followed by selecting the best combination of false color by using Optimal Index Factor (OIF in ILWIS software. Greenness, brightness and wetness indexes along with NDVI index of land cover were then derived in each period using Fuzzy Art map Supervised Classification, Principal Components Analysis and Tasseled-cap Transformation. The results indicated that Pca2 index can properly demonstrate increasing and decreasing changes among the main components as greenness index can display decreasing and no changes in land uses among tasseled-cap components, while the wetness index would reflect increasing changes in land use with high accuracy. Moreover, the precision and results of NDVI index is so close to that of greenness index. The overall results of the study suggest that the urban surface area is annually increased at a rate of 109.6 ha, which was a major decline in agricultural and range land use.

  13. Mapping of land cover in northern California with simulated hyperspectral satellite imagery

    Science.gov (United States)

    Clark, Matthew L.; Kilham, Nina E.

    2016-09-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands

  14. Fade measurements at L-band and UHF in mountainous terrain for land mobile satellite systems

    Science.gov (United States)

    Vogel, Wolfhard J.; Goldhirsh, Julius

    1988-01-01

    Fading results related to land mobile satellite communications at L-band (1502 MHz) and UHF (870 MHz) are described. These results were derived from an experiment performed in a series of canyon passes in the Boulder, Colorado region of the US. The experimental configuration involved a helicopter as the source platform, which maintained a relatively fixed geometry with a mobile van containing the receiver and data-acquisition system. An unobstructed line of sight between the radiating sources and the receiving van was, for the most part, also maintained. In this configuration, the dominant mechanism causing signal fading (or enhancement) is a result of multipath. The resulting fade distributions demonstrated that at the 1 percent and 5 percent levels, 5.5- and 2.6-dB fades were on the average exceeded at L-band and 4.8- and 2.4-dB at UHF, respectively, for a path elevation angle of 45 deg. The canyon results as compared with previous roadside-tree-shadowing results demonstrate that the deciding factor dictating fade margin for future land mobile satellite systems is tree shadowing rather than fades caused by multipath.

  15. Land Cover and Seasonality Effects on Biomass Burning Emissions and Air Quality Impacts Observed from Satellites

    Science.gov (United States)

    Zoogman, P.; Hoffman, A.; Gonzalez Abad, G.; Miller, C. E.; Nowlan, C. R.; Huang, G.; Liu, X.; Chance, K.

    2016-12-01

    Trace gas emissions from biomass burning can vary greatly both regionally and from event to event, but our current scientific understanding is unable to fully explain this variability. The large uncertainty in ozone formation resulting from fire emissions has posed a great challenge for assessing fire impacts on air quality and atmospheric composition. Satellite observations from OMI offer a powerful tool to observe biomass burning events by providing observations globally over a range of environmental conditions that effect emissions of NOx, formaldehyde, and glyoxal. We have investigated the seasonal relationship of biomass burning enhancements of these trace gases derived from OMI observations over tropical South America, Africa, and Indonesia. Land cover type (also derived from satellite observations) has a significant impact on formaldehyde and glyoxal enhancements from fire activity. We have found that the chemical ratio between formaldehyde and glyoxal is dependent on the burned land type and will present our current hypotheses for the spatial variation of this ratio in the tropics. Furthermore, in individual case studies we will investigate how these chemical ratios can inform our knowledge of the secondary formation of ozone, particularly during exceptional pollution events.

  16. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 x 0.5 latitude-longitude resolution for the period from 1948 to the...

  17. Determining Land-Surface Parameters from the ERS Wind Scatterometer

    NARCIS (Netherlands)

    Woodhouse, I.H.; Hoekman, D.H.

    2000-01-01

    The ERS-1 wind scatterometer (WSC) has a resolution cell of about 50 km but provides a high repetition rate (less than four days) and makes measurements at multiple incidence angles. In order to retrieve quantitative geophysical parameters over land surfaces using this instrument, a method is presen

  18. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 0.5 latitude-longitude resolution for the period from 1948 to the present...

  19. Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

    Directory of Open Access Journals (Sweden)

    F. Alkhaier

    2012-07-01

    Full Text Available The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Moreover, these measurements can help to include the effect of shallow groundwater on surface energy balance within land surface models and climate studies, which broadens the methods that yield more reliable and informative results. To examine the capacity of MODIS in detecting the effect of shallow groundwater on land surface temperature and the surface energy balance in an area within Al-Balikh River basin in northern Syria, we studied the interrelationship between in-situ measured water table depths and land surface temperatures measured by MODIS. We, also, used the Surface Energy Balance System (SEBS to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. We found out that the daytime temperature increased while the nighttime temperature decreased when the depth of the water table increased. And, when the water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. This concords with the findings of a companion paper (Alkhaier et al., 2012. The observed clear relationships were the result of meeting both conditions that were concluded in the companion paper, i.e. high potential evaporation and big contrast in day-night temperature. Moreover, the prevailing conditions in this study area helped SEBS to yield accurate estimates. Under bare soil conditions and under the prevailing weather conditions, we conclude that MODIS is suitable for detecting the effect of shallow groundwater because it has proper imaging times and adequate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

  20. A global assessment of the local impacts of land cover changes on the surface energy budget

    Science.gov (United States)

    Cescatti, A.; Duveiller, G.; Hooker, J.

    2016-12-01

    Biophysical effects of land use and land cover change (LULCC) on climate have received less attention than biogeochemical effects. Yet, their impact is potentially more perceptible because the effect is almost immediate at local scales. Biophysical effects depend on the specific LULCC transition, and can change in sign and magnitude across space and time. Spatially explicit assessments are therefore required to describe these phenomena. Whilst accurately characterising these local biophysical effects using Land Surface Models (LSMs) can be problematic given the strong modelling assumptions that must be made, satellite remote sensing instruments operationally measure several of the key energy fluxes at high temporal and spatial resolution across the entire planet. We leverage this synoptic property of remote sensing to develop a methodology capable of isolating the biophysical signal of potential vegetation transitions at local scale. Because mapping LULCC accurately at global scale is notoriously challenging, and because many potential transitions may not yet have occurred in various places, the approach relies on trading space for time over a moving window as a surrogate for monitoring real change. The result is a global dataset with a spatial resolution of 1° indicating the potential change in all terms of the surface energy balance (excepting the soil heat flux) for all transitions amongst 7 different plant functional types that are widely used by the land surface modelling community. This dataset will serve three main purposes: (1) to derive a data-driven diagnostic of the local biophysical effects of LULCC on the surface energy budget and local climate; (2) to provide a benchmark to assess model performances; and (3) to develop guidelines for the monitoring, reporting and verification of climate mitigation and adaptation plans that account for land biophysical impacts on climate.

  1. Subsurface Emission Effects in AMSR-E Measurements: Implications for Land Surface Microwave Emissivity Retrieval

    Science.gov (United States)

    Galantowicz, John F.; Moncet, Jean-Luc; Liang, Pan; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher

    2011-01-01

    An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions

  2. Inter-Comparison of In-Situ Sensors for Land Surface Temperature Measurements

    Science.gov (United States)

    Krishnan, P.; Kochendorfer, J.; Meyers, T. P.; Guillevic, P. C.; Hook, S. J.

    2014-12-01

    Land Surface Temperature (LST) is a key variable in the determination of land surface processes from local to global scales. It has been identified as one of the most important environmental data records and is widely used in meteorological, climatological, hydrological, ecological, biophysical, and biochemical studies. Despite its importance, accurate in-situ measurements of LST are not yet available for the whole globe and are not routinely conducted at weather stations along with standard meteorological observations, with few exceptions including NOAA's United States Climate Reference Network. Even though satellite radiometric measurements of LST are a powerful tool, there are still large uncertainties associated with the retrieval of remotely sensed LST measurements. To improve confidence in the methods, algorithms, and parameters used to derive remotely sensed LST, validation of satellite data using high-quality ground-based measurements is required. With the objective of improving the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based measurements, intensive experiments were conducted at NOAA/ATDD in Oak ridge, TN from September 2013 to 2014. During the study period, multiple measurements of land surface skin temperature were made using infra-red temperature sensors - including the JPL radiometer, two models of Apogee infrared radiometers, and thermocouples embedded in the ground surface. In addition, aspirated air temperature and four-band net radiation measurements were also made. Overall the in situ LST measurements from the different sensors were in good agreement with each other, with a correlation coefficient of ~1 and root mean square error of <1 oC.

  3. Object-based Dimensionality Reduction in Land Surface Phenology Classification

    Directory of Open Access Journals (Sweden)

    Brian E. Bunker

    2016-11-01

    Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

  4. The impact of land use on microbial surface water pollution.

    Science.gov (United States)

    Schreiber, Christiane; Rechenburg, Andrea; Rind, Esther; Kistemann, Thomas

    2015-03-01

    Our knowledge relating to water contamination from point and diffuse sources has increased in recent years and there have been many studies undertaken focusing on effluent from sewage plants or combined sewer overflows. However, there is still only a limited amount of microbial data on non-point sources leading to diffuse pollution of surface waters. In this study, the concentrations of several indicator micro-organisms and pathogens in the upper reaches of a river system were examined over a period of 16 months. In addition to bacteria, diffuse pollution caused by Giardia lamblia and Cryptosporidium spp. was analysed. A single land use type predestined to cause high concentrations of all microbial parameters could not be identified. The influence of different land use types varies between microbial species. The microbial concentration in river water cannot be explained by stable non-point effluent concentrations from different land use types. There is variation in the ranking of the potential of different land use types resulting in surface water contamination with regard to minimum, median and maximum effects. These differences between median and maximum impact indicate that small-scale events like spreading manure substantially influence the general contamination potential of a land use type and may cause increasing micro-organism concentrations in the river water by mobilisation during the next rainfall event. Copyright © 2014 Elsevier GmbH. All rights reserved.

  5. 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.

  6. Spatial and Quantitative Comparison of Satellite-Derived Land Cover Products over China

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gen-Suo

    2012-01-01

    Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer (MODIS), Global Land Cover 2000 (GLC2000), and the National Land Cover/Use Data- sets (NLCD) products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.

  7. Use of Landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey.

    Science.gov (United States)

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2°C) in the Salt Lake Basin area during the 28-year period (1984-2011). Analysis of air temperature data also showed increases at a rate of 1.5-2°C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  8. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  9. Visir-Sat - a Prospective Micro-Satellite Based Multi-Spectral Thermal Mission for Land Applications

    Science.gov (United States)

    Ruecker, G.; Menz, G.; Heinemann, S.; Hartmann, M.; Oertel, D.

    2015-04-01

    Current space-borne thermal infrared satellite systems aimed at land surface remote sensing retain some significant deficiencies, in particular in terms of spatial resolution, spectral coverage, number of imaging bands and temperature-emissivity separation. The proposed VISible-to-thermal IR micro-SATellite (VISIR-SAT) mission addresses many of these limitations, providing multi-spectral imaging data with medium-to-high spatial resolution (80m GSD from 800 km altitude) in the thermal infrared (up to 6 TIR bands, between 8 and 11μm) and in the mid infrared (1 or 2 MIR bands, at 4μm). These MIR/TIR bands will be co-registered with simultaneously acquired high spatial resolution (less than 30 m GSP) visible and near infrared multi-spectral imaging data. To enhance the spatial resolution of the MIR/TIR multi-spectral imagery during daytime, data fusion methods will be applied, such as the Multi-sensor Multi-resolution Technique (MMT), already successfully tested over agricultural terrain. This image processing technique will make generation of Land Surface Temperature (LST) EO products with a spatial resolution of 30 x 30 m2 possible. For high temperature phenomena such as vegetation- and peat-fires, the Fire Disturbance Essential Climate Variables (ECV) "Active fire location" and "Fire Radiative Power" will be retrieved with less than 100 m spatial resolution. Together with the effective fire temperature and the spatial extent even for small fire events the innovative system characteristics of VISIR-SAT go beyond existing and planned IR missions. The comprehensive and physically high-accuracy products from VISIR-SAT (e.g. for fire monitoring) may synergistically complement the high temperature observations of Sentinel-3 SLSTR in a unique way. Additionally, VISIR-SAT offers a very agile sensor system, which will be able to conduct intelligent and flexible pointing of the sensor's line-of-sight with the aim to provide global coverage of cloud free imagery every 5

  10. THE EFFECT OF LANDING SURFACE ON THE PLANTAR KINETICS OF CHINESE PARATROOPERS USING HALF-SQUAT LANDING

    Directory of Open Access Journals (Sweden)

    Yi Li

    2013-09-01

    Full Text Available The objective of the study was to determine the effect of landing surface on plantar kinetics during a half-squat landing. Twenty male elite paratroopers with formal parachute landing training and over 2 years of parachute jumping experience were recruited. The subjects wore parachuting boots in which pressure sensing insoles were placed. Each subject was instructed to jump off a platform with a height of 60 cm, and land on either a hard or soft surface in a half-squat posture. Outcome measures were maximal plantar pressure, time to maximal plantar pressure (T-MPP, and pressure-time integral (PTI upon landing on 10 plantar regions. Compared to a soft surface, hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. Shorter T- MPP was found during hard surface landing in the 1st and 2nd metatarsal and medial rear foot. Landing on a hard surface landing resulted in a lower PTI than a soft surface in the 1stphalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the1st to 4thmetatarsal region for hard surface landing, and the 1stphalangeal and 5thmetatarsal region for soft surface landing

  11. Surface radiation at sea validation of satellite-derived data with shipboard measurements

    Directory of Open Access Journals (Sweden)

    Hein Dieter Behr

    2009-03-01

    Full Text Available Quality-controlled and validated radiation products are the basis for their ability to serve the climate and solar energy community. Satellite-derived radiation fluxes are well preferred for this task as they cover the whole research area in time and space. In order to monitor the accuracy of these data, validation with well maintained and calibrated ground based measurements is necessary. Over sea, however, long-term accurate reference data sets from calibrated instruments recording radiation are scarce. Therefore data from research vessels operating at sea are used to perform a reasonable validation. A prerequisite is that the instruments on board are maintained as well as land borne stations. This paper focuses on the comparison of radiation data recorded on board of the German Research Vessel "Meteor" during her 13 months cruise across the Mediterranean and the Black Sea with CM-SAF products using NOAA- and MSG-data (August 2006-August 2007: surface incoming short-wave radiation (SIS and surface downward long-wave radiation (SDL. Measuring radiation fluxes at sea causes inevitable errors, e.g.shadowing of fields of view of the radiometers by parts of the ship. These ship-inherent difficulties are discussed at first. A comparison of pairs of ship-recorded and satellite-derived mean fluxes for the complete measuring period delivers a good agreement: the mean bias deviation (MBD for SIS daily means is −7.6 W/m2 with a median bias of −4 W/m2 and consistently the MBD for monthly means is −7.3 W/m2, for SDL daily means the MBD is 8.1 and 6 W/m2 median bias respectively. The MBD for monthly means is 8.2 W/m2. The variances of the daily means (ship and satellite have the same annual courses for both fluxes. No significant dependence of the bias on the total cloud cover recorded according to WMO (1969 has been found. The results of the comparison between ship-based observations and satellite retrieved surface radiation reveal the good accuracy

  12. Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

    Science.gov (United States)

    de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

    2013-12-01

    Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of

  13. Attenuating the surface Urban Heat Island within the Local Thermal Zones through land surface modification.

    Science.gov (United States)

    Wang, Jiong; Ouyang, Wanlu

    2017-02-01

    Inefficient mitigation of excessive heat is attributed to the discrepancy between the scope of climate research and conventional planning practice. This study approaches this problem at both domains. Generally, the study, on one hand, claims that the climate research of the temperature phenomenon should be at local scale, where implementation of planning and design strategies can be more feasible. On the other hand, the study suggests that the land surface factors should be organized into zones or patches, which conforms to the urban planning and design manner. Thus in each zone, the land surface composition of those excessively hot places can be compared to the zonal standard. The comparison gives guidance to the modification of the land surface factors at the target places. Specifically, this study concerns the Land Surface Temperature (LST) in Wuhan, China. The land surface is classified into Local Thermal Zones (LTZ). The specifications of temperature sensitive land surface factors are relative homogeneous in each zone and so is the variation of the LST. By extending the city scale analysis of Urban Heat Island into local scale, the Local Surface Urban Heat Islands (LSUHIs) are extracted. Those places in each zone that constantly maintain as LSUHI and exceed the homogenous LST variation are considered as target places or hotspots with higher mitigation or adaptation priority. The operation is equivalent to attenuate the abnormal LST variation in each zone. The framework is practical in the form of prioritization and zoning, and mitigation strategies are essentially operated locally.

  14. Environmental impact classification with fuzzy sets for urban land cover from satellite remote sensing data

    Science.gov (United States)

    Zoran, Maria A.; Nicolae, Doina N.; Talianu, Camelia

    2004-10-01

    Urban area is a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in urban's land cover are due to natural and anthropogenic causes. A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic, dynamics processes, and climatic change effects. Synergetic use of quasi-simultaneously acquired multi-sensor data may therefore allow for a better approach of change detection and environmental impact classification and assessment in urban area. It is difficult to quantify the environmental impacts of human and industrial activities in urban areas. There are often many different indicators than can conflict with each other, frequently important observations are lacking, and potentially valuable information may non-quantitative in nature. Fuzzy set theory offers a modern methodology for dealing with these problems and provides useful approach to difficult classification problems for satellite remote sensing data. This paper describes how fuzzy logic can be applied to analysis of environmental impacts for urban land cover. Based on classified Landsat TM, SPOT images and SAR ERS-1 for Bucharest area, Romania, it was performed a land cover classification and subsequent environmental impact analysis.

  15. Passive remote sensing of the atmospheric water vapour content above land surfaces

    Science.gov (United States)

    Bartsch, B.; Bakan, S.; Fischer, J.

    The global distribution of the atmospheric water vapour content plays an important role in the weather forecast and climate research. Nowadays there exist various methods dealing with remote sensing of the atmospheric water vapour content. Unfortunately, most of them are restricted to ocean areas, since, in general, the emission of land surfaces is not known well enough. Therefore, a new method is developed which allows the detection of the atmospheric total water vapour content from aircraft or satellite with the aid of backscattered solar radiation in the near infrared above land surfaces. The Matrix-Operator-Method has been used to simulate backscattered solar radiances, including various atmospheric profiles of temperature, pressure, water vapour, and aerosols of various types, several sun zenith angles, and different types of land surfaces. From these calculations it can be concluded, that the detection of water vapour content in cloudless atmospheres is possible with an error of < 10 % even for higher aerosol contents. In addition to the theoretical results first comparisons with aircraft measurements of the backscattered solar radiances are shown. These measurements have been carried out with the aid of OVID (Optical Visible and near Infrared Detector), a new multichannel array spectrometer, in 1993.

  16. Vegetation, land surface brightness, and temperature dynamics after aspen forest die-off

    Science.gov (United States)

    Huang, Cho-ying; Anderegg, William R. L.

    2014-07-01

    Forest dynamics following drought-induced tree mortality can affect regional climate through biophysical surface properties. These dynamics have not been well quantified, particularly at the regional scale, and are a large uncertainty in ecosystem-climate feedback. We investigated regional biophysical characteristics through time (1995-2011) in drought-impacted (2001-2003), trembling aspen (Populus tremuloides Michx.) forests by utilizing Landsat time series green and brown vegetation cover, surface brightness (total shortwave albedo), and daytime land surface temperature. We quantified the temporal dynamics and postdrought recovery of these characteristics for aspen forests experiencing severe drought-induced mortality in the San Juan National Forest in southwestern Colorado, USA. We partitioned forests into three categories from healthy to severe mortality (Healthy, Intermediate, and Die-off) by referring to field observations of aspen canopy mortality and live aboveground biomass losses. The vegetation cover of die-off areas in 2011 (26.9% of the aspen forest) was significantly different compared to predrought conditions (decrease of 7.4% of the green vegetation cover and increase of 12.1% of the brown vegetation cover compared to 1999). The surface brightness of the study region 9 years after drought however was comparable to predrought estimates (12.7-13.7%). Postdrought brightness was potentially influenced by understory shrubs, since they became the top layer green canopies in disturbed sites from a satellite's point of view. Satellite evidence also showed that the differences of land surface temperature among the three groups increased substantially (≥45%) after drought, possibly due to the reduction of plant evapotranspiration in the Intermediate and Die-off sites. Our results suggest that the mortality-affected systems have not recovered in terms of the surface biophysical properties. We also find that the temporal dynamics of vegetation cover holds

  17. On the Potential Predictability of Seasonal Land-Surface Climate

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J

    2001-10-01

    The chaotic behavior of the continental climate of an atmospheric general circulation model is investigated from an ensemble of decadal simulations with common specifications of radiative forcings and monthly ocean boundary conditions, but different initial states of atmosphere and land. The variability structures of key model land-surface processes appear to agree sufficiently with observational estimates to warrant detailed examination of their predictability on seasonal time scales. This predictability is inferred from several novel measures of spatio-temporal reproducibility applied to eleven model variables. The reproducibility statistics are computed for variables in which the seasonal cycle is included or excluded, the former case being most pertinent to climate model simulations, and the latter to predictions of the seasonal anomalies. Because the reproducibility metrics in the latter case are determined in the context of a ''perfectly'' known ocean state, they are properly viewed as estimates of the potential predictability of seasonal climate. Inferences based on these reproducibility metrics are shown to be in general agreement with those derived from more conventional measures of potential predictability. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is considerably higher in the Tropics; its spatial reproducibility also fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation phenomenon. However, the detailed sensitivities to initial conditions depend somewhat on the land-surface process: pressure and temperature anomalies exhibit the highest temporal reproducibilities, while hydrological and turbulent flux anomalies show the highest spatial

  18. Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

    Science.gov (United States)

    Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

    2017-06-01

    Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with

  19. Land Mobile Satellite Service (LMSS): A conceptual system design and identification of the critical technologies. Part 1: Executive summary

    Science.gov (United States)

    Naderi, F. (Editor)

    1982-01-01

    A system design for a satellite aided land mobile service is described. The advanced system is based on a geostationary satellite which employs a large UHF reflector to communicate with small user antennas on mobile vehicles. It is shown that the system through multiple beam antennas and frequency reuse provides for radiotelephone and dispatch channels. It is concluded that the system is technologically feasible to provide service to rural and remote regions.

  20. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  1. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  2. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  3. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  4. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  5. The effect of landing surface on the plantar kinetics of chinese paratroopers using half-squat landing.

    Science.gov (United States)

    Li, Yi; Wu, Ji; Zheng, Chao; Huang, Rong Rong; Na, Yuhong; Yang, Fan; Wang, Zengshun; Wu, Di

    2013-01-01

    The objective of the study was to determine the effect of landing surface on plantar kinetics during a half-squat landing. Twenty male elite paratroopers with formal parachute landing training and over 2 years of parachute jumping experience were recruited. The subjects wore parachuting boots in which pressure sensing insoles were placed. Each subject was instructed to jump off a platform with a height of 60 cm, and land on either a hard or soft surface in a half-squat posture. Outcome measures were maximal plantar pressure, time to maximal plantar pressure (T-MPP), and pressure-time integral (PTI) upon landing on 10 plantar regions. Compared to a soft surface, hard surface produced higher maximal plantar pressure in the 1(st) to 4(th) metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5(th) metatarsal region. Shorter T- MPP was found during hard surface landing in the 1(st) and 2(nd) metatarsal and medial rear foot. Landing on a hard surface landing resulted in a lower PTI than a soft surface in the 1(st)phalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the1(st) to 4(th)metatarsal region for hard surface landing, and the 1(st)phalangeal and 5(th)metatarsal region for soft surface landing. Key PointsUnderstanding plantar kinetics during the half-squat landing used by Chinese paratroopers can assist in the design of protective footwear.Compared to landing on a soft surface, a hard surface produced higher maximal plantar pressure in the 1(st) to 4(th) metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5(th) metatarsal region.A shorter time to maximal plantar pressure was found during a hard surface landing in the 1(st) and 2(nd) metatarsals and medial rear foot.Landing on a hard surface resulted in a lower pressure-time integral than landing on a soft surface in the 1(st) phalangeal region.For Chinese paratroopers, specific foot prosthesis should be designed to protect

  6. Retrieving Land Surface Temperature and Emissivity from Multispectral and Hyperspectral Thermal Infrared Instruments

    Science.gov (United States)

    Hook, Simon; Hulley, Glynn; Nicholson, Kerry

    2017-04-01

    Land Surface Temperature and Emissivity (LST&E) data are critical variables for studying a variety of Earth surface processes and surface-atmosphere interactions such as evapotranspiration, surface energy balance and water vapor retrievals. LST&E have been identified as an important Earth System Data Record (ESDR) by NASA and many other international organizations Accurate knowledge of the LST&E is a key requirement for many energy balance models to estimate important surface biophysical variables such as evapotranspiration and plant-available soil moisture. LST&E products are currently generated from sensors in low earth orbit (LEO) such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites as well as from sensors in geostationary Earth orbit (GEO) such as the Geostationary Operational Environmental Satellites (GOES) and airborne sensors such as the Hyperspectral Thermal Emission Spectrometer (HyTES). LST&E products are generated with varying accuracies depending on the input data, including ancillary data such as atmospheric water vapor, as well as algorithmic approaches. NASA has identified the need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. We will discuss the different approaches that can be used to retrieve surface temperature and emissivity from multispectral and hyperspectral thermal infrared sensors using examples from a variety of different sensors such as those mentioned, and planned new sensors like the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Hyperspectral Infrared Imager (HyspIRI). We will also discuss a project underway at NASA to develop a single unified product from some the individual sensor products and assess the errors associated with the product.

  7. Using remotely sensed data to estimate area-averaged daily surface fluxes over a semi-arid mixed agricultural land

    OpenAIRE

    2008-01-01

    Optical remote sensing has been widely used for diagnostics of land surface atmosphere exchanges, including evapotranspiration (ET). Estimating ET now benefits from modeling maturity at local scale, while ongoing challenges include both spatial and temporal issues: influences of spatial heterogeneities on non-linear behavior when upscaling and extrapolation of instantaneous estimates at satellite overpass to the daily scale. Both issues are very important when using remote sensing for managin...

  8. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2014-09-01

    Full Text Available Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a high spatio–temporal resolution is currently very scarce. This paper proposes a method for deriving land surface albedo with a high spatio–temporal resolution (space: 30 m and time: 2–4 days. The proposed method works by combining the land surface reflectance data at 30 m spatial resolution obtained from the charge-coupled devices in the Huanjing-1A and -1B (HJ-1A/B satellites with the Moderate Resolution Imaging Spectroradiometer (MODIS land surface bidirectional reflectance distribution function (BRDF parameters product (MCD43A1, which is at a spatial resolution of 500 m. First, the land surface BRDF parameters for HJ-1A/B land surface reflectance with a spatial–temporal resolutions of 30 m and 2–4 day are calculated on the basis of the prior knowledge from the MODIS BRDF product; then, the calculated high resolution BRDF parameters are integrated over the illuminating/viewing hemisphere to produce the white- and black-sky albedos at 30 m resolution. These results form the basis for the final land surface albedo derivation by accounting for the proportion of direct and diffuse solar radiation arriving at the ground. The albedo retrieved by this novel method is compared with MODIS land surface albedo products, as well as with ground measurements. The results show that the derived land surface albedo during the growing season of 2012 generally achieved a mean absolute accuracy of ±0.044, and a root mean square error of 0.039, confirming the effectiveness of the newly proposed method.

  9. Photosynthesis sensitivity to climate change in land surface models

    Science.gov (United States)

    Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

    2016-04-01

    Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

  10. Comparative Assessment of Satellite-Retrieved Surface Net Radiation: An Examination on CERES and SRB Datasets in China

    Directory of Open Access Journals (Sweden)

    Xin Pan

    2015-04-01

    Full Text Available Surface net radiation plays an important role in land–atmosphere interactions. The net radiation can be retrieved from satellite radiative products, yet its accuracy needs comprehensive assessment. This study evaluates monthly surface net radiation generated from the Clouds and the Earth’s Radiant Energy System (CERES and the Surface Radiation Budget project (SRB products, respectively, with quality-controlled radiation data from 50 meteorological stations in China for the period from March 2000 to December 2007. Our results show that surface net radiation is generally overestimated for CERES (SRB, with a bias of 26.52 W/m2 (18.57 W/m2 and a root mean square error of 34.58 W/m2 (29.49 W/m2. Spatially, the satellite-retrieved monthly mean of surface net radiation has relatively small errors for both CERES and SRB at inland sites in south China. Substantial errors are found at northeastern sites for two datasets, in addition to coastal sites for CERES. Temporally, multi-year averaged monthly mean errors are large at sites in western China in spring and summer, and in northeastern China in spring and winter. The annual mean error fluctuates for SRB, but decreases for CERES between 2000 and 2007. For CERES, 56% of net radiation errors come from net shortwave (NSW radiation and 44% from net longwave (NLW radiation. The errors are attributable to environmental parameters including surface albedo, surface water vapor pressure, land surface temperature, normalized difference vegetation index (NDVI of land surface proxy, and visibility for CERES. For SRB, 65% of the errors come from NSW and 35% from NLW radiation. The major influencing factors in a descending order are surface water vapor pressure, surface albedo, land surface temperature, NDVI, and visibility. Our findings offer an insight into error patterns in satellite-retrieved surface net radiation and should be valuable to improving retrieval accuracy of surface net radiation. Moreover, our

  11. Relative Efficiency of Surface Energy Budgets Over Different Land Covers

    Science.gov (United States)

    Yang, Jiachuan

    The partitioning of available solar energy into different fluxes at the Earth's surface is important in determining different physical processes, such as turbulent transport, subsurface hydrology, land-atmospheric interactions, etc. Direct measurements of these turbulent fluxes were carried out using eddy-covariance (EC) towers. However, the distribution of EC towers is sparse due to relatively high cost and practical difficulties in logistics and deployment. As a result, data is temporally and spatially limited and is inadequate to be used for researches at large scales, such as regional and global climate modeling. Besides field measurements, an alternative way is to estimate turbulent fluxes based on the intrinsic relations between surface energy budget components, largely through thermodynamic equilibrium. These relations, referred as relative efficiency, have been included in several models to estimate the magnitude of turbulent fluxes in surface energy budgets such as latent heat and sensible heat. In this study, three theoretical models based on the lumped heat transfer model, the linear stability analysis and the maximum entropy principle respectively, were investigated. Model predictions of relative efficiencies were compared with turbulent flux data over different land covers, viz. lake, grassland and suburban surfaces. Similar results were observed over lake and suburban surface but significant deviation is found over vegetation surface. The relative efficiency of outgoing longwave radiation is found to be orders of magnitude deviated from theoretic predictions. Meanwhile, results show that energy partitioning process is influenced by the surface water availability to a great extent. The study provides insight into what property is determining energy partitioning process over different land covers and gives suggestion for future models.

  12. Surface Characteristics of Green Island Wakes from Satellite Imagery

    Science.gov (United States)

    Cheng, Kai-Ho; Hsu, Po-Chun; Ho, Chung-Ru

    2017-04-01

    Characteristics of an island wake induced by the Kuroshio Current flows pass by Green Island, a small island 40 km off southeast of Taiwan is investigated by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. The MODIS sea surface temperature (SST) and chlorophyll-a (chl-a) imagery is produced at 250-meter resolution from 2014 to 2015 using the SeaDAS software package which is developed by the National Aeronautics and Space Administration. The wake occurrence is 59% observed from SST images during the data span. The average cooling area is 190 km2, but the area is significantly changed with wind directions. The wake area is increased during southerly winds and is reduced during northerly winds. Besides, the average cooling SST was about 2.1 oC between the front and rear island. Comparing the temperature difference between the wake and its left side, the difference is 1.96 oC. In addition, the wakes have 1 3 times higher than normal in chlorophyll concentration. The results indicate the island mass effect makes the surface water of Green island wake colder and chl-a higher.

  13. Understanding the Life Cycle Surface Land Requirements of Natural Gas-Fired Electricity

    Energy Technology Data Exchange (ETDEWEB)

    Heath, Garvin A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Macknick, Jordan E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bush, Brian W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jordaan, Sarah [University of Calgary; Johns Hopkins University; Mohammadi, Ehsan [University of Calgary; Ben-Horin, Dan [Formerly NREL; Urrea, Victoria [Formerly NREL; Marceau, Danielle [University of Calgary

    2017-10-02

    The surface land use of fossil fuel acquisition and utilization has not been well characterized, inhibiting consistent comparisons of different electricity generation technologies. Here we present a method for robust estimation of the life cycle land use of electricity generated from natural gas through a case study that includes inventories of infrastructure, satellite imagery and well-level production. Approximately 500 sites in the Barnett Shale of Texas were sampled across five life cycle stages (production, gathering, processing, transmission and power generation). Total land use (0.62 m2 MWh-1, 95% confidence intervals +/-0.01 m2 MWh-1) was dominated by midstream infrastructure, particularly pipelines (74%). Our results were sensitive to power plant heat rate (85-190% of the base case), facility lifetime (89-169%), number of wells per site (16-100%), well lifetime (92-154%) and pipeline right of way (58-142%). When replicated for other gas-producing regions and different fuels, our approach offers a route to enable empirically grounded comparisons of the land footprint of energy choices.

  14. Land Surface Models Evaluation for Two Different Land-Cover Types: Cropland and Forest

    Directory of Open Access Journals (Sweden)

    Daeun Kim

    2016-02-01

    Full Text Available Land Surface Model (LSM is an important tool used to understand the complicated hydro-meteorological flux interaction systems between the land surface and atmosphere in hydrological cycles. Over the past few decades, LSMs have further developed to more accurately estimate weather and climate hydrological processes. Common Land Model (CLM and Noah Land Surface Model (Noah LSM are used in this paper to estimate the hydro-meteorological fluxes for model applicability assessment at two different flux tower sites in Korea during the summer monsoon season. The estimated fluxes such as net radiation (RN, sensible heat flux (H, latent heat flux (LE, ground heat flux (G, and soil temperature (Ts were compared with the observed data from flux towers. The simulated RN from both models corresponded well with the in situ data. The root-mean-square error (RMSE values were 39 - 44 W m-2 for the CLM and 45 - 50 W m-2 for the Noah LSM while the H and LE showed relatively larger discrepancies with each observation. The estimated Ts from the CLM corresponded comparatively well with the observed soil temperature. The CLM estimations generally showed better statistical results than those from the Noah LSM, even though the estimated hydro-meteorological fluxes from both models corresponded reasonably with the observations. A sensitivity test indicated that differences according to different locations between the estimations from models and observations were caused by field conditions including the land-cover type and soil texture. In addition the estimated RN, H, LE, and G were more sensitive than the estimated Ts in both models.

  15. 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

  16. Temporal Dynamics of Soil Moisture Variability at the Landscape Scale: Implications for Land Surface Models.

    Science.gov (United States)

    Montaldo, N.; Albertson, J. D.

    2001-12-01

    Meteorological and hydrological forecasting models share soil moisture as a critical boundary condition. Partitioning of received energy at the land surface depends directly on this variable, as does the partitioning of rainfall into its possible routes over and through the soil. In Land Surface Models (LSMs) the temporal dynamic of soil moisture spatial variability is a fundamental issue in large-scale flux predictions. From remote sensing observations soil moisture values are averaged in the horizontal over rather large regions (pixels). The averaging areas will be getting even larger as we move from aircraft mounted sensors to satellite mounting. These data are to be used ultimately to estimate spatial averages of other processes that depend on soil moisture, such as, runoff generation, drainage, evaporation, sensible heat fluxes, crop yield, microbial activity, etc. Consequently, the LSMs have to predict spatial averaged flux over large region from average values of the soil moisture. But soil moisture variances affect flux predictions, which depend nonlinearly on soil moisture, because many of the other processes possess distinct threshold aspects to their nonlinear dependence on soil moisture. Through application of well-developed Reynolds averaging rules from fluid mechanics to the equation of Richards and Darcy-Buckingham, we write a conservation equation for the horizontal variance of soil moisture. And, through closure arguments, we are able to describe the individual terms that produce and destroy spatial variance through time in terms of the mean soil moisture state and other observable system properties such as vegetation and soil properties variability. Finally, we calculate land surface fluxes from second order Taylor expansion, using our soil moisture variance closure model, and the other observable system properties. In this work, we demonstrate significant improvements in land surface large-scale flux predictions using the proposed soil moisture

  17. Temporal Dynamics of Soil Moisture Variability: Implications For Land Surface Models

    Science.gov (United States)

    Montaldo, N.; Albertson, J. D.

    Meteorological and hydrological forecasting models share soil moisture as a critical boundary condition. Partitioning of received energy at the land surface depends di- rectly on this variable, as does the partitioning of rainfall into its possible routes over and through the soil. In Land Surface Models (LSMs) the temporal dynamic of soil moisture spatial variability is a fundamental issue in large-scale flux predictions. From remote sensing observations soil moisture values are averaged in the horizontal over rather large regions (pixels). The averaging areas will be getting even larger as we move from aircraft mounted sensors to satellite mounting. These data are to be used ultimately to estimate spatial averages of other processes that depend on soil moisture, such as, runoff generation, drainage, evaporation, sensible heat fluxes, crop yield, mi- crobial activity, etc. Consequently, the LSMs have to predict spatial averaged flux over large region from average values of the soil moisture. But soil moisture variances af- fect flux predictions, which depend nonlinearly on soil moisture, because many of the other processes possess distinct threshold aspects to their nonlinear dependence on soil moisture. Through application of well-developed Reynolds averaging rules from fluid mechanics to the equation of Richards and Darcy-Buckingham, we write a con- servation equation for the horizontal variance of soil moisture. And, through closure arguments, we are able to describe the individual terms that produce and destroy spa- tial variance through time in terms of the mean soil moisture state and other observable system properties such as vegetation and soil properties variability. Finally, we calcu- late land surface fluxes from second order Taylor expansion, using our soil moisture variance closure model, and the other observable system properties. In this work, we demonstrate significant improvements in land surface large-scale flux predictions us- ing the proposed

  18. Innovative approach to retrieve land surface emissivity and land surface temperature in areas of highly dynamic emissivity changes by using thermal infrared data

    Science.gov (United States)

    Heinemann, Sascha; Muro, Javier; Burkart, Andreas; Schultz, Johannes; Thonfeld, Frank; Menz, Gunter

    2016-04-01

    The land surface temperature (LST) is an extremely significant parameter in order to understand the processes of energetic interactions between the Earth's surface and the atmosphere. This knowledge is significant for various environmental research questions, particularly with regard to climate change. The current challenge is to reduce the higher deviations during daytime especially for bare areas with a maximum of 5.7 Kelvin. These temperature differences are time and vegetation cover dependent. This study shows an innovative approach to retrieve land surface emissivity (LSE) and LST by using thermal infrared (TIR) data from satellite sensors, such as SEVIRI and AATSR. So far there are no methods to derive LSE/LST particularly in areas of highly dynamic emissivity changes. Therefore especially for regions with large surface temperature amplitude in the diurnal cycle such as bare and uneven soil surfaces but also for regions with seasonal changes in vegetation cover including various surface areas such as grassland, mixed forests or agricultural land different methods were investigated to identify the most appropriate one. The LSE is retrieved by using the day/night Temperature-Independent Spectral Indices (TISI) method, while the Generalised Split-Window (GSW) method is used to retrieve the LST. Nevertheless different GSW algorithms show that equal LSEs lead to large LST differences. For bare surfaces during daytime the difference is about 6 Kelvin. Additionally LSE is also measured using a NDVI-based threshold method (NDVITHM) to distinguish between soil, dense vegetation cover and pixel composed of soil and vegetation. The data used for this analysis were derived from MODIS TIR. The analysis is implemented with IDL and an intercomparison is performed to determine the most effective methods. To compensate temperature differences between derived and ground truth data appropriate correction terms, by comparing derived LSE/LST data with ground-based measurements

  19. How you cannot find rain with changes in land surface temperature

    Science.gov (United States)

    Wanders, Niko

    2017-04-01

    Estimating precipitation from space-born sensors is valuable source of observation in poorly-gauged regions. For example, hydrological modelling and monitoring greatly benefits from the increased near-real time data availability for improved accuracy in the simulations of water resources. As is true for all satellite product, precipitation estimated from space are far from perfect and scientist have used many techniques to improve their accuracy. In this study, I tried to improve the space-born precipitation estimates by using remotely sensed soil moisture to observe sudden increases in soil wetness as a result of precipitation. After a month of massaging the data and applied methodology I realized that the gain was very marginal and I was drilling a dry hole. Driven by these disappointing results I tried some random other satellite products to see if they showed correlation with the precipitation signal. There I found a causality that I had not expected at the start of this study, linking land surface temperature to precipitation. It seemed that using changes in land surface temperature strongly correlated with precipitation totals, driven by a cooling of the soil as a result of increase wetness. This link could not only be modelled, but more surprisingly it could be observed from space and used to improve the satellite precipitation estimates. The reduction in the precipitation uncertainty was far better than for any of the three soil moisture products, contrary to what one might expect. This was far from the anticipated result but it showed me that sometimes you should think out of the box and not only use observations for their intended purpose. This experience has motivated me to not only use the obvious observation or method and try techniques and methods from other disciplines to see if we can improve our understanding of the hydrological cycle.

  20. How can we use MODIS land surface temperature to validate long-term urban model simulations?

    Science.gov (United States)

    Hu, Leiqiu; Brunsell, Nathaniel A.; Monaghan, Andrew J.; Barlage, Michael; Wilhelmi, Olga V.

    2014-03-01

    High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change. Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature. The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation. For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations. The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.

  1. Land-surface studies with a directional neutron detector.

    Energy Technology Data Exchange (ETDEWEB)

    Desilets, Darin (Sandia National Laboratories, Albuquerque, NM); Brennan, James S.; Mascarenhas, Nicholas; Marleau, Peter

    2009-09-01

    Direct measurements of cosmic-ray neutron intensity were recorded with a neutron scatter camera developed at SNL. The instrument used in this work is a prototype originally designed for nuclear non-proliferation work, but in this project it was used to characterize the response of ambient neutrons in the 0.5-10 MeV range to water located on or above the land surface. Ambient neutron intensity near the land surface responds strongly to the presence of water, suggesting the possibility of an indirect method for monitoring soil water content, snow water equivalent depth, or canopy intercepted water. For environmental measurements the major advantage of measuring neutrons with the scatter camera is the limited (60{sup o}) field of view that can be obtained, which allows observations to be conducted at a previously unattainable spatial scales. This work is intended to provide new measurements of directional fluxes which can be used in the design of new instruments for passively and noninvasively observing land-surface water. Through measurements and neutron transport modeling we have demonstrated that such a technique is feasible.

  2. Variational assimilation of land surface temperature within the ORCHIDEE Land Surface Model Version 1.2.6

    Science.gov (United States)

    Benavides Pinjosovsky, Hector Simon; Thiria, Sylvie; Ottlé, Catherine; Brajard, Julien; Badran, Fouad; Maugis, Pascal

    2017-01-01

    The SECHIBA module of the ORCHIDEE land surface model describes the exchanges of water and energy between the surface and the atmosphere. In the present paper, the adjoint semi-generator software called YAO was used as a framework to implement a 4D-VAR assimilation scheme of observations in SECHIBA. The objective was to deliver the adjoint model of SECHIBA (SECHIBA-YAO) obtained with YAO to provide an opportunity for scientists and end users to perform their own assimilation. SECHIBA-YAO allows the control of the 11 most influential internal parameters of the soil water content, by observing the land surface temperature or remote sensing data such as the brightness temperature. The paper presents the fundamental principles of the 4D-VAR assimilation, the semi-generator software YAO and a large number of experiments showing the accuracy of the adjoint code in different conditions (sites, PFTs, seasons). In addition, a distributed version is available in the case for which only the land surface temperature is observed.

  3. The Influence of Land Surface Changes on Regional Climate in Northwest China

    Institute of Scientific and Technical Information of China (English)

    XU Xingkui; ZHANG Feng; Jason K.LEVY

    2007-01-01

    Land surface changes effect the regional climate due to the complex coupling of land-atmosphere interactions. From 1995 to 2000, a decrease in the vegetation density and an increase in ground-level thermodynamic activity has been documented by multiple data sources in Northwest China, including meteorological, reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF), National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and TIROS Operational Vertical Sounder (TOVS) satellite remote sensing data. As the ground-level thermodynamic activity increases, humid air from the surrounding regions converge toward desert (and semi-desert) regions, causing areas with high vegetation cover to become gradually more arid. Furthermore, land surface changes in Northwest China are responsible for a decrease in total cloud cover, a decline in the fraction of low and middle clouds, an increase in high cloud cover (due to thermodynamic activity) and other regional climatic adaptations. It is proposed that, beginning in 1995, these cloud cover changes contributed to a "greenhouse" effect, leading to the rapid air temperature increases and other regional climate impacts that have been observed over Northwest China.

  4. Impervious Surface Area Mapping using Landsat Imagery: Applications to Hydrology and Land Use Change Monitoring

    Science.gov (United States)

    Smith, A.; Goetz, S. J.; Mazzacato, M. E.; Jantz, C.; Wright, R.

    2002-12-01

    Impervious surfaces include rooftops, roads, parking lots and other areas that are impermeable to moisture. As the amount of built environment around urban areas has increased, it has been widely recognized that more impervious surface area (ISA) results in greater volume and intensity of stream flow, which can degrade stream health and require expensive modifications to flood control structures. Other effects include increased urban "heat island" influences and changes in local weather. If impervious areas could be accurately mapped using satellite imagery, it would provide valuable input to many applications, from hydrologic modeling to land use planning. We have developed a method to map subpixel ISA with Landsat Thematic Mapper (TM) imagery and classification - regression tree algorithms. This approach provides highly accurate (90+ percent) maps of ISA, but also permits estimation of the proportion of each cell occupied by impervious materials (between 0-100 percent). We report on a recently completed a map of ISA for the entire 163,000 km2 Chesapeake Bay watershed, a region of highly altered land cover and rapid land use change. We also report on the mapping of change patterns, indicated by ISA changes between 1986 - 2001, in an 18,000 km2 area centered on Baltimore - Washington, D.C. We review the methods, issues, technical challenges, results, accuracy, and advantages of this approach, and provide an overview of various applications for which the products are currently being used.

  5. A blended land emissivity product from the Inter-Comparison of different Land Surface Emissivity Estimates

    Science.gov (United States)

    Norouzi, H.; Temimi, M.; Khanbilvardi, R.

    2012-12-01

    Passive microwave observations are routinely used to estimate rain rate, cloud liquid water, and total precipitable water. In order to have accurate estimations from microwave, the contribution of the surface should be accounted for. Over land, due to the complex interaction between the microwave signal and the soil surface, retrieval of land surface emissivity and other surface and subsurface parameters is not straightforward. Several microwave emissivity products from various microwave sensors have been proposed. However, lack of ground truth measurements makes the validation of these products difficult. This study aims to inter-compare several available emissivity products over land and ultimately proposes a unique blended product that overcomes the flaws of each individual product. The selected products are based on observations from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Advanced Microwave Sounding unit (AMSU), and the Special Sensor Microwave Imager/Sounder (SSMIS). In retrieval of emissivities from these sensors different methods and ancillary data have been used. Some inherent discrepancies between the selected products can be introduced by as the difference in geometry in terms of incident angle, spectral response, and the foot print size which can affect the estimations. Moreover, ancillary data especially skin temperature and cloud mask cover can cause significant discrepancies between various estimations. The time series and correlation between emissivity maps are explored to assess the consistency of emissivity variations with geophysical variable such as snow, precipitation and drought. Preliminary results reveal that inconsistency between products varies based on land cover type due to penetration depth effect and ancillary data. Six years of estimations are employed in this research study, and a global blended emissivity estimations based on all product with minimal discrepancies

  6. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms

    Directory of Open Access Journals (Sweden)

    João P. A. Martins

    2016-09-01

    Full Text Available Land surface temperature (LST is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This study analyzes calibration strategies while considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere, indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis—Satellite Application Facility to calibrate its LST algorithms, applied both for current and forthcoming sensors.

  7. Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

    Science.gov (United States)

    Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

    2016-09-01

    Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

  8. Procedure to detect impervious surfaces using satellite images and light detection and ranging (lidar) data

    Science.gov (United States)

    Rodríguez-Cuenca, B.; Alonso-Rodríguez, M. C.; Domenech-Tofiño, E.; Valcárcel Sanz, N.; Delgado-Hernández, J.; Peces-Morera, Juan José; Arozarena-Villar, Antonio

    2014-10-01

    The detection of impervious surfaces is an important issue in the study of urban and rural environments. Imperviousness refers to water's inability to pass through a surface. Although impervious surfaces represent a small percentage of the Earth's surface, knowledge of their locations is relevant to planning and managing human activities. Impervious structures are primarily manmade (e.g., roads and rooftops). Impervious surfaces are an environmental concern because many processes that modify the normal function of land, air, and water resources are initiated during their construction. This paper presents a novel method of identifying impervious surfaces using satellite images and light detection and ranging (LIDAR) data. The inputs for the procedure are SPOT images formed by four spectral bands (corresponding to red, green, near-infrared and mid-infrared wavelengths), a digital terrain model, and an .las file. The proposed method computes five decision indexes from the input data to classify the studied area into two categories: impervious (subdivided into buildings and roads) and non-impervious surfaces. The impervious class is divided into two subclasses because the elements forming this category (mainly roads and rooftops) have different spectral and height properties, and it is difficult to combine these elements into one group. The classification is conducted using a decision tree procedure. For every decision index, a threshold is set for which every surface is considered impervious or non-impervious. The proposed method has been applied to four different regions located in the north, center, and south of Spain, providing satisfactory results for every dataset.

  9. Using Microwave Observations to Estimate Land Surface Temperature during Cloudy Conditions

    Science.gov (United States)

    Holmes, T. R.; Crow, W. T.; Hain, C.; Anderson, M. C.

    2014-12-01

    Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and passive microwave observations (MW). TIR is the most commonly used approach and the method of choice to provide standard LST products for various satellite missions. MW-based LST retrievals on the other hand are not as widely adopted for land applications; currently their principle use is in soil moisture retrieval algorithms. MW and TIR technologies present two highly complementary and independent means of measuring LST. MW observations have a high tolerance to clouds but a low spatial resolution, and TIR has a high spatial resolution with temporal sampling restricted to clear skies. The nature of the temperature at the very surface layer of the land makes it difficult to combine temperature estimates between different methods. The skin temperature is characterized by a strong diurnal cycle that is dependant in timing and amplitude on the exact sensing depth and thermal properties of the vegetation. This paper builds on recent progress in characterizing the main structural components of the DTC that explain differences in TIR and MW estimates of LST. Spatial patterns in DTC timing (phase lag with solar noon) and DTC amplitude have been calculated for TIR, MW and compared to weather prediction estimates. Based on these comparisons MW LST can be matched to the TIR record. This paper will compare in situ measurements of LST with satellite estimates from (downscaled) TIR and (reconciled) MW products. By contrasting the validation results of clear sky days with those of cloudy days the expected tolerance to clouds of the MW observations will be tested. The goal of this study is to determine the weather conditions in which MW can supplement the TIR LST record.

  10. Developing first time-series of land surface temperature from AATSR with uncertainty estimates

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2013-04-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Earth Observation satellites provide the opportunity to obtain global coverage of LST approximately every 3 days or less. One such source of satellite retrieved LST has been the Advanced Along-Track Scanning Radiometer (AATSR); with LST retrieval being implemented in the AATSR Instrument Processing Facility in March 2004. Here we present first regional and global time-series of LST data from AATSR with estimates of uncertainty. Mean changes in temperature over the last decade will be discussed along with regional patterns. Although time-series across all three ATSR missions have previously been constructed (Kogler et al., 2012), the use of low resolution auxiliary data in the retrieval algorithm and non-optimal cloud masking resulted in time-series artefacts. As such, considerable ESA supported development has been carried out on the AATSR data to address these concerns. This includes the integration of high resolution auxiliary data into the retrieval algorithm and subsequent generation of coefficients and tuning parameters, plus the development of an improved cloud mask based on the simulation of clear sky conditions from radiance transfer modelling (Ghent et al., in prep.). Any inference on this LST record is though of limited value without the accompaniment of an uncertainty estimate; wherein the Joint Committee for Guides in Metrology quote an uncertainty as "a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand that is the value of the particular quantity to be measured". Furthermore, pixel level uncertainty fields are a mandatory requirement in the on-going preparation of the LST product for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3

  11. Can interannual land surface signal be discerned in composite AVHRR data?

    Science.gov (United States)

    Cihlar, J.; Chen, J. M.; Li, Z.; Huang, F.; Latifovic, R.; Dixon, R.

    1998-09-01

    The ability to make repeated measurements of the changing Earth's surface is the principal advantage of satellite remote sensing. To realize its potential, it is necessary that true surface changes be isolated in the satellite signal from other effects which also influence the signal. In this study, we explore the magnitude of such effects in composite NOAA advanced very high resolution radiometer (AVHRR) images with a pixel spacing of 1 km. A compositing procedure is frequently used in the preparation of data sets for land biosphere studies to minimize the effect of clouds. However, the composite images contain residual artifacts which make it difficult to compare measurements at various times. We have employed a 4-year (1993-1996) AVHRR data set from NOAA 11 and 14 covering the Canadian landmass and corrected these data for the influence of the remaining clouds (full pixel or subpixel), atmospheric attenuation, and bidirectional reflectance. We have found that such corrections are essential for studies of interannual variations. The magnitude of the interannual signal varied with the AVHRR channel, land cover type, and satellite sensor but it was reduced by a factor of 2 to 8 between top of the atmosphere and the normalized surface reflectance. The remaining variations consisted of true interannual signal and the residual noise in the data (including sensor calibration) which was not removed by the correction process. Assuming that barren or sparsely vegetated land in northern Canada has not changed over the 4-year period, the mean residual uncertainty in surface reflectance of the selected sites was 0.012 for AVHRR channel 1, 0.042 for channel 2, and 0.068 for the normalized difference vegetation index (NDVI). These values decreased to 0.011, 0.024 and 0.038, respectively, when excluding 1994 data because their atmospheric and bidirectional corrections were hampered by high solar zenith angles (mean values above 55° in all 1994 composite periods). The errors

  12. Relating trends in land surface-air temperature difference to soil moisture and evapotranspiration

    Science.gov (United States)

    Veal, Karen; Taylor, Chris; Gallego-Elvira, Belen; Ghent, Darren; Harris, Phil; Remedios, John

    2016-04-01

    Soil water is central to both physical and biogeochemical processes within the Earth System. Drying of soils leads to evapotranspiration (ET) becoming limited or "water-stressed" and is accompanied by rises in land surface temperature (LST), land surface-air temperature difference (delta T), and sensible heat flux. Climate models predict sizable changes to the global water cycle but there is variation between models in the time scale of ET decay during dry spells. The e-stress project is developing novel satellite-derived diagnostics to assess the ability of Earth System Models (ESMs) to capture behaviour that is due to soil moisture controls on ET. Satellite records of LST now extend 15 years or more. MODIS Terra LST is available from 2000 to the present and the Along-Track Scanning Radiometer (ATSR) LST record runs from 1995 to 2012. This paper presents results from an investigation into the variability and trends in delta T during the MODIS Terra mission. We use MODIS Terra and MODIS Aqua LST and ESA GlobTemperature ATSR LST with 2m air temperatures from reanalyses to calculate trends in delta T and "water-stressed" area. We investigate the variability of delta T in relation to soil moisture (ESA CCI Passive Daily Soil Moisture), vegetation (MODIS Monthly Normalized Difference Vegetation Index) and precipitation (TRMM Multi-satellite Monthly Precipitation) and compare the temporal and spatial variability of delta T with model evaporation data (GLEAM). Delta T anomalies show significant negative correlations with soil moisture, in different seasons, in several regions across the planet. Global mean delta T anomaly is small (magnitude mostly less than 0.2 K) between July 2002 and July 2008 and decreases to a minimum in early 2010. The reduction in delta T anomaly coincides with an increase in soil moisture anomaly and NDVI anomaly suggesting an increase in evapotranspiration and latent heat flux with reduced sensible heat flux. In conclusion there have been

  13. Satellite NO2 data improve national land use regression models for ambient NO2 in a small densely populated country

    NARCIS (Netherlands)

    Hoek, Gerard; Eeftens, Marloes; Beelen, Rob; Fischer, Paul; Brunekreef, Bert; Boersma, K. Folkert; Veefkind, Pepijn

    2015-01-01

    Land use regression (LUR) modelling has increasingly been applied to model fine scale spatial variation of outdoor air pollutants including nitrogen dioxide (NO2). Satellite observations of tropospheric NO2 improved LUR model in very large study areas, including Canada, United States and Australia.

  14. 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

  15. Improvement in the geopotential derived from satellite and surface data (GEM 7 and 8)

    Science.gov (United States)

    Wagner, C. A.; Lerch, F. J.; Brownd, J. E.; Richardson, J. A.

    1976-01-01

    A refinement was obtained in the earth's gravitational field using satellite and surface data. In addition to a more complete treatment of data previously employed on 27 satellites, the new satellite solution (Goddard Earth Model 7) includes 64,000 laser measurements taken on 7 satellites during the international satellite geodesy experiment (ISAGEX) program. The GEM 7, containing 400 harmonic terms, is complete through degree and order 16. The companion solution GEM 8 combines the same satellite data as in GEM 7 with surface gravimetry over 39% of the earth. The GEM 8 is complete to degree and order 25. Extensive tests on data independent of the solution show that the undulation of the geoidal surface computed by GEM 7 has an accuracy of about 3m (rms). The overall accuracy of the geoid estimated by GEM 8 is estimated to be about 4-1/4m (rms), an improvement of almost 1m over previous solutions.

  16. Retrieval of aerosol optical depth over land surfaces from AVHRR data

    Directory of Open Access Journals (Sweden)

    L. Mei

    2013-02-01

    Full Text Available The Advanced Very High Resolution Radiometer (AVHRR radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 μm and 2.1 μm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 μm was obtained. The comparison of the estimated surface reflectance at 0.64 μm with MODIS reflectance products (MOD09 shows a strong correlation (R = 0.7835. Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR data. A simplified Look-Up Table (LUT method, adopted from Bremen AErosol Retrieval (BAER algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 μm channel, such as those currently planned to

  17. Land cover change detection based on satellite data for an arid area to the south of Aksu in Taklimakan desert

    Institute of Scientific and Technical Information of China (English)

    Kiyoshi; TSUCHIYA; Tamotsu; IGARSHI; Muhtar; QONG

    2010-01-01

    An experiment is made to detect the land-cover change in the area located to the south of Aksu in the northern Taklimakan desert through analyses of satellite data pixel by pixel basis. The analyzed data are those observed in the late summer and early autumn of 1973, 1977, 1993 and 1995. As a parameter of land-cover, SAVI (Soil Adjusted Vegetation Index) derived from the data of Landsat MSS and JERS-1 OPS (Optical Sensor) is used. The result indicates the increase of vegetation in the oasis areas, confluent area of the Yarkant and Kashgar Rivers and around reservoirs while little change occurs in the desert area. The 1973 satellite image shows the abundant flow in the Yarkant River while the river is almost dried up in the satellite images of later years. The trend of the decrease in the Hotan River flow is recognized although not so dramatic as that of the Yarkant River.

  18. Gravimetric geodesy and sea surface topography studies by means of satellite-to-satellite tracking and satellite altimetry

    Science.gov (United States)

    Siry, J. W.

    1972-01-01

    A satellite-to-satellite tracking experiment is planned between ATS-F and GEOS-C with a range accuracy of 2-meters and a range rate accuracy of 0.035 centimeters per second for a 10-second integration time. This experiment is planned for 1974. It is anticipated that it will improve the spatial resolution of the satellite geoid by half an order of magnitude to about 6 degrees. Longer integration times should also permit a modest increase in the acceleration resolution. Satellite altimeter data will also be obtained by means of GEOS-C. An overall accuracy of 5-meters in altitude is the goal. The altimeter, per se, is expected to have an instrumental precision of about 2 meters, and an additional capability to observe with a precision of about 0.2 meters for limited periods.

  19. Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques

    Science.gov (United States)

    Nampak, Haleh; Pradhan, Biswajeet

    2016-07-01

    Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

  20. Potential association of dengue hemorrhagic fever incidence and remote senses land surface temperature, Thailand, 1998.

    Science.gov (United States)

    Nitatpattana, Narong; Singhasivanon, Pratap; Kiyoshi, Honda; Andrianasolo, Haja; Yoksan, Sutee; Gonzalez, Jean-Paul; Barbazan, Philippe

    2007-05-01

    A pilot study was designed to analyze a potential association between dengue hemorrhagic fever (DHF) incidence and, temperature computed by satellite. DHF is a mosquito transmitted disease, and water vapor and humidity are known to have a positive effect on mosquito life by increasing survival time and shortening the development cycle. Among other available satellite data, Land Surface Temperature (LST) was chosen as an indicator that combined radiated earth temperature and atmospheric water vapor concentration. Monthly DHF incidence was recorded by province during the 1998 epidemic and obtained as a weekly combined report available from the National Ministry of Public Health. Conversely, LST was calculated using remotely sensed data obtained from thermal infrared sensors of NOAA satellites and computed on a provincial scale. Out of nine selected study provinces, five (58.3%) exhibited an LST with a significant positive correlation with rainfall (p < 0.05). In four out of nineteen surveyed provinces (21.3%), LST showed a significant positive correlation with DHF incidence (p < 0.05). Positive association between LST and DHF incidence was significantly correlated in 75% of the cases during non-epidemic months, while no correlation was found during epidemic months. Non-climatic factors are supposed to be at the origin of this discrepancy between seasonality in climate (LST) and DHF incidence during epidemics.

  1. Interactions of satellite-speed helium atoms with satellite-surfaces. 1. Spatial distributions of reflected helium atoms

    Energy Technology Data Exchange (ETDEWEB)

    Liu, S.M.; Rodgers, W.E.; Knuth, E.L.

    1975-06-01

    Interactions of satellite-speed helium atoms with practical satellite surfaces were investigated experimentally, and spatial distributions of satellite-speed helium beams scattered from four different engineering surfaces were measured. The 7000-m/s helium beams were produced using an arc-heated supersonic molecular beam source. The test surfaces included cleaned 6061-T6 aluminum plate, anodized aluminum foil, white paint, and quartz surfaces. Both in-plane (in the plane containing the incident beam and the surface normal) and out-of-plane spatial distributions of reflected helium atoms were measured for six different incidence angles (0, 15, 30, 45, 60, and 75 deg from the surface normal). It was found that a large fraction of the incident helium atoms were scattered back in the vicinity of the incoming beam, particularly in the case of glancing incidence angles. This unexpected scattering feature results perhaps from the gross roughness of these test surfaces. This prominent backscattering could yield drag coefficients which are higher than for surfaces with either forward-lobed or diffusive (cosine) scattering patterns. (auth)

  2. Assessment of the consistency among global microwave land surface emissivity products

    Directory of Open Access Journals (Sweden)

    H. Norouzi

    2014-09-01

    Full Text Available The goal of this work is to inter-compare a number of global land surface emissivity products over various land-cover conditions to assess their consistency. Ultimately, the discrepancies between the studied emissivity products will help interpreting the divergences among numerical weather prediction models in which land emissivity is a key surface boundary parameter. The intercompared retrieved land emissivity products were generated over five-year period (2003–2007 using observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E, Special Sensor Microwave Imager (SSM/I, The Tropical Rainfall Measuring Mission (TRMM Microwave Imager (TMI and Windsat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity values from four products were also compared to soil moisture estimates and satellite-based vegetation index to assess their sensitivities to the changes in land surface conditions. Results show that systematic differences among products exist and variation of emissivities at each product has similar frequency dependency at any land cover type. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower across various land cover condition which may be attributed to the 1.30 a.m./p.m. overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analysed products was the lowest (less than 0.01 in rain forest regions for all products and the highest in northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute

  3. CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    G. McCamley

    2012-07-01

    Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

  4. Accounting for surface reflectance anisotropy in satellite retrievals of tropospheric NO2

    Directory of Open Access Journals (Sweden)

    B. Buchmann

    2010-05-01

    Full Text Available Surface reflectance is a key parameter in satellite trace gas retrievals in the UV/visible range and in particular for the retrieval of nitrogen dioxide (NO2 vertical tropospheric columns (VTCs. Current operational retrievals rely on coarse-resolution reflectance data and do not account for the generally anisotropic properties of surface reflectance. Here we present a NO2 VTC retrieval that uses MODIS bi-directional reflectance distribution function (BRDF data at high temporal (8 days and spatial (1 km×1 km resolution in combination with the LIDORT radiative transfer model to account for the dependence of surface reflectance on viewing and illumination geometry. The method was applied to two years of NO2 observations from the Ozone Monitoring Instrument (OMI over Europe. Due to its wide swath, OMI is particularly sensitive to BRDF effects. Using representative BRDF parameters for various land surfaces, we found that in July (low solar zenith angles and November (high solar zenith angles and for typical viewing geometries of OMI, differences between MODIS black-sky albedos and surface bi-directional reflectances are of the order of 0–10% and 0–40%, respectively, depending on the position of the OMI pixel within the swath. In the retrieval, black-sky albedo was treated as a Lambertian (isotropic reflectance, while for BRDF effects we used the kernel-based approach in the MODIS BRDF product. Air Mass Factors were computed using the LIDORT radiative transfer model based on these surface reflectance conditions. Differences in NO2 VTCs based on the Lambertian and BRDF approaches were found to be of the order of 0–3% in July and 0–20% in November with the extreme values found at large viewing angles. The much larger differences in November are partly due to higher solar zenith angles and partly to the choice of a priori NO2 profiles – the latter typically have more pronounced maxima in the boundary layer during the cold season. However, BRDF

  5. A New Approach for Parameter Optimization in Land Surface Model

    Institute of Scientific and Technical Information of China (English)

    LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin

    2011-01-01

    In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.

  6. Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

    Science.gov (United States)

    Quattrochi, D. A.; Jedlovec, G.; Meyer, P. J.

    2011-12-01

    potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

  7. Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

    Science.gov (United States)

    Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul

    2011-01-01

    potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

  8. Citizen science land cover classification based on ground and satellite imagery: Case study Day River in Vietnam

    Science.gov (United States)

    Nguyen, Son Tung; Minkman, Ellen; Rutten, Martine

    2016-04-01

    Citizen science is being increasingly used in the context of environmental research, thus there are needs to evaluate cognitive ability of humans in classifying environmental features. With the focus on land cover, this study explores the extent to which citizen science can be applied in sensing and measuring the environment that contribute to the creation and validation of land cover data. The Day Basin in Vietnam was selected to be the study area. Different methods to examine humans' ability to classify land cover were implemented using different information sources: ground based photos - satellite images - field observation and investigation. Most of the participants were solicited from local people and/or volunteers. Results show that across methods and sources of information, there are similar patterns of agreement and disagreement on land cover classes among participants. Understanding these patterns is critical to create a solid basis for implementing human sensors in earth observation. Keywords: Land cover, classification, citizen science, Landsat 8

  9. Preliminary comparative assessment of land use for the Satellite Power System (SPS) and alternative electric energy technologies

    Science.gov (United States)

    Newsom, D. E.; Wolsko, T.

    1980-01-01

    A preliminary comparative assessment of land use for the satellite power system (SPS), other solar technologies, and alternative electric energy technologies was conducted. The alternative technologies are coal gasification/combined-cycle, coal fluidized-bed combustion (FBC), light water reactor (LWR), liquid metal fast breeder reactor (LMFBR), terrestrial photovoltaics (TPV), solar thermal electric (STE), and ocean thermal energy conversion (OTEC). The major issues of a land use assessment are the quantity, purpose, duration, location, and costs of the required land use. The phased methodology described treats the first four issues, but not the costs. Several past efforts are comparative or single technology assessment are reviewed briefly. The current state of knowledge about land use is described for each technology. Conclusions are drawn regarding deficiencies in the data on comparative land use and needs for further research.

  10. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  11. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

  12. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    Science.gov (United States)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

  13. Towards an improved land surface scheme for prairie landscapes

    Science.gov (United States)

    Mekonnen, M. A.; Wheater, H. S.; Ireson, A. M.; Spence, C.; Davison, B.; Pietroniro, A.

    2014-04-01

    The prairie region of Canada and the United States is characterized by millions of small depressions of glacial origin called prairie potholes. The transfer of surface runoff in this landscape is mainly through a “fill and spill” mechanism among neighboring potholes. While non-contributing areas, that is small internally drained basins, are common on this landscape, during wet periods these areas can become hydrologically connected to larger regional drainage systems. Accurate prediction of prairie surface runoff generation and streamflow thus requires realistic representation of the dynamic threshold-mediated nature of these contributing areas. This paper presents a new prairie surface runoff generation algorithm for land surface schemes and large scale hydrological models that conceptualizes a hydrologic unit as a combination of variable and interacting storage elements. The proposed surface runoff generation algorithm uses a probability density function to represent the spatial variation of pothole storages and assumes a unique relationship between storage and the fractional contributing area for runoff (and hence amount of direct runoff generated) within a grid cell. In this paper the parameters that define this relationship are obtained by calibration against streamflow. The model was compared to an existing hydrology-land surface scheme (HLSS) applied to a typical Canadian prairie catchment, the Assiniboine River. The existing configuration is based on the Canadian Land Surface Scheme (CLASS) and WATROF (a physically-based overland and interflow scheme). The new configuration consists of CLASS coupled with the new PDMROF model. Results showed that the proposed surface runoff generation algorithm performed better at simulating streamflow, and appears to capture the dynamic nature of contributing areas in an effective and parsimonious manner. A pilot evaluation based on 1 m LiDAR data from a small (10 km2) experimental area suggests that the shape of the

  14. Changes in Land Surface Water Dynamics since the 1990s and Relation to Population Pressure

    Science.gov (United States)

    Prigent, C.; Papa, F.; Aires, F.; Jimenez, C.; Rossow, W. B.; Matthews, E.

    2012-01-01

    We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, in section 4, insisting on the potential applications of the wetland dataset.

  15. The new single-channel approaches for retrieving land surface temperature and the preliminary results

    Science.gov (United States)

    Chen, Feng; Yang, Song; Liu, Lin; Zhao, Xiaofeng

    2014-11-01

    Two satellites named HJ-1A and HJ-1B were launched on 6 September 2008, which are intended for environment and disaster monitoring and forecasting. The infrared scanner (IRS) onboard HJ-1B has one thermal infrared band. Currently, for sensors with one thermal band (e.g. Landsat TM/ETM+ and HJ-1B), several empirical algorithms have been developed to estimate land surface temperature (LST). However, surface emissivity and atmospheric parameters which are not readily accessible to general users are required for these empirical methods. To resolve this problem, particularly for HJ-1B, new retrieval methodology is desired. According to proper assumptions, two approaches were proposed, which included the single-channel method based on temporal and spatial information (MTSC) and the image based single-channel method (IBSC). The newly developed methods are mainly for estimating LST accurately from one thermal band, even without any accurate information related to the atmospheric parameters and land surface emissivity. In this paper, we introduce and give preliminary assessments on the new approaches. Assessments generally show good agreement between the HJ-1B retrieved results and the MODIS references. Especially, over sea and water areas the biases were less than 1K while the root mean square errors were about 1K for both MTSC and IBSC methods. As expected, the MTSC method did superiorly to the IBSC method, owning to spatiotemporal information is incorporated into the MTSC method, although more experiments and comparisons should be conducted further.

  16. Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data

    Directory of Open Access Journals (Sweden)

    Baojuan Shan

    2013-01-01

    Full Text Available Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Remote sensing of the Earth’s energy budget, particularly with instruments flown on geostationary satellites, allows for near-real-time evaluation of cloud and surface radiation properties. The persistence and coverage of geostationary remote sensing instruments grant the frequent retrieval of near-instantaneous quasi-global skin temperature. Among other cloud and clear-sky retrieval parameters, NASA Langley provides a non-polar, high-resolution land and ocean skin temperature dataset for atmospheric modelers by applying an inverted correlated k-distribution method to clear-pixel values of top-of-atmosphere infrared temperature. The present paper shows that this method yields clear-sky skin temperature values that are, for the most part, within 2 K of measurements from ground-site instruments, like the Southern Great Plains Atmospheric Radiation Measurement (ARM Infrared Thermometer and the National Climatic Data Center Apogee Precision Infrared Thermocouple Sensor. The level of accuracy relative to the ARM site is comparable to that of the Moderate-resolution Imaging Spectroradiometer (MODIS with the benefit of an increased number of daily measurements without added bias or increased error. Additionally, matched comparisons of the high-resolution skin temperature product with MODIS land surface temperature reveal a level of accuracy well within 1 K for both day and night. This confidence will help in characterizing the diurnal and seasonal biases and root-mean-square differences between the retrievals and modeled values from the NASA Goddard Earth Observing System Version 5 (GEOS-5 in preparation for assimilation of the retrievals into GEOS-5. Modelers should find the immediate availability and broad coverage of these skin temperature

  17. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  18. Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta

    Institute of Scientific and Technical Information of China (English)

    QIAN Le-Xiang; CUI Hai-Sha; CHANG Jie

    2006-01-01

    Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes(LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth, which caused LST to raise 4.56 ℃ in the newly urbanized part of the study area. Overall, remote sensing and CIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.

  19. Cultivated Land Changes and Their Driving Forces-A Satellite Remote Sensing Analysis in the Yellow River Delta, China

    Institute of Scientific and Technical Information of China (English)

    ZHAO Geng-Xing; G.LIN; J.J.FLETCHER; C.YUILL

    2004-01-01

    Taking Kenli County in the Yellow River Delta, China, as the study area and using digital satellite remote sensing techniques, cultivated land use changes and their corresponding driving forces were explored in this study. An interactive interpretation and a manual modification procedure were carried out to acquire cultivated land information. An overlay method based on classification results and a visual change detection method which was supported by land use maps were employed to detect the cultivated land changes. Based on the changes that were revealed and a spatial analysis between cultivated land use and related natural and socio-economic factors, the driving forces for cultivated land use changes in the study area were determined.The results showed a decrease in cultivated land in Kenli County of 5321.8 ha from 1987 to 1998, i.e.,an average annual decrement of 483.8 ha, which occurred mainly in the central paddy field region and the northeast dry land region. Adverse human activities, soil salinization and water deficiencies were the driving forces that caused these cultivated land use changes.

  20. The role of GMES / Sentinels in Land-Surface Earth System Science

    Science.gov (United States)

    Moreno, J.

    2009-04-01

    A general trend in the current status of representation of Land Surface schemes into Earth System models is driven by the parameterisation of "cycles" instead of individual processes. Particular emphasis is made to account for couplings among the individual cycles, as between the carbon and water cycles. Moreover, the current tendency is to use the measured data -time series in most cases- together with models, in a data assimilation scenario where inputs from multiple sources are integrated. Such approach is more and more necessary as land models tend to be more complex