WorldWideScience

Sample records for sensed land surface

  1. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, Jesslyn 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.

  2. Remote sensing of land surface temperature: The directional viewing effect

    International Nuclear Information System (INIS)

    Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.

    1997-01-01

    Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied

  3. 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

  4. 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

  5. ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE

    Directory of Open Access Journals (Sweden)

    Z. Zou

    2017-09-01

    Full Text Available Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.

  6. 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

  7. LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

    Science.gov (United States)

    Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

    2014-11-01

    The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

  8. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    Science.gov (United States)

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  9. Multi-sensor remote sensing parameterization of heat fluxes over heterogeneous land surfaces

    NARCIS (Netherlands)

    Faivre, R.D.

    2014-01-01

    The parameterization of heat transfer by remote sensing, and based on SEBS scheme for turbulent heat fluxes retrieval, already proved to be very convenient for estimating evapotranspiration (ET) over homogeneous land surfaces. However, the use of such a method over heterogeneous landscapes (e.g.

  10. Surface Properties and Characteristics of Mars Landing Sites from Remote Sensing Data and Ground Truth

    Science.gov (United States)

    Golombek, M. P.; Haldemann, A. F.; Simpson, R. A.; Furgason, R. L.; Putzig, N. E.; Huertas, A.; Arvidson, R. E.; Heet, T.; Bell, J. F.; Mellon, M. T.; McEwen, A. S.

    2008-12-01

    Surface characteristics at the six sites where spacecraft have successfully landed on Mars can be related favorably to their signatures in remotely sensed data from orbit and from the Earth. Comparisons of the rock abundance, types and coverage of soils (and their physical properties), thermal inertia, albedo, and topographic slope all agree with orbital remote sensing estimates and show that the materials at the landing sites can be used as ground truth for the materials that make up most of the equatorial and mid- to moderately high-latitude regions of Mars. The six landing sites sample two of the three dominant global thermal inertia and albedo units that cover ~80% of the surface of Mars. The Viking, Spirit, Mars Pathfinder, and Phoenix landing sites are representative of the moderate to high thermal inertia and intermediate to high albedo unit that is dominated by crusty, cloddy, blocky or frozen soils (duricrust that may be layered) with various abundances of rocks and bright dust. The Opportunity landing site is representative of the moderate to high thermal inertia and low albedo surface unit that is relatively dust free and composed of dark eolian sand and/or increased abundance of rocks. Rock abundance derived from orbital thermal differencing techniques in the equatorial regions agrees with that determined from rock counts at the surface and varies from ~3-20% at the landing sites. The size-frequency distributions of rocks >1.5 m diameter fully resolvable in HiRISE images of the landing sites follow exponential models developed from lander measurements of smaller rocks and are continuous with these rock distributions indicating both are part of the same population. Interpretation of radar data confirms the presence of load bearing, relatively dense surfaces controlled by the soil type at the landing sites, regional rock populations from diffuse scattering similar to those observed directly at the sites, and root-mean-squared slopes that compare favorably

  11. Estimating Daily Global Evapotranspiration Using Penman–Monteith Equation and Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Roozbeh Raoufi

    2017-11-01

    Full Text Available Daily evapotranspiration (ET is modeled globally for the period 2000–2013 based on the Penman–Monteith equation with radiation and vapor pressures derived using remotely sensed Land Surface Temperature (LST from the MODerate resolution Imaging Spectroradiometer (MODIS on the Aqua and Terra satellites. The ET for a given land area is based on four surface conditions: wet/dry and vegetated/non-vegetated. For each, the ET resistance terms are based on land cover, leaf area index (LAI and literature values. The vegetated/non-vegetated fractions of the land surface are estimated using land cover, LAI, a simplified version of the Beer–Lambert law for describing light transition through vegetation and newly derived light extension coefficients for each MODIS land cover type. The wet/dry fractions of the land surface are nonlinear functions of LST derived humidity calibrated using in-situ ET measurements. Results are compared to in-situ measurements (average of the root mean squared errors and mean absolute errors for 39 sites are 0.81 mm day−1 and 0.59 mm day−1, respectively and the MODIS ET product, MOD16, (mean bias during 2001–2013 is −0.2 mm day−1. Although the mean global difference between MOD16 and ET estimates is only 0.2 mm day−1, local temperature derived vapor pressures are the likely contributor to differences, especially in energy and water limited regions. The intended application for the presented model is simulating ET based on long-term climate forecasts (e.g., using only minimum, maximum and mean daily or monthly temperatures.

  12. Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw

    uxes, such as sensible heat ux, ground heat ux and net radiation, are also necessary. While it is possible to measure those uxes with ground-based instruments at local scales, at region scales they usually need to be modelled or estimated with the help of satellite remote sensing data. Even though...... to increase the spatial resolution of the reliable DTD-modelled fluxes from 1 km to 30 m. Furthermore, synergies between remote sensing based models and distributed hydrological models were studied with the aim of improving spatial performance of the hydrological models through incorporation of remote sensing...... of this study was to look at, and improve, various approaches for modelling the land-surface energy uxes at different spatial scales. The work was done using physically-based Two-Source Energy Balance (TSEB) approach as well as semi-empirical \\Triangle" approach. The TSEB-based approach was the main focus...

  13. The influence of land surface parameters on energy flux densities derived from remote sensing data

    Energy Technology Data Exchange (ETDEWEB)

    Tittebrand, A.; Schwiebus, A. [Inst. for Hydrology und Meteorology, TU Dresden (Germany); Berger, F.H. [Observatory Lindenberg, German Weather Service, Lindenberg (Germany)

    2005-04-01

    Knowledge of the vegetation properties surface reflectance, normalised difference vegetation index (NDVI) and leaf area index (LAI) are essential for the determination of the heat and water fluxes between terrestrial ecosystems and the atmosphere. Remote sensing data can be used to derive spatial estimates of the required surface properties. The determination of land surface parameters and their influence on radiant and energy flux densities is investigated with data of different remote sensing systems. Sensitivity studies show the importance of correctly derived land surface properties to estimate the key quantity of the hydrological cycle, the evapotranspiration (L.E), most exactly. In addition to variable parameters like LAI or NDVI there are also parameters which are can not be inferred from satellite data but needed for the Penman-Monteith approach. Fixed values are assumed for these variables because they have little influence on L.E. Data of Landsat-7 ETM+ and NOAA-16 AVHRR are used to show results in different spatial resolution. The satellite derived results are compared with ground truth data provided by the Observatory Lindenberg of the German Weather Service. (orig.)

  14. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    Science.gov (United States)

    Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, P.; Williams, C.; Ardö, J.; Boucher, M.; Cappelaere, B.; de Grandcourt, A.; Nickless, A.; Nouvellon, Y.; Scholes, R.; Kutsch, W.

    2013-03-01

    Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

  15. Do Surface Energy Fluxes Reveal Land Use/Land Cover Change in South Florida?: A Remote Sensing Perspective

    Science.gov (United States)

    Kandel, H. P.; Melesse, A. M.

    2017-12-01

    Series of changes on land use/ land cover in South Florida resulting from drainage and development activities during early to mid-20th followed by restoration measures since late-20th century have had prominent impacts on hydrologic regime and energy fluxes in the region. Previous results from numerical modeling and MODIS-based analysis have shown a shift in dominance of heat fluxes: from latent to sensible along the axes of urbanization, and an opposite along the axes of restoration. This study implements a slightly modified version of surface energy balance algorithm (SEBAL) on cloud-masked Landsat imageries archived over the period of 30-years combined with ground-meteorological data for South Florida using spatial analysis model in ArcGIS and calculates energy flux components: sensible heat flux, latent heat flux, and ground heat flux. The study finally computes variation of Bowen's ratio (BR) and daily evapotranspiration (ET) rate over various land covers for different years. Coexistences are apparent between increased BR and increased intensity of urbanization, and between increased daily ET rates and improved best management practices in agricultural areas. An increase in mean urban BR from 1.67 in 1984 to 3.06 in 2010 show plausible link of BR with urban encroachment of open lands, and expulsion of additional heat by increased population/automobiles/factories/air conditioning units. Likewise, increase in mean agricultural daily ET rates from 0.21 mm/day to 3.60 mm/day between 1984 to 2010 probably shows the effects of improved moisture conditions on the northern farm lands as the results of restoration practices. Once new observed data become available to corroborate these results, remote sensing methods-owing to their greater spatial and temporal details-can be used as assessment measures both for the progress of restoration evaluation and for the extent detection of human-induced climate change.

  16. Spatial and temporal patterns of land surface fluxes from remotely sensed surface temperatures within an uncertainty modelling framework

    Directory of Open Access Journals (Sweden)

    M. F. McCabe

    2005-01-01

    Full Text Available Characterising the development of evapotranspiration through time is a difficult task, particularly when utilising remote sensing data, because retrieved information is often spatially dense, but temporally sparse. Techniques to expand these essentially instantaneous measures are not only limited, they are restricted by the general paucity of information describing the spatial distribution and temporal evolution of evaporative patterns. In a novel approach, temporal changes in land surface temperatures, derived from NOAA-AVHRR imagery and a generalised split-window algorithm, are used as a calibration variable in a simple land surface scheme (TOPUP and combined within the Generalised Likelihood Uncertainty Estimation (GLUE methodology to provide estimates of areal evapotranspiration at the pixel scale. Such an approach offers an innovative means of transcending the patch or landscape scale of SVAT type models, to spatially distributed estimates of model output. The resulting spatial and temporal patterns of land surface fluxes and surface resistance are used to more fully understand the hydro-ecological trends observed across a study catchment in eastern Australia. The modelling approach is assessed by comparing predicted cumulative evapotranspiration values with surface fluxes determined from Bowen ratio systems and using auxiliary information such as in-situ soil moisture measurements and depth to groundwater to corroborate observed responses.

  17. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-02-01

    The increase in irrigated agriculture in Saudi Arabia is having a large impact on its limited groundwater resources. While large-scale water storage changes can be estimated using satellite data, monitoring groundwater abstraction rates is largely non-existent at either farm or regional level, so water management decisions remain ill-informed. Although determining water use from space at high spatiotemporal resolutions remains challenging, a number of approaches have shown promise, particularly in the retrieval of crop water use via evaporation. Apart from satellite-based estimates, land surface models offer a continuous spatial-temporal evolution of full land-atmosphere water and energy exchanges. In this study, we first examine recent trends in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight into the challenges of evaporation retrieval in arid environments. Finally, we present a novel method aimed to retrieve groundwater abstraction rates used in irrigated fields by constraining a land surface model with remote sensing-based evaporation observations. The approach is used to reproduce reported irrigation rates over 41 center-pivot irrigation fields presenting a range of crop dynamics over the course of one year. The results of this application are promising, with mean absolute errors below 3 mm:day-1, bias of -1.6 mm:day-1, and a first rough estimate of total annual abstractions of 65.8 Mm3 (close to the estimated value using reported farm data, 69.42 Mm3). However, further efforts to address the overestimation of bare soil evaporation in the model are required. The uneven coverage of satellite data within the study site allowed us to evaluate its impact on the optimization, with a better match between observed and obtained irrigation rates on fields with

  18. Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

    Science.gov (United States)

    Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

    2010-01-01

    In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

  19. Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperature

    Science.gov (United States)

    Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

  20. Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperatures

    Science.gov (United States)

    Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Arnold, James E. (Technical Monitor)

    2001-01-01

    Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (plus or minus 5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

  1. A review on remotely sensed land surface temperature anomaly as an earthquake precursor

    Science.gov (United States)

    Bhardwaj, Anshuman; Singh, Shaktiman; Sam, Lydia; Joshi, P. K.; Bhardwaj, Akanksha; Martín-Torres, F. Javier; Kumar, Rajesh

    2017-12-01

    The low predictability of earthquakes and the high uncertainty associated with their forecasts make earthquakes one of the worst natural calamities, capable of causing instant loss of life and property. Here, we discuss the studies reporting the observed anomalies in the satellite-derived Land Surface Temperature (LST) before an earthquake. We compile the conclusions of these studies and evaluate the use of remotely sensed LST anomalies as precursors of earthquakes. The arrival times and the amplitudes of the anomalies vary widely, thus making it difficult to consider them as universal markers to issue earthquake warnings. Based on the randomness in the observations of these precursors, we support employing a global-scale monitoring system to detect statistically robust anomalous geophysical signals prior to earthquakes before considering them as definite precursors.

  2. Assimilation of remotely sensed chlorophyll fluorescence data into the land surface model CLM4

    Science.gov (United States)

    Wieneke, S.; Ahrends, H. E.; Rascher, U.; Schween, J.; Schickling, A.; Crewell, S.

    2013-12-01

    Photosynthesis is the most important exchange process of CO2 between the atmosphere and the land-surface. Therefore, the prediction of vegetation response to environmental conditions like increasing CO2 concentrations or plant stress is crucial for a reliable prediction of climate change. Photosynthesis is a complex physiological process that consists of numerous bio-physical sub-processes and chemical reactions. Spatial and temporal patterns of photosynthesis depend on dynamic plant-specific adaptation strategies to highly variable environmental conditions. Photosynthesis can be estimated using land-surface models, but, while state-of-the-art models often rely on Plant Functional Type (PFT) specific constants, they poorly simulate the dynamic adaptation of the physiological status of plant canopies in space and time. Remotely sensed sun-induced chlorophyll fluorescence (SICF) gives us now the possibility to estimate the diurnal dynamic vitality of the photosynthetic apparatus at both, the leaf and canopy levels. We installed within the framework of the Transregio32 project (www.tr32.de) automated hyperspectral fluorescence sensors at an agricultural site (winter wheat) in the Rur catchment area in West Germany at the end of July 2012. End of August, additional measurements of SIFC on nearby temperate grassland site (riparian meadow) and on a sugar beet field were performed. Spatial covering SICF data of the region were obtained during a measurement campaign using the newly developed air-borne hyperspectral sensor HyPlant on the 23 and 27 August 2012. SIFC data and data provided by eddy covariance measurements will be used to update certain model parameters that are normally set as constants. First model results demonstrate that the assimilation of SIFC into the Community Land Model 4 (CLM4) will result in a more realistic simulation of plant-specific adaptation strategies and therefore in a more realistic simulation of photosynthesis in space and time.

  3. Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

    Science.gov (United States)

    Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

    2014-08-01

    The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

  4. Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

    Science.gov (United States)

    Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

    2012-12-01

    The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some

  5. Selection of soil hydraulic properties in a land surface model using remotely-sensed soil moisture and surface temperature

    Science.gov (United States)

    Shellito, P. J.; Small, E. E.; Gutmann, E. D.

    2013-12-01

    Synoptic-scale weather is heavily influenced by latent and sensible heating from the land surface. The partitioning of available energy between these two fluxes as well as the distribution of moisture throughout the soil column is controlled by a unique set of soil hydraulic properties (SHPs) at every location. Weather prediction systems, which use coupled land surface and atmospheric models in their forecasts, must therefore be parameterized with estimates of SHPs. Currently, land surface models (LSMs) obtain SHP values by assuming a correlation exists between SHPs and the soil type, which the USDA maps in 12 classes. This method is spurious because texture is only one control of many that affects SHPs. Alternatively, SHPs can be obtained by calibrating them within the framework of an LSM. Because remotely-sensed data have the potential for continent-wide application, there is a critical need to understand their specific role in calibration efforts and the extent to which such calibrated SHPs can improve model simulations. This study focuses on SHP calibration with soil moisture content (SMC) and land surface temperature (Ts), data that are available from the SMOS and MODIS satellite missions, respectively. The scientific goals of this study are: (1) What is the model performance tradeoff between weighting SMC and Ts differently during the calibration process? (2) What can the tradeoff between calibration using in-situ and remotely-sensed SMC reveal about SHP scaling? (3) How are these relationships influenced by climatic regime and vegetation type? (4) To what extent can calibrated SHPs improve model performance over that of texture-based SHPs? Model calibrations are carried out within the framework of the Noah LSM using the Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm in five different climatic regimes. At each site, a five-dimensional parameter space of SHPs is searched to find the location that minimizes the difference between observed and

  6. Comparing and Combining Remotely Sensed Land Surface Temperature Products for Improved Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Robert M. Parinussa

    2016-02-01

    Full Text Available Land surface temperature (LST is an important variable that provides a valuable connection between the energy and water budget and is strongly linked to land surface hydrology. Space-borne remote sensing provides a consistent means for regularly observing LST using thermal infrared (TIR and passive microwave observations each with unique strengths and weaknesses. The spatial resolution of TIR based LST observations is around 1 km, a major advantage when compared to passive microwave observations (around 10 km. However, a major advantage of passive microwaves is their cloud penetrating capability making them all-weather sensors whereas TIR observations are routinely masked under the presence of clouds and aerosols. In this study, a relatively simple combination approach that benefits from the cloud penetrating capacity of passive microwave sensors was proposed. In the first step, TIR and passive microwave LST products were compared over Australia for both anomalies and raw timeseries. A very high agreement was shown over the vast majority of the country with R2 typically ranging from 0.50 to 0.75 for the anomalies and from 0.80 to 1.00 for the raw timeseries. Then, the scalability of the passive microwave based LST product was examined and a pixel based merging approach through linear scaling was proposed. The individual and merged LST products were further compared against independent LST from the re-analysis model outputs. This comparison revealed that the TIR based LST product agrees best with the re-analysis data (R2 0.26 for anomalies and R2 0.76 for raw data, followed by the passive microwave LST product (R2 0.16 for anomalies and R2 0.66 for raw data and the combined LST product (R2 0.18 for anomalies and R2 0.62 for raw data. It should be noted that the drop in performance comes with an increased revisit frequency of approximately 20% compared to the revised frequency of the TIR alone. Additionally, this comparison against re

  7. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    CSIR Research Space (South Africa)

    Marshall, M

    2013-03-01

    Full Text Available , latent energy (LE: ET energy equivalent) during the rainy season is the primary regulator after solar forcing of energy balance seasonal variability, the strength of which changes signifi- cantly across land cover types (Ramier et al., 2009). At inter... Table 1. Acronyms and their definitions in order of appearance. Acronym Definition ET Evapotranspiration LE Latent Heat LSM Land Surface Model NDVI Normalized Difference Vegetation Index PET Potential Evapotranspiration AMMA African Monsoon...

  8. Parametrization of Land Surface Temperature Fields with Optical and Microwave Remote Sensing in Brazil's Atlantic Forest

    Science.gov (United States)

    McDonald, K. C.; Khan, A.; Carnaval, A. C.

    2016-12-01

    Brazil is home to two of the largest and most biodiverse ecosystems in the world, primarily encompassed in forests and wetlands. A main region of interest in this project is Brazil's Atlantic Forest (AF). Although this forest is only a fraction of the size of the Amazon rainforest, it harbors significant biological richness, making it one of the world's major hotspots for biodiversity. The AF is located on the East to Southeast region of Brazil, bordering the Atlantic Ocean. As luscious and biologically rich as this region is, the area covered by the Atlantic Forest has been diminishing over past decades, mainly due to human influences and effects of climate change. We examine 1 km resolution Land Surface Temperature (LST) data from NASA's Moderate-resolution Imaging Spectroradiometer (MODIS) combined with 25 km resolution radiometric temperature derived from NASA's Advanced Microwave Scanning Radiometer on EOS (AMSR-E) to develop a capability employing both in combination to assess LST. Since AMSR-E is a microwave remote sensing instrument, products derived from its measurements are minimally effected by cloud cover. On the other hand, MODIS data are heavily influenced by cloud cover. We employ a statistical downscaling technique to the coarse-resolution AMSR-E datasets to enhance its spatial resolution to match that of MODIS. Our approach employs 16-day composite MODIS LST data in combination with synergistic ASMR-E radiometric brightness temperature data to develop a combined, downscaled dataset. Our goal is to use this integrated LST retrieval with complementary in situ station data to examine associated influences on regional biodiversity

  9. Land Surface Data Assimilation

    Science.gov (United States)

    Houser, P. R.

    2012-12-01

    Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land

  10. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  11. Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

    Science.gov (United States)

    Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

    2016-04-01

    In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

  12. 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

    City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will

  13. Viking landing sites, remote-sensing observations, and physical properties of Martian surface materials

    Science.gov (United States)

    Moore, H.J.; Jakosky, B.M.

    1989-01-01

    Important problems that confront future scientific exploration of Mars include the physical properties of Martian surface materials and the geologic processes that formed the materials. The design of landing spacecraft, roving vehicles, and sampling devices and the selection of landing sites, vehicle traverses, and sample sites will be, in part, guided by the physical properties of the materials. Four materials occur in the sample fields of the Viking landers: (1) drift, (2) crusty to cloddy, (3) blocky, and (4) rock. The first three are soillike. Drift materials is weak, loose, and porous. We estimate that it has a dielectric constant near 2.4 and a thermal inertia near 1 ?? 10-3 to 3 ?? 10-3 (cal cm-2 sec 1 2 K-1) because of its low bulk density, fine grain size, and small cohesion. Crusty to cloddy material is expected to have a dielectric constant near 2.8 and a thermal inertia near 4 ?? 10-3 to 7 ?? 10-3 because of its moderate bulk density and cementation of grains. Blocky material should have a dielectric constant near 3.3 and a thermal inertia near 7 ?? 10-3 to 9 ?? 10-3 because of its moderate bulk density and cementation. Common basaltic rocks have dielectric constans near 8 and thermal inertias near 30 ?? 10-3 to 60 ?? 10-3. Comparisons of estimated dielectric constants and thermal inertias of the materials at the landing sites with those obtained remotely by Earth-based radars and Viking Orbiter thermal sensors suggest that the materials at the landing sites are good analogs for materials elsewhere on Mars. Correlation of remotely estimated dielectric constant and thermal inertias indicates two modal values for paired values of dielectric constants and thermal inertias near (A) 2 and 2 ?? 10-3 and (B) 3 and 6 ?? 10-3, respectively. These two modes are comparable to the dielectric constants and thermal inertias for drift and crusty to cloddy material, respectively. Dielectric constants and thermal inertias for blocky material are larger but conistent

  14. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  15. Evaluation of coarse scale land surface remote sensing albedo product over rugged terrain

    Science.gov (United States)

    Wen, J.; Xinwen, L.; You, D.; Dou, B.

    2017-12-01

    Satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. The accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. And more literatures investigated the validation methods about the albedo validation in a flat or homogenous surface. However, the albedo performance over rugged terrain is still unknow due to the validation method limited. A multi-validation strategy is implemented to give a comprehensive albedo validation, which will involve the high resolution albedo processing, high resolution albedo validation based on in situ albedo, and the method to upscale the high resolution albedo to a coarse scale albedo. Among them, the high resolution albedo generation and the upscale method is the core step for the coarse scale albedo validation. In this paper, the high resolution albedo is generated by Angular Bin algorithm. And a albedo upscale method over rugged terrain is developed to obtain the coarse scale albedo truth. The in situ albedo located 40 sites in mountain area are selected globally to validate the high resolution albedo, and then upscaled to the coarse scale albedo by the upscale method. This paper takes MODIS and GLASS albedo product as a example, and the prelimarily results show the RMSE of MODIS and GLASS albedo product over rugged terrain are 0.047 and 0.057, respectively under the RMSE with 0.036 of high resolution albedo.

  16. Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

    Science.gov (United States)

    Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

    2016-01-01

    Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

  17. Impact of Land Cover Change Induced by a Fire Event on the Surface Energy Fluxes Derived from Remote Sensing

    Directory of Open Access Journals (Sweden)

    Juan M. Sánchez

    2015-11-01

    Full Text Available Forest fires affect the natural cycle of the vegetation, and the structure and functioning of ecosystems. As a consequence of defoliation and vegetation mortality, surface energy flux patterns can suffer variations. Remote sensing techniques together with surface energy balance modeling offer the opportunity to explore these changes. In this paper we focus on a Mediterranean forest ecosystem. A fire event occurred in 2001 in Almodóvar del Pinar (Spain affecting a pine and shrub area. A two-source energy balance approach was applied to a set of Landsat 5-TM and Landsat 7-EMT+ images to estimate the surface fluxes in the area. Three post-fire periods were analyzed, six, seven, nine, and 11 years after the fire event. Results showed the regeneration of the shrub area in 6–7 years, in contrast to the pine area, where an important decrease in evapotranspiration, around 1 mm·day−1, remained. Differences in evapotranspiration were mitigated nine and 11 years after the fire in the pine area, whereas significant deviations in the rest of the terms of the energy balance equation were still observed. The combined effect of changes in the vegetation structure and surface variables, such as land surface temperature, albedo, or vegetation coverage, is responsible for these variations in the surface energy flux patterns.

  18. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-01-01

    in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight

  19. Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Frederick Policelli

    2018-02-01

    Full Text Available Lake Chad, located in the middle of the African Sahel belt, underwent dramatic decreases in the 1970s and 1980s leaving less than ten percent of its 1960s surface water extent as open water. In this paper, we present an extended record (dry seasons 1988–2016 of the total surface water area of the lake (including both open water and flooded vegetation derived using Land Surface Temperature (LST data (dry seasons 2000–2016 from the NASA Terra MODIS sensor and EUMETSAT Meteosat-based LST measurements (dry seasons 1988–2001 from an earlier study. We also examine the total surface water area for Lake Chad using radar data (dry seasons 2015–2016 from the ESA Sentinel-1a mission. For the limited number of radar data sets available to us (18 data sets, we find on average a close match between the estimates from these data and the corresponding estimates from LST, though we find spatial differences in the estimates using the two types of data. We use these spatial differences to adjust the record (dry seasons 2000–2016 from MODIS LST. Then we use the adjusted record to remove the bias of the existing LST record (dry seasons 1988–2001 derived from Meteosat measurements and combine the two records. From this composite, extended record, we plot the total surface water area of the lake for the dry seasons of 1988–1989 through 2016–2017. We find for the dry seasons of 1988–1989 to 2016–2017 that the maximum total surface water area of the lake was approximately 16,800 sq. km (February and May, 2000, the minimum total surface water area of the lake was approximately 6400 sq. km (November, 1990, and the average was approximately 12,700 sq. km. Further, we find the total surface water area of the lake to be highly variable during this period, with an average rate of increase of approximately 143 km2 per year.

  20. 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

  1. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    NARCIS (Netherlands)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F. D.

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of

  2. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    NARCIS (Netherlands)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F. D.

    2017-01-01

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of

  3. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    Science.gov (United States)

    Romaguera, Mireia; Vaughan, R. Greg; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F.D.

    2018-01-01

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of LST, the LSTgt. We hypothesize that in geothermal areas the LSM time series will underestimate the LST as compared to the remote sensing data, since the former does not account for the geothermal component in its model.In order to extract LSTgt, two approaches of different nature (physical based and data mining) were developed and tested in an area of about 560 × 560 km2 centered at the Kenyan Rift. Pre-dawn data in the study area during the first 45 days of 2012 were analyzed.The results show consistent spatial and temporal LSTgt patterns between the two approaches, and systematic differences of about 2 K. A geothermal area map from surface studies was used to assess LSTgt inside and outside the geothermal boundaries. Spatial means were found to be higher inside the geothermal limits, as well as the relative frequency of occurrence of high LSTgt. Results further show that areas with strong topography can result in anomalously high LSTgt values (false positives), which suggests the need for a slope and aspect correction in the inputs to achieve realistic results in those areas. The uncertainty analysis indicates that large uncertainties of the input parameters may limit detection of LSTgt anomalies. To validate the approaches, higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over the Olkaria geothermal field were used. An established method to estimate radiant geothermal flux was applied providing values between 9 and 24 W/m2 in the geothermal area, which coincides with the LSTgt flux rates obtained with the proposed approaches.The proposed approaches are a first step in estimating LSTgt

  4. Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures

    Directory of Open Access Journals (Sweden)

    Kristina M. McNyset

    2015-12-01

    Full Text Available Although water temperature is important to stream biota, it is difficult to collect in a spatially and temporally continuous fashion. We used remotely-sensed Land Surface Temperature (LST data to estimate mean daily stream temperature for every confluence-to-confluence reach in the John Day River, OR, USA for a ten year period. Models were built at three spatial scales: site-specific, subwatershed, and basin-wide. Model quality was assessed using jackknife and cross-validation. Model metrics for linear regressions of the predicted vs. observed data across all sites and years: site-specific r2 = 0.95, Root Mean Squared Error (RMSE = 1.25 °C; subwatershed r2 = 0.88, RMSE = 2.02 °C; and basin-wide r2 = 0.87, RMSE = 2.12 °C. Similar analyses were conducted using 2012 eight-day composite LST and eight-day mean stream temperature in five watersheds in the interior Columbia River basin. Mean model metrics across all basins: r2 = 0.91, RMSE = 1.29 °C. Sensitivity analyses indicated accurate basin-wide models can be parameterized using data from as few as four temperature logger sites. This approach generates robust estimates of stream temperature through time for broad spatial regions for which there is only spatially and temporally patchy observational data, and may be useful for managers and researchers interested in stream biota.

  5. Linking land use changes to surface water quality variability in Lake Victoria: some insights from remote sensing

    Science.gov (United States)

    Mugo, R. M.; Limaye, A. S.; Nyaga, J. W.; Farah, H.; Wahome, A.; Flores, A.

    2016-12-01

    The water quality of inland lakes is largely influenced by land use and land cover changes within the lake's catchment. In Africa, some of the major land use changes are driven by a number of factors, which include urbanization, intensification of agricultural practices, unsustainable farm management practices, deforestation, land fragmentation and degradation. Often, the impacts of these factors are observable on changes in the land cover, and eventually in the hydrological systems. When the natural vegetation cover is reduced or changed, the surface water flow patterns, water and nutrient retention capacities are also changed. This can lead to high nutrient inputs into lakes, leading to eutrophication, siltation and infestation of floating aquatic vegetation. To assess the relationship between land use and land cover changes in part of the Lake Victoria Basin, a series of land cover maps were derived from Landsat imagery. Changes in land cover were identified through change maps and statistics. Further, the surface water chlorophyll-a concentration and turbidity were derived from MODIS-Aqua data for Lake Victoria. Chlrophyll-a and turbidity are good proxy indicators of nutrient inputs and siltation respectively. The trends in chlorophyll-a and turbidity concentrations were analyzed and compared to the land cover changes over time. Certain land cover changes related to agriculture and urban development were clearly identifiable. While these changes might not be solely responsible for variability in chlrophyll-a and turbidity concentrations in the lake, they are potentially contributing factors to this problem. This work illustrates the importance of addressing watershed degradation while seeking to solve water quality related problems.

  6. Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data

    Directory of Open Access Journals (Sweden)

    C. Corbari

    2010-10-01

    Full Text Available Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST for a distributed hydrological water balance model (FEST-EWB using LST from AHS (airborne hyperspectral scanner, with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model.

    Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity.

    Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in a hydrological process.

    The study site is the agricultural area of Barrax (Spain that is a heterogeneous area with a patchwork of irrigated and non irrigated vegetated fields and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

  7. Land surface Verification Toolkit (LVT)

    Science.gov (United States)

    Kumar, Sujay V.

    2017-01-01

    LVT is a framework developed to provide an automated, consolidated environment for systematic land surface model evaluation Includes support for a range of in-situ, remote-sensing and other model and reanalysis products. Supports the analysis of outputs from various LIS subsystems, including LIS-DA, LIS-OPT, LIS-UE. Note: The Land Information System Verification Toolkit (LVT) is a NASA software tool designed to enable the evaluation, analysis and comparison of outputs generated by the Land Information System (LIS). The LVT software is released under the terms and conditions of the NASA Open Source Agreement (NOSA) Version 1.1 or later. Land Information System Verification Toolkit (LVT) NOSA.

  8. High resolution land surface modeling utilizing remote sensing parameters and the Noah-UCM: a case study in the Los Angeles Basin

    Science.gov (United States)

    Vahmani, P.; Hogue, T. S.

    2014-07-01

    In the current work we investigate the utility of remote sensing based surface parameters in the Noah-UCM (urban canopy model) over a highly developed urban area. Landsat and fused Landsat-MODIS data are utilized to generate high resolution (30 m) monthly spatial maps of green vegetation fraction (GVF), impervious surface area (ISA), albedo, leaf area index (LAI), and emissivity in the Los Angeles metropolitan area. The gridded remotely sensed parameter datasets are directly substituted for the land-use/lookup-table values in the Noah-UCM modeling framework. Model performance in reproducing ET (evapotranspiration) and LST (land surface temperature) fields is evaluated utilizing Landsat-based LST and ET estimates from CIMIS (California Irrigation Management Information System) stations as well as in-situ measurements. Our assessment shows that the large deviations between the spatial distributions and seasonal fluctuations of the default and measured parameter sets lead to significant errors in the model predictions of monthly ET fields (RMSE = 22.06 mm month-1). Results indicate that implemented satellite derived parameter maps, particularly GVF, enhance the Noah-UCM capability to reproduce observed ET patterns over vegetated areas in the urban domains (RMSE = 11.77 mm month-1). GVF plays the most significant role in reproducing the observed ET fields, likely due to the interaction with other parameters in the model. Our analysis also shows that remotely sensed GVF and ISA improve the model capability to predict the LST differences between fully vegetated pixels and highly developed areas. However, the model still underestimates remotely sensed LST values over highly developed areas. We hypothesize that the LST underestimation is due to structural formulation in the UCM and cannot be immediately solved with available parameter choices.

  9. Land surface temperature as an indicator of the unsaturated zone thickness: A remote sensing approach in the Atacama Desert.

    Science.gov (United States)

    Urqueta, Harry; Jódar, Jorge; Herrera, Christian; Wilke, Hans-G; Medina, Agustín; Urrutia, Javier; Custodio, Emilio; Rodríguez, Jazna

    2018-01-15

    Land surface temperature (LST) seems to be related to the temperature of shallow aquifers and the unsaturated zone thickness (∆Z uz ). That relationship is valid when the study area fulfils certain characteristics: a) there should be no downward moisture fluxes in an unsaturated zone, b) the soil composition in terms of both, the different horizon materials and their corresponding thermal and hydraulic properties, must be as homogeneous and isotropic as possible, c) flat and regular topography, and d) steady state groundwater temperature with a spatially homogeneous temperature distribution. A night time Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image and temperature field measurements are used to test the validity of the relationship between LST and ∆Z uz at the Pampa del Tamarugal, which is located in the Atacama Desert (Chile) and meets the above required conditions. The results indicate that there is a relation between the land surface temperature and the unsaturated zone thickness in the study area. Moreover, the field measurements of soil temperature indicate that shallow aquifers dampen both the daily and the seasonal amplitude of the temperature oscillation generated by the local climate conditions. Despite empirically observing the relationship between the LST and ∆Z uz in the study zone, such a relationship cannot be applied to directly estimate ∆Z uz using temperatures from nighttime thermal satellite images. To this end, it is necessary to consider the soil thermal properties, the soil surface roughness and the unseen water and moisture fluxes (e.g., capillarity and evaporation) that typically occur in the subsurface. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. High-resolution land surface modeling utilizing remote sensing parameters and the Noah UCM: a case study in the Los Angeles Basin

    Science.gov (United States)

    Vahmani, P.; Hogue, T. S.

    2014-12-01

    In the current work we investigate the utility of remote-sensing-based surface parameters in the Noah UCM (urban canopy model) over a highly developed urban area. Landsat and fused Landsat-MODIS data are utilized to generate high-resolution (30 m) monthly spatial maps of green vegetation fraction (GVF), impervious surface area (ISA), albedo, leaf area index (LAI), and emissivity in the Los Angeles metropolitan area. The gridded remotely sensed parameter data sets are directly substituted for the land-use/lookup-table-based values in the Noah-UCM modeling framework. Model performance in reproducing ET (evapotranspiration) and LST (land surface temperature) fields is evaluated utilizing Landsat-based LST and ET estimates from CIMIS (California Irrigation Management Information System) stations as well as in situ measurements. Our assessment shows that the large deviations between the spatial distributions and seasonal fluctuations of the default and measured parameter sets lead to significant errors in the model predictions of monthly ET fields (RMSE = 22.06 mm month-1). Results indicate that implemented satellite-derived parameter maps, particularly GVF, enhance the capability of the Noah UCM to reproduce observed ET patterns over vegetated areas in the urban domains (RMSE = 11.77 mm month-1). GVF plays the most significant role in reproducing the observed ET fields, likely due to the interaction with other parameters in the model. Our analysis also shows that remotely sensed GVF and ISA improve the model's capability to predict the LST differences between fully vegetated pixels and highly developed areas.

  11. Seasonal evaluation of the land surface scheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian region in Hungary

    Directory of Open Access Journals (Sweden)

    E. L. Wipfler

    2011-04-01

    Full Text Available 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 Hungary and compared to model outcomes. Atmospheric forcings are obtained from a hindcast run with the Regional Climate Model RACMO2. Although HTESSEL slightly underpredicts the seasonal evaporative fraction as compared to satellite estimates, the mean, 10th and 90th percentile of this variable are of the same magnitude as the satellite observations. The initial water as stored in the soil and snow layer does not have a significant effect on the statistical properties of the evaporative fraction. However, the spatial distribution of the initial soil and snow water significantly affects the spatial distribution of the calculated evaporative fraction and the models ability to reproduce evaporation correctly in low precipitation areas in the considered region. HTESSEL performs weaker in dryer areas. In Western Hungary these areas are situated in the Danube valley, which is partly covered by irrigated cropland and which also may be affected by shallow groundwater. Incorporating (lateral groundwater flow and irrigation, processes that are not included now, may improve HTESSELs ability to predict evaporation correctly. Evaluation of the model skills using other test areas and larger evaluation periods is needed to confirm the results.

    Based on earlier sensitivity analysis, the effect of a number of modifications to HTESSEL has been assessed. A more physically based reduction function for dry soils has been introduced, the soil depth is made variable and the effect of swallow groundwater included. However, the combined modification does not lead to a significantly improved performance of HTESSEL.

  12. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

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

  13. 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...... 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...... 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...

  14. Linking Land Use Changes to Surface Water Quality Variability in Lake Victoria: Some Insights From Remote Sensing (GC41B-1101)

    Science.gov (United States)

    Limaye, Ashutosh; Mugo, Robinson; Wanjohi, James; Farah, Hussein; Wahome, Anastasia; Flores, Africa; Irwin, Dan

    2016-01-01

    Various land use changes driven by urbanization, conversion of grasslands and woodlands into farmlands, intensification of agricultural practices, deforestation, land fragmentation and degradation are taking place in Africa. In Kenya, agriculture is the main driver of land use conversions. The impacts of these land use changes are observable in land cover maps, and eventually in the hydrological systems. Reduction or change of natural vegetation cover types increases the speed of surface runoff and reduces water and nutrient retention capacities. This can lead to high nutrient inputs into lakes, resulting in eutrophication, siltation and infestation of floating aquatic vegetation. To assess if changes in land use could be contributing to increased phytoplankton blooms and sediment loads into Lake Victoria, we analyzed land use land cover data from Landsat, as well as surface chlorophyll-a and total suspended matter from MODIS-Aqua sensor.

  15. Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

    Science.gov (United States)

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

    2010-05-01

    The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

  16. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Longhenry, Ryan

    2018-06-13

    The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

  17. 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......., because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail...

  18. Nasa's Land Remote Sensing Plans for the 1980's

    Science.gov (United States)

    Higg, H. C.; Butera, K. M.; Settle, M.

    1985-01-01

    Research since the launch of LANDSAT-1 has been primarily directed to the development of analysis techniques and to the conduct of applications studies designed to address resource information needs in the United States and in many other countries. The current measurement capabilities represented by MSS, TM, and SIR-A and B, coupled with the present level of remote sensing understanding and the state of knowledge in the discipline earth sciences, form the foundation for NASA's Land Processes Program. Science issues to be systematically addressed include: energy balance, hydrologic cycle, biogeochemical cycles, biological productivity, rock cycle, landscape development, geological and botanical associations, and land surface inventory, monitoring, and modeling. A global perspective is required for using remote sensing technology for problem solving or applications context. A successful model for this kind of activity involves joint research with a user entity where the user provides a test site and ground truth and NASA provides the remote sensing techniques to be tested.

  19. 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...

  20. 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

  1. LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring

    Science.gov (United States)

    Moorthy, Inian; Fritz, Steffen; See, Linda; McCallum, Ian

    2017-04-01

    Currently within the EU's Earth Observation (EO) monitoring framework, there is a need for low-cost methods for acquiring high quality in-situ data to create accurate and well-validated environmental monitoring products. To help address this need, a new four year Horizon 2020 project entitled LandSense will link remote sensing data with modern participatory data collection methods that involve citizen scientists. This paper will describe the citizen science activities within the LandSense Observatory that aim to deliver concrete, measurable and quality-assured ground-based data that will complement existing satellite monitoring systems. LandSense will deploy advanced tools, services and resources to mobilize and engage citizens to collect in-situ observations (i.e. ground-based data and visual interpretations of EO imagery). Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources will help reduce costs, extend GEOSS and Copernicus capacities, and support comprehensive environmental monitoring systems. Policy-relevant campaigns will be implemented in close collaboration with multiple stakeholders to ensure that citizen observations address user requirements and contribute to EU-wide environmental governance and decision-making. Campaigns for addressing local and regional Land Use and Land Cover (LULC) issues are planned for select areas in Austria, France, Germany, Spain, Slovenia and Serbia. Novel LandSense services (LandSense Campaigner, FarmLand Support, Change Detector and Quality Assurance & Control) will be deployed and tested in these areas to address critical LULC issues (i.e. urbanization, agricultural land use and forest/habitat monitoring). For example, local residents in the cities of Vienna, Tulln, and Heidelberg will help cooperatively detect and map changes in land cover and green space to address key issues of urban sprawl, land take and flooding. Such campaigns are facilitated through

  2. THE EFFECT OF LAND USE CHANGE ON LAND SURFACE TEMPERATURE IN THE NETHERLANDS

    Directory of Open Access Journals (Sweden)

    S. Youneszadeh

    2015-12-01

    Full Text Available The Netherlands is a small country with a relatively large population which experienced a rapid rate of land use changes from 2000 to 2008 years due to the industrialization and population increase. Land use change is especially related to the urban expansion and open agriculture reduction due to the enhanced economic growth. This research reports an investigation into the application of remote sensing and geographical information system (GIS in combination with statistical methods to provide a quantitative information on the effect of land use change on the land surface temperature. In this study, remote sensing techniques were used to retrieve the land surface temperature (LST by using the MODIS Terra (MOD11A2 Satellite imagery product. As land use change alters the thermal environment, the land surface temperature (LST could be a proper change indicator to show the thermal changes in relation with land use changes. The Geographical information system was further applied to extract the mean yearly land surface temperature (LST for each land use type and each province in the 2003, 2006 and 2008 years, by using the zonal statistic techniques. The results show that, the inland water and offshore area has the highest night land surface temperature (LST. Furthermore, the Zued (South-Holland province has the highest night LST value in the 2003, 2006 and 2008 years. The result of this research will be helpful tool for urban planners and environmental scientists by providing the critical information about the land surface temperature.

  3. Use of remote sensing for land use policy formulation

    Science.gov (United States)

    1987-01-01

    The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

  4. Surface holograms for sensing application

    Science.gov (United States)

    Zawadzka, M.; Naydenova, I.

    2018-01-01

    Surface gratings with periodicity of 2 μm and amplitude in the range of 175 and 240 nm were fabricated in a plasticized polyvinylchloride doped with a metalloporphyrin (ZnTPP), via a single laser pulse holographic ablation process. The effect of the laser pulse energy on the profiles of the fabricated surface structure was investigated. The sensing capabilities of the fabricated diffractive structures towards amines (triethylamine, diethylamine) and pyridine vapours were then explored; the holographic structures were exposed to the analyte vapours and changes in the intensity of the diffracted light were monitored in real time at 473 nm. It was demonstrated that surface structures, fabricated in a polymer doped with a metalloporphyrin which acts as analyte receptor, have a potential in sensing application.

  5. Land remote sensing commercialization: A status report

    Science.gov (United States)

    Bishop, W. P.; Heacock, E. L.

    1984-01-01

    The current offer by the United States Department of Commerce to transfer the U.S. land remote sensing program to the private sector is described. A Request for Proposals (RFP) was issued, soliciting offers from U.S. firms to provide a commercial land remote sensing satellite system. Proposals must address a complete system including satellite, communications, and ground data processing systems. Offerors are encouraged to propose to take over the Government LANDSAT system which consists of LANDSAT 4 and LANDSAT D'. Also required in proposals are the market development procedures and plans to ensure that commercialization is feasible and the business will become self-supporting at the earliest possible time. As a matter of Federal Policy, the solicitation is designed to protect both national security and foreign policy considerations. In keeping with these concerns, an offeror must be a U.S. Firm. Requirements for data quality, quantity, distribution and delivery are met by current operational procedures. It is the Government's desire that the Offeror be prepared to develop and operate follow-on systems without Government subsidies. However, to facilitate rapid commercialization, an offeror may elect to include in his proposal mechanisms for short term government financial assistance.

  6. 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.

  7. Land surface Verification Toolkit (LVT) - a generalized framework for land surface model evaluation

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J.; Harrison, K.; Liu, Y.; Shaw, M.

    2012-06-01

    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 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.

  8. New Directions in Land Remote Sensing Policy and International Cooperation

    Science.gov (United States)

    Stryker, Timothy

    2010-12-01

    Recent changes to land remote sensing satellite data policies in Brazil and the United States have led to the phenomenal growth in the delivery of land imagery to users worldwide. These new policies, which provide free and unrestricted access to land remote sensing data over a standard electronic interface, are expected to provide significant benefits to scientific and operational users, and open up new areas of Earth system science research and environmental monitoring. Freely-available data sets from the China-Brazil Earth Resources Satellites (CBERS), the U.S. Landsat satellites, and other satellite missions provide essential information for land surface monitoring, ecosystems management, disaster mitigation, and climate change research. These missions are making important contributions to the goals and objectives of regional and global terrestrial research and monitoring programs. These programs are in turn providing significant support to the goals and objectives of the United Nations Framework Convention on Climate Change (UN FCCC), the Global Earth Observation System of Systems (GEOSS), and the UN Reduction in Emissions from Deforestation and Degradation (REDD) program. These data policies are well-aligned with the "Data Democracy" initiative undertaken by the international Committee on Earth Observation Satellites (CEOS), through its current Chair, Brazil's National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais, or INPE), and its former chairs, South Africa's Council for Scientific and Industrial Research (CSIR) and Thailand's Geo Informatics and Space Technology Development Agency (GISTDA). Comparable policies for land imaging data are under consideration within Europe and Canada. Collectively, these initiatives have the potential to accelerate and improve international mission collaboration, and greatly enhance the access, use, and application of land surface imagery for environmental monitoring and societal adaption to changing

  9. Near-surface land disposal

    International Nuclear Information System (INIS)

    Kittel, J.H.

    1989-01-01

    The Radioactive Waste Management Handbook provides a comprehensive, systematic treatment of nuclear waste management. Near-Surface Land Disposal, the first volume, is a primary and secondary reference for the technical community. To those unfamiliar with the field, it provides a bridge to a wealth of technical information, presenting the technology associated with the near-surface disposal of low or intermediate level wastes. Coverage ranges from incipient planning to site closure and subsequent monitoring. The book discusses the importance of a systems approach during the design of new disposal facilities so that performance objectives can be achieved; gives an overview of the radioactive wastes cosigned to near-surface disposal; addresses procedures for screening and selecting sites; and emphasizes the importance of characterizing sites and obtaining reliable geologic and hydrologic data. The planning essential to the development of particular sites (land acquisition, access, layout, surface water management, capital costs, etc.) is considered, and site operations (waste receiving, inspection, emplacement, closure, stabilization, etc.) are reviewed. In addition, the book presents concepts for improved confinement of waste, important aspects of establishing a monitoring program at the disposal facility, and corrective actions available after closure to minimize release. Two analytical techniques for evaluating alternative technologies are presented. Nontechnical issues surrounding disposal, including the difficulties of public acceptance are discussed. A glossary of technical terms is included

  10. Surface rights on Aboriginal lands

    International Nuclear Information System (INIS)

    McElhanney, W.L.

    1998-01-01

    Several issues regarding access and activity by petroleum industry on Aboriginal and Metis lands are discussed. Some alternative means by which both industry and Aboriginal groups can approach the matter of surface rights are presented. A historical account of how surface rights have been interpreted in the past was given. It was emphasized that the approach to surface rights compensation and negotiation for both aboriginal and industry parties must begin with adequate consultation. Rigid adherence to the usual past practice of geologically identifying locations, surveying and requesting a lease will no longer suffice. The aboriginal community must be consulted with as much lead time as possible, even assisted financially to identify traditional use areas that require protection, or cannot be disturbed, or require particular mitigation measures. Once this has been done, the operator can proceed to outline the scope of his project, detailing the timing, location, business and employment opportunities and other economic opportunities to the community. 21 refs

  11. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    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......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...... by the hydrological model is found to be insensitive to model resolution. Furthermore, this study highlights the effect of bias precipitation by regional climate model and it implications for hydrological modelling....

  12. evaluation of land surface temperature parameterization ...

    African Journals Online (AJOL)

    user

    Surface temperature (Ts) is vital to the study of land-atmosphere interactions and ... representation of Ts in Global Climate Models using available ..... Obviously, the influence of the ambient .... diurnal cycle over land under clear and cloudy.

  13. Extreme Maximum Land Surface Temperatures.

    Science.gov (United States)

    Garratt, J. R.

    1992-09-01

    There are numerous reports in the literature of observations of land surface temperatures. Some of these, almost all made in situ, reveal maximum values in the 50°-70°C range, with a few, made in desert regions, near 80°C. Consideration of a simplified form of the surface energy balance equation, utilizing likely upper values of absorbed shortwave flux (1000 W m2) and screen air temperature (55°C), that surface temperatures in the vicinity of 90°-100°C may occur for dry, darkish soils of low thermal conductivity (0.1-0.2 W m1 K1). Numerical simulations confirm this and suggest that temperature gradients in the first few centimeters of soil may reach 0.5°-1°C mm1 under these extreme conditions. The study bears upon the intrinsic interest of identifying extreme maximum temperatures and yields interesting information regarding the comfort zone of animals (including man).

  14. Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

    Science.gov (United States)

    Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

    2014-01-01

    Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

  15. 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.

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

    Science.gov (United States)

    Santanello, J. A.; Kumar, S.; Peters-Lidard, C. D.; Harrison, K. W.; Zhou, S.

    2012-12-01

    Land-atmosphere (L-A) interactions play a 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 (LIS-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.

  17. Land surface and climate parameters and malaria features in Vietnam

    Science.gov (United States)

    Liou, Y. A.; Anh, N. K.

    2017-12-01

    Land surface parameters may affect local microclimate, which in turn alters the development of mosquito habitats and transmission risks (soil-vegetation-atmosphere-vector borne diseases). Forest malaria is a chromic issue in Southeast Asian countries, in particular, such as Vietnam (in 1991, approximate 2 million cases and 4,646 deaths were reported (https://sites.path.org)). Vietnam has lowlands, sub-tropical high humidity, and dense forests, resulting in wide-scale distribution and high biting rate of mosquitos in Vietnam, becoming a challenging and out of control scenario, especially in Vietnamese Central Highland region. It is known that Vietnam's economy mainly relies on agriculture and malaria is commonly associated with poverty. There is a strong demand to investigate the relationship between land surface parameters (land cover, soil moisture, land surface temperature, etc.) and climatic variables (precipitation, humidity, evapotranspiration, etc.) in association with malaria distribution. GIS and remote sensing have been proven their powerful potentials in supporting environmental and health studies. The objective of this study aims to analyze physical attributes of land surface and climate parameters and their links with malaria features. The outcomes are expected to illustrate how remotely sensed data has been utilized in geohealth applications, surveillance, and health risk mapping. In addition, a platform with promising possibilities of allowing disease early-warning systems with citizen participation will be proposed.

  18. Land-surface modelling in hydrological perspective ? a review

    OpenAIRE

    Overgaard , J.; Rosbjerg , D.; Butts , M. B.

    2006-01-01

    International audience; 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, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opport...

  19. Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements

    Directory of Open Access Journals (Sweden)

    S. Saadi

    2018-04-01

    Full Text Available In semiarid areas, agricultural production is restricted by water availability; hence, efficient agricultural water management is a major issue. The design of tools providing regional estimates of evapotranspiration (ET, one of the most relevant water balance fluxes, may help the sustainable management of water resources. Remote sensing provides periodic data about actual vegetation temporal dynamics (through the normalized difference vegetation index, NDVI and water availability under water stress (through the surface temperature Tsurf, which are crucial factors controlling ET. In this study, spatially distributed estimates of ET (or its energy equivalent, the latent heat flux LE in the Kairouan plain (central Tunisia were computed by applying the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE model fed by low-resolution remote sensing data (Terra and Aqua MODIS. The work's goal was to assess the operational use of the SPARSE model and the accuracy of the modeled (i sensible heat flux (H and (ii daily ET over a heterogeneous semiarid landscape with complex land cover (i.e., trees, winter cereals, summer vegetables. SPARSE was run to compute instantaneous estimates of H and LE fluxes at the satellite overpass times. The good correspondence (R2  =  0.60 and 0.63 and RMSE  =  57.89 and 53.85 W m−2 for Terra and Aqua, respectively between instantaneous H estimates and large aperture scintillometer (XLAS H measurements along a path length of 4 km over the study area showed that the SPARSE model presents satisfactory accuracy. Results showed that, despite the fairly large scatter, the instantaneous LE can be suitably estimated at large scales (RMSE  =  47.20 and 43.20 W m−2 for Terra and Aqua, respectively, and R2  =  0.55 for both satellites. Additionally, water stress was investigated by comparing modeled (SPARSE and observed (XLAS water stress values; we found that

  20. Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements

    Science.gov (United States)

    Saadi, Sameh; Boulet, Gilles; Bahir, Malik; Brut, Aurore; Delogu, Émilie; Fanise, Pascal; Mougenot, Bernard; Simonneaux, Vincent; Lili Chabaane, Zohra

    2018-04-01

    In semiarid areas, agricultural production is restricted by water availability; hence, efficient agricultural water management is a major issue. The design of tools providing regional estimates of evapotranspiration (ET), one of the most relevant water balance fluxes, may help the sustainable management of water resources. Remote sensing provides periodic data about actual vegetation temporal dynamics (through the normalized difference vegetation index, NDVI) and water availability under water stress (through the surface temperature Tsurf), which are crucial factors controlling ET. In this study, spatially distributed estimates of ET (or its energy equivalent, the latent heat flux LE) in the Kairouan plain (central Tunisia) were computed by applying the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) model fed by low-resolution remote sensing data (Terra and Aqua MODIS). The work's goal was to assess the operational use of the SPARSE model and the accuracy of the modeled (i) sensible heat flux (H) and (ii) daily ET over a heterogeneous semiarid landscape with complex land cover (i.e., trees, winter cereals, summer vegetables). SPARSE was run to compute instantaneous estimates of H and LE fluxes at the satellite overpass times. The good correspondence (R2 = 0.60 and 0.63 and RMSE = 57.89 and 53.85 W m-2 for Terra and Aqua, respectively) between instantaneous H estimates and large aperture scintillometer (XLAS) H measurements along a path length of 4 km over the study area showed that the SPARSE model presents satisfactory accuracy. Results showed that, despite the fairly large scatter, the instantaneous LE can be suitably estimated at large scales (RMSE = 47.20 and 43.20 W m-2 for Terra and Aqua, respectively, and R2 = 0.55 for both satellites). Additionally, water stress was investigated by comparing modeled (SPARSE) and observed (XLAS) water stress values; we found that most points were located within a 0.2 confidence interval, thus the

  1. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Wang, T.X.

    2014-01-01

    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

  2. Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

    Science.gov (United States)

    Nguyen, L. H.; Henebry, G. M.

    2017-12-01

    The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

  3. Testing the accuracy of remote sensing land use maps

    Science.gov (United States)

    Vangenderen, J. L.; Lock, B. F.; Vass, P. A.

    1977-01-01

    Some of the main aspects that need to be considered in a remote sensing sampling design are: (1) the frequency that any one land use type (on the ground) is erroneously attributed to another class by the interpreter; (2) the frequency that the wrong land use (as observed on the ground) is erroneously included in any one class by the remote sensing interpreter; (3) the proportion of all land (as determined in the field) that is mistakenly attributed by the interpreter; and (4) the determination of whether the mistakes are random (so that the overall proportions are approximately correct) or subject to a persistent bias. A sampling and statistical testing procedure is presented which allows an approximate answer to each of these aspects. The concept developed and described incorporates the probability of making incorrect interpretations at particular prescribed accuracy levels, for a certain number of errors, for a particular sample size. It is considered that this approach offers a meaningful explanation of the interpretation accuracy level of an entire remote sensing land use survey.

  4. 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 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. Key Points Understanding 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 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. A shorter time to maximal plantar pressure was found during a hard surface landing in the 1st and 2nd 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 1st phalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the 1st to 4th metatarsal

  5. ENVIRONMENTAL IMPACT ASSESSMENT OF LAND USE PLANING AROUND THE LEASED LIMESTONE MINE USING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    P. Ranade

    2007-01-01

    Full Text Available Mining activities and the waste products produced can have significant impact on the surrounding environment - ranging from localized surface and ground water contamination to the damaging effects of airborne pollutants on the regional ecosystem. The long term monitoring of environmental impacts requires a cost effective method to characterize land cover and land cover changes over time. As per the guidelines of Ministry of Environment and Forest, Govt. of India, it is mandatory to study and analyze the impacts of mining on its surroundings. The use of remote sensing technology to generate reliable land cover maps is a valuable asset to completing environmental assessments over mining affected areas. In this paper, a case study has been discussed to study the land use – land cover status around 10 Km radius of open cast limestone mine area and the subsequent impacts on environmental as well as social surroundings.

  6. 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.

  7. 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.

  8. Climate Impacts of Fire-Induced Land-Surface Changes

    Science.gov (United States)

    Liu, Y.; Hao, X.; Qu, J. J.

    2017-12-01

    One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

  9. Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

    Science.gov (United States)

    Lo, C. P.; Quattrochi, Dale A.

    2003-01-01

    Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

  10. The use of the Space Shuttle for land remote sensing

    Science.gov (United States)

    Thome, P. G.

    1982-01-01

    The use of the Space Shuttle for land remote sensing will grow significantly during the 1980's. The main use will be for general land cover and geological mapping purposes by worldwide users employing specialized sensors such as: high resolution film systems, synthetic aperture radars, and multispectral visible/IR electronic linear array scanners. Because these type sensors have low Space Shuttle load factors, the user's preference will be for shared flights. With this strong preference and given the present prognosis for Space Shuttle flight frequency as a function of orbit inclination, the strongest demand will be for 57 deg orbits. However, significant use will be made of lower inclination orbits. Compared with freeflying satellites, Space Shuttle mission investment requirements will be significantly lower. The use of the Space Shuttle for testing R and D land remote sensors will replace the free-flying satellites for most test programs.

  11. Long-Term Monitoring of Desert Land and Natural Resources and Application of Remote Sensing Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Hamada, Yuki [Argonne National Lab. (ANL), Argonne, IL (United States); Rollins, Katherine E. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-11-01

    Monitoring environmental impacts over large, remote desert regions for long periods of time can be very costly. Remote sensing technologies present a promising monitoring tool because they entail the collection of spatially contiguous data, automated processing, and streamlined data analysis. This report provides a summary of remote sensing products and refinement of remote sensing data interpretation methodologies that were generated as part of the U.S. Department of the Interior Bureau of Land Management Solar Energy Program. In March 2015, a team of researchers from Argonne National Laboratory (Argonne) collected field data of vegetation and surface types from more than 5,000 survey points within the eastern part of the Riverside East Solar Energy Zone (SEZ). Using the field data, remote sensing products that were generated in 2014 using very high spatial resolution (VHSR; 15 cm) multispectral aerial images were validated in order to evaluate potential refinements to the previous methodologies to improve the information extraction accuracy.

  12. Land and Forest Management by Land Use/ Land Cover Analysis and Change Detection Using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    Ankana

    2016-01-01

    Full Text Available Remote sensing and Geographical Information System (GIS are the most effective tools in spatial data analysis. Natural resources like land, forest and water, these techniques have proved a valuable source of information generation as well as in the management and planning purposes. This study aims to suggest possible land and forest management strategies in Chakia tahsil based on land use and land cover analysis and the changing pattern observed during the last ten years. The population of Chakia tahsil is mainly rural in nature. The study has revealed that the northern part of the region, which offers for the settlement and all the agricultural practices constitutes nearly 23.48% and is a dead level plain, whereas the southern part, which constitute nearly 76.6% of the region is characterized by plateau and is covered with forest. The southern plateau rises abruptly from the northern alluvial plain with a number of escarpments. The contour line of 100 m mainly demarcates the boundary between plateau and plain. The plateau zone is deeply dissected and highly rugged terrain. The resultant topography comprises of a number of mesas and isolated hillocks showing elevation differences from 150 m to 385 m above mean sea level. Being rugged terrain in the southern part, nowadays human encroachment are taking place for more land for the cultivation. The changes were well observed in the land use and land cover in the study region. A large part of fallow land and open forest were converted into cultivated land.

  13. The Improvement of Land Cover Classification by Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Liya Sun

    2015-06-01

    Full Text Available Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.

  14. Surface mining and land reclamation in Germany

    Energy Technology Data Exchange (ETDEWEB)

    Nephew, E.A.

    1972-05-01

    Mining and land restoration methods as well as planning and regulatory procedures employed in West Germany to ameliorate environmental impacts from large-scale surface mining are described. The Rhineland coalfield in North Rhine Westphalia contains some 55 billion tons of brown-coal (or lignite), making the region one of Europe's most important energy centers. The lignite is extracted from huge, open-pit mines, resulting in large areas of disturbed land. The German reclamation approach is characterized by planning and carrying out the mining process as one continuum from early planning to final restoration of land and its succeeding use. Since the coalfield is located in a populated region with settlements dating back to Roman times, whole villages lying in the path of the mining operations sometimes have to be evacuated and relocated. Even before mining begins, detailed concepts must be worked out for the new landscape which will follow: the topography, the water drainage system, lakes and forests, and the intended land-use pattern are designed and specified in advance. Early, detailed planning makes it possible to coordinate mining and concurrent land reclamation activities. The comprehensive approach permits treating the overall problem as a whole rather than dealing with its separate aspects on a piecemeal basis.

  15. Estimation of surface air temperature over central and eastern Eurasia from MODIS land surface temperature

    International Nuclear Information System (INIS)

    Shen Suhung; Leptoukh, Gregory G

    2011-01-01

    Surface air temperature (T a ) is a critical variable in the energy and water cycle of the Earth–atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T a from satellite remotely sensed land surface temperature (T s ) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T a and MODIS T s . The relationships between the maximum T a and daytime T s depend significantly on land cover types, but the minimum T a and nighttime T s have little dependence on the land cover types. The largest difference between maximum T a and daytime T s appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T a were estimated from 1 km resolution MODIS T s under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T a were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T a varies from 2.4 °C over closed shrublands to 3.2 °C over grasslands, and the MAE of the estimated minimum T a is about 3.0 °C.

  16. ASSESSING LAND COVER CHANGES CAUSED BY GRANITE QUARRYING USING REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    R. S. Moeletsi

    2017-11-01

    Full Text Available Dimension stone quarrying in the area between Rustenburg and Brits in the North West Province of South Africa has been in existence for over 70 decades. The unique characteristics of the granite deposits in South Africa resulted in making the country a global producer of the granite rocks. This led to intensified quarrying activities between Rustenburg and Brits town. However, this surface mining method, has a potential to impact the environment in a negative way causing loss in vegetation, depletion of natural resources, loss of scenic beauty and contamination of surface water resources. To assess the land cover changes caused by granite quarrying activities, remotely sensed data in the form of Landsat images between 1998 and 2015 were used. Supervised classification was used to create maps. Accuracy assessment using Google EarthTM as a reference data yielded an overall accuracy of 78 %. The post classification change detection method was used to assess land cover changes within the granite quarries. Granite quarries increased by 1174.86 ha while formation of quarry lakes increased to 5.3 ha over the 17-year period. Vegetation cover decreased by 1308 ha in area while 18.3 ha bare land was lost during the same period. This study demonstrated the utility of remote sensing to detect changes in land cover within granite quarries.

  17. Estimation of land surface temperature of Kaduna metropolis ...

    African Journals Online (AJOL)

    Estimation of land surface temperature of Kaduna metropolis, Nigeria using landsat images. Isa Zaharaddeen, Ibrahim I. Baba, Ayuba Zachariah. Abstract. Understanding the spatial variation of Land Surface Temperature (LST), will be helpful in urban micro climate studies. This study estimates the land surface temperature ...

  18. Communicating why land surface heterogeneity matters

    Science.gov (United States)

    Tague, C.; Burke, W.; Bart, R. R.; Turpin, E.; Wood, T.; Gordon, D.

    2017-12-01

    As hydrologic scientists, we know that land surface heterogeneity can have nuanced and sometimes dramatic impacts on the water cycle. Land surface characteristics, including the structure and composition of vegetation and soil storage and drainage properties, alter how incoming precipitation is translated into streamflow and evapotranspiration. Land surface heterogeneity can explain why this partitioning of incoming precipitation cannot always be computed by a simple water budget calculation. We also know that land surface characteristics are dynamic - vegetation grows and changes with fire, disease and human actions and these changes will alter the partitioning of water - how much so, however depends itself on other site characteristics - soil water storage and the timing and magnitude of precipitation. This complex impact of space-time dynamics on the water cycle is something we need to effectively communicate to non-experts. For example, we may want to explain why sometimes forest management practices increase water availability but sometimes they don't - or why the impacts of urbanization or fire are location specific. If we do not communicate these dependencies we risk over-simplifying and eroding scientific credibility when observed effects don't match simple generalizations. On the other hand excessive detail can overwhelm and disengage audiences. So how do we help different communities public, private landowners, other scientists, NGOs, governments to better understand the role of space-time heterogeneity. To address this issue, we present some results from ongoing work that looks at the impact of fuel treatment of forest ecohydrology. This work stem from a collaboration between an ecohydrologic modeling team, social-scientists, a visual artist and compute graphics students. We use a coupled model, validated with field measurements, to show why spatial heterogeneity matters for understanding the impact of fuel treatments on the water cycle for the Sierra

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

    KAUST Repository

    Houborg, Rasmus; Cescatti, Alessandro; Gitelson, Anatoly A.

    2013-01-01

    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

  20. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  1. ENVISAT Land Surface Processes. Phase 2

    Science.gov (United States)

    vandenHurk, B. J. J. M.; Su, Z.; Verhoef, W.; Menenti, M.; Li, Z.-L.; Wan, Z.; Moene, A. F.; Roerink, G.; Jia, I.

    2002-01-01

    This is a progress report of the 2nd phase of the project ENVISAT- Land Surface Processes, which has a 3-year scope. In this project, preparative research is carried out aiming at the retrieval of land surface characteristics from the ENVISAT sensors MERIS and AATSR, for assimilation into a system for Numerical Weather Prediction (NWP). Where in the 1st phase a number of first shot experiments were carried out (aiming at gaining experience with the retrievals and data assimilation procedures), the current 2nd phase has put more emphasis on the assessment and improvement of the quality of the retrieved products. The forthcoming phase will be devoted mainly to the data assimilation experiments and the assessment of the added value of the future ENVISAT products for NWP forecast skill. Referring to the retrieval of albedo, leaf area index and atmospheric corrections, preliminary radiative transfer calculations have been carried out that should enable the retrieval of these parameters once AATSR and MERIS data become available. However, much of this work is still to be carried out. An essential part of work in this area is the design and implementation of software that enables an efficient use of MODTRAN(sub 4) radiative transfer code, and during the current project phase familiarization with these new components has been achieved. Significant progress has been made with the retrieval of component temperatures from directional ATSR-images, and the calculation of surface turbulent heat fluxes from these data. The impact of vegetation cover on the retrieved component temperatures appears manageable, and preliminary comparison of foliage temperature to air temperatures were encouraging. The calculation of surface fluxes using the SEBI concept,which includes a detailed model of the surface roughness ratio, appeared to give results that were in reasonable agreement with local measurements with scintillometer devices. The specification of the atmospheric boundary conditions

  2. A new MRI land surface model HAL

    Science.gov (United States)

    Hosaka, M.

    2011-12-01

    A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

  3. Operational remote sensing of aerosols over land to account for directional effects

    International Nuclear Information System (INIS)

    Ramon, Didier; Santer, Richard

    2001-01-01

    The assumption that the ground is a Lambertian reflector is commonly adopted in operational atmospheric corrections of spaceborne sensors. Through a simple modeling of directional effects in radiative transfer following the second simulation of the satellite signal in the solar spectrum (6S) approach, we propose an operational method to account for the departure from Lambertian behavior of a reflector covered by a scattering medium. This method relies on the computation of coupling terms between the reflecting and the scattering media and is able to deal with a two-layer atmosphere. We focus on the difficult problem of aerosol remote sensing over land. One popular sensing method relies on observations over dense dark vegetation, for which the surface reflectance is low and quite well defined in the blue and in the red. Therefore a study was made for three cases: (1) dark vegetation covered by atmospheric aerosols, (2) atmospheric aerosols covered by molecules, and finally (3) dark vegetation covered by atmospheric aerosols covered by molecules. Comparisons of top-of-the-atmosphere reflectances computed with our modeling and reference computations made with the successive-order-of-scattering code show the robustness of the modeling in the blue and in the red for aerosol optical thicknesses as great as 0.6 and solar zenith angles as large as 60 deg. . The model begins to fail only in the blue for large solar zenith angles. The benefits expected for aerosol remote sensing over land are evaluated with an aerosol retrieval scheme developed for the Medium-Resolution Imaging Spectrometer. The main result is a better constraint on the aerosol model with inclusion of directional effects and a weaker effect on the optical thickness of the retrieval aerosol. The directional scheme is then applied to the aerosol remote-sensing problem in actual Indian Remote Sensing Satellite P3/Modular Optoelectronic Scanner images over land and shows significant improvement compared with a

  4. All-weather Land Surface Temperature Estimation from Satellite Data

    Science.gov (United States)

    Zhou, J.; Zhang, X.

    2017-12-01

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

  5. Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

    Science.gov (United States)

    Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

    2018-06-01

    This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

  6. Urban land use: Remote sensing of ground-basin permeability

    Science.gov (United States)

    Tinney, L. R.; Jensen, J. R.; Estes, J. E.

    1975-01-01

    A remote sensing analysis of the amount and type of permeable and impermeable surfaces overlying an urban recharge basin is discussed. An effective methodology for accurately generating this data as input to a safe yield study is detailed and compared to more conventional alternative approaches. The amount of area inventoried, approximately 10 sq. miles, should provide a reliable base against which automatic pattern recognition algorithms, currently under investigation for this task, can be evaluated. If successful, such approaches can significantly reduce the time and effort involved in obtaining permeability data, an important aspect of urban hydrology dynamics.

  7. Use of remote sensing techniques for inventorying and planning utilization of land resources in South Dakota

    Science.gov (United States)

    Myers, V. I.; Frazee, C. J.; Rusche, A. E.; Moore, D. G.; Nelson, G. D.; Westin, F. C.

    1974-01-01

    The basic procedures for interpreting remote sensing imagery to rapidly develop general soils and land use inventories were developed and utilized in Pennington County, South Dakota. These procedures and remote sensing data products were illustrated and explained to many user groups, some of whom are interested in obtaining similar data. The general soils data were integrated with land soils data supplied by the county director of equalization to prepare a land value map. A computer print-out of this map indicating a land value for each quarter section is being used in tax reappraisal of Pennington County. The land use data provided the land use planners with the present use of land in Pennington County. Additional uses of remote sensing applications are also discussed including tornado damage assessment, hail damage evaluation, and presentation of soil and land value information on base maps assembled from ERTS-1 imagery.

  8. Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

    Science.gov (United States)

    Shen, Suhung; Leptoukh, Gregory G.

    2011-01-01

    Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

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

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Land surface temperature can provide noteworthy information about the surface ... modelling the surface energy balance (Kalma, et al., 2008; ... Landsat, in addition some of the Landsat data have cloud cover and ..... The Impact Of Urban.

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

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2013-09-01

    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, although subgrid topography also has major controls on surface processes. In this study, we developed a new subgrid classification method (SGC that accounts for variability of both topography and vegetation cover. Each model grid cell was represented with a variable number of elevation classes and each elevation class was further described by a variable number of vegetation types optimized for each model grid given a predetermined total number of land response units (LRUs. The subgrid structure of the Community Land Model (CLM was used to illustrate the newly developed method in this study. Although the new method increases the computational burden in the model simulation compared to the CLM subgrid vegetation representation, it greatly reduced the variations of elevation within each subgrid class and is able to explain at least 80% of the total subgrid plant functional types (PFTs. 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 (SGC1: M elevation bands–N PFTs method; SGC2: N PFTs–M elevation bands method. Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0°and 2.0° with three maximum-allowed total number of LRUs (i.e., NLRU of 24, 18 and 12 over North America (NA, the new method yielded more computationally efficient subgrid representation compared to SGC1 and SGC2, particularly at coarser model resolutions and moderate computational intensity (NLRU = 18. It also explained the most PFTs and elevation variability that is more homogeneously distributed spatially. The SGC method will be implemented in CLM over the NA continent to assess its impacts on

  11. 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...

  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. Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

    Science.gov (United States)

    Ding, Hua; Li, Ru Ren; Shuang Sun, Li; Wang, Xin; Liu, Yu Mei

    2018-05-01

    Taking Landsat remote sensing image as the main data source, the research on land use changes in Panjin City in 2005 to 2015 is made with the support of remote sensing platform and GIS platform in this paper; the range of land use changes and change rate are analyzed through the classification of remote sensing image; the dynamic analysis on land changes is made with the help of transfer matrix of land use type; the quantitative calculation on all kinds of dynamic change features of land changes is made by utilizing mathematical model; and the analysis on driving factors of land changes of image is made at last. The research results show that, in recent ten years, the area of cultivated land in Panjin City decreased, the area of vegetation increased, and meanwhile the area of road increased drastically, the settlement place decreased than ever, and water area changed slightly.

  14. Advances in land modeling of KIAPS based on the Noah Land Surface Model

    Science.gov (United States)

    Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

    2017-08-01

    As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

  15. A remote sensing evaluation for agronomic land use mapping in ...

    African Journals Online (AJOL)

    It has become essential to prepare land use maps because these are recognized as necessary tools for the preparation of land capability, land classification and land suitability maps which in turn provide guidelines for the regional planning, development and future orientation of agriculture in the regional system.

  16. 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...

  17. 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

  18. 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.

  19. 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 unders...

  20. Remote Sensing of Smoke, Land and Clouds from the NASA ER-2 during SAFARI 2000

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Moeller, Christopher C.; Revercomb, Henry E.; Chu, D. Allen

    2002-01-01

    The NASA ER-2 aircraft was deployed to southern Africa between August 17 and September 25, 2000 as part of the Southern Africa Regional Science Initiative (SAFARI) 2000. This aircraft carried a sophisticated array of multispectral scanners, multiangle spectroradiometers, a monostatic lidar, a gas correlation radiometer, upward and downward spectral flux radiometers, and two metric mapping cameras. These observations were obtained over a 3200 x 2800 km region of savanna, woody savanna, open shrubland, and grassland ecosystems throughout southern Africa, and were quite often coordinated with overflights by NASA's Terra and Landsat 7 satellites. The primary purpose of this sophisticated high altitude observing platform was to obtain independent observations of smoke, clouds, and land surfaces that could be used to check the validity of various remote sensing measurements derived by Earth-orbiting satellites. These include such things as the accuracy of the Moderate Resolution Imaging Spectro-radiometer (MODIS) cloud mask for distinguishing clouds and heavy aerosol from land and ocean surfaces, and Terra analyses of cloud optical and micro-physical properties, aerosol properties, leaf area index, vegetation index, fire occurrence, carbon monoxide, and surface radiation budget. In addition to coordination with Terra and Landsat 7 satellites, numerous flights were conducted over surface AERONET sites, flux towers in South Africa, Botswana, and Zambia, and in situ aircraft from the University of Washington, South Africa, and the United Kingdom.

  1. 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...

  2. Impact of high resolution land surface initialization in Indian summer ...

    Indian Academy of Sciences (India)

    The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years ... surface initialization using a regional climate model. ...... ization of the snow field in a cloud model; J. Clim. Appl.

  3. 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

  4. 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...

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

    KAUST Repository

    Rosas, Jorge; Houborg, Rasmus; McCabe, Matthew

    2015-01-01

    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

  6. Current Application of Remote Sensing Techniques in Land Use ...

    African Journals Online (AJOL)

    Land use mapping is important for evaluation, management and conservation of natural resources of an area and the knowledge on the existing land use is one of the prime pre-requisites for suggesting better use of land. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and ...

  7. Scaling of surface energy fluxes using remotely sensed data

    Science.gov (United States)

    French, Andrew Nichols

    Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates

  8. Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watersched

    NARCIS (Netherlands)

    Saran, S.; Sterk, G.; Kumar, S.

    2009-01-01

    Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division

  9. Remote sensing and GIS for land use/cover mapping and integrated land management: case from the middle Ganga plain

    Science.gov (United States)

    Singh, R. B.; Kumar, Dilip

    2012-06-01

    In India, land resources have reached a critical stage due to the rapidly growing population. This challenge requires an integrated approach toward harnessing land resources, while taking into account the vulnerable environmental conditions. Remote sensing and Geographical Information System (GIS) based technologies may be applied to an area in order to generate a sustainable development plan that is optimally suited to the terrain and to the productive potential of the local resources. The present study area is a part of the middle Ganga plain, known as Son-Karamnasa interfluve, in India. Alternative land use systems and the integration of livestock enterprises with the agricultural system have been suggested for land resources management. The objective of this paper is to prepare a land resource development plan in order to increase the productivity of land for sustainable development. The present study will contribute necessary input for policy makers to improve the socio-economic and environmental conditions of the region.

  10. Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments

    Directory of Open Access Journals (Sweden)

    Jianguang Wen

    2018-02-01

    Full Text Available Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

  11. 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.

  12. Effect of water table dynamics on land surface hydrologic memory

    Science.gov (United States)

    Lo, Min-Hui; Famiglietti, James S.

    2010-11-01

    The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

  13. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    OpenAIRE

    Gao, Bo; Jia, Li; Wang, Tianxing

    2014-01-01

    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 pr...

  14. Apollo 16 landing site: Summary of earth based remote sensing data, part W

    Science.gov (United States)

    Zisk, S. H.; Masursky, H.; Milton, D. J.; Schaber, G. G.; Shorthill, R. W.; Thompson, T. W.

    1972-01-01

    Infrared and radar studies of the Apollo 16 landing site are summarized. Correlations and comparisons between earth based remote sensing data, IR observations, and other data are discussed in detail. Remote sensing studies were devoted to solving two problems: (1) determining the physical difference between Cayley and Descartes geologic units near the landing site; and (2) determining the nature of the bright unit of Descartes mountain material.

  15. Surface Acoustic Wave Devices for Harsh Environment Wireless Sensing

    Directory of Open Access Journals (Sweden)

    David W. Greve

    2013-05-01

    Full Text Available Langasite surface acoustic wave devices can be used to implement harsh-environment wireless sensing of gas concentration and temperature. This paper reviews prior work on the development of langasite surface acoustic wave devices, followed by a report of recent progress toward the implementation of oxygen gas sensors. Resistive metal oxide films can be used as the oxygen sensing film, although development of an adherent barrier layer will be necessary with the sensing layers studied here to prevent interaction with the langasite substrate. Experimental results are presented for the performance of a langasite surface acoustic wave oxygen sensor with tin oxide sensing layer, and these experimental results are correlated with direct measurements of the sensing layer resistivity.

  16. Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data

    Directory of Open Access Journals (Sweden)

    Yuanxin Jia

    2018-03-01

    Full Text Available Land use is of great importance for urban planning, environmental monitoring, and transportation management. Several methods have been proposed to obtain land use maps of urban areas, and these can be classified into two categories: remote sensing methods and social sensing methods. However, remote sensing and social sensing approaches have specific disadvantages regarding the description of social and physical features, respectively. Therefore, an appropriate fusion strategy is vital for large-area land use mapping. To address this issue, we propose an efficient land use mapping method that combines remote sensing imagery (RSI and mobile phone positioning data (MPPD for large areas. We implemented this method in two steps. First, a support vector machine was adopted to classify the RSI and MPPD. Then, the two classification results were fused using a decision fusion strategy to generate the land use map. The proposed method was applied to a case study of the central area of Beijing. The experimental results show that the proposed method improved classification accuracy compared with that achieved using MPPD alone, validating the efficacy of this new approach for identifying land use. Based on the land use map and MPPD data, activity density in key zones during daytime and nighttime was analyzed to illustrate the volume and variation of people working and living across different regions.

  17. Land surface sensitivity of mesoscale convective systems

    Science.gov (United States)

    Tournay, Robert C.

    Mesoscale convective systems (MCSs) are important contributors to the hydrologic cycle in many regions of the world as well as major sources of severe weather. MCSs continue to challenge forecasters and researchers alike, arising from difficulties in understanding system initiation, propagation, and demise. One distinct type of MCS is that formed from individual convective cells initiated primarily by daytime heating over high terrain. This work is aimed at improving our understanding of the land surface sensitivity of this class of MCS in the contiguous United States. First, a climatology of mesoscale convective systems originating in the Rocky Mountains and adjacent high plains from Wyoming southward to New Mexico is developed through a combination of objective and subjective methods. This class of MCS is most important, in terms of total warm season precipitation, in the 500 to 1300m elevations of the Great Plains (GP) to the east in eastern Colorado to central Nebraska and northwest Kansas. Examining MCSs by longevity, short lasting MCSs (15 hrs) reveals that longer lasting systems tend to form further south and have a longer track with a more southerly track. The environment into which the MCS is moving showed differences across commonly used variables in convection forecasting, with some variables showing more favorable conditions throughout (convective inhibition, 0-6 km shear and 250 hPa wind speed) ahead of longer lasting MCSs. Other variables, such as convective available potential energy, showed improving conditions through time for longer lasting MCSs. Some variables showed no difference across longevity of MCS (precipitable water and large-scale vertical motion). From subsets of this MCS climatology, three regions of origin were chosen based on the presence of ridgelines extending eastward from the Rocky Mountains known to be foci for convection initiation and subsequent MCS formation: Southern Wyoming (Cheyenne Ridge), Colorado (Palmer divide) and

  18. Performing and updating an inventory of Oregon's expanding irrigated agricultural lands utilizing remote sensing technology

    Science.gov (United States)

    Hall, M. J.

    1981-01-01

    An inventory technique based upon using remote sensing technology, interpreting both high altitude aerial photography and LANDSAT multispectral scanner imagery, is discussed. It is noted that once the final land use inventory maps of irrigated agricultural lands are available and approximately scaled they may be overlaid directly onto either multispectral scanner or return beam vidicon prints, thereby providing an inexpensive updating procedure.

  19. A Study on Land Suitability for Rice Cultivation in Khordha District of Odisha (India) Using Remote Sensing and GIS

    Science.gov (United States)

    Rath, Sudhansu S.; Panda, Jagabandhu; Annadurai, R.; Nanda, Sachikanta

    2018-05-01

    With the global population on the rise, it is important to address the increasing demand for food. According to FAO (Food and Agriculture Organization, United Nations), by 2050, the developing countries must double their food production to meet the growing demand. Proper land utilization can be one of the solutions for this problem. In view of this, the current study focussed on land suitability analysis for Khordha district of Odisha (India) for rice crop. This study estimated that the amount of land suitable for rice cropping was 195,731 ha against the currently cultivated land of 122,183.38 ha. Therefore, there was a possibility of more amount of land that could be available for rice cultivation in Khordha district than the currently cultivated area. In order to perform this exercise, the land use and land cover data from IRS (Indian remote sensing satellite), soil nutrient parameters like pH values and nitrogen, potassium, phosphorous and organic carbon contents were considered. In addition, the climatic parameters such as near surface temperature, rainfall and number of rainy days were taken into account. The unused land identified in Khordha district in this study might be utilized for cultivating rice crop in this region.

  20. A Study on Land Suitability for Rice Cultivation in Khordha District of Odisha (India) Using Remote Sensing and GIS

    Science.gov (United States)

    Rath, Sudhansu S.; Panda, Jagabandhu; Annadurai, R.; Nanda, Sachikanta

    2018-02-01

    With the global population on the rise, it is important to address the increasing demand for food. According to FAO (Food and Agriculture Organization, United Nations), by 2050, the developing countries must double their food production to meet the growing demand. Proper land utilization can be one of the solutions for this problem. In view of this, the current study focussed on land suitability analysis for Khordha district of Odisha (India) for rice crop. This study estimated that the amount of land suitable for rice cropping was 195,731 ha against the currently cultivated land of 122,183.38 ha. Therefore, there was a possibility of more amount of land that could be available for rice cultivation in Khordha district than the currently cultivated area. In order to perform this exercise, the land use and land cover data from IRS (Indian remote sensing satellite), soil nutrient parameters like pH values and nitrogen, potassium, phosphorous and organic carbon contents were considered. In addition, the climatic parameters such as near surface temperature, rainfall and number of rainy days were taken into account. The unused land identified in Khordha district in this study might be utilized for cultivating rice crop in this region.

  1. Exploring Land Use and Land Cover of Geotagged Social-Sensing Images Using Naive Bayes Classifier

    Directory of Open Access Journals (Sweden)

    Asamaporn Sitthi

    2016-09-01

    Full Text Available Online social media crowdsourced photos contain a vast amount of visual information about the physical properties and characteristics of the earth’s surface. Flickr is an important online social media platform for users seeking this information. Each day, users generate crowdsourced geotagged digital imagery containing an immense amount of information. In this paper, geotagged Flickr images are used for automatic extraction of low-level land use/land cover (LULC features. The proposed method uses a naive Bayes classifier with color, shape, and color index descriptors. The classified images are mapped using a majority filtering approach. The classifier performance in overall accuracy, kappa coefficient, precision, recall, and f-measure was 87.94%, 82.89%, 88.20%, 87.90%, and 88%, respectively. Labeled-crowdsourced images were filtered into a spatial tile of a 30 m × 30 m resolution using the majority voting method to reduce geolocation uncertainty from the crowdsourced data. These tile datasets were used as training and validation samples to classify Landsat TM5 images. The supervised maximum likelihood method was used for the LULC classification. The results show that the geotagged Flickr images can classify LULC types with reasonable accuracy and that the proposed approach improves LULC classification efficiency if a sufficient spatial distribution of crowdsourced data exists.

  2. STUDY ON REMOTE SENSING IMAGE CHARACTERISTICS OF ECOLOGICAL LAND: CASE STUDY OF ORIGINAL ECOLOGICAL LAND IN THE YELLOW RIVER DELTA

    Directory of Open Access Journals (Sweden)

    G. Q. An

    2018-04-01

    Full Text Available Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

  3. Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

    Science.gov (United States)

    An, G. Q.

    2018-04-01

    Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

  4. Nanostructured surfaces for microfluidics and sensing applications.

    Energy Technology Data Exchange (ETDEWEB)

    Picraux, Samuel Thomas (Arizona State University); Piech, Marcin (United Technologies Corp.); Schneider, John F.; Vail, Sean (Arizona State University); Hayes, Mark A. (Arizona State University); Garcia, Anthony A.; Bell, Nelson Simmons; Gust, D (Arizona State University); Yang, Dongqing (Arizona State University)

    2007-01-01

    The present work demonstrates the use of light to move liquids on a photoresponsive monolayer, providing a new method for delivering analyses in lab-on-chip environments for microfluidic systems. The light-driven motion of liquids was achieved on photoresponsive azobenzene modified surfaces. The surface energy components of azobenzene modified surfaces were calculated by Van Oss theory. The motion of the liquid was achieved by generation of a surface tension gradient by isomerization of azobenzene monolayers using UV and Visible light, thereby establishing a surface energy heterogeneity on the edge of the droplet. Contact angle measurements of various solvents were used to demonstrate the requirement for fluid motion.

  5. Research and Application of Remote Sensing Monitoring Method for Desertification Land Under Time and Space Constraints

    Science.gov (United States)

    Zhang, Nannnan; Wang, Rongbao; Zhang, Feng

    2018-04-01

    Serious land desertification and sandified threaten the urban ecological security and the sustainable economic and social development. In recent years, a large number of mobile sand dunes in Horqin sandy land flow into the northwest of Liaoning Province under the monsoon, make local agriculture suffer serious harm. According to the characteristics of desertification land in northwestern Liaoning, based on the First National Geographical Survey data, the Second National Land Survey data and the 1984-2014 Landsat satellite long time sequence data and other multi-source data, we constructed a remote sensing monitoring index system of desertification land in Northwest Liaoning. Through the analysis of space-time-spectral characteristics of desertification land, a method for multi-spectral remote sensing image recognition of desertification land under time-space constraints is proposed. This method was used to identify and extract the distribution and classification of desertification land of Chaoyang City (a typical citie of desertification in northwestern Liaoning) in 2008 and 2014, and monitored the changes and transfers of desertification land from 2008 to 2014. Sandification information was added to the analysis of traditional landscape changes, improved the analysis model of desertification land landscape index, and the characteristics and laws of landscape dynamics and landscape pattern change of desertification land from 2008 to 2014 were analyzed and revealed.

  6. [Using a modified remote sensing imagery for interpreting changes in cultivated saline-alkali land].

    Science.gov (United States)

    Gao, Hui; Liu, Hui-tao; Liu, Hong-juan; Liu, Jin-tong

    2015-04-01

    This paper developed a new interpretation symbol system for grading and classifying saline-alkali land, using Huanghua, a cosatal city in Hebei Province as a case. The system was developed by inverting remote sensing images from 1992 to 2011 based on site investigation, plant cover characteristics and features of remote sensing images. Combining this interpretation symbol system with supervising classification method, the information on arable land was obtained for the coastal saline-alkali ecosystem of Huanghua City, and the saline-alkali land area, changes in intensity of salinity-alkalinity and spatial distribution from 1992 to 2011 were analyzed. The results showed that salinization of arable land in Huanghua City alleviated from 1992 to 2011. The severely and moderately saline-alkali land area decreased in 2011 compared with 1992, while the non/slightly saline land area increased. The moderately saline-alkali land in southeast transformed to non/slightly saline-alkaline, while the severely saline-alkali land in west of the city far from the coastal zone became moderately saline-alkaline. The center of gravity (CG) of severely and non/slightly saline-alkali land moved closer the coastline, while that of the moderately saline-alkali land moved from southwest coastal line to northwest. Factors influencing changes in arable land within the saline-alkali ecosystem of Huanghua City were climate, hydrology and human activities.

  7. Determination of Optimum Viewing Angles for the Angular Normalization of Land Surface Temperature over Vegetated Surface

    Directory of Open Access Journals (Sweden)

    Huazhong Ren

    2015-03-01

    Full Text Available Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF is first extended to the thermal infrared (TIR domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (Te-nadir from different viewing directions, and the results show that this model can obtain reliable Te-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The Te-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors.

  8. Integrated ancillary and remote sensing data for land use ...

    African Journals Online (AJOL)

    Full Name

    The application of GMM to remote sensing image classification ... A . The boundary that has a Mahalanobis distance to the centre ... yields the Baye's theorem: ..... bands were extracted using the layer properties tool and visualised in MATLAB ...

  9. Control of cavity acoustics by surface waviness in landing configurations

    CSIR Research Space (South Africa)

    Dala, L

    2014-08-01

    Full Text Available ): 2321-3051 INTERNATIONAL JOURNAL OF RESEARCH IN AERONAUTICAL AND MECHANICAL ENGINEERING Control of Cavity Acoustics by Surface Waviness In Landing Configurations Laurent Dala CSIR, DPSS/Aeronautics Systems, Pretoria 0001, South Africa...

  10. Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

    Science.gov (United States)

    Reichle, Rolf H.; Koster, Randal D.; deLannoy, Gabrielle J. M.; Forman, Barton A.; Liu, Qing; Mahanama, Sarith P. P.; Toure, Ally

    2012-01-01

    The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

  11. Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

    International Nuclear Information System (INIS)

    Cosentino, B.L.; Lillesand, T.M.

    1991-01-01

    Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

  12. Using remote sensing imagery and GIS to identify land cover and land use within Ceahlau Massif (Romania

    Directory of Open Access Journals (Sweden)

    GEORGE CRACU

    2014-11-01

    Full Text Available Using remote sensing imagery and GIS to identify land cover and land use within Ceahlău Massif (Romania. In this study we considerer land cover and land use asessment within Ceahlău Massif (Romania using satellite imagery and GIS . To achieve this goal, we used a Landsat 7 ETM + satellite image, which was processed using specialized software in analyzing satellite images and GIS software in several stages:  Downloading, importing and layer stack of all spectral bands composing satellite image;  Establishment of areas of interest for each category of land cover and land use, which were digitized on - screen and for which spectral signatures characteristics were established;  Supervised image classification using Maximum Likelihood Method;  Importing the resulting m ap (raster in GIS environment and creating the final land cover/land use map for Ceahlău Massif. In the study area we identified nine land cover/land use classes: deciduous forests, mixed forests, coniferous forests, secondary grasslands, subalpine vegeta tion, alpine meadows, agricultural land, lakes and built area. By analizing the spatial distribution of these classes, it was found that forests are the best represented class, occupying an area of 188.4 km² (56.4% of total, followed by secondary grassl and, which occupies an area of 68.2 km² (20.4% of total, lakes (26.6 km² or 7.98% of total and agricultural land (16.1 km² or 4.86%

  13. Turbulent flow over an interactive alternating land-water surface

    Science.gov (United States)

    Van Heerwaarden, C.; Mellado, J. P.

    2014-12-01

    The alternating land-water surface is a challenging surface to represent accurately in weather and climate models, but it is of great importance for the surface energy balance in polar regions. The complexity of this surface lies in the fact that secondary circulations, which form at the boundary of water and land, interact strongly with the surface energy balance. Due to its large heat capacity, the water temperature adapts slowly to the flow, thus the properties of the atmosphere determine the uptake of energy from the water. In order to study this complex system in a simpler way, retaining only the most essential physics, we have simplified the full surface energy balance including radiation. We have derived a boundary condition that mimics the full balance and can be formulated as a so-called Robin boundary condition: a linear combination of Dirichlet (fixed temperature) and Neumann (fixed temperature gradient) ones. By spatially varying the coefficients, we are able to express land and water using this boundary condition. We have done a series of direct numerical simulations in which we generate artificial land-water patterns from noise created from a Gaussian spectrum centered around a dominant wave number. This method creates realistic random patterns, but we are still in control of the length scales. We show that the system can manifest itself in three regimes: micro-, meso- and macro-scale. In the micro-scale, we find perfect mixing of the near-surface atmosphere that results in identical air properties over water and land. In the meso-scale, secondary circulations alter the heat exchange considerably by advecting air between land and water. In addition, they bring the surface temperature of the land closer to that of the air, thereby modulating the energy loss due to outgoing longwave radiation. In the macro-scale regime, the flow over land and water become independent of each other and only the large scale forcings determine the energy balance.

  14. Interactive Computing and Processing of NASA Land Surface Observations Using Google Earth Engine

    Science.gov (United States)

    Molthan, Andrew; Burks, Jason; Bell, Jordan

    2016-01-01

    Google's Earth Engine offers a "big data" approach to processing large volumes of NASA and other remote sensing products. h\\ps://earthengine.google.com/ Interfaces include a Javascript or Python-based API, useful for accessing and processing over large periods of record for Landsat and MODIS observations. Other data sets are frequently added, including weather and climate model data sets, etc. Demonstrations here focus on exploratory efforts to perform land surface change detection related to severe weather, and other disaster events.

  15. Identification of soil erosion land surfaces by Landsat data analysis and processing

    International Nuclear Information System (INIS)

    Lo Curzio, S.

    2009-01-01

    In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

  16. THE USE OF SATELLITE REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEMS ON CRITICAL LAND ANALYSIS

    Directory of Open Access Journals (Sweden)

    Agus Suharyanto

    2013-06-01

    Full Text Available Critical land classification can be analyzed using combination between Top Soil Thickness - Land erosion method, and BRLT methods. Both methods are needed soil erosion data as one of input data. The soil erosion data can be analyzed using USLE and MUSLE methods. The combination of two critical land analyses methods with input soil erosion data from two analyses methods will be produced four combinations of critical land classification. In this research, four of the critical land classification and two soil erosion classification will be analyzed using GIS. The best method to classify critical land will be investigated in this research. The best classified critical land is the classified critical land data is nearest with the field condition. Percentage of vegetation cover (PVC is one of the most important input data in the critical land classification analysis using BRLKT method. This data have 50% weight. PVC condition is classified into five categories i.e. very good, good, fair, poor, and very poor. Each category have score 5, 4, 3, 2, 1 respectively. To analyze this PVC classification, NDVI generated from satellite remote sensing data is used in this research. From the four methods of land critical classification analyses used in this research, critical land classified using BRLKT method with input soil erosion analyzed using method is produced the critical land classification nearest with the critical land condition in the field.

  17. Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

    Science.gov (United States)

    Kumar, Lalit; Ghosh, Manoj Kumer

    2012-01-01

    Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

  18. 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.

  19. Remote sensing of wet lands in irrigated areas

    Science.gov (United States)

    Ham, H. H.

    1972-01-01

    The use of airborne remote sensing techniques to: (1) detect drainage problem areas, (2) delineate the problem in terms of areal extent, depth to the water table, and presence of excessive salinity, and (3) evaluate the effectiveness of existing subsurface drainage facilities, is discussed. Experimental results show that remote sensing, as demonstrated in this study and as presently constituted and priced, does not represent a practical alternative as a management tool to presently used visual and conventional photographic methods in the systematic and repetitive detection and delineation of wetlands.

  20. From land to water: bringing dielectric elastomer sensing to the underwater realm

    Science.gov (United States)

    Walker, Christopher; Anderson, Iain

    2016-04-01

    Since the late 1990's dielectric elastomers (DEs) have been investigated for their use as sensors. To date, there have been some impressive developments: finger displacement controls for video games and integration with medical rehabilitation devices to aid patient recovery. It is clear DE sensing is well established for dry applications, the next frontier, however, is to adapt this technology for the other 71% of the Earth's surface. With proven and perhaps improved water resistance, many new applications could be developed in areas such as diver communication and control of underwater robotics; even wearable devices on land must withstand sweat, washing, and the rain. This study investigated the influence of fresh and salt water on DE sensing. In particular, sensors have been manufactured with waterproof connections and submersed in fresh and salt water baths. Temperature and resting capacitance were recorded. Issues with the basic DE sensor have been identified and compensated for with modifications to the sensor. The electrostatic field, prior and post modification, has been modeled with ANSYS Maxwell. The aim of this investigation was to identify issues, perform modifications and propose a new sensor design suited to wet and underwater applications.

  1. Quantitative estimation of land surface evapotranspiration in Taiwan based on MODIS data

    Directory of Open Access Journals (Sweden)

    Che-sheng Zhan

    2011-09-01

    Full Text Available Land surface evapotranspiration (ET determines the local and regional water-heat balances. Accurate estimation of regional surface ET provides a scientific basis for the formulation and implementation of water conservation programs. This study set up a table of the momentum roughness length and zero-plane displacement related with land cover and an empirical relationship between land surface temperature and air temperature. A revised quantitative remote sensing ET model, the SEBS-Taiwan model, was developed. Based on Moderate Resolution Imaging Spectroradiometer (MODIS data, SEBS-Taiwan was used to simulate and evaluate the typical actual daily ET values in different seasons of 2002 and 2003 in Taiwan. SEBS-Taiwan generally performed well and could accurately simulate the actual daily ET. The simulated daily ET values matched the observed values satisfactorily. The results indicate that the net regional solar radiation, evaporation ratio, and surface ET values for the whole area of Taiwan are larger in summer than in spring, and larger in autumn than in winter. The results also show that the regional average daily ET values of 2002 are a little higher than those of 2003. Through analysis of the ET values from different types of land cover, we found that forest has the largest ET value, while water areas, bare land, and urban areas have the lowest ET values. Generally, the Northern Taiwan area, including Ilan County, Nantou County, and Hualien County, has higher ET values, while other cities, such as Chiayi, Taichung, and Tainan, have lower ET values.

  2. Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey.

    Science.gov (United States)

    Reis, Selçuk

    2008-10-01

    Mapping land use/land cover (LULC) changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities), negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS) in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel). In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude) by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2%) (especially in tea gardens), urban (117%), pasture (-72.8%) and forestry (-12.8%) areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.

  3. Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey

    Directory of Open Access Journals (Sweden)

    Selçuk Reis

    2008-10-01

    Full Text Available Mapping land use/land cover (LULC changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities, negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel. In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2% (especially in tea gardens, urban (117%, pasture (-72.8% and forestry (-12.8% areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.

  4. Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

    Science.gov (United States)

    Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

    2017-09-01

    With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  5. 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.

  6. Wireless sensing on surface hydrocarbon production systems

    International Nuclear Information System (INIS)

    Kane, D; McStay, D; Mulholland, J; Costello, L

    2009-01-01

    The use of wireless sensor networks for monitoring and optimising the performance of surface hydrocarbon production systems is reported. Wireless sensor networks are shown to be able to produce comprehensively instrumented XTs and other equipment that generate the data required by Intelligent Oilfield systems. The information produced by such systems information can be used for real-time operational control, production optimization and troubleshooting.

  7. Surface Characterization for Land-Atmosphere Studies of CLASIC

    Science.gov (United States)

    Jackson, T. J.; Kustas, W.; Torn, M. S.; Meyers, T.; Prueger, J.; Fischer, M. L.; Avissar, R.; Yueh, S.; Anderson, M.; Miller, M.

    2006-12-01

    The Cloud and Land Surface Interaction Campaign will focus on interactions between the land surface, convective boundary layer, and cumulus clouds. It will take place in the Southern Great Plains (SGP) area of the U.S, specifically within the US DOE ARM Climate Research Facility. The intensive observing period will be June of 2007, which typically covers the winter wheat harvest in the region. This region has been the focus of several related experiments that include SGP97, SGP99, and SMEX03. For the land surface, some of the specific science questions include 1) how do spatial variations in land cover along this trajectory modulate the cloud structure and the low-level water vapor budget, 2) what are the relationships between land surface characteristics (i.e., soil texture, vegetation type and fractional cover) and states (particularly soil moisture and surface temperature) and the resulting impact of the surface energy balance on boundary layer and cloud structure and dynamics and aerosol loading; and 3) what is the interplay between cumulus cloud development and surface energy balance partitioning between latent and sensible heat, and implications for the carbon flux? Most of these objectives will require flux and state measurements throughout the dominant land covers and distributed over the geographic domain. These observations would allow determining the level of up- scaling/aggregation required in order to understand the impact of landscape changes affecting energy balance/flux partitioning and impact on cloud/atmospheric dynamics. Specific contributions that are planned to be added to CLASIC include continuous tower-based monitoring of surface fluxes for key land cover types prior to, during, and post-IOP, replicate towers to quantify flux variance within each land cover, boundary layer properties and fluxes from a helicopter-based system, airplane- and satellite-based flux products throughout the region, aircraft- and tower-based concentration data for

  8. Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

    Science.gov (United States)

    Yueh, Simon H.

    2004-01-01

    Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

  9. GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

    Directory of Open Access Journals (Sweden)

    K. Fukue

    2016-06-01

    Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

  10. Molecularly engineered graphene surfaces for sensing applications: A review

    International Nuclear Information System (INIS)

    Liu, Jingquan; Liu, Zhen; Barrow, Colin J.; Yang, Wenrong

    2015-01-01

    Highlights: • The importance of surface chemistry of graphene materials is clearly described. • We discuss molecularly engineered graphene surfaces for sensing applications. • We describe the latest developments of these materials for sensing technology. - Abstract: Graphene is scientifically and commercially important because of its unique molecular structure which is monoatomic in thickness, rigorously two-dimensional and highly conjugated. Consequently, graphene exhibits exceptional electrical, optical, thermal and mechanical properties. Herein, we critically discuss the surface modification of graphene, the specific advantages that graphene-based materials can provide over other materials in sensor research and their related chemical and electrochemical properties. Furthermore, we describe the latest developments in the use of these materials for sensing technology, including chemical sensors and biosensors and their applications in security, environmental safety and diseases detection and diagnosis

  11. Molecularly engineered graphene surfaces for sensing applications: A review

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jingquan, E-mail: jliu@qdu.edu.cn [College of Chemical Science and Engineering, Laboratory of Fiber Materials and Modern Textile, The Growing Base for State Key Laboratory, Qingdao University, Qingdao (China); Liu, Zhen; Barrow, Colin J. [Centre for Chemistry and Biotechnology, Deakin University, Geelong, VIC 3217 (Australia); Yang, Wenrong, E-mail: wenrong.yang@deakin.edu.au [Centre for Chemistry and Biotechnology, Deakin University, Geelong, VIC 3217 (Australia)

    2015-02-15

    Highlights: • The importance of surface chemistry of graphene materials is clearly described. • We discuss molecularly engineered graphene surfaces for sensing applications. • We describe the latest developments of these materials for sensing technology. - Abstract: Graphene is scientifically and commercially important because of its unique molecular structure which is monoatomic in thickness, rigorously two-dimensional and highly conjugated. Consequently, graphene exhibits exceptional electrical, optical, thermal and mechanical properties. Herein, we critically discuss the surface modification of graphene, the specific advantages that graphene-based materials can provide over other materials in sensor research and their related chemical and electrochemical properties. Furthermore, we describe the latest developments in the use of these materials for sensing technology, including chemical sensors and biosensors and their applications in security, environmental safety and diseases detection and diagnosis.

  12. Considerations and techniques for incorporating remotely sensed imagery into the land resource management process.

    Science.gov (United States)

    Brooner, W. G.; Nichols, D. A.

    1972-01-01

    Development of a scheme for utilizing remote sensing technology in an operational program for regional land use planning and land resource management program applications. The scheme utilizes remote sensing imagery as one of several potential inputs to derive desired and necessary data, and considers several alternative approaches to the expansion and/or reduction and analysis of data, using automated data handling techniques. Within this scheme is a five-stage program development which includes: (1) preliminary coordination, (2) interpretation and encoding, (3) creation of data base files, (4) data analysis and generation of desired products, and (5) applications.

  13. Atmospheric teleconnection influence on North American land surface phenology

    Science.gov (United States)

    Dannenberg, Matthew P.; Wise, Erika K.; Janko, Mark; Hwang, Taehee; Kolby Smith, W.

    2018-03-01

    Short-term forecasts of vegetation activity are currently not well constrained due largely to our lack of understanding of coupled climate-vegetation dynamics mediated by complex interactions between atmospheric teleconnection patterns. Using ecoregion-scale estimates of North American vegetation activity inferred from remote sensing (1982-2015), we examined seasonal and spatial relationships between land surface phenology and the atmospheric components of five teleconnection patterns over the tropical Pacific, north Pacific, and north Atlantic. Using a set of regression experiments, we also tested for interactions among these teleconnection patterns and assessed predictability of vegetation activity solely based on knowledge of atmospheric teleconnection indices. Autumn-to-winter composites of the Southern Oscillation Index (SOI) were strongly correlated with start of growing season timing, especially in the Pacific Northwest. The two leading modes of north Pacific variability (the Pacific-North American, PNA, and West Pacific patterns) were significantly correlated with start of growing season timing across much of southern Canada and the upper Great Lakes. Regression models based on these Pacific teleconnections were skillful predictors of spring phenology across an east-west swath of temperate and boreal North America, between 40°N-60°N. While the North Atlantic Oscillation (NAO) was not strongly correlated with start of growing season timing on its own, we found compelling evidence of widespread NAO-SOI and NAO-PNA interaction effects. These results suggest that knowledge of atmospheric conditions over the Pacific and Atlantic Oceans increases the predictability of North American spring phenology. A more robust consideration of the complexity of the atmospheric circulation system, including interactions across multiple ocean basins, is an important step towards accurate forecasts of vegetation activity.

  14. Effect of climatic change on surface environments in the typical region of Horqin Sandy Land

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The town of Agura,a typical region in Horqin Sandy Land,was selected as the study area in this paper.Using 12 remote sensing images and climatic data from the past 20 years,the effects of climate change on surface environments were analyzed.The impact indices of climatic factors,along with their corresponding ranks,were used to characterize the responses of different types of surface environments to climate change.Results show that in the past 20 years,the surface environments of the study area have been deteriorating.Furthermore,there is a positive relationship between the changes in surface environments and those in climatic factors.Various climatic factors influence surface environments in different ways and at different levels.The most sensitive factor is relative humidity,followed by precipitation and evaporation.Overall,moisture is the key factor that affects the changes in surface environments of arid and semi-arid areas.

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

    Directory of Open Access Journals (Sweden)

    Dong Jiang

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

  16. Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies

    Data.gov (United States)

    National Aeronautics and Space Administration — The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces...

  17. 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.

  18. Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

    Science.gov (United States)

    Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

    2017-12-01

    Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

  19. IRSeL-An approach to enhance continuity and accuracy of remotely sensed land cover data

    Science.gov (United States)

    Rathjens, H.; Dörnhöfer, K.; Oppelt, N.

    2014-09-01

    Land cover data gives the opportunity to study interactions between land cover status and environmental issues such as hydrologic processes, soil properties, or biodiversity. Land cover data often are based on classification of remote sensing data that seldom provides the requisite accuracy, spatial availability and temporal observational frequency for environmental studies. Thus, there is a high demand for accurate and spatio-temporal complete time series of land cover. In the past considerable research was undertaken to increase land cover classification accuracy, while less effort was spent on interpolation techniques. The purpose of this article is to present a space-time interpolation and revision approach for remotely sensed land cover data. The approach leverages special properties known for agricultural areas such as crop rotations or temporally static land cover classes. The newly developed IRSeL-tool (Interpolation and improvement of Remotely Sensed Land cover) corrects classification errors and interpolates missing land cover pixels. The easy-to-use tool solely requires an initial land cover data set. The IRSeL specific interpolation and revision technique, the data input requirements and data output structure are described in detail. A case study in an area around the city of Neumünster in Northern Germany from 2006 to 2012 was performed for IRSeL validation with initial land cover data sets (Landsat TM image classifications) for the years 2006, 2007, 2009, 2010 and 2011. The results of the case study showed that IRSeL performs well; including years with no classification data overall accuracy values for IRSeL interpolated pixels range from 0.63 to 0.81. IRSeL application significantly increases the accuracy of the land cover data; overall accuracy values rise 0.08 in average resulting in overall accuracy values of at least 0.86. Considering estimated reliabilities, the IRSeL tool provides a temporally and spatially completed and revised land cover

  20. Surface plasmon resonance optical cavity enhanced refractive index sensing

    Czech Academy of Sciences Publication Activity Database

    Giorgini, A.; Avino, S.; Malara, P.; Gagliardi, G.; Casalino, M.; Coppola, G.; Iodice, M.; Adam, Pavel; Chadt, Karel; Homola, Jiří; De Natale, P.

    2013-01-01

    Roč. 38, č. 11 (2013), s. 1951-1953 ISSN 0146-9592 R&D Projects: GA ČR GBP205/12/G118 Institutional support: RVO:67985882 Keywords : Resonators * Surface plasmons * Optical sensing and sensors Subject RIV: BH - Optics, Masers, Lasers Impact factor: 3.179, year: 2013

  1. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  2. Land Cover Change and Remote Sensing in the Classroom: An Exercise to Study Urban Growth

    Science.gov (United States)

    Delahunty, Tina; Lewis-Gonzales, Sarah; Phelps, Jack; Sawicki, Ben; Roberts, Charles; Carpenter, Penny

    2012-01-01

    The processes and implications of urban growth are studied in a variety of disciplines as urban growth affects both the physical and human landscape. Remote sensing methods provide ways to visualize and mathematically represent urban growth; and resultant land cover change data enable both quantitative and qualitative analysis. This article helps…

  3. Use of remote sensing for land use policy formulation. [in Michigan

    Science.gov (United States)

    Boylan, M.

    1977-01-01

    The use of remotely sensed data for eliminating abuses and mismanagement of land and water resources in Michigan is discussed. Applications discussed include inventory of mosquito breeding sites; analysis of biomass in old field ecosystems used for wastewater recycling; areas for agricultural use; and preservation of the Grand Mere Dune environment. Services to users are described and contact activities reported.

  4. An algorithm to retrieve Land Surface Temperature using Landsat-8 ...

    African Journals Online (AJOL)

    Ayodeji Ogunode;Mulemwa Akombelwa

    The results show temperature variation over a long period of time can be ... Remote sensing of LST using infrared radiation gives the average surface temperature of the scene ... advantage over previous Landsat series. ..... Li, F., Jackson, T. J., Kustas, W. P., Schmugge, T. J., French, A. N., Cosh, M. H. & Bindlish, R. 2004.

  5. Remote sensing in Michigan for land resource management: Highway impact assessment

    Science.gov (United States)

    1972-01-01

    An existing section of M-14 freeway constructed in 1964 and a potential extension from Ann Arbor to Plymouth, Michigan provided an opportunity for investigating the potential uses of remote sensing techniques in providing projective information needed for assessing the impact of highway construction. Remote sensing data included multispectral scanner imagery and aerial photography. Only minor effects on vegetation, soils, and land use were found to have occurred in the existing corridor. Adverse changes expected to take place in the corridor proposed for extension of the freeway can be minimized by proper design of drainage ditches and attention to good construction practices. Remote sensing can be used to collect and present many types of data useful for highway impact assessment on land use, vegetation categories and species, soil properties and hydrologic characteristics.

  6. Afforestation in China cools local land surface temperature

    OpenAIRE

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

    2014-01-01

    International audience; 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 adjace...

  7. 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.

  8. Simulation and Analysis of Topographic Effect on Land Surface Albedo over Mountainous Areas

    Science.gov (United States)

    Hao, D.; Wen, J.; Xiao, Q.

    2017-12-01

    Land surface albedo is one of the significant geophysical variables affecting the Earth's climate and controlling the surface radiation budget. Topography leads to the formation of shadows and the redistribution of incident radiation, which complicates the modeling and estimation of the land surface albedo. Some studies show that neglecting the topography effect may lead to significant bias in estimating the land surface albedo for the sloping terrain. However, for the composite sloping terrain, the topographic effects on the albedo remain unclear. Accurately estimating the sub-topographic effect on the land surface albedo over the composite sloping terrain presents a challenge for remote sensing modeling and applications. In our study, we focus on the development of a simplified estimation method for land surface albedo including black-sky albedo (BSA) and white-sky albedo (WSA) of the composite sloping terrain at a kilometer scale based on the fine scale DEM (30m) and quantitatively investigate and understand the topographic effects on the albedo. The albedo is affected by various factors such as solar zenith angle (SZA), solar azimuth angle (SAA), shadows, terrain occlusion, and slope and aspect distribution of the micro-slopes. When SZA is 30°, the absolute and relative deviations between the BSA of flat terrain and that of rugged terrain reaches 0.12 and 50%, respectively. When the mean slope of the terrain is 30.63° and SZA=30°, the absolute deviation of BSA caused by SAA can reach 0.04. The maximal relative and relative deviation between the WSA of flat terrain and that of rugged terrain reaches 0.08 and 50%. These results demonstrate that the topographic effect has to be taken into account in the albedo estimation.

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

    African Journals Online (AJOL)

    Dr-Adeline

    Keywords: Urban growth, urban heat Island, land surface temperatures, ... climate from the resulting increase in LST can impact on the development of ... were not available (due to high cloud cover) in a given season, 2011 images ..... Sailor, D.J. and H. Fan, 2002: Modeling the diurnal variability of effective albedo for cities.

  10. 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

  11. Regional seasonal warming anomalies and land-surface feedbacks

    Science.gov (United States)

    Coffel, E.; Horton, R. M.

    2017-12-01

    Significant seasonal variations in warming are projected in some regions, especially central Europe, the southeastern U.S., and central South America. Europe in particular may experience up to 2°C more warming during June, July, and August than in the annual mean, enhancing the risk of extreme summertime heat. Previous research has shown that heat waves in Europe and other regions are tied to seasonal soil moisture variations, and that in general land-surface feedbacks have a strong effect on seasonal temperature anomalies. In this study, we show that the seasonal anomalies in warming are also due in part to land-surface feedbacks. We find that in regions with amplified warming during the hot season, surface soil moisture levels generally decline and Bowen ratios increase as a result of a preferential partitioning of incoming energy into sensible vs. latent. The CMIP5 model suite shows significant variability in the strength of land-atmosphere coupling and in projections of future precipitation and soil moisture. Due to the dependence of seasonal warming on land-surface processes, these inter-model variations influence the projected summertime warming amplification and contribute to the uncertainty in projections of future extreme heat.

  12. 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...

  13. 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...

  14. The characteristics and interpretability of land surface change and implications for project design

    Science.gov (United States)

    Sohl, Terry L.; Gallant, Alisa L.; Loveland, Thomas R.

    2004-01-01

    The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

  15. 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.

  16. Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

    Science.gov (United States)

    Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

    2018-06-01

    Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

  17. Remotely Sensed Land Imagery and Access Systems: USGS Updates

    Science.gov (United States)

    Lamb, R.; Pieschke, R.; Lemig, K.

    2017-12-01

    The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has implemented a number of updates to its suite of remotely sensed products and distribution systems. These changes will greatly expand the availability, accessibility, and usability of the image products from USGS. As of late 2017, several new datasets are available for public download at no charge from USGS/EROS Center. These products include Multispectral Instrument (MSI) Level-1C data from the Sentinel-2B satellite, which was launched in March 2017. Along with Sentinel-2A, the Sentinel-2B images are now being distributed through USGS systems as part of a collaborative effort with the European Space Agency (ESA). The Sentinel-2 imagery is highly complementary to multispectral data collected by the USGS Landsat 7 and 8 satellites. With these two missions operating together, the potential local revisit rate can be reduced to 2-4 days. Another product addition is Resourcesat-2 data acquired over the United States by the Indian Space Research Organisation (ISRO). The Resourcesat-2 products from USGS consist of Advanced Wide Field Sensor (AWiFS) and Linear Imaging Self-Scanning Sensor Three (LISS-3) images acquired August 2016 to present. In an effort to maximize future Landsat data interoperability, including time series analysis of the 45+ year archive, the reprocessing of Collection 1 for all historical Landsat Level 1 products is nearly complete. The USGS is now working on operational release of higher-level science products to support analysis of the Landsat archive at the pixel level. Major upgrades were also completed in 2017 for several USGS data discovery and access systems, including the LandsatLook Viewer (https://landsatlook.usgs.gov/) and GloVis Tool (https://glovis.usgs.gov/). Other options are now being developed to further enhance data access and overall user experience. These future options will be discussed and community feedback will be encouraged.

  18. Label-free surface plasmon sensing towards cancer diagnostics

    Science.gov (United States)

    Sankaranarayanan, Goutham

    The main objective of this thesis is to develop a conventional, home-built SPR bio-sensor to demonstrate bio-sensing applications. This emphasizes the understanding of basic concepts of Surface Plasmon Resonance and various interrogation techniques. Intensity Modulation was opted to perform the label-free SPR bio-sensing experiments due to its cost-efficient and compact setup. Later, label-free surface plasmon sensing was carried out to study and understand the bio-molecular interactions between (1). BSA and Anti BSA molecules and (2). Exosome/Liposome on thin metal (Au) films. Exosomes are cell-derived vesicles present in bodily fluids like blood, saliva, urine, epididymal fluid containing miRNAs, RNA, proteins, etc., at stable quantities during normal health conditions. The exosomes comprise varied constituents based on their cell origin from where they are secreted and is specific to that particular origin. However an exacerbated release is observed during tumor or cancer conditions. This increased level of exosomes present in the sample, can be detected using the SPR bio-sensor demonstrated in this thesis and effective thickness of adsorption on Au surface can be estimated. Also, chemically synthesized liposome particles were studied to determine if they can generate an equivalent sensor response to that of exosomes to consider them as an alternate. Finally a 10ppb Mercury (Hg) sensing was performed as part of Environment Monitoring application and results have been tabulated and compared.

  19. 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.

  20. Impacts of Climate Change and Land use Changes on Land Surface Radiation and Energy Budgets

    Science.gov (United States)

    Land surface radiation and energy budgets are critical to address a variety of scientific and application issues related to climate trends, weather predictions, hydrologic and biogeophysical modeling, and the monitoring of ecosystem health and agricultural crops. This is an introductory paper to t...

  1. 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.

  2. The Remote Sensing of Surface Radiative Temperature over Barbados.

    Science.gov (United States)

    remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

  3. SENSING URBAN LAND-USE PATTERNS BY INTEGRATING GOOGLE TENSORFLOW AND SCENE-CLASSIFICATION MODELS

    Directory of Open Access Journals (Sweden)

    Y. Yao

    2017-09-01

    Full Text Available With the rapid progress of China’s urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model’s ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI. Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs. To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737 for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  4. Contrasting self-aggregation over land and ocean surfaces

    Science.gov (United States)

    Inda Diaz, H. A.; O'Brien, T. A.

    2017-12-01

    The spontaneous organization of convection into clusters, or self-aggregation, demonstrably changes the nature and statistics of precipitation. While there has been much recent progress in this area, the processes that control self-aggregation are still poorly understood. Most of the work to date has focused on self-aggregation over ocean-like surfaces, but it is particularly pressing to understand what controls convective aggregation over land, since the associated change in precipitation statistics—between non-aggregated and aggregated convection—could have huge impacts on society and infrastructure. Radiative-convective equilibrium (RCE), has been extensively used as an idealized framework to study the tropical atmosphere. Self-aggregation manifests in numerous numerical models of RCE, nevertheless, there is still a lack of understanding in how it relates to convective organization in the observed world. Numerous studies have examined self-aggregation using idealized Cloud Resolving Models (CRMs) and General Circulation Models over the ocean, however very little work has been done on RCE and self-aggregation over land. Idealized models of RCE over ocean have shown that aggregation is sensitive to sea surface temperature (SST), more intense precipitation occurs in aggregated systems, and a variety of feedbacks—such as surface flux, cloud radiative, and upgradient moisture transport— contribute to the maintenance of aggregation, however it is not clear if these results apply over land. Progress in this area could help relate understanding of self-aggregation in idealized simulations to observations. In order to explore the behavior of self-aggregation over land, we use a CRM to simulate idealized RCE over land. In particular, we examine the aggregation of convection and how it compares with aggregation over ocean. Based on previous studies, where a variety of different CRMs exhibit a SST threshold below which self-aggregation does not occur, we hypothesize

  5. Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

    Science.gov (United States)

    Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

    2011-01-01

    The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near

  6. Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

    Science.gov (United States)

    Siemann, Amanda Lynn

    The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the

  7. SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water...

  8. SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes,...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. Impacts of land use and land cover on surface and air temperature in urban landscapes

    Science.gov (United States)

    Crum, S.; Jenerette, D.

    2015-12-01

    Accelerating urbanization affects regional climate as the result of changing land cover and land use (LCLU). Urban land cover composition may provide valuable insight into relationships among urbanization, air, and land-surface temperature (Ta and LST, respectively). Climate may alter these relationships, where hotter climates experience larger LULC effects. To address these hypotheses we examined links between Ta, LST, LCLU, and vegetation across an urban coastal to desert climate gradient in southern California, USA. Using surface temperature radiometers, continuously measuring LST on standardized asphalt, concrete, and turf grass surfaces across the climate gradient, we found a 7.2°C and 4.6°C temperature decrease from asphalt to vegetated cover in the coast and desert, respectively. There is 131% more temporal variation in asphalt than turf grass surfaces, but 37% less temporal variation in concrete than turf grass. For concrete and turf grass surfaces, temporal variation in temperature increased from coast to desert. Using ground-based thermal imagery, measuring LST for 24 h sequences over citrus orchard and industrial use locations, we found a 14.5°C temperature decrease from industrial to orchard land use types (38.4°C and 23.9°C, respectively). Additionally, industrial land use types have 209% more spatial variation than orchard (CV=0.20 and 0.09, respectively). Using a network of 300 Ta (iButton) sensors mounted in city street trees throughout the region and hyperspectral imagery data we found urban vegetation greenness, measured using the normalized difference vegetation index (NDVI), was negatively correlated to Ta at night across the climate gradient. Contrasting previous findings, the closest coupling between NDVI and Ta is at the coast from 0000 h to 0800 h (highest r2 = 0.6, P urbanized regions of southern California, USA decrease Ta and LST and spatial variation in LST, while built surfaces and land uses have the opposite effect. Furthermore

  15. Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

    Science.gov (United States)

    Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

    2017-10-01

    As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

  16. The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran

    Science.gov (United States)

    Fathizad, Hassan; Tazeh, Mahdi; Kalantari, Saeideh; Shojaei, Saeed

    2017-10-01

    Land use changes can bring about changes in land surface temperature (LST) which is influenced by climatic conditions and physical characteristics of the land surface. In this study, spatiotemporal variations of land surface temperature have been investigated in the desert area of Dasht-e-Abbas, Ilam, based on a variety of land use changes. The investigated periods for the study include 1990, 2000 and 2010 using Landsat image data. First, in mapping land use we used the Fuzzy ARTMAP Neural Network Classification method followed by determination of the NDVI Index to estimate land surface temperature. The results show an increase in LST in areas where degradation, land use and land cover changes have occurred. In 1990, 2000 and 2010, the average land surface temperature of the Fair Rangelands was 26.72 °C, 30.06 °C and 30.95 °C, respectively. This rangeland has been reduced by about 5%. For poor rangelands, the average LSTs were 26.95, 32.83 and 34.49 Cº, respectively which had a 18% reduction. In 1990, 2000 and 2010, the average land surface temperatures of agricultural lands were 24.31 °C, 27.87 °C and 28.61 °C, respectively which has been an increasing trend. The reason can be attributed to changes in cropping patterns of the study area.

  17. Determination of wetland ecosystem boundaries and validation of land use maps using remote sensing: Fuente de Piedra case study (Spain)

    Science.gov (United States)

    Sánchez, Antonio; Malak, Dania Abdul; Schröder, Christoph; Martinez-Murillo, Juan F.

    2016-04-01

    Remote sensing techniques (SRS) are valid tools for wetland monitoring that could support wetland managers in assessing the spatial and temporal changes in wetland ecosystems as well as in understanding their condition and the ecosystem services they provide. This study focuses on the one hand, on drawing hydro-ecological guidelines for the delimitation of wetland ecosystems; and on the other hand, to assess the reliability of widely available satellite images (Landsat) in estimating the land use/ land cover types covering wetlands. This research develops comprehensive guidelines to determine the boundaries of the Fuente de Piedra wetland ecosystem located in Andalusia, Spain and defines the main land use/ land cover classes covering this ecosystem using Landsat 8 images. An accuracy of the SRS results delivered is tested using the regional inventory of land use produced by the regional government of Andalusia in 2011. By using the ecological and hydrological settings of the area, the boundaries of the Fuente de Piedra wetland ecosystem are determined as an alternative to improve the current delimitations methodology (the Ramsar and Natura 2000 delineations), used by the local authorities so far and based mainly on administrative reasoning. In terms of the land use land cover definition in the area, Fuente de Piedra wetland ecosystem shows to cover a total area of 195 km2 composed mainly by agricultural areas (81.46%): olive groves, non-irrigated arable land and pastures, being 54.82%, 25.71% and 0.93% of the surface respectively. Wetland related land covers (water surface, wetland vegetation) represent 6.85% while natural vegetation is distributed in forest, 1.67%, and shrub areas, 4.14%, being 5.81% in total. 4.58% of the area corresponds to urban and other artificial surfaces. The rest, 1.30%, is composed of different areas without vegetation (sands, bare rock, dumps, etc.). The classification of the Landsat images made with the newly developed SWOS toolbox

  18. Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

    Science.gov (United States)

    Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

    2017-12-01

    An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

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

    Science.gov (United States)

    Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

    2009-01-01

    As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated land surface form classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Since land surface forms strongly influence the differentiation and distribution of terrestrial ecosystems, they are one of the key input layers in this biophysical stratification. After extensive investigation into various land surface form mapping methodologies, the decision was made to use the methodology developed by the Missouri Resource Assessment Partnership (MoRAP). MoRAP made modifications to Hammond's land surface form classification, which allowed the use of 30-meter source data and a 1-km2 window for analyzing the data cell and its surrounding cells (neighborhood analysis). While Hammond's methodology was based on three topographic variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief. Using the MoRAP method, slope is classified as gently sloping when more than 50 percent of the area in a 1-km2 neighborhood has slope less than 8 percent, otherwise the area is considered moderately sloping. Local relief, which is the difference between the maximum and minimum elevation in a neighborhood, is classified into five groups: 0-15 m, 16-30 m, 31-90 m, 91-150 m, and >150 m. The land surface form classes are derived by combining slope and local relief to create eight landform classes: flat plains (gently sloping and local relief = 90 m), low hills (not gently sloping and local relief = 150 m). However, in the USGS application of the MoRAP methodology, an additional local relief group was used (> 400 m) to capture additional local topographic variation. As a result, low

  20. Surface drainage in leveled land: Implication of slope

    Directory of Open Access Journals (Sweden)

    Antoniony S. Winkler

    Full Text Available ABSTRACT In the lowlands of Rio Grande do Sul, land leveling is mostly carried out with no slope for the purpose of rice production. In this environment, soils with a low hydraulic conductivity are predominant owing to the presence of a practically impermeable B-horizon near the surface. Land leveling leads to soil accommodation resulting in the formation of depressions where water accumulates after heavy rainfalls, subsequently leading to problems with crops implanted in succession to rice, such as soybeans. The objective of this research was to quantify the areas and volumes of water accumulation in soil as a function of the slope of land leveling. Five typical leveled lowland areas were studied as a part of this research. The original areas presented slopes of 0, 0.20, 0.25, 0.28 and 0.40%, which were used to generate new digital elevation models with slopes between 0 and 0.5%. These newly generated digital models were used to map the depressions with surface water storage. In conclusion, land leveling with slopes higher than 0.1% is recommended to minimize problems with superficial water storage in rice fields.

  1. 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.

  2. Validation of Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2017-12-01

    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. Validation of the level-2 SL_2_LST product, which became freely available on an operational basis from 5th July 2017 builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities. 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 the Sea and Land Surface Temperature Radiometer (SLSTR) which is designed around biome

  3. Surface emitting ring quantum cascade lasers for chemical sensing

    Science.gov (United States)

    Szedlak, Rolf; Hayden, Jakob; Martín-Mateos, Pedro; Holzbauer, Martin; Harrer, Andreas; Schwarz, Benedikt; Hinkov, Borislav; MacFarland, Donald; Zederbauer, Tobias; Detz, Hermann; Andrews, Aaron Maxwell; Schrenk, Werner; Acedo, Pablo; Lendl, Bernhard; Strasser, Gottfried

    2018-01-01

    We review recent advances in chemical sensing applications based on surface emitting ring quantum cascade lasers (QCLs). Such lasers can be implemented in monolithically integrated on-chip laser/detector devices forming compact gas sensors, which are based on direct absorption spectroscopy according to the Beer-Lambert law. Furthermore, we present experimental results on radio frequency modulation up to 150 MHz of surface emitting ring QCLs. This technique provides detailed insight into the modulation characteristics of such lasers. The gained knowledge facilitates the utilization of ring QCLs in combination with spectroscopic techniques, such as heterodyne phase-sensitive dispersion spectroscopy for gas detection and analysis.

  4. Urbanization Process and Variation of Energy Budget of Land Surfaces

    Directory of Open Access Journals (Sweden)

    Ciro Gardi

    2007-06-01

    Full Text Available Urban areas are increasing at a rate much higher than human population growth in many part of the world; actually more than 73 towns in the world are larger than 1000 km2. The European Environmental Agency indicates an urban area average growth rate, over the last 20 years, of 20%. The urbanization process, and the consequent soil sealing, determines not only the losses of the ecological functions of the soil, but also a variation of the energy budget of land surfaces, that affect the microclimatic conditions (heat islands. The alteration of the energy budget are determined by the variations of albedo and roughness of surfaces, but especially by the net losses of evapotranspirating areas. In the present research we have assessed the variation of Parma territory energy budget, induced by the change in land use over the last 122 years. The urban area increase between 1881 and 2003 was 535%.

  5. The Impacts on Illegal Farmland Conversion of Adopting Remote Sensing Technology for Land Inspection in China

    Directory of Open Access Journals (Sweden)

    Taiyang Zhong

    2014-07-01

    Full Text Available While China’s central government has adopted remote sensing technology in land inspection since 2000, little empirical research has been done on its effect. This study aims to measure the effect of satellite imagery-based land inspection (SIBI on illegal farmland conversion. The data used in this study were collected for the period from 1997 to 2010 at the province-level. The econometrics approach for panel data model was used in this research. The results showed that SIBI has a deterrent effect of approximately 2.42 ha for every increase of 1% in proportion to the area of prefecture-level regions inspected in a province-level region. The results also indicate land inspections with RS (Remote Sensing technology saved approximately 11,880 ha farmland from illegal conversion during 2000–2010 with an estimated contribution of reducing illegal farmland conversion by nearly 11%. Furthermore, the governance structure change for land inspection has also contributed to deterring illegal farmland conversion. The deterrent effects due to land inspection by the Supervisor of State Land (SSL are about 7332 ha during 2008–2010 with an estimated contribution of reducing illegal farmland conversion by nearly 33%. In conclusion, although SIBI has strengthened China’s central capacity to uncover illegal farmland conversion and weakened local governments’ abilities to hide illegal farmland conversion, it has limited impact on illegal farmland conversion since it is just a technical tool. Improvements in the land inspection governance structure have also helped to deter illegal farmland conversion.

  6. Using Modified Remote Sensing Imagery to Interpret Changes in Cultivated Land under Saline-Alkali Conditions

    Directory of Open Access Journals (Sweden)

    Hui Gao

    2016-07-01

    Full Text Available Managing the rapidly changing saline-alkali land under cultivation in the coastal areas of China is important not only for mitigating the negative impacts of such land on the environment, but also for ensuring long-term sustainability of agriculture. In this light, setting up rapid monitoring systems to assist decision-making in developing sustainable management plans is therefore an absolute necessity. In this study, we developed a new interpretation system where symbols are used to grade and classify saline-alkali lands in space and time, based on the characteristics of plant cover and features of remote sensing images. The system was used in combination with the maximum likelihood supervised classification to analyze the changes in cultivated lands under saline-alkali conditions in Huanghua City. The analysis revealed changes in the area and spatial distribution of cultivated under saline-alkali conditions in the region. The total area of saline-alkali land was 139,588.8 ha in 1992 and 134,477.5 ha in 2011. Compared with 1992, severely and moderately saline-alkali land areas decreased in 2011. However, non/slightly saline land areas increased over that in 1992. The results showed that the salinization rate of arable lands in Huanghua City decreased from 1992 to 2011. The moderately saline-alkali land southeast of the city transformed into non/slightly saline-alkaline. Then, severely saline-alkali land far from the coastal zone west of the city became moderately saline-alkaline. Spatial changes in cultivated saline-alkali lands in Huanghua City were such that the centers of gravity (CG of severely and non/slightly saline-alkali land moved closer the coastline, while that of the moderately saline-alkali land moved from southwest coastal line to northwest. Factors influencing changes in cultivated lands in the saline-alkali ecosystem included climate, hydrology and human activity. Thus, studies are required to further explore these factors in

  7. Impact of land cover and population density on land surface temperature: case study in Wuhan, China

    Science.gov (United States)

    Li, Lin; Tan, Yongbin; Ying, Shen; Yu, Zhonghai; Li, Zhen; Lan, Honghao

    2014-01-01

    With the rapid development of urbanization, the standard of living has improved, but changes to the city thermal environment have become more serious. Population urbanization is a driving force of residential expansion, which predominantly influences the land surface temperature (LST). We obtained the land covers and LST maps of Wuhan from Landsat-5 images in 2000, 2002, 2005, and 2009, and discussed the distribution of land use/cover change and LST variation, and we analyzed the correlation between population distribution and LST values in residential regions. The results indicated massive variation of land cover types, which was shown as a reduction in cultivatable land and the expansion of building regions. High-LST regions concentrated on the residential and industrial areas with low vegetation coverage. In the residential region, the population density (PD) had effects on the LST values. Although the area or variation of residential regions was close, lower PD was associated with lower mean LST or LST variation. Thus, decreasing the high-LST regions concentration by reducing the PD may alleviate the urban heat island effect on the residential area. Taken together, these results can provide supports for urban planning projects and studies on city ecological environments.

  8. 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

  9. Linking land use with pesticides in Dutch surface waters.

    Science.gov (United States)

    Van't, Zelfde M T; Tamis, W L M; Vijver, M G; De Snoo, G R

    2012-01-01

    Compared with other European countries The Netherlands has a relatively high level of pesticide consumption, particularly in agriculture. Many of the compounds concerned end up in surface waters. Surface water quality is routinely monitored and numerous pesticides are found to be present in high concentrations, with various standards being regularly exceeded. Many standards-breaching pesticides exhibit regional patterns that can be traced back to land use. These patterns have been statistically analysed by correlating surface area per land use category with standards exceedance per pesticide, thereby identifying numerous significant correlations with respect to breaches of both the ecotoxicological standard (Maximum Tolerable Risk, MTR) and the drinking water standard. In the case of the MTR, greenhouse horticulture, floriculture and bulb-growing have the highest number as well as percentage of standard-breaching pesticides, despite these market segments being relatively small in terms of area cropped. Cereals, onions, vegetables, perennial border plants and pulses are also associated with many pesticides that exceed the drinking water standard. When a correction is made for cropped acreage, cereals and potatoes also prove to be a major contributor to monitoring sites where the MTR standard is exceeded. Over the period 1998-2006 the land-use categories with the most and highest percentage of standards-exceeding pesticides (greenhouse horticulture, bulb-growing and flower cultivation) showed an increase in the percentage of standards-exceeding compounds.

  10. On the predictability of land surface fluxes from meteorological variables

    Science.gov (United States)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

    2018-01-01

    Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

  11. Importance of Surface Texture to Infrared Remote Sensing Interpretations

    Science.gov (United States)

    Kirkland, L. E.; Adams, P. M.; Herr, K. C.; Salisbury, J. W.

    2001-11-01

    Thermal infrared remote sensing may be used to identify minerals present on the surface using diagnostic spectral bands. As band depth (spectral contrast) exhibited by the mineral increases, the mineral is easier to detect. In order to determine the expected spectral contrast, thermal infrared spectra of typical mineral endmembers are commonly measured in the laboratory. For example, for calcite, well-crystalline limestone is commonly studied. However, carbonates occur in several forms, including thin coatings, indurated carbonate (calcrete), and hot springs deposits. Different formation pathways may cause different microstructures and surface textures. This in turn can also affect the surface texture of the weathered material. Different surface textures can affect the measured band contrast, through roughness that causes a cavity (hohlraum) effect, and particle size and roughness on a scale that causes volume scattering. Thus since detection limits vary with the spectral contrast, surface texture can be an important variable in how detectable a mineral is. To study these issues, we have examined limestone and calcrete deposits at Mormon Mesa, Nevada that have two distinctly different microstructures and surface texture [Kirkland et al., 2001]. The limestone studied has larger grains and the grains frequently have flat, smooth surfaces on the order of 10-50 microns in cross-section length. The calcrete has smaller, more angular calcite grains, which exhibit almost no flat surfaces longer than 5 microns in cross-section length. We will show scanning electron microscope images to compare the different microstructures and surface textures of both the fresh and weathered surfaces, and we will show corresponding thermal infrared spectra to illustrate the different spectral signatures. The results demonstrate the importance of understanding the microstructure of mineral deposits to accurately interpret infrared remote sensing data, especially for studies that lack ground

  12. Monitoring and Evaluation of Cultivated Land Irrigation Guarantee Capability with Remote Sensing

    Science.gov (United States)

    Zhang, C., Sr.; Huang, J.; Li, L.; Wang, H.; Zhu, D.

    2015-12-01

    Abstract: Cultivated Land Quality Grade monitoring and evaluation is an important way to improve the land production capability and ensure the country food safety. Irrigation guarantee capability is one of important aspects in the cultivated land quality monitoring and evaluation. In the current cultivated land quality monitoring processing based on field survey, the irrigation rate need much human resources investment in long investigation process. This study choses Beijing-Tianjin-Hebei as study region, taking the 1 km × 1 km grid size of cultivated land unit with a winter wheat-summer maize double cropping system as study object. A new irrigation capacity evaluation index based on the ratio of the annual irrigation requirement retrieved from MODIS data and the actual quantity of irrigation was proposed. With the years of monitoring results the irrigation guarantee capability of study area was evaluated comprehensively. The change trend of the irrigation guarantee capability index (IGCI) with the agricultural drought disaster area in rural statistical yearbook of Beijing-Tianjin-Hebei area was generally consistent. The average of IGCI value, the probability of irrigation-guaranteed year and the weighted average which controlled by the irrigation demand index were used and compared in this paper. The experiment results indicate that the classification result from the present method was close to that from irrigation probability in the gradation on agriculture land quality in 2012, with overlap of 73% similar units. The method of monitoring and evaluation of cultivated land IGCI proposed in this paper has a potential in cultivated land quality level monitoring and evaluation in China. Key words: remote sensing, evapotranspiration, MODIS cultivated land quality, irrigation guarantee capability Authors: Chao Zhang, Jianxi Huang, Li Li, Hongshuo Wang, Dehai Zhu China Agricultural University zhangchaobj@gmail.com

  13. The Identification of Land Utilization in Coastal Reclamation Areas in Tianjin Using High Resolution Remote Sensing Images

    Science.gov (United States)

    Meng, Y.; Cao, Y.; Tian, H.; Han, Z.

    2018-04-01

    In recent decades, land reclamation activities have been developed rapidly in Chinese coastal regions, especially in Bohai Bay. The land reclamation areas can effectively alleviate the contradiction between land resources shortage and human needs, but some idle lands that left unused after the government making approval the usage of sea areas are also supposed to pay attention to. Due to the particular features of land coverage identification in large regions, traditional monitoring approaches are unable to perfectly meet the needs of effectively and quickly land use classification. In this paper, Gaofen-1 remotely sensed satellite imagery data together with sea area usage ownership data were used to identify the land use classifications and find out the idle land resources. It can be seen from the result that most of the land use types and idle land resources can be identified precisely.

  14. A global data set of land-surface parameters

    International Nuclear Information System (INIS)

    Claussen, M.; Lohmann, U.; Roeckner, E.; Schulzweida, U.

    1994-01-01

    A global data set of land surface parameters is provided for the climate model ECHAM developed at the Max-Planck-Institut fuer Meteorologie in Hamburg. These parameters are: background (surface) albedo α, surface roughness length z 0y , leaf area index LAI, fractional vegetation cover or vegetation ratio c y , and forest ratio c F . The global set of surface parameters is constructed by allocating parameters to major exosystem complexes of Olson et al. (1983). The global distribution of ecosystem complexes is given at a resolution of 0.5 0 x 0.5 0 . The latter data are compatible with the vegetation types used in the BIOME model of Prentice et al. (1992) which is a potential candidate of an interactive submodel within a comprehensive model of the climate system. (orig.)

  15. Nano Sensing and Energy Conversion Using Surface Plasmon Resonance (SPR

    Directory of Open Access Journals (Sweden)

    Iltai (Isaac Kim

    2015-07-01

    Full Text Available Nanophotonic technique has been attracting much attention in applications of nano-bio-chemical sensing and energy conversion of solar energy harvesting and enhanced energy transfer. One approach for nano-bio-chemical sensing is surface plasmon resonance (SPR imaging, which can detect the material properties, such as density, ion concentration, temperature, and effective refractive index in high sensitivity, label-free, and real-time under ambient conditions. Recent study shows that SPR can successfully detect the concentration variation of nanofluids during evaporation-induced self-assembly process. Spoof surface plasmon resonance based on multilayer metallo-dielectric hyperbolic metamaterials demonstrate SPR dispersion control, which can be combined with SPR imaging, to characterize high refractive index materials because of its exotic optical properties. Furthermore, nano-biophotonics could enable innovative energy conversion such as the increase of absorption and emission efficiency and the perfect absorption. Localized SPR using metal nanoparticles show highly enhanced absorption in solar energy harvesting. Three-dimensional hyperbolic metamaterial cavity nanostructure shows enhanced spontaneous emission. Recently ultrathin film perfect absorber is demonstrated with the film thickness is as low as ~1/50th of the operating wavelength using epsilon-near-zero (ENZ phenomena at the wavelength close to SPR. It is expected to provide a breakthrough in sensing and energy conversion applications using the exotic optical properties based on the nanophotonic technique.

  16. Operational monitoring of land-cover change using multitemporal remote sensing data

    Science.gov (United States)

    Rogan, John

    2005-11-01

    Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation

  17. Soil Structure - A Neglected Component of Land-Surface Models

    Science.gov (United States)

    Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

    2017-12-01

    Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity

  18. Open land cover from OpenStreetMap and remote sensing

    Science.gov (United States)

    Schultz, Michael; Voss, Janek; Auer, Michael; Carter, Sarah; Zipf, Alexander

    2017-12-01

    OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011-2016, and 46% of the area was representative of 2016-2017.

  19. Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

    Science.gov (United States)

    Abdolghafoorian, A.; Farhadi, L.

    2017-12-01

    Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

  20. Mapping the global land surface using 1 km AVHRR data

    Science.gov (United States)

    Lauer, D.T.; Eidenshink, J.C.

    1998-01-01

    The scientific requirements for mapping the global land surface using 1 km advanced very high resolution radiometer (AVHRR) data have been set forth by the U.S. Global Change Research Program; the International Geosphere Biosphere Programme (IGBP); The United Nations; the National Oceanic and Atmospheric Administration (NOAA); the Committee on Earth Observations Satellites; and the National Aeronautics and Space Administration (NASA) mission to planet Earth (MTPE) program. Mapping the global land surface using 1 km AVHRR data is an international effort to acquire, archive, process, and distribute 1 km AVHRR data to meet the needs of the international science community. A network of AVHRR receiving stations, along with data recorded by NOAA, has been acquiring daily global land coverage since April 1, 1992. A data set of over 70,000 AVHRR images is archived and distributed by the United States Geological Survey (USGS) EROS Data Center, and the European Space Agency. Under the guidance of the IGBP, processing standards have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are for the study of surface vegetation condition, mapping land cover, and deriving biophysical characteristics of terrestrial ecosystems. A time-series of 54 10-day global vegetation index composites for the period of April 1, 1992 through September 1993 has been produced. The production of a time-series of 33 10-day global vegetation index composites using NOAA-14 data for the period of February 1, 1995 through December 31, 1995 is underway. The data products are available from the USGS, in cooperation with NASA's MTPE program and other international organizations.

  1. lands

    Directory of Open Access Journals (Sweden)

    A.T. O'Geen

    2015-04-01

    Full Text Available Groundwater pumping chronically exceeds natural recharge in many agricultural regions in California. A common method of recharging groundwater — when surface water is available — is to deliberately flood an open area, allowing water to percolate into an aquifer. However, open land suitable for this type of recharge is scarce. Flooding agricultural land during fallow or dormant periods has the potential to increase groundwater recharge substantially, but this approach has not been well studied. Using data on soils, topography and crop type, we developed a spatially explicit index of the suitability for groundwater recharge of land in all agricultural regions in California. We identified 3.6 million acres of agricultural land statewide as having Excellent or Good potential for groundwater recharge. The index provides preliminary guidance about the locations where groundwater recharge on agricultural land is likely to be feasible. A variety of institutional, infrastructure and other issues must also be addressed before this practice can be implemented widely.

  2. Land surface skin temperature climatology: benefitting from the strengths of satellite observations

    International Nuclear Information System (INIS)

    Jin Menglin; Dickinson, Robert E

    2010-01-01

    Surface skin temperature observations (T skin ), as obtained by satellite remote sensing, provide useful climatological information of high spatial resolution and global coverage that enhances the traditional ground observations of surface air temperature (T air ) and so, reveal new information about land surface characteristics. This letter analyzes nine years of moderate-resolution imaging spectroradiometer (MODIS) skin temperature observations to present monthly skin temperature diurnal, seasonal, and inter-annual variations at a 0.05 deg. latitude/longitude grid over the global land surface and combines these measurements with other MODIS-based variables in an effort to understand the physical mechanisms responsible for T skin variations. In particular, skin temperature variations are found to be closely related to vegetation cover, clouds, and water vapor, but to differ from 2 m surface T air in terms of both physical meaning and magnitude. Therefore, the two temperatures (T skin and T air ) are complementary in their contribution of valuable information to the study of climate change.

  3. Land Cover Classification Using Integrated Spectral, Temporal, and Spatial Features Derived from Remotely Sensed Images

    Directory of Open Access Journals (Sweden)

    Yongguang Zhai

    2018-03-01

    Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.

  4. Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

    Science.gov (United States)

    Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

    2012-01-01

    Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

  5. Remotely sensed soil temperatures beneath snow-free skin-surface using thermal observations from tandem polar-orbiting satellites: An analytical three-time-scale model

    DEFF Research Database (Denmark)

    Zhan, Wenfeng; Zhou, Ji; Ju, Weimin

    2014-01-01

    Subsurface soil temperature is a key variable of land surface processes and not only responds to but also modulates the interactions of energy fluxes at the Earth's surface. Thermal remote sensing has traditionally been regarded as incapable of detecting the soil temperature beneath the skin-surf...

  6. Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

    Science.gov (United States)

    Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

    2018-06-01

    Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

  7. The esa earth explorer land surface processes and interactions mission

    Science.gov (United States)

    Labandibar, Jean-Yves; Jubineau, Franck; Silvestrin, Pierluigi; Del Bello, Umberto

    2017-11-01

    The European Space Agency (ESA) is defining candidate missions for Earth Observation. In the class of the Earth Explorer missions, dedicated to research and pre-operational demonstration, the Land Surface Processes and Interactions Mission (LSPIM) will acquire the accurate quantitative measurements needed to improve our understanding of the nature and evolution of biosphere-atmosphere interactions and to contribute significantly to a solution of the scaling problems for energy, water and carbon fluxes at the Earth's surface. The mission is intended to provide detailed observations of the surface of the Earth and to collect data related to ecosystem processes and radiation balance. It is also intended to address a range of issues important for environmental monitoring, renewable resources assessment and climate models. The mission involves a dedicated maneuvering satellite which provides multi-directional observations for systematic measurement of Land Surface BRDF (BiDirectional Reflectance Distribution Function) of selected sites on Earth. The satellite carries an optical payload : PRISM (Processes Research by an Imaging Space Mission), a multispectral imager providing reasonably high spatial resolution images (50 m over 50 km swath) in the whole optical spectral domain (from 450 nm to 2.35 μm with a resolution close to 10 nm, and two thermal bands from 8.1 to 9.1 μm). This paper presents the results of the Phase A study awarded by ESA, led by ALCATEL Space Industries and concerning the design of LSPIM.

  8. Surface Ionization and Soft Landing Techniques in Mass Spectrometry

    International Nuclear Information System (INIS)

    Futrell, Jean H.; Laskin, Julia

    2010-01-01

    The advent of soft ionization techniques, notably electrospray and laser desorption ionization methods, has extended mass spectrometric methods to large molecules and molecular complexes. This both greatly expands applications of mass spectrometry and makes the activation and dissociation of complex ions an integral part of large molecule mass spectrometry. A corollary of the much greater number of internal degrees of freedom and high density of states associated with molecular complexity is that internal energies much higher than the dissociation energies for competing fragmentation processes are required for observable fragmentation in time scales sampled by mass spectrometers. This article describes the kinetics of surface-induced dissociation (SID), a particularly efficient activation method for complex ions. Two very important characteristics of SID are very rapid, sub-picosecond activation and precise control of ion internal energy by varying ion collision energy. The nature of the surface plays an important role in SID, determining both efficiency and mechanism of ion activation. Surface composition and morphology strongly influence the relative importance of competing reactions of SID, ion capture (soft-landing), surface reaction and neutralization. The important features of SID and ion soft-landing are described briefly in this review and more fully in the recommended reading list.

  9. Analysing Regional Land Surface Temperature Changes by Satellite Data, a Case Study of Zonguldak, Turkey

    Science.gov (United States)

    Sekertekin, A.; Kutoglu, S.; Kaya, S.; Marangoz, A. M.

    2014-12-01

    In recent years, climate change is one of the most important problems that the ecological system of the world has been encountering. Global warming and climate change have been studied frequently by all disciplines all over the world and Geomatics Engineering also contributes to such studies by means of remote sensing, global positioning system etc. Monitoring Land Surface Temperature (LST) via remote sensing satellites is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and 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. Generally three algorithms are used to obtain LST by using Landsat 5 TM data. These algorithms are radiative transfer equation method, single channel method and mono-window algorithm. Radiative transfer equation method is not applicable because during the satellite pass, atmospheric parameters must be measured in-situ. In this research, mono window algorithm was implemented to Landsat 5 TM image. Besides, meteorological data such as humidity and temperature are used in the algorithm. Acquisition date of the image is 28.08.2011 and our study area is Zonguldak, Turkey. High resolution images are used to investigate the relationships between LST and land cover type. As a result of these analyses, area with vegetation cover has approximately 5 ºC lower temperature than the city center and arid land. Because different surface properties like reinforced concrete construction, green zones and sandbank are all together in city center, LST differs about 10 ºC in the city center. The temperature around some places in thermal power plant region Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature because of land cover structure. Thanks to this

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

    Science.gov (United States)

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

    2014-12-01

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

  11. 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.

  12. 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

  13. Surface-enhanced Raman scattering sensing on black silicon

    International Nuclear Information System (INIS)

    Gervinskas, Gediminas; Seniutinas, Gediminas; Hartley, Jennifer S.; Stoddart, Paul R.; Juodkazis, Saulius; Kandasamy, Sasikaran; Fahim, Narges F.

    2013-01-01

    Reactive ion etching was used to fabricate black-Si over the entire surface area of 4-inch Si wafers. After 20 min of the plasma treatment, surface reflection well below 2% was achieved over the 300-1000 nm spectral range. The spikes of the black-Si substrates were coated by gold, resulting in an island film for surface-enhanced Raman scattering (SERS) sensing. A detection limit of 1 x 10 -6 M (at count rate > 10 2 s -1 . mW -1 ) was achieved for rhodamine 6G in aqueous solution when drop cast onto a ∝ 100-nm-thick Au coating. The sensitivity increases for thicker coatings. A mixed mobile-on-immobile platform for SERS sensing is introduced by using dog-bone Au nanoparticles on the Au/black-Si substrate. The SERS intensity shows a non-linear dependence on the solid angle (numerical aperture of excitation/collection optics) for a thick gold coating that exhibits a 10 times higher enhancement. This shows promise for augmented sensitivity in SERS applications. (copyright 2013 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  14. Surface-enhanced Raman scattering sensing on black silicon

    Energy Technology Data Exchange (ETDEWEB)

    Gervinskas, Gediminas; Seniutinas, Gediminas; Hartley, Jennifer S.; Stoddart, Paul R.; Juodkazis, Saulius [Centre for Micro-Photonics and Industrial Research Institute Swinburne, Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, VIC (Australia); The Australian National Fabrication Facility-ANFF, Victoria node, Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, VIC (Australia); Kandasamy, Sasikaran [Melbourne Centre for Nanofabrication, Clayton, VIC (Australia); Fahim, Narges F. [Centre for Micro-Photonics and Industrial Research Institute Swinburne, Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, VIC (Australia)

    2013-12-15

    Reactive ion etching was used to fabricate black-Si over the entire surface area of 4-inch Si wafers. After 20 min of the plasma treatment, surface reflection well below 2% was achieved over the 300-1000 nm spectral range. The spikes of the black-Si substrates were coated by gold, resulting in an island film for surface-enhanced Raman scattering (SERS) sensing. A detection limit of 1 x 10{sup -6} M (at count rate > 10{sup 2} s{sup -1}. mW{sup -1}) was achieved for rhodamine 6G in aqueous solution when drop cast onto a {proportional_to} 100-nm-thick Au coating. The sensitivity increases for thicker coatings. A mixed mobile-on-immobile platform for SERS sensing is introduced by using dog-bone Au nanoparticles on the Au/black-Si substrate. The SERS intensity shows a non-linear dependence on the solid angle (numerical aperture of excitation/collection optics) for a thick gold coating that exhibits a 10 times higher enhancement. This shows promise for augmented sensitivity in SERS applications. (copyright 2013 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  15. Interdependencies of Arctic land surface processes: A uniquely sensitive environment

    Science.gov (United States)

    Bowling, L. C.

    2007-12-01

    The circumpolar arctic drainage basin is composed of several distinct ecoregions including steppe grassland and cropland, boreal forest and tundra. Land surface hydrology throughout this diverse region shares several unique features such as dramatic seasonal runoff differences controlled by snowmelt and ice break-up; the storage of significant portions of annual precipitation as snow and in lakes and wetlands; and the effects of ephemeral and permanently frozen soils. These arctic land processes are delicately balanced with the climate and are therefore important indicators of change. The litany of recently-detected changes in the Arctic includes changes in snow precipitation, trends and seasonal shifts in river discharge, increases and decreases in the extent of surface water, and warming soil temperatures. Although not unique to the arctic, increasing anthropogenic pressures represent an additional element of change in the form of resource extraction, fire threat and reservoir construction. The interdependence of the physical, biological and social systems mean that changes in primary indicators have large implications for land cover, animal populations and the regional carbon balance, all of which have the potential to feed back and induce further change. In fact, the complex relationships between the hydrological processes that make the Artic unique also render observed historical change difficult to interpret and predict, leading to conflicting explanations. For example, a decrease in snow accumulation may provide less insulation to the underlying soil resulting in greater frost development and increased spring runoff. Similarly, melting permafrost and ground ice may lead to ground subsidence and increased surface saturation and methane production, while more complete thaw may enhance drainage and result in drier soil conditions. The threshold nature of phase change around the freezing point makes the system especially sensitive to change. In addition, spatial

  16. Monitoring and Assessment of Military Installation Land Condition under Training Disturbance Using Remote Sensing

    Science.gov (United States)

    Rijal, Santosh

    Various military training activities are conducted in more than 11.3 million hectares of land (> 5,500 training sites) in the United States (U.S.). These training activities directly and indirectly degrade the land. Land degradation can impede continuous military training. In order to sustain long term training missions and Army combat readiness, the environmental conditions of the military installations need to be carefully monitored and assessed. Furthermore, the National Environmental Policy Act of 1969 (NEPA) and the U.S. Army Regulation 200-2 require the DoD to minimize the environmental impacts of training and document the environmental consequences of their actions. To achieve these objectives, the Department of Army initiated an Integrated Training Area Management (ITAM) program to manage training lands through assessing their environmental requirements and establishing policies and procedures to achieve optimum, sustainable use of training lands. One of the programs under ITAM, Range and Training Land Assessment (RTLA) was established to collect field-based data for monitoring installation's environmental condition. Due to high cost and inefficiencies involved in the collection of field data, the RTLA program was stopped in several military installations. Therefore, there has been a strong need to develop an efficient and low cost remote sensing based methodology for assessing and monitoring land conditions of military installations. It is also important to make a long-term assessment of installation land condition for understanding cumulative impacts of continuous military training activities. Additionally, it is unclear that compared to non-military land condition, to what extent military training activities have led to the degradation of land condition for military installations. The first paper of this dissertation developed a soil erosion relevant and image derived cover factor (ICF) based on linear spectral mixture (LSM) analysis to assess and

  17. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  18. Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

    International Nuclear Information System (INIS)

    Zin, M H M; Ahmad, B

    2014-01-01

    The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest

  19. Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

    Science.gov (United States)

    Zin, M. H. M.; Ahmad, B.

    2014-02-01

    The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.

  20. Land-Surface-Atmosphere Coupling in Observations and Models

    Directory of Open Access Journals (Sweden)

    Alan K Betts

    2009-07-01

    Full Text Available The diurnal cycle and the daily mean at the land-surface result from the coupling of many physical processes. The framework of this review is largely conceptual; looking for relationships and information in the coupling of processes in models and observations. Starting from the surface energy balance, the role of the surface and cloud albedos in the shortwave and longwave fluxes is discussed. A long-wave radiative scaling of the diurnal temperature range and the night-time boundary layer is summarized. Several aspects of the local surface energy partition are presented: the role of soilwater availability and clouds; vector methods for understanding mixed layer evolution, and the coupling between surface and boundary layer that determines the lifting condensation level. Moving to larger scales, evaporation-precipitation feedback in models is discussed; and the coupling of column water vapor, clouds and precipitation to vertical motion and moisture convergence over the Amazon. The final topic is a comparison of the ratio of surface shortwave cloud forcing to the diabatic precipitation forcing of the atmosphere in ERA-40 with observations.

  1. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    Science.gov (United States)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

  2. Assessment and prediction of land ecological environment quality change based on remote sensing-a case study of the Dongting lake area in China

    Science.gov (United States)

    Hu, Wenmin; Wang, Zhongcheng; Li, Chunhua; Zhao, Jin; Li, Yi

    2018-02-01

    Multi-source remote sensing data is rarely used for the comprehensive assessment of land ecologic environment quality. In this study, a digital environmental model was proposed with the inversion algorithm of land and environmental factors based on the multi-source remote sensing data, and a comprehensive index (Ecoindex) was applied to reconstruct and predict the land environment quality of the Dongting Lake Area to assess the effect of human activities on the environment. The main finding was that with the decrease of Grade I and Grade II quality had a decreasing tendency in the lake area, mostly in suburbs and wetlands. Atmospheric water vapour, land use intensity, surface temperature, vegetation coverage, and soil water content were the main driving factors. The cause of degradation was the interference of multi-factor combinations, which led to positive and negative environmental agglomeration effects. Positive agglomeration, such as increased rainfall and vegetation coverage and reduced land use intensity, could increase environmental quality, while negative agglomeration resulted in the opposite. Therefore, reasonable ecological restoration measures should be beneficial to limit the negative effects and decreasing tendency, improve the land ecological environment quality and provide references for macroscopic planning by the government.

  3. Land Surface Phenologies of the Northern Great Plains: Possible Futures Arising From Land and Climate Change

    Science.gov (United States)

    Henebry, G. M.; Wimberly, M. C.; Senay, G.; Wang, A.; Chang, J.; Wright, C. R.; Hansen, M. C.

    2008-12-01

    Land cover change across the Northern Great Plains of North America over the past three decades has been driven by changes in agricultural management (conservation tillage; irrigation), government incentives (Conservation Reserve Program; subsidies to grain-based ethanol), crop varieties (cold-hardy soybean), and market dynamics (increasing world demand). Climate change across the Northern Great Plains over the past three decades has been evident in trends toward earlier warmth in the spring and a longer frost-free season. Together these land and climate changes induce shifts in local and regional land surface phenologies (LSPs). Any significant shift in LSP may correspond to a significant shift in evapotranspiration, with consequences for regional hydrometeorology. We explored possible future scenarios involving land use and climate change in six steps. First, we defined the nominal draw areas of current and future biorefineries in North Dakota, South Dakota, Nebraska, Minnesota, and Iowa and masked those land cover types within the draw areas that were unlikely to change to agricultural use (open water, settlements, forests, etc.). Second, we estimated the proportion of corn and soybean remaining within the masked draw areas using MODIS-derived crop maps. Third, in each draw area, we modified LSPs to simulate crop changes for a control and two treatment scenarios. In the control, we used LSP profiles identified from MODIS Collection 5 NBAR data. In one treatment, we increased the proportion of tallgrass LSPs in the draw areas to represent widespread cultivation of a perennial cellulosic crop, like switchgrass. In a second treatment, we increased the proportion of corn LSPs in the draw areas to represent increased corn cultivation. Fourth, we characterized the seasonal progression of the thermal regime associated with the LSP profiles using MODIS Land Surface Temperature (LST) products. Fifth, we modeled the LSP profile as a quadratic function of accumulated

  4. Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment

    DEFF Research Database (Denmark)

    Guzinski, R.; Nieto, H.; Stisen, S.

    2015-01-01

    Evapotranspiration (ET) is the main link between the natural water cycle and the land surface energy budget. Therefore water-balance and energy-balance approaches are two of the main methodologies for modelling this process. The water-balance approach is usually implemented as a complex....... The temporal patterns produced by the remote sensing and hydrological models are quite highly correlated (r ≈ 0.8). This indicates potential benefits to the hydrological modelling community of integrating spatial information derived through remote sensing methodology (contained in the ET maps...

  5. Remote sensing estimates of impervious surfaces for hydrological modelling of changes in flood risk during high-intensity rainfall events

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    This paper addresses the accuracy and applicability of medium resolution (MR) remote sensing estimates of impervious surfaces (IS) for urban land cover change analysis. Landsat-based vegetation indices (VI) are found to provide fairly accurate measurements of sub-pixel imperviousness for urban...... areas at different geographical locations within Europe, and to be applicable for cities with diverse morphologies and dissimilar climatic and vegetative conditions. Detailed data on urban land cover changes can be used to examine the diverse environmental impacts of past and present urbanisation...

  6. Tools and Services for Working with Multiple Land Remote Sensing Data Products

    Science.gov (United States)

    Krehbiel, C.; Friesz, A.; Harriman, L.; Quenzer, R.; Impecoven, K.; Maiersperger, T.

    2016-12-01

    The availability of increasingly large and diverse satellite remote sensing datasets provides both an opportunity and a challenge across broad Earth science research communities. On one hand, the extensive assortment of available data offer unprecedented opportunities to improve our understanding of Earth science and enable data use across a multitude of science disciplines. On the other hand, increasingly complex formats, data structures, and metadata can be an obstacle to data use for the broad user community that is interested in incorporating remote sensing Earth science data into their research. NASA's Land Processes Distributed Active Archive Center (LP DAAC) provides easy to use Python notebook tutorials for services such as accessing land remote sensing data from the LP DAAC Data Pool and interpreting data quality information from MODIS. We use examples to demonstrate the capabilities of the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), such as spatially and spectrally subsetting data, decoding valuable quality information, and exploring initial analysis results within the user interface. We also show data recipes for R and Python scripts that help users process ASTER L1T and ASTER Global Emissivity Datasets.

  7. Improving Frozen Precipitation Density Estimation in Land Surface Modeling

    Science.gov (United States)

    Sparrow, K.; Fall, G. M.

    2017-12-01

    The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

  8. Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

    Directory of Open Access Journals (Sweden)

    Z. Q. Peng

    2016-11-01

    Full Text Available Evapotranspiration (ET plays an important role in surface–atmosphere interactions and can be monitored using remote sensing data. However, surface heterogeneity, including the inhomogeneity of landscapes and surface variables, significantly affects the accuracy of ET estimated from satellite data. The objective of this study is to assess and reduce the uncertainties resulting from surface heterogeneity in remotely sensed ET using Chinese HJ-1B satellite data, which is of 30 m spatial resolution in VIS/NIR bands and 300 m spatial resolution in the thermal-infrared (TIR band. A temperature-sharpening and flux aggregation scheme (TSFA was developed to obtain accurate heat fluxes from the HJ-1B satellite data. The IPUS (input parameter upscaling and TRFA (temperature resampling and flux aggregation methods were used to compare with the TSFA in this study. The three methods represent three typical schemes used to handle mixed pixels from the simplest to the most complex. IPUS handles all surface variables at coarse resolution of 300 m in this study, TSFA handles them at 30 m resolution, and TRFA handles them at 30 and 300 m resolution, which depends on the actual spatial resolution. Analyzing and comparing the three methods can help us to get a better understanding of spatial-scale errors in remote sensing of surface heat fluxes. In situ data collected during HiWATER-MUSOEXE (Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces of the Heihe Watershed Allied Telemetry Experimental Research were used to validate and analyze the methods. ET estimated by TSFA exhibited the best agreement with in situ observations, and the footprint validation results showed that the R2, MBE, and RMSE values of the sensible heat flux (H were 0.61, 0.90, and 50.99 W m−2, respectively, and those for the latent heat flux (LE were 0.82, −20.54, and 71.24 W m−2, respectively. IPUS yielded the largest errors

  9. Estimation of Surface Soil Moisture from Thermal Infrared Remote Sensing Using an Improved Trapezoid Method

    Directory of Open Access Journals (Sweden)

    Yuting Yang

    2015-06-01

    Full Text Available Surface soil moisture (SM plays a fundamental role in energy and water partitioning in the soil–plant–atmosphere continuum. A reliable and operational algorithm is much needed to retrieve regional surface SM at high spatial and temporal resolutions. Here, we provide an operational framework of estimating surface SM at fine spatial resolutions (using visible/thermal infrared images and concurrent meteorological data based on a trapezoidal space defined by remotely sensed vegetation cover (Fc and land surface temperature (LST. Theoretical solutions of the wet and dry edges were derived to achieve a more accurate and effective determination of the Fc/LST space. Subjectivity and uncertainty arising from visual examination of extreme boundaries can consequently be largely reduced. In addition, theoretical derivation of the extreme boundaries allows a per-pixel determination of the VI/LST space such that the assumption of uniform atmospheric forcing over the entire domain is no longer required. The developed approach was tested at the Tibetan Plateau Soil Moisture/Temperature Monitoring Network (SMTMN site in central Tibet, China, from August 2010 to August 2011 using Moderate Resolution Imaging Spectroradiometer (MODIS Terra images. Results indicate that the developed trapezoid model reproduced the spatial and temporal patterns of observed surface SM reasonably well, with showing a root-mean-square error of 0.06 m3·m−3 at the site level and 0.03 m3·m−3 at the regional scale. In addition, a case study on 2 September 2010 highlighted the importance of the theoretically calculated wet and dry edges, as they can effectively obviate subjectivity and uncertainties in determining the Fc/LST space arising from visual interpretation of satellite images. Compared with Land Surface Models (LSMs in Global Land Data Assimilation System-1, the remote sensing-based trapezoid approach gave generally better surface SM estimates, whereas the LSMs showed

  10. Measuring the Surface Temperature of the Cryosphere using Remote Sensing

    Science.gov (United States)

    Hall, Dorothy K.

    2012-01-01

    A general description of the remote sensing of cryosphere surface temperatures from satellites will be provided. This will give historical information on surface-temperature measurements from space. There will also be a detailed description of measuring the surface temperature of the Greenland Ice Sheet using Moderate-Resolution Imaging Spectroradiometer (MODIS) data which will be the focus of the presentation. Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate data record, trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the MODIS IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now freely available to download at 6.25-km spatial resolution on a polar stereographic grid. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends of the duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. The consistency of this IST record, with temperature and melt records from other sources will be discussed.

  11. The role of GIS and remote sensing in land degradation assessment and conservation mapping: some user experiences and expectations

    NARCIS (Netherlands)

    Lynden, van G.W.J.; Mantel, S.

    2001-01-01

    Planning strategies for sustainable land management require solid base line data on natural resources (soils, physiography, climate, vegetation, land use, etc.) and on socio-economic aspects. GIS and remote sensing have an important role in linkage and analysis of such data, in particular for

  12. A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

    NARCIS (Netherlands)

    Joshi, Neha; Baumann, Matthias; Ehammer, Andrea; Reiche, Johannes

    2016-01-01

    The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral

  13. Modeling land-surface/atmosphere dynamics for CHAMMP

    International Nuclear Information System (INIS)

    Gutowski, W.J. Jr.

    1993-01-01

    Project progress is described on a DOE CHAMP project to model the land-surface/atmosphere coupling in a heterogeneous environment. This work is a collaboration between scientists at Iowa State University and the University of New Hampshire. Work has proceeded in two areas: baseline model coupling and data base development for model validation. The core model elements (land model, atmosphere model) have been ported to the Principal Investigator's computing system and baseline coupling has commenced. The initial target data base is the set of observations from the FIFE field campaign, which is in the process of being acquired. For the remainder of the project period, additional data from the region surrounding the FIFE site and from other field campaigns will be acquired to determine how to best extrapolate results from the initial target region to the rest of the globe. In addition, variants of the coupled model will be used to perform experiments examining resolution requirements and coupling strategies for land-atmosphere coupling in a heterogeneous environment

  14. Scale issues in remote sensing

    CERN Document Server

    Weng, Qihao

    2014-01-01

    This book provides up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. The book is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as a supplemental reading for graduate level students.

  15. Land use and surface process domains on alpine hillslopes

    Science.gov (United States)

    Kuhn, Nikolaus J.; Caviezel, Chatrina; Hunziker, Matthias

    2015-04-01

    Shrubs and trees are generally considered to protect hillslopes from erosion. As a consequence, shrub encroachment on mountain pastures after abandoning grazing is not considered a threat to soils. However, the abandonment of mown or grazed grasslands causes a shift in vegetation composition and thus a change in landscape ecology and geomorphology. On many alpine slopes, current changes in land use and vegetation cover are accompanied by climate change, potentially generating a new geomorphic regime. Most of the debate focuses on the effect of land abandonment on water erosion rates. Generally, an established perennial vegetation cover improves the mechanical anchoring of the soil and the regulation of the soil water budget, including runoff generation and erosion. However, changing vegetation composition affects many other above- and below-ground properties like root density, -diversity and -geometry, soil structure, pore volume and acidity. Each combination of these properties can lead to a distinct scenario of dominating surface processes, often not reflected by common erosion risk assessment procedures. The study of soil properties along a chronosequence of green alder (alnusviridis) encroachment on the Unteralptal in central Switzerland reveals that shrub encroachment changes soil and vegetation properties towards an increase of resistance to run-off related erosion processes, but a decrease of slope stability against shallow landslides. The latter are a particular threat because of the currently increasing frequency of slide-triggering high magnitude rainfalls. The potential change of process domain on alpine pastures highlights the need for a careful use of erosion models when assessing future land use and climate scenarios. In mountains, but also other intensively managed agricultural landscapes, risk assessment without the appropriate reflection on the shifting relevance of surface processes carries the risk of missing future threats to environmental

  16. Downscaling Coarse Actual ET Data Using Land Surface Resistance

    Science.gov (United States)

    Shen, T.

    2017-12-01

    This study proposed a new approach of downscaling ETWATCH 1km actual evapotranspiration (ET) product to a spatial resolution of 30m using land surface resistance that simulated mainly from monthly Landsat8 data and Jarvis method, which combined the benefits of both high temporal resolution of ETWATCH product and fine spatial resolution of Landsat8. The driving factor, surface resistance (Rs), was chosen for the reason that could reflect the transfer ability of vapor flow over canopy. Combined resistance Rs both upon canopy conditions, atmospheric factors and available water content of soil, which remains stable inside one ETWATCH pixel (1km). In this research, we used ETWATCH 1km ten-day actual ET product from April to October in a total of twenty-one images and monthly 30 meters cloud-free NDVI of 2013 (two images from HJ as a substitute due to cloud contamination) combined meteorological indicators for downscaling. A good agreement and correlation were obtained between the downscaled data and three flux sites observation in the middle reach of Heihe basin. The downscaling results show good consistency with the original ETWATCH 1km data both temporal and spatial scale over different land cover types with R2 ranged from 0.8 to 0.98. Besides, downscaled result captured the progression of vegetation transpiration well. This study proved the practicability of new downscaling method in the water resource management.

  17. Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

    Directory of Open Access Journals (Sweden)

    Jianwu Yan

    2013-01-01

    Full Text Available Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS. Our findings are summarized as follows. (i Spatiotemporal variation patterns of sensible heat flux (H and evapotranspiration (ET under the land cover scenarios (A2a or B2a and climate change scenario (A1B are unanimous. (ii Both H and ET take on a single peak pattern, and the peak occurs in June or July. (iii Based on the regional interannual variability analysis, H displays a downward trend (10% and ET presents an increasing trend (15%. (iv The annual average H and ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

  18. Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS).

    Science.gov (United States)

    Zhang, Yuanzhi; Chen, Zhengyi; Zhu, Boqin; Luo, Xiuyue; Guan, Yanning; Guo, Shan; Nie, Yueping

    2008-12-01

    The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.

  19. A Multisensor Approach to Global Retrievals of Land Surface Albedo

    Directory of Open Access Journals (Sweden)

    Aku Riihelä

    2018-05-01

    Full Text Available Satellite-based retrievals offer the most cost-effective way to comprehensively map the surface albedo of the Earth, a key variable for understanding the dynamics of radiative energy interactions in the atmosphere-surface system. Surface albedo retrievals have commonly been designed separately for each different spaceborne optical imager. Here, we introduce a novel type of processing framework that combines the data from two polar-orbiting optical imager families, the Advanced Very High-Resolution Radiometer (AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS. The goal of the paper is to demonstrate that multisensor albedo retrievals can provide a significant reduction in the sampling time required for a robust and comprehensive surface albedo retrieval, without a major degradation in retrieval accuracy, as compared to state-of-the-art single-sensor retrievals. We evaluated the multisensor retrievals against reference in situ albedo measurements and compare them with existing datasets. The results show that global land surface albedo retrievals with a sampling period of 10 days can offer near-complete spatial coverage, with a retrieval bias mostly comparable to existing single sensor datasets, except for bright surfaces (deserts and snow where the retrieval framework shows degraded performance because of atmospheric correction design compromises. A level difference is found between the single sensor datasets and the demonstrator developed here, pointing towards a need for further work in the atmospheric correction, particularly over bright surfaces, and inter-sensor radiance homogenization. The introduced framework is expandable to include other sensors in the future.

  20. Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

    Directory of Open Access Journals (Sweden)

    O. Orhan

    2016-06-01

    Full Text Available The main purpose of this paper is to investigate multi-temporal land surface temperature (LST and Normalized Difference Vegetation Index (NDVI changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST, Normalized Difference Vegetation Index (NDVI maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

  1. 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.

  2. Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

    Science.gov (United States)

    Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

    2017-12-01

    Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

  3. Albedo and land surface temperature shift in hydrocarbon seepage potential area, case study in Miri Sarawak Malaysia

    Science.gov (United States)

    Suherman, A.; Rahman, M. Z. A.; Busu, I.

    2014-02-01

    The presence of hydrocarbon seepage is generally associated with rock or mineral alteration product exposures, and changes of soil properties which manifest with bare development and stress vegetation. This alters the surface thermodynamic properties, changes the energy balance related to the surface reflection, absorption and emission, and leads to shift in albedo and LST. Those phenomena may provide a guide for seepage detection which can be recognized inexpensively by remote sensing method. District of Miri is used for study area. Available topographic maps of Miri and LANDSAT ETM+ were used for boundary construction and determination albedo and LST. Three land use classification methods, namely fixed, supervised and NDVI base classifications were employed for this study. By the intensive land use classification and corresponding statistical comparison was found a clearly shift on albedo and land surface temperature between internal and external seepage potential area. The shift shows a regular pattern related to vegetation density or NDVI value. In the low vegetation density or low NDVI value, albedo of internal area turned to lower value than external area. Conversely in the high vegetation density or high NDVI value, albedo of internal area turned to higher value than external area. Land surface temperature of internal seepage potential was generally shifted to higher value than external area in all of land use classes. In dense vegetation area tend to shift the temperature more than poor vegetation area.

  4. Albedo and land surface temperature shift in hydrocarbon seepage potential area, case study in Miri Sarawak Malaysia

    International Nuclear Information System (INIS)

    Suherman, A; Rahman, M Z A; Busu, I

    2014-01-01

    The presence of hydrocarbon seepage is generally associated with rock or mineral alteration product exposures, and changes of soil properties which manifest with bare development and stress vegetation. This alters the surface thermodynamic properties, changes the energy balance related to the surface reflection, absorption and emission, and leads to shift in albedo and LST. Those phenomena may provide a guide for seepage detection which can be recognized inexpensively by remote sensing method. District of Miri is used for study area. Available topographic maps of Miri and LANDSAT ETM+ were used for boundary construction and determination albedo and LST. Three land use classification methods, namely fixed, supervised and NDVI base classifications were employed for this study. By the intensive land use classification and corresponding statistical comparison was found a clearly shift on albedo and land surface temperature between internal and external seepage potential area. The shift shows a regular pattern related to vegetation density or NDVI value. In the low vegetation density or low NDVI value, albedo of internal area turned to lower value than external area. Conversely in the high vegetation density or high NDVI value, albedo of internal area turned to higher value than external area. Land surface temperature of internal seepage potential was generally shifted to higher value than external area in all of land use classes. In dense vegetation area tend to shift the temperature more than poor vegetation area

  5. Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

    Science.gov (United States)

    Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

    2010-01-01

    Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

  6. Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

    Directory of Open Access Journals (Sweden)

    Claire E. Bulgin

    2018-04-01

    Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

  7. The Effect Of Land Cover/Land Use On Groundwater Resources In Southern Egypt (Luxor Area): Remote Sensing And Field Studies

    International Nuclear Information System (INIS)

    Faid, A.M.; Hinz, E.A.; Montgomery, H.

    2003-01-01

    The impact of land cover/land use on groundwater can be critical. Land cover / land use maps give an early warning for planners and developers to protect groundwater resources from depletion and preserve its sustain ability. These land cover / land use maps can be used for the planning of groundwater development to prevent the deterioration of the aquifer. The Research Institute for Groundwater of Egypt (RIGW) has carried out hydrogeological studies in 1990 to evaluate the potentiality of groundwater in Luxor area in southern Egypt close to the Nile valley. The region is characterized by a rapid and continuous increase in land reclamation and development on the fringes which surround the already heavily cultivated land within the Nile valley. This presented a need for continuous monitoring and information updating over a vast region in a short time and at a reasonable cost. This study illustrates how remote sensing techniques can be effectively used for monitoring changes in land cover / land use in an effort to aid groundwater management. Landsat Thematic Mapper (TM) data collected in 1984 and 2000 were processed and analyzed over the study area to produce land cover/land use maps. The Normalized Difference Vegetation Index (NDVI) technique is used for Landsat TM images of to quantify areas which are covered by vegetation. Results indicated significant increase in cultivated areas. Remote sensing results are compared with iso-piezo metric maps and iso-salinity maps that were produced in 1984 and 2000. Comparison of these maps indicates groundwater depletion and salinity increase from 1984 to 2000. We relate this to the increase of the area being cultivated

  8. Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

    Science.gov (United States)

    Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

    1999-01-01

    This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

  9. Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

    Science.gov (United States)

    Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

    2017-09-15

    Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

    Science.gov (United States)

    Hogan, Christine A.

    1996-01-01

    A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

  11. Integrating remotely sensed surface water extent into continental scale hydrology.

    Science.gov (United States)

    Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

    2016-12-01

    In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R 2 , RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that

  12. Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5

    Directory of Open Access Journals (Sweden)

    D. Wang

    2017-07-01

    Full Text Available Land surface models bear substantial biases in simulating surface water and energy budgets despite the continuous development and improvement of model parameterizations. To reduce model biases, Parr et al. (2015 proposed a method incorporating satellite-based evapotranspiration (ET products into land surface models. Here we apply this bias correction method to the Community Land Model version 4.5 (CLM4.5 and test its performance over the conterminous US (CONUS. We first calibrate a relationship between the observational ET from the Global Land Evaporation Amsterdam Model (GLEAM product and the model ET from CLM4.5, and assume that this relationship holds beyond the calibration period. During the validation or application period, a simulation using the default CLM4.5 (CLM is conducted first, and its output is combined with the calibrated observational-vs.-model ET relationship to derive a corrected ET; an experiment (CLMET is then conducted in which the model-generated ET is overwritten with the corrected ET. Using the observations of ET, runoff, and soil moisture content as benchmarks, we demonstrate that CLMET greatly improves the hydrological simulations over most of the CONUS, and the improvement is stronger in the eastern CONUS than the western CONUS and is strongest over the Southeast CONUS. For any specific region, the degree of the improvement depends on whether the relationship between observational and model ET remains time-invariant (a fundamental hypothesis of the Parr et al. (2015 method and whether water is the limiting factor in places where ET is underestimated. While the bias correction method improves hydrological estimates without improving the physical parameterization of land surface models, results from this study do provide guidance for physically based model development effort.

  13. Black Sea impact on its west-coast land surface temperature

    Science.gov (United States)

    Cheval, Sorin; Constantin, Sorin

    2018-03-01

    This study investigates the Black Sea influence on the thermal characteristics of its western hinterland based on satellite imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). The marine impact on the land surface temperature (LST) values is detected at daily, seasonal and annual time scales, and a strong linkage with the land cover is demonstrated. The remote sensing products used within the study supply LST data with complete areal coverage during clear sky conditions at 1-km spatial resolution, which is appropriate for climate studies. The sea influence is significant up to 4-5 km, by daytime, while the nighttime influence is very strong in the first 1-2 km, and it gradually decreases westward. Excepting the winter, the daytime temperature increases towards the plateau with the distance from the sea, e.g. with a gradient of 0.9 °C/km in the first 5 km in spring or with 0.7 °C/km in summer. By nighttime, the sea water usually remains warmer than the contiguous land triggering higher LST values in the immediate proximity of the coastline in all seasons, e.g. mean summer LST is 19.0 °C for the 1-km buffer, 16.6 °C for the 5-km buffer and 16.0 °C for the 10-km buffer. The results confirm a strong relationship between the land cover and thermal regime in the western hinterland of the Black Sea coast. The satellite-derived LST and air temperature values recorded at the meteorological stations are highly correlated for similar locations, but the marine influence propagates differently, pledging for distinct analysis. Identified anomalies in the general observed trends are investigated in correlation with sea surface temperature dynamics in the coastal area.

  14. An Overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)

    Science.gov (United States)

    Sellers, P. J.; Hall, F. G.; Asrar, G.; Strebel, D. E.; Murphy, R. E.

    1992-11-01

    In the summer of 1983 a group of scientists working in the fields of meteorology, biology, and remote sensing met to discuss methods for modeling and observing land-surface—atmosphere interactions on regional and global scales. They concluded, first, that the existing climate models contained poor representations of the processes controlling the exchanges of energy, water, heat, and carbon between the land surface and the atmosphere and, second, that satellite remote sensing had been underutilized as a means of specifying global fields of the governing biophysical parameters. Accordingly, a multiscale, multidisciplinary experiment, FIFE, was initiated to address these two issues. The objectives of FIFE were specified as follows: (1) Upscale integration of models: The experiment was designed to test the soil-plant-atmosphere models developed by biometeorologists for small-scale applications (millimeters to meters) and to develop methods to apply them at the larger scales (kilometers) appropriate to atmospheric models and satellite remote sensing. (2) Application of satellite remote sensing: Even if the first goal were achieved to yield a "perfect" model of vegetation-atmosphere exchanges, it would have very limited applications without a global observing system for initialization and validation. As a result, the experiment was tasked with exploring methods for using satellite data to quantify important biophysical states and rates for model input. The experiment was centered on a 15 × 15 km grassland site near Manhattan, Kansas. This area became the focus for an extended monitoring program of satellite, meteorological, biophysical, and hydrological data acquisition from early 1987 through October 1989 and a series of 12- to 20-day intensive field campaigns (IFCs), four in 1987 and one in 1989. During the IFCs the fluxes of heat, moisture, carbon dioxide, and radiation were measured with surface and airborne equipment in coordination with measurements of surface

  15. Rural Land Use Change during 1986-2002 in Lijiang, China, Based on Remote Sensing and GIS Data.

    Science.gov (United States)

    Peng, Jian; Wu, Jiansheng; Yin, He; Li, Zhengguo; Chang, Qing; Mu, Tianlong

    2008-12-11

    As a local environmental issue with global importance, land use/land cover change (LUCC) has always been one of the key issues in geography and environmental studies with the expansion of regional case studies. While most of LUCC studies in China have focused on urban land use change, meanwhile, compared with the rapid change of urban land use in the coastal areas of eastern China, slow but distinct rural land use changes have also occurred in the mountainous areas of western China since the late 1980s. In this case through a study in Lijiang County of Yunnan Province, with the application of remote sensing data and geographic information system techniques, the process of rural land use change in mountain areas of western China was monitored through extensive statistical analysis of detailed regional data. The results showed significant increases in construction land, paddy field and dry land, and a decrease in dense forest land and waste grassland between 1986 and 2002. The conversions between dense forest land and sparse forest land, grassland, waste grassland and dry land were the primary processes of rural land use change. Sparse forest land had the highest rate of land use change, with glacier or snow-capped land the lowest; while human settlement and rural economic development were found to be the main driving forces of regional difference in the integrated land use change rate among the 24 towns of Lijiang County. Quantified through landscape metrics, spatial patterns of rural land use change were represented as an increase in landscape diversity and landscape fragmentation, and the regularization of patch shapes, suggesting the intensification of human disturbances and degradation of ecological quality in the rural landscape.

  16. Uncertainty in Land Cover observations and its impact on near surface climate

    Science.gov (United States)

    Georgievski, Goran; Hagemann, Stefan

    2017-04-01

    Land Cover (LC) and its bio-geo-physical feedbacks are important for the understanding of climate and its vulnerability to changes on the surface of the Earth. Recently ESA has published a new LC map derived by combining remotely sensed surface reflectance and ground-truth observations. For each grid-box at 300m resolution, an estimate of confidence is provided. This LC data set can be used in climate modelling to derive land surface boundary parameters for the respective Land Surface Model (LSM). However, the ESA LC classes are not directly suitable for LSMs, therefore they need to be converted into the model specific surface presentations. Due to different design and processes implemented in various climate models they might differ in the treatment of artificial, water bodies, ice, bare or vegetated surfaces. Nevertheless, usually vegetation distribution in models is presented by means of plant functional types (PFT), which is a classification system used to simplify vegetation representation and group different vegetation types according to their biophysical characteristics. The method of LC conversion into PFT is also called "cross-walking" (CW) procedure. The CW procedure is another source of uncertainty, since it depends on model design and processes implemented and resolved by LSMs. These two sources of uncertainty, (i) due to surface reflectance conversion into LC classes, (ii) due to CW procedure, have been studied by Hartley et al (2016) to investigate their impact on LSM state variables (albedo, evapotranspiration (ET) and primary productivity) by using three standalone LSMs. The present study is a follow up to that work and aims at quantifying the impact of these two uncertainties on climate simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) using prescribed sea surface temperature and sea ice. The main focus is on the terrestrial water cycle, but the impacts on surface albedo, wind patterns, 2m temperatures

  17. Urban percent impervious surface and its relationship with land surface temperature in Yantai City, China

    International Nuclear Information System (INIS)

    Yu, Xinyang; Lu, Changhe

    2014-01-01

    This study investigated percent impervious surface area (PISA) extracted by a four-endmember normalized spectral mixture analysis (NSMA) method and evaluated the reliability of PISA as an indicator of land surface temperature (LST). Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images for Yantai city, eastern China obtained from USGS were used as the main data source. The results demonstrated that four-endmember NSMA method performed better than the typical three-endmember one, and there was a strong linear relationship between LST and PISA for the two images, which suggest percent impervious surface area provides an alternative parameter for analyzing LST quantitatively in urban areas

  18. Landcover Change, Land Surface Temperature, Surface Albedo and Topography in the Plateau Region of North-Central Nigeria

    Directory of Open Access Journals (Sweden)

    Shakirudeen Odunuga

    2015-04-01

    Full Text Available This study assessed the change in some environmental parameters in the Plateau region of North-Central Nigeria (Barakinladi, Jos, and Kafachan environs using the nexus of landcover change, land surface temperature, surface albedo, and topography. The study employed both remote sensing and statistical techniques for the period between 1986 and 2014 to analyze the dynamics between and within these environmental variables. In Barakinladi, the built up landcover change is highest (increasing from 39.53% to 47.59% between 1986 and 2014; LST ranges from 19.09 °C to 38.59 °C in 1986 and from 22.68 °C and 41.68 °C in 2014; and the albedo ranges between 0.014 and 0.154 in 1986 and 0.017 and 0.248 in 2014. In Jos, the built-up landcover occupied 34.26% in 1986 and 36.67% in 2014; LST values range between 20.83 °C and 41.33 °C in 1986 and between 21.61 °C and 42.64 °C in 2014; and the albedo ranges between 0.003 and 0.211 in 1986 and 0.15 and 0.237 in 2014. In Kafachan area, the built up landcover occupied 32.95% in 1986 and 39.01% in 2014. Urbanization and agricultural activities, including animal grazing, were responsible for the gradual loss in vegetation and increasing average LST and albedo. The results also revealed that changing landcover and topography have a relationship with surface albedo and land surface temperature, thereby impacting significantly on ecosystem services delivered by the natural system.

  19. A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

    Science.gov (United States)

    Caradonna, Grazia; Novelli, Antonio; Tarantino, Eufemia; Cefalo, Raffaela; Fratino, Umberto

    2016-06-01

    Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

  20. Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

    Science.gov (United States)

    Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

    2017-12-01

    The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks

  1. Online Global Land Surface Temperature Estimation from Landsat

    Directory of Open Access Journals (Sweden)

    David Parastatidis

    2017-11-01

    Full Text Available This study explores the estimation of land surface temperature (LST for the globe from Landsat 5, 7 and 8 thermal infrared sensors, using different surface emissivity sources. A single channel algorithm is used for consistency among the estimated LST products, whereas the option of using emissivity from different sources provides flexibility for the algorithm’s implementation to any area of interest. The Google Earth Engine (GEE, an advanced earth science data and analysis platform, allows the estimation of LST products for the globe, covering the time period from 1984 to present. To evaluate the method, the estimated LST products were compared against two reference datasets: (a LST products derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, as higher-level products based on the temperature-emissivity separation approach; (b Landsat LST data that have been independently produced, using different approaches. An overall RMSE (root mean square error of 1.52 °C was observed and it was confirmed that the accuracy of the LST product is dependent on the emissivity; different emissivity sources provided different LST accuracies, depending on the surface cover. The LST products, for the full Landsat 5, 7 and 8 archives, are estimated “on-the-fly” and are available on-line via a web application.

  2. 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.

  3. Developing first time-series of land surface temperature from AATSR with uncertainty estimates

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2013-04-01

    . The uncertainty analysis takes into account the expected performance of the retrieval algorithm under varying surface and atmospheric conditions. We characterise the uncertainties in terms of: radiometric noise; fractional vegetation cover as representative of surface emissivity; atmospheric water vapour; and uncertainties as a result of the coefficient fitting process. The total uncertainty budget is a combination of these four components added together in quadrature. The uncertainty due to misclassification of cloudy pixels is difficult to propagate to LST uncertainty bars and has yet to be evaluated in the framework of the current study. The progress made here will allow other time series of LST to be compared with the record from AATSR with greater certainty and hence increases confidence in our knowledge of recent surface temperature changes over the land. References Ghent, D., Corlett, G., and Remedios, J. Advancing the AATSR land surface temperature retrieval with higher resolution auxiliary datasets, in prep. Kogler, C., Pinnock, S., Arino, O., Casadio, S., Corlett, G., Prata, F., and Bras, T. Note on the quality of the (A)ATSR land surface temperature record from 1991 to 2009, International Journal of Remote Sensing, 33, 4178-4192, 2012

  4. Effect of a combined inversion and plantarflexion surface on ankle kinematics and EMG activities in landing

    Directory of Open Access Journals (Sweden)

    Divya Bhaskaran

    2015-12-01

    Conclusion: These findings suggest that compared to the inversion surface, the combined plantarflexion and inversion surface seems to provide a more unstable surface condition for lateral ankle sprains during landing.

  5. Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

    Science.gov (United States)

    Yu, Q.; Li, J.; Tian, Y. Q.

    2017-12-01

    Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

  6. Improving Land Surface Temperature Retrievals over Mountainous Regions

    Directory of Open Access Journals (Sweden)

    Virgílio A. Bento

    2017-01-01

    Full Text Available Algorithms for Land Surface Temperature (LST retrieval from infrared measurements are usually sensitive to the amount of water vapor present in the atmosphere. The Satellite Application Facilities on Climate Monitoring and Land Surface Analysis (CM SAF and LSA SAF are currently compiling a 25 year LST Climate data record (CDR, which uses water vapor information from ERA-Int reanalysis. However, its relatively coarse spatial resolution may lead to systematic errors in the humidity profiles with implications in LST, particularly over mountainous areas. The present study compares LST estimated with three different retrieval algorithms: a radiative transfer-based physical mono-window (PMW, a statistical mono-window (SMW, and a generalized split-windows (GSW. The algorithms were tested over the Alpine region using ERA-Int reanalysis data and relied on the finer spatial scale Consortium for Small-Scale Modelling (COSMO model data as a reference. Two methods were developed to correct ERA-Int water vapor misestimation: (1 an exponential parametrization of total precipitable water (TPW appropriate for SMW/GSW; and (2 a level reduction method to be used in PMW. When ERA-Int TPW was used, the algorithm missed the right TPW class in 87% of the cases. When the exponential parametrization was used, the missing class rate decreased to 9%, and when the level reduction method was applied, the LST corrections went up to 1.7 K over the study region. Overall, the correction for pixel orography in TPW leads to corrections in LST estimations, which are relevant to ensure that long-term LST records meet climate requirements, particularly over mountainous regions.

  7. Extending Participatory Sensing to Personal Exposure Using Microscopic Land Use Regression Models

    Directory of Open Access Journals (Sweden)

    Luc Dekoninck

    2017-05-01

    Full Text Available Personal exposure is sensitive to the personal features and behavior of the individual, and including interpersonal variability will improve the health and quality of life evaluations. Participatory sensing assesses the spatial and temporal variability of environmental indicators and is used to quantify this interpersonal variability. Transferring the participatory sensing information to a specific study population is a basic requirement for epidemiological studies in the near future. We propose a methodology to reduce the void between participatory sensing and health research. Instantaneous microscopic land-use regression modeling (µLUR is an innovative approach. Data science techniques extract the activity-specific and route-sensitive spatiotemporal variability from the data. A data workflow to prepare and apply µLUR models to any mobile population is presented. The µLUR technique and data workflow are illustrated with models for exposure to traffic related Black Carbon. The example µLURs are available for three micro-environments; bicycle, in-vehicle, and indoor. Instantaneous noise assessments supply instantaneous traffic information to the µLURs. The activity specific models are combined into an instantaneous personal exposure model for Black Carbon. An independent external validation reached a correlation of 0.65. The µLURs can be applied to simulated behavioral patterns of individuals in epidemiological cohorts for advanced health and policy research.

  8. Remote Sensing Mars Landing Sites: An Out-of-School Time Planetary Science Education Activity for Middle School Students

    Science.gov (United States)

    Anderson, R. B.; Gaither, T. A.; Edgar, L. A.; Milazzo, M. P.; Vaughan, R. G.; Rubino-Hare, L.; Clark, J.; Ryan, S.

    2017-12-01

    As part of the Planetary Learning that Advances the Nexus of Engineering, Technology, and Science (PLANETS) project, we have developed an out-of-school time unit for middle school students focused on planetary remote sensing. The activity is divided into two exercises, with the goal of choosing a scientifically interesting and safe landing site for a future Mars mission. Students are introduced to NASA data from several actual and proposed landing sites and must use what they learn about remote sensing to choose a site that satisfies scientific and engineering criteria. The activity also includes background information for educators, including a summary of how landing on Mars helps answer major scientific questions, brief overviews of the data sets that the students will use, summaries of the site geology, and a list of relevant vocabulary. The first exercise introduces students to the concept of reflectance spectroscopy and how it can be used to identify the "fingerprints" of different minerals on the surface of Mars. Students are provided with simplified maps of mineral spectra at the four sites, based on Compact Reconnaissance Imaging Spectrometer (CRISM) observations, as well as a reference sheet with the spectra of common minerals on Mars. They can use this information to determine which sites have hydrated minerals, mafic minerals, or both. The second exercise adds data from the Mars Orbital Laser Altimeter (MOLA), and high resolution visible data from the Context Camera (CTX) on the Mars Reconnaissance Orbiter. Students learn about laser altimetry and how to interpret topographic contours to assess whether a landing site is too rough. The CTX data allow students to study the sites at higher resolution, with annotations that indicate key landforms of interest. These data, along with the spectroscopy data, allow students to rank the sites based on science and engineering criteria. This activity was developed as a collaboration between subject matter experts at

  9. Noctis Landing: A Proposed Landing Site/Exploration Zone for Human Missions to the Surface of Mars

    Science.gov (United States)

    Lee, Pascal; Acedillo, Shannen; Braham, Stephen; Brown, Adrian; Elphic, Richard; Fong, Terry; Glass, Brian; Hoftun, Christopher; Johansen, Brage W.; Lorber, Kira; hide

    2015-01-01

    identified in CRISM data in many locations in this area. Noctis Landing is the lowest-altitude location on Mars that straddles both the Tharsis region (above average geothermal gradients) and Valles Marineris (minimal crustal thickness from surface (valley floor) to a subsurface liquid water table. Noctis Landing has the potential for being an ideal site for eventual deep drilling on Mars to access deep subsurface liquid water and potentially encountering extant life. Available data remains insufficient to fully qualify the Noctis Landing site. Additional remote sensing data (visible, Near and Mid-IR, and radar) and surface reconnaissance via a high-mobility robotic rover are recommended. In particular, it will be important to assess the trafficability of the site, and its potential for yielding water and metals as a resource. Access to plateau tops from the Noctis Landing site on the canyon floor should be demonstrated. Future exploration of the site would also be enhanced significantly by the availability of robotic (tele-operatable) surveying and sample-collecting drones. Testing of the use of such collaborative science and exploration technologies should be conducted at terrestrial sites such as the Haughton-Mars Project site on Devon Island, High Arctic, among others. Note: Noctis Landing is not an official Mars nomenclature name for this location. Because the area of the proposed LS/EZ had no name, and because it is close to Noctis Labyrinthus to the West while being distinct from it, the provisional name Noctis Landing is proposed. Noctis means night in Latin.

  10. A New Fusion Technique of Remote Sensing Images for Land Use/Cover

    Institute of Scientific and Technical Information of China (English)

    WU Lian-Xi; SUN Bo; ZHOU Sheng-Lu; HUANG Shu-E; ZHAO Qi-Guo

    2004-01-01

    In China,accelerating industrialization and urbanization following high-speed economic development and population increases have greatly impacted land use/cover changes,making it imperative to obtain accurate and up to date information on changes so as to evaluate their environmental effects. The major purpose of this study was to develop a new method to fuse lower spatial resolution multispectral satellite images with higher spatial resolution panchromatic ones to assist in land use/cover mapping. An algorithm of a new fusion method known as edge enhancement intensity modulation (EEIM) was proposed to merge two optical image data sets of different spectral ranges. The results showed that the EEIM image was quite similar in color to lower resolution multispectral images,and the fused product was better able to preserve spectral information. Thus,compared to conventional approaches,the spectral distortion of the fused images was markedly reduced. Therefore,the EEIM fusion method could be utilized to fuse remote sensing data from the same or different sensors,including TM images and SPOT5 panchromatic images,providing high quality land use/cover images.

  11. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing

    Directory of Open Access Journals (Sweden)

    Chudong Huang

    2015-07-01

    Full Text Available The coupling relationship between urban vegetation and land surface temperature (LST has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI, urban vegetation abundance (UVA and urban forest abundance (UFA are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

  12. Land Use Transformation Rule Analysis in Beijing-Tianjin-Tangshan Region Using Remote Sensing and GIS Technology

    Directory of Open Access Journals (Sweden)

    Shang-min Zhao

    2016-01-01

    Full Text Available Based on land use classification system, this paper acquires the land use distribution status at 2000, 2005, and 2010 in Beijing-Tianjin-Tangshan Region using remote sensing images, field survey data, images in Google Earth, and visual interpretation methods. Then, the land use transformation rules from 2000 to 2010 are achieved using GIS (geographic information system technology. The research results shows the following: (1 as to the distribution area of the land use types, dry field has the largest area, followed by forest land, building land, paddy field, water area, grassland, and unused land; (2 from 2000 to 2010, the area of building land has the largest increase, which is mainly transformed from cropland and sea reclamation area; the largest decreased land use type is paddy field, which mainly transforms to dry field and building land; (3 the high increase of building land and decrease of cropland suggest the land use transformation in the quick development process of economy; meanwhile, the total area of forestland and grassland changes little, so the ecological environment does not have apparent deterioration in the 1st decade of the new century.

  13. Monitoring land- and water-use dynamics in the Columbia Plateau using remote-sensing computer analysis and integration techniques

    International Nuclear Information System (INIS)

    Wukelic, G.E.; Foote, H.P.; Blair, S.C.; Begej, C.D.

    1981-09-01

    This study successfully utilized advanced, remote-sensing computer-analysis techniques to quantify and map land- and water-use trends potentially relevant to siting, developing, and operating a national high-level nuclear waste repository on the US Department of Energy's (DOE) Hanford Site in eastern Washington State. Specifically, using a variety of digital data bases (primarily multidate Landsat data) and digital analysis programs, the study produced unique numerical data and integrated data reference maps relevant to regional (Columbia Plateau) and localized (Pasco Basin) hydrologic considerations associated with developing such a facility. Accordingly, study results should directly contribute to the preparation of the Basalt Waste Isolation Project site-characterization report currently in progress. Moreover, since all study data developed are in digital form, they can be called upon to contribute to furute reference repository location monitoring and reporting efforts, as well as be utilized in other DOE programmatic areas having technical and/or environmental interest in the Columbia Plateau region. The results obtained indicate that multidate digital Landsat data provide an inexpensive, up-to-date, and accurate data base and reference map of natural and cultural features existing in any region. These data can be (1) computer enhanced to highlight selected surface features of interest; (2) processed/analyzed to provide regional land-cover/use information and trend data; and (3) combined with other line and point data files to accomodate interactive, correlative analyses and integrated color-graphic displays to aid interpretation and modeling efforts

  14. SPATIAL AND TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE IN FUJIAN PROVINCE FROM 2001 TO 2015

    Directory of Open Access Journals (Sweden)

    Y. Li

    2018-04-01

    Full Text Available Land surface temperature (LST is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1 the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2 The annual mean temperature of LST declines slightly among 15 years in Fujian. 3 Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.

  15. Spatial and Temporal Variation of Land Surface Temperature in Fujian Province from 2001 TO 2015

    Science.gov (United States)

    Li, Y.; Wang, X.; Ding, Z.

    2018-04-01

    Land surface temperature (LST) is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G) filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1) the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2) The annual mean temperature of LST declines slightly among 15 years in Fujian. 3) Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.

  16. GEOEPIDERM – AN ECOLOGICAL CONCEPT THAT INTEGRATES SOIL COVER WITH ASSOCIATED LAND SURFACE COMPONENTS

    Directory of Open Access Journals (Sweden)

    I. Munteanu

    2008-10-01

    Full Text Available Based on the new concept of the “Epiderm of the Earth” introduced by the 2006 edition of the WRB-SR, the idea of “geoepiderm” has been developed. Besides its holistic meaning, by including both soil and non-soil materials found in the first 2 meters of the land surface, the term “geoepiderm” has a strong ecological sense, by suggesting similarity with the skin of the living organisms, as such, this concept is fully concordant with that of “Gaia” (Living Earth developed by James Lovelock. According to the main pedo-ecological characteristics of the soil and not soil coverings from the earth surface, ten kinds (classes of ‘geoepiderms” have been identified:1 – Protoderma (Entiderma– the primitive (emerging geoepiderm (mainly non-soil materials; five main subtypes: a Regoderma, b Leptoderma, c Areniderma, d Fluviderma and e Gleyoderma, were identified;2 – Cryoderma (Geliderma – geoepiderm of cold, mainly artic and subartic, regions with mean annual soil temperature <00C (often with perennial frozen subsoil - permafrost:3 – Arididerma – geoepiderm of arid regions and salt affected lands with limited or scarce available moisture; two subtypes: a Desertiderma, b Saliderma4 – Inceptiderma (or Juvenilederma – with 2 subtypes: a Cambiderma – a young (incipiently developed geoepiderm and b Andiderma, geoepiderm developed in volcanic materials;5 – Euderma – nutrient rich geoepiderm with two main subtypes: a Cherniderma (or Molliderma and b Luviderma (or Alfiderma;6 – Oligoderma – geoepiderm with low macro-nutrient and weatherable minerals content with 2 subtypes: a Podziderma (or Spodiderma and b Acriderma (or Ultiderma;7 – Ferriderma (Oxiderma or Senilederma – geoepiderm strongly weathered and with iron and aluminium hydroxides enrichment and low weatherable minerals reserve;8 – Vertiderma (Contractilederma – Contractile geoepiderm, developed from swelling clays;9 – Histoderma (Organiderma

  17. Autonomous target recognition using remotely sensed surface vibration measurements

    Science.gov (United States)

    Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

    1993-09-01

    The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

  18. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  19. NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  20. Dealing with missing data in remote sensing images within land and crop classification

    Science.gov (United States)

    Skakun, Sergii; Kussul, Nataliia; Basarab, Ruslan

    Optical remote sensing images from space provide valuable data for environmental monitoring, disaster management [1], agriculture mapping [2], so forth. In many cases, a time-series of satellite images is used to discriminate or estimate particular land parameters. One of the factors that influence the efficiency of satellite imagery is the presence of clouds. This leads to the occurrence of missing data that need to be addressed. Numerous approaches have been proposed to fill in missing data (or gaps) and can be categorized into inpainting-based, multispectral-based, and multitemporal-based. In [3], ancillary MODIS data are utilized for filling gaps and predicting Landsat data. In this paper we propose to use self-organizing Kohonen maps (SOMs) for missing data restoration in time-series of satellite imagery. Such approach was previously used for MODIS data [4], but applying this approach for finer spatial resolution data such as Sentinel-2 and Landsat-8 represents a challenge. Moreover, data for training the SOMs are selected manually in [4] that complicates the use of the method in an automatic mode. SOM is a type of artificial neural network that is trained using unsupervised learning to produce a discretised representation of the input space of the training samples, called a map. The map seeks to preserve the topological properties of the input space. The reconstruction of satellite images is performed for each spectral band separately, i.e. a separate SOM is trained for each spectral band. Pixels that have no missing values in the time-series are selected for training. Selecting the number of training pixels represent a trade-off, in particular increasing the number of training samples will lead to the increased time of SOM training while increasing the quality of restoration. Also, training data sets should be selected automatically. As such, we propose to select training samples on a regular grid of pixels. Therefore, the SOM seeks to project a large number

  1. Water Balance in the Amazon Basin from a Land Surface Model Ensemble

    Science.gov (United States)

    Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo; hide

    2014-01-01

    Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

  2. LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

    Science.gov (United States)

    See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

    2016-04-01

    The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

  3. Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

    Science.gov (United States)

    Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

    2017-12-01

    Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the

  4. Impact of Optimized Land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

    Science.gov (United States)

    Kumar, S.; Santanello, J. A.; Peters-Lidard, C. D.; Harrison, K.

    2011-12-01

    Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature 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) 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 module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spinup of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

  5. Human Mars Landing Site and Impacts on Mars Surface Operations

    Science.gov (United States)

    Hoffman, Stephen J.; Bussey, Ben

    2016-01-01

    This paper describes NASA's initial steps for identifying and evaluating candidate Exploration Zones (EZs) and Regions of Interests (ROIs) for the first human crews that will explore the surface of Mars. NASA's current effort to define the exploration of this planet by human crews, known as the Evolvable Mars Campaign (EMC), provides the context in which these EZs and ROIs are being considered. The EMC spans all aspects of a human Mars mission including launch from Earth, transit to and from Mars, and operations on the surface of Mars. An EZ is a collection of ROIs located within approximately 100 kilometers of a centralized landing site. ROIs are areas relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. The EZ also contains one or more landing sites and a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. With the EMC as a conceptual basis, the EZ model has been refined to a point where specific site selection criteria for scientific exploration and in situ resource utilization can be defined. In 2015 these criteria were distributed to the planetary sciences community and the in situ resource utilization and civil engineering communities as part of a call for EZ proposals. The resulting "First Landing Site/Exploration Zone Workshop for Human Missions to the Surface of Mars" was held in October 2015 during which 47 proposals for EZs and ROIs were presented and discussed. Proposed locations spanned all longitudes and all allowable latitudes (+/- 50 degrees). Proposed justification for selecting one of these EZs also spanned a significant portion of the scientific and resource criteria provided to the community. Several important findings resulted from this Workshop including: (a) a strong consensus that, at a scale of 100 km (radius), multiple places on Mars exist that have both sufficient scientific interest

  6. Shallow to Deep Convection Transition over a Heterogeneous Land Surface Using the Land Model Coupled Large-Eddy Simulation

    Science.gov (United States)

    Lee, J.; Zhang, Y.; Klein, S. A.

    2017-12-01

    The triggering of the land breeze, and hence the development of deep convection over heterogeneous land should be understood as a consequence of the complex processes involving various factors from land surface and atmosphere simultaneously. That is a sub-grid scale process that many large-scale models have difficulty incorporating it into the parameterization scheme partly due to lack of our understanding. Thus, it is imperative that we approach the problem using a high-resolution modeling framework. In this study, we use SAM-SLM (Lee and Khairoutdinov, 2015), a large-eddy simulation model coupled to a land model, to explore the cloud effect such as cold pool, the cloud shading and the soil moisture memory on the land breeze structure and the further development of cloud and precipitation over a heterogeneous land surface. The atmospheric large scale forcing and the initial sounding are taken from the new composite case study of the fair-weather, non-precipitating shallow cumuli at ARM SGP (Zhang et al., 2017). We model the land surface as a chess board pattern with alternating leaf area index (LAI). The patch contrast of the LAI is adjusted to encompass the weak to strong heterogeneity amplitude. The surface sensible- and latent heat fluxes are computed according to the given LAI representing the differential surface heating over a heterogeneous land surface. Separate from the surface forcing imposed from the originally modeled surface, the cases that transition into the moist convection can induce another layer of the surface heterogeneity from the 1) radiation shading by clouds, 2) adjusted soil moisture pattern by the rain, 3) spreading cold pool. First, we assess and quantifies the individual cloud effect on the land breeze and the moist convection under the weak wind to simplify the feedback processes. And then, the same set of experiments is repeated under sheared background wind with low level jet, a typical summer time wind pattern at ARM SGP site, to

  7. Bridging Epidemiology and Remote Sensing: A Case Study of Dengue Fever and Land Use and Land Cover Change in Roatán, Honduras

    Science.gov (United States)

    Tuholske, C.; Brooks, T.

    2015-12-01

    Dengue fever is one of the fastest spreading infectious diseases in Latin America and the Caribbean. As part of a yearlong epidemiological study of dengue, this paper takes the first step to model the relationship between the urban/built environment and incidents of dengue fever in Roatán, Honduras. Roatán has experienced an 80-fold increase in annual tourists since the 1990s, with over 1.2 million people now visiting the island yearly. In tandem, the Caribbean island's population has exploded from fewer than 13,000 people in the 1970s to over 100,000 people today. Using broadband remote sensed satellite imagery, this paper maps and measures how this massive influx of tourists and population has altered the island's landscape. Results from a decision tree classifying technique applied to a Landsat 5 Thematic Mapper (TM) image from 1985 and Landsat 8 Operational Land Imager (OLI) image from 2014 suggest a rapid pace of urbanization; built and impervious surface has increased over 300% in the last 30 years. Emerging research suggests, similar to other mosquito-borne diseases, a correlation between built environment and risk to dengue because of the increase in stagnate water that serve as disease-host reservoirs. This remote sensing analysis will be integrated with georeferenced household level data of cases of dengue collected during a year-long cross-sectional study of dengue patients in Roatán. The result will be to model the relationship between dengue fever and urban/built environment.

  8. Land surface temperature retrieval from MODIS and VIRR data in northwest China

    International Nuclear Information System (INIS)

    Wang, L J; Zuo, H C; Ren, P C; Qiang, B

    2014-01-01

    By using the Gulang Heterogeneous Underlying Surface Layer Experiment (GHUSLE) data, the accuracy of land surface temperature (LST) in Northwest China retrieved by the Moderate-Resolution Imaging Spectroradiometer(MODIS) and Visible and InfraRed Radiometer(VIRR) data is verified. Furthermore, a new LST algorithm for heterogeneous underlying surface is developed and the LST retrieved by the two remote sensing data using three algorithms are compared with the observed data. Results suggest that the new algorithm is the best one in the case of heterogeneous underlying surface, Kerr algorithm accuracy is not satisfying and Becker algorithm is ranked just ahead Kerr algorithm. Especially, the differences in retrieval accuracy among them are more obvious when using the VIRR data. Compared with the observed LST, the root mean square errors of the LST retrieved by MODIS and VIRR data are the least when using the new algorithm, the specific values are 2.55 K and 3.78 K, respectively. The LST retrieved by MODIS data are closer to observed values and higher than its counterpart retrieved by VIRR data. When the new LST retrieval algorithm used, the LST retrieved by MODIS and VIRR data are the closest

  9. Near-field Oblique Remote Sensing of Stream Water-surface Elevation, Slope, and Surface Velocity

    Science.gov (United States)

    Minear, J. T.; Kinzel, P. J.; Nelson, J. M.; McDonald, R.; Wright, S. A.

    2014-12-01

    A major challenge for estimating discharges during flood events or in steep channels is the difficulty and hazard inherent in obtaining in-stream measurements. One possible solution is to use near-field remote sensing to obtain simultaneous water-surface elevations, slope, and surface velocities. In this test case, we utilized Terrestrial Laser Scanning (TLS) to remotely measure water-surface elevations and slope in combination with surface velocities estimated from particle image velocimetry (PIV) obtained by video-camera and/or infrared camera. We tested this method at several sites in New Mexico and Colorado using independent validation data consisting of in-channel measurements from survey-grade GPS and Acoustic Doppler Current Profiler (ADCP) instruments. Preliminary results indicate that for relatively turbid or steep streams, TLS collects tens of thousands of water-surface elevations and slopes in minutes, much faster than conventional means and at relatively high precision, at least as good as continuous survey-grade GPS measurements. Estimated surface velocities from this technique are within 15% of measured velocity magnitudes and within 10 degrees from the measured velocity direction (using extrapolation from the shallowest bin of the ADCP measurements). Accurately aligning the PIV results into Cartesian coordinates appears to be one of the main sources of error, primarily due to the sensitivity at these shallow oblique look angles and the low numbers of stationary objects for rectification. Combining remotely-sensed water-surface elevations, slope, and surface velocities produces simultaneous velocity measurements from a large number of locations in the channel and is more spatially extensive than traditional velocity measurements. These factors make this technique useful for improving estimates of flow measurements during flood flows and in steep channels while also decreasing the difficulty and hazard associated with making measurements in these

  10. Mapping the global depth to bedrock for land surface modelling

    Science.gov (United States)

    Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

    2017-12-01

    Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

  11. Representing Reservoir Stratification in Land Surface and Earth System Models

    Science.gov (United States)

    Yigzaw, W.; Li, H. Y.; Leung, L. R.; Hejazi, M. I.; Voisin, N.; Payn, R. A.; Demissie, Y.

    2017-12-01

    A one-dimensional reservoir stratification modeling has been developed as part of Model for Scale Adaptive River Transport (MOSART), which is the river transport model used in the Accelerated Climate Modeling for Energy (ACME) and Community Earth System Model (CESM). Reservoirs play an important role in modulating the dynamic water, energy and biogeochemical cycles in the riverine system through nutrient sequestration and stratification. However, most earth system models include lake models that assume a simplified geometry featuring a constant depth and a constant surface area. As reservoir geometry has important effects on thermal stratification, we developed a new algorithm for deriving generic, stratified area-elevation-storage relationships that are applicable at regional and global scales using data from Global Reservoir and Dam database (GRanD). This new reservoir geometry dataset is then used to support the development of a reservoir stratification module within MOSART. The mixing of layers (energy and mass) in the reservoir is driven by eddy diffusion, vertical advection, and reservoir inflow and outflow. Upstream inflow into a reservoir is treated as an additional source/sink of energy, while downstream outflow represented a sink. Hourly atmospheric forcing from North American Land Assimilation System (NLDAS) Phase II and simulated daily runoff by ACME land component are used as inputs for the model over the contiguous United States for simulations between 2001-2010. The model is validated using selected observed temperature profile data in a number of reservoirs that are subject to various levels of regulation. The reservoir stratification module completes the representation of riverine mass and heat transfer in earth system models, which is a major step towards quantitative understanding of human influences on the terrestrial hydrological, ecological and biogeochemical cycles.

  12. Analyzing Land Use Changes in the Metropolitan Jilin City of Northeastern China Using Remote Sensing and GIS.

    Science.gov (United States)

    Hu, Dan; Yang, Guodong; Wu, Qiong; Li, Hongqing; Liu, Xusheng; Niu, Xuefeng; Wang, Zhiheng; Wang, Qiong

    2008-09-03

    Remote sensing and GIS have been widely employed to study temporal and spatial urban land use changes in southern and southeastern China. However, few studies have been conducted in northeastern regions. This study analyzed land use change and spatial patterns of urban expansion in the metropolitan area of Jilin City, located on the extension of Changbai Mountain, based on aerial photos from 1989 and 2005 Spot images. The results indicated that urban land and transportation land increased dramatically (by 94.04% and 211.20%, respectively); isolated industrial and mining land decreased moderately (by 29.54%); rural residential land increased moderately (by 26.48%); dry land and paddy fields increased slightly (by 15.68% and 11.78%, respectively); forest and orchards decreased slightly (by 5.27% and 4.61%, respectively); grasslands and unused land decreased dramatically (by 99.12% and 86.04%, respectively). Sloped dry land (more than 4 degrees) was mainly distributed on the land below 10 degrees with an east, southeastern and south sunny direction aspect, and most sloped dry land transformed to forest was located on an east aspect lower than 12 degrees, while forest changed to dry land were mainly distributed on east and south aspects lower than 10 degrees. A spatial dependency analysis of land use change showed that the increased urban land was a logarithmic function of distance to the Songhua River. This study also provided some data with spatial details about the uneven land development in the upstream areas of Songhua River basin.

  13. Analyzing Land Use Changes in the Metropolitan Jilin City of Northeastern China Using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    Qiong Wang

    2008-09-01

    Full Text Available Remote sensing and GIS have been widely employed to study temporal and spatial urban land use changes in southern and southeastern China. However, few studies have been conducted in northeastern regions. This study analyzed land use change and spatial patterns of urban expansion in the metropolitan area of Jilin City, located on the extension of Changbai Mountain, based on aerial photos from 1989 and 2005 Spot images. The results indicated that urban land and transportation land increased dramatically (by 94.04% and 211.20%, respectively; isolated industrial and mining land decreased moderately (by 29.54%; rural residential land increased moderately (by 26.48%; dry land and paddy fields increased slightly (by 15.68% and 11.78%, respectively; forest and orchards decreased slightly (by 5.27% and 4.61%, respectively; grasslands and unused land decreased dramatically (by 99.12% and 86.04%, respectively. Sloped dry land (more than 4 degrees was mainly distributed on the land below 10 degrees with an east, southeastern and south sunny direction aspect, and most sloped dry land transformed to forest was located on an east aspect lower than 12 degrees, while forest changed to dry land were mainly distributed on east and south aspects lower than 10 degrees. A spatial dependency analysis of land use change showed that the increased urban land was a logarithmic function of distance to the Songhua River. This study also provided some data with spatial details about the uneven land development in the upstream areas of Songhua River basin.

  14. Application of SMAP Data for Ocean Surface Remote Sensing

    Science.gov (United States)

    Fore, A.; Yueh, S. H.; Tang, W.; Stiles, B. W.; Hayashi, A.

    2017-12-01

    The Soil Moisture Active Passive (SMAP) mission was launched January 31st, 2015. It is designed to measure the soil moisture over land using a combined active / passive L-band system. Due to the Aquarius mission, L-band model functions for ocean winds and salinity are mature and are directly applicable to the SMAP mission. In contrast to Aquarius, the higher resolution and scanning geometry of SMAP allow for wide-swath ocean winds and salinities to be retrieved. In this talk we present the SMAP Sea Surface Salinity (SSS) and extreme winds dataset and its performance. First we discuss the heritage of SMAP SSS algorithms, showing that SMAP and Aquarius show excellent agreement in the ocean surface roughness correction. Then, we give an overview of some newly developed algorithms that are only relevant to the SMAP system; a new galaxy correction and land correction enabling SSS retrievals up to 40 km from coast. We discuss recent improvements to the SMAP data processing for version 4.0. Next we compare the performance of the SMAP SSS to in-situ salinity measurements obtained from ARGO floats, tropical moored buoys, and ship-based data. SMAP SSS has accuracy of 0.2 PSU on a monthly basis compared to ARGO gridded data in tropics and mid-latitudes. In tropical oceans, time series comparison of salinity measured at 1 m depth by moored buoys indicates SMAP can track large salinity changes within a month. Synergetic analysis of SMAP, SMOS, and Argo data allows us to identify and exclude erroneous buoy data from assessment of SMAP SSS. The resulting SMAP-buoy matchup analysis gives a mean standard deviation (STD) of 0.22 PSU and correlation of 0.73 on weekly scale; at monthly scale the mean STD decreased to 0.17 PSU and the correlation increased to 0.8. In addition to SSS, SMAP provides a view into tropical cyclones having much higher sensitivity than traditional scatterometers. We validate the high-winds using collocations with SFMR during tropical cyclones as well as

  15. Sensing and control for autonomous vehicles applications to land, water and air vehicles

    CERN Document Server

    Pettersen, Kristin; Nijmeijer, Henk

    2017-01-01

    This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light intervention work, underwater survey and collection of oceanographic/biological data. Autonomous unmanned aerial systems can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and a minimum of intelligence. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles. Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data, for assimilation of climate and environmental models and to complement global satellite sy...

  16. Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

    Science.gov (United States)

    Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

    2017-12-01

    Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and

  17. A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

    Science.gov (United States)

    Li, Jing; Xie, Weixin; Pei, Jihong

    2018-03-01

    Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

  18. Modelling land surface fluxes of CO2 in response to climate change and nitrogen deposition

    DEFF Research Database (Denmark)

    Hansen, Kristina; Ambelas Skjøth, Carsten; Geels, Camilla

    Climate change, land use variations, and impacts of atmospheric nitrogen (N) deposition represent uncertainties for the prediction of future greenhouse gas exchange between land surfaces and the atmosphere as the mechanisms describing nutritional effects are not well developed in climate...... climate feedback mechanisms of CO2 between changes in management, land use practise, and climate change....

  19. Optical Feather and Foil for Shape and Dynamic Load Sensing of Critical Flight Surfaces, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Future flight vehicles may comprise complex flight surfaces requiring coordinated in-situ sensing and actuation. Inspired by the complexity of the flight surfaces on...

  20. Wireless Metal Detection and Surface Coverage Sensing for All-Surface Induction Heating

    Directory of Open Access Journals (Sweden)

    Veli Tayfun Kilic

    2016-03-01

    Full Text Available All-surface induction heating systems, typically comprising small-area coils, face a major challenge in detecting the presence of a metallic vessel and identifying its partial surface coverage over the coils to determine which of the coils to power up. The difficulty arises due to the fact that the user can heat vessels made of a wide variety of metals (and their alloys. To address this problem, we propose and demonstrate a new wireless detection methodology that allows for detecting the presence of metallic vessels together with uniquely sensing their surface coverages while also identifying their effective material type in all-surface induction heating systems. The proposed method is based on telemetrically measuring simultaneously inductance and resistance of the induction coil coupled with the vessel in the heating system. Here, variations in the inductance and resistance values for an all-surface heating coil loaded by vessels (made of stainless steel and aluminum at different positions were systematically investigated at different frequencies. Results show that, independent of the metal material type, unique identification of the surface coverage is possible at all freqeuncies. Additionally, using the magnitude and phase information extracted from the coupled coil impedance, unique identification of the vessel effective material is also achievable, this time independent of its surface coverage.

  1. An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

    Science.gov (United States)

    Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

    2015-12-01

    Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

  2. Regional Geological Mapping in the Graham Land of Antarctic Peninsula Using LANDSAT-8 Remote Sensing Data

    Science.gov (United States)

    Pour, A. B.; Hashim, M.; Park, Y.

    2017-10-01

    Geological investigations in Antarctica confront many difficulties due to its remoteness and extreme environmental conditions. In this study, the applications of Landsat-8 data were investigated to extract geological information for lithological and alteration mineral mapping in poorly exposed lithologies in inaccessible domains such in Antarctica. The north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. Continuum Removal (CR) spectral mapping tool and Independent Components Analysis (ICA) were applied to Landsat-8 spectral bands to map poorly exposed lithologies at regional scale. Pixels composed of distinctive absorption features of alteration mineral assemblages associated with poorly exposed lithological units were detected by applying CR mapping tool to VNIR and SWIR bands of Landsat-8.Pixels related to Si-O bond emission minima features were identified using CR mapping tool to TIR bands in poorly mapped andunmapped zones in north-eastern Graham Land at regional scale. Anomaly pixels in the ICA image maps related to spectral featuresof Al-O-H, Fe, Mg-O-H and CO3 groups and well-constrained lithological attributions from felsic to mafic rocks were detectedusing VNIR, SWIR and TIR datasets of Landsat-8. The approach used in this study performed very well for lithological andalteration mineral mapping with little available geological data or without prior information of the study region.

  3. Impacts of a Changing Climate and Land Use on Reindeer Pastoralism: Indigenous Knowledge and Remote Sensing

    Science.gov (United States)

    Maynard, N. G.; Oskal, A.; Turi, A.; Mathiesen, J. M.; Eira, S. D.; Yurchak, I. M. G.; Etylin, B.; Gebelein, J.

    2009-01-01

    The Arctic is home to many indigenous peoples, including those who depend on reindeer herding for their livelihood, in one of the harshest environments in the world. For the largely nomadic peoples, reindeer not only form a substantial part of the Arctic food base and economy, but they are also culturally important, shaping their way of life, mythologies, festivals and ceremonies. Reindeer pastoralism or husbandry has been practiced by numerous peoples all across Eurasia for thousands of years and involves moving herds of reindeer, which are very docile animals, from pasture to pasture depending on the season. Thus, herders must adapt on a daily basis to find optimal conditions for their herds according to the constantly changing conditions. Climate change and variability plus rapid development are increasingly creating major changes in the physical environment, ecology, and cultures of these indigenous reindeer herder communities in the North, and climate changes are occurring significantly faster in the Arctic than the rest of the globe, with correspondingly dramatic impacts (Oskal, 2008). In response to these changes, Eurasian reindeer herders have created the EALAT project, a comprehensive new initiative to study these impacts and to develop local adaptation strategies based upon their traditional knowledge of the land and its uses - in targeted partnership with the science and remote sensing community - involving extensive collaborations and coproduction of knowledge to minimize the impacts of the various changes. This chapter provides background on climate and development challenges to reindeer husbandry across the Arctic and an overview of the EALAT initiative, with an emphasis on indigenous knowledge, remote sensing, Geographic Information Systems (GIS), and other scientific data to 'co-produce' datasets for use by herders for improved decision-making and herd management. It also provides a description of the EALAT monitoring data integration and sharing

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

    Science.gov (United States)

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

    2018-04-01

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

  5. Infiltration of surface mined land reclaimed by deep tillage treatments

    International Nuclear Information System (INIS)

    Chong, S.K.; Cowsert, P.

    1994-01-01

    Surface mining of coal leads to the drastic disturbance of soils. Compaction of replaced subsoil and topsoil resulting from hauling, grading, and leveling procedures produces a poor rooting medium for crop growth. Soil compaction results in high bulk density, low macroporosity, poor water infiltration capacity, and reduced elongation of plant roots. In the United States, Public Law 95-87 mandates that the rooting medium of mined soils have specific textural characteristics and be graded and shaped to a topography similar to premining conditions. Also, crop productivity levels equivalent to those prior to mining must be achieved, especially for prime farmland. Alleviation of compaction has been the major focus of reclamation, and recently new techniques to augment the rooting zone with deep-ripping and loosening equipment have come to the forefront. Several surface mine operators in the Illinois coal basin are using deep tillage equipment that is capable of loosening soils to greater depths than is possible with conventional farm tillage equipment. Information on the beneficial effects of these loosening procedures on soil hydrological properties, such as infiltration, runoff potential, erosion, and water retention, is extremely important for future mined land management. However, such information is lacking. In view of the current yield demonstration regulation for prime farmland and other unmined soils, it is important that as much information as possible be obtained concerning the effect of deep tillage on soil hydrologic properties. The objectives of this study are: (1) to compare infiltration rates and related soil physical properties of mined soils reclaimed by various deep tillage treatments and (2) to study the temporal variability of infiltration and related physical properties of the reclaimed mined soil after deep tillage treatment

  6. The use of desk studies, remote sensing and surface geological and geophysical techniques in site investigations

    International Nuclear Information System (INIS)

    Mather, J.D.

    1984-02-01

    The geoscientific investigations required to characterise a site for the underground disposal of radioactive wastes involve a wide range of techniques and expertise. Individual national investigations need to be planned with the specific geological environment and waste form in mind. However, in any investigation there should be a planned sequence of operations leading through desk studies and surface investigations to the more expensive and sophisticated sub-surface investigations involving borehole drilling and the construction of in situ test facilities. Desk studies are an important and largely underestimated component of site investigations. Most developed countries have archives of topographical, geological and environmental data within government agencies, universities, research institutes and learned societies. Industry is another valuable source but here confidentiality can be a problem. However, in developing countries and in some regions of developed countries the amount of basic data, which needs to be collected over many decades, will not be as extensive. In such regions remote sensing offers a rapid method of examining large areas regardless of land access, vegetation or geological setting, rapidly and at relatively low cost. It can also be used to examine features, such as discontinuity patterns, over relatively small areas in support of intensive ground investigations. Examples will be given of how remote sensing has materially contributed to site characterisation in a number of countries, particularly those such as Sweden, Canada and the United Kingdom where the major effort has concentrated on crystalline rocks. The main role of desk studies and surface investigations is to provide basic data for the planning and execution of more detailed subsurface investigations. However, such studies act as a valuable screening mechanism and if they are carried out correctly can enable adverse characteristics of a site to be identified at an early stage before

  7. Land surface cleanup of plutonium at the Nevada Test Site

    International Nuclear Information System (INIS)

    Ebeling, L.L.; Evans, R.B.; Walsh, E.J.

    1991-01-01

    The Nevada Test Site (NTS) covers approximately 3300 km 2 of high desert and is located approximately 100 km northwest of Las Vegas, Nevada. Soil contaminated by plutonium exists on the NTS and surrounding areas from safety tests conducted in the 1950s and 1960s. About 150 curies of contamination have been measured over 1200 hectares of land surface. Most contamination is found in the top 5 cm of soil but may be found deep as 25 cm. The cost of conventional removal and disposal of the full soil volume has been estimated at over $500,000,000. This study is directed toward minimizing the volume of waste which must be further processed and disposed of by precisely controlling soil removal depth. The following soil removal machines were demonstrated at the NTS: (1) a CMI Corporation Model PR-500FL pavement profiler, (2) a CMI Corporation Model Tr-225B trimmer reclaimer, (3) a Caterpillar Model 623 elevating scraper equipped with laser depth control, (4) a Caterpillar Model 14G motor grader equipped with laser depth control, (5) a Caterpillar Model 637 auger scraper, and (6) a XCR Series Guzzler vacuum truck. 5 refs., 5 figs

  8. 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.

  9. Reliable low precision simulations in land surface models

    Science.gov (United States)

    Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

    2017-12-01

    Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

  10. Enhancing Access to Land Remote Sensing Data through Mainstream Social Media Channels

    Science.gov (United States)

    Sohre, T.; Maiersperger, T.

    2011-12-01

    Social media tools are changing the way that people discover information, communicate, and collaborate. Government agencies supporting the Land Remote Sensing user community have begun taking advantage of standard social media tools and capabilities. National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) data centers have started providing outreach utilizing services including Facebook, Twitter, and YouTube videos. Really Simple Syndication (RSS) Feeds have become more standard means of sharing information, and a DataCasting tool was created as a NASA Technology Infusion effort to make RSS-based technology for accessing Earth Science information available. The United States Geological Survey (USGS) has also started using social media to allow the community access to news feeds and real-time earthquake alerts; listen to podcasts; get updates on new USGS publications, videos, and photographs; and more. Twitter feeds have been implemented in 2011 for the USGS Land Cover and Landsat user communities. In early 2011, the NASA Land Processes Distributed Active Archive Center (LP DAAC) user working group suggested the investigation of concepts for creating and distributing "bundles" of data, which would aggregate theme-based data sets from multiple sources. The LP DAAC is planning to explore the use of standard social bookmarking tools to support community developed bundles through the use of tools such as Delicious, Digg, or StumbleUpon. This concept would allow science users to organize and discover common links to data resources based on community developed tags, or a folksonomy. There are challenges that will need to be addressed such as maintaining the quality of tags but a social bookmarking system may have advantages over traditional search engines or formal ontologies for identifying and labeling various data sets relevant to a theme. As classification is done by the community of scientists who understand the data, the tagged data sets

  11. Recent trends (2003-2013) of land surface heat fluxes on the southern side of the central Himalayas, Nepal

    Science.gov (United States)

    Amatya, Pukar Man; Ma, Yaoming; Han, Cunbo; Wang, Binbin; Devkota, Lochan Prasad

    2015-12-01

    Novice efforts have been made in order to study the regional distribution of land surface heat fluxes on the southern side of the central Himalayas utilizing high-resolution remotely sensed products, but these have been on instantaneous scale. In this study the Surface Energy Balance System model is used to obtain annual averaged maps of the land surface heat fluxes for 11 years (2003-2013) and study their annual trends on the central Himalayan region. The maps were derived at 5 km resolution using monthly input products ranging from satellite derived to Global Land Data Assimilation System meteorological data. It was found that the net radiation flux is increasing as a result of decreasing precipitation (drier environment). The sensible heat flux did not change much except for the northwestern High Himalaya and High Mountains. In northwestern High Himalaya sensible heat flux is decreasing because of decrease in wind speed, ground-air temperature difference, and increase in winter precipitation, whereas in High Mountains it is increasing due to increase in ground-air temperature difference and high rate of deforestation. The latent heat flux has an overall increasing trend with increase more pronounced in the lower regions compared to high elevated regions. It has been reported that precipitation is decreasing with altitude in this region. Therefore, the increasing trend in latent heat flux can be attributed to increase in net radiation flux under persistent forest cover and irrigation land used for agriculture.

  12. Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

    Science.gov (United States)

    Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

    2017-12-01

    The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance

  13. High resolution remote sensing of water surface patterns

    Science.gov (United States)

    Woodget, A.; Visser, F.; Maddock, I.; Carbonneau, P.

    2012-12-01

    The assessment of in-stream habitat availability within fluvial environments in the UK traditionally includes the mapping of patterns which appear on the surface of the water, known as 'surface flow types' (SFTs). The UK's River Habitat Survey identifies ten key SFTs, including categories such as rippled flow, upwelling, broken standing waves and smooth flow. SFTs result from the interaction between the underlying channel morphology, water depth and velocity and reflect the local flow hydraulics. It has been shown that SFTs can be both biologically and hydraulically distinct. SFT mapping is usually conducted from the river banks where estimates of spatial coverage are made by eye. This approach is affected by user subjectivity and inaccuracies in the spatial extent of mapped units. Remote sensing and specifically the recent developments in unmanned aerial systems (UAS) may now offer an alternative approach for SFT mapping, with the capability for rapid and repeatable collection of very high resolution imagery from low altitudes, under bespoke flight conditions. This PhD research is aimed at investigating the mapping of SFTs using high resolution optical imagery (less than 10cm) collected from a helicopter-based UAS flown at low altitudes (less than 100m). This paper presents the initial findings from a series of structured experiments on the River Arrow, a small lowland river in Warwickshire, UK. These experiments investigate the potential for mapping SFTs from still and video imagery of different spatial resolutions collected at different flying altitudes and from different viewing angles (i.e. vertical and oblique). Imagery is processed using 3D mosaicking software to create orthophotos and digital elevation models (DEM). The types of image analysis which are tested include a simple, manual visual assessment undertaken in a GIS environment, based on the high resolution optical imagery. In addition, an object-based image analysis approach which makes use of the

  14. Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

    Science.gov (United States)

    Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

    2017-11-01

    Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

  15. AMSR-E/Aqua Monthly Global Microwave Land Surface Emissivity

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer - Earth Observing System...

  16. Determination of Temporal Change Land Use / Land Cover Using Remote Sensing and Geographic Information System Techniques the Central District of Samsun (1984-2011

    Directory of Open Access Journals (Sweden)

    Orhan DENGİZ

    2014-03-01

    Full Text Available In our day natural resources fall short against endless human needs and increasing population. It is required for lands which are the leading natural resources to be used and planned according to natural environment potential. This study was conducted in Central district of Samsun province covered about 341 km2 and located between the latitudes 41° 25‟ 52”- 41° 12‟ 22” to 41° 42‟ 34” to north and longitudes 36° 09‟ 52”-36° 24‟ 31” east. Determination of land use efficiency of district selected for this study using satellite image and GIS was aimed. For this purpose the data of General Directorate of Rural Services which belongs to 1984 year, ASTER satellite images which belongs to 2005 and 2011 years and topographic maps were used. For performing calculations in ENVI 5.0v software unclassified classification applied and four main classes were formed. For determining the unclassified classes as classified the field work applied. The result of the classification forest, pasture, farm lands and non agricultural areas were determined as land use-land covers. For determining land use efficiency analog data were digitized and transferred to GIS database. Land use types and land use capability classes of 1984 year converted raster data by using GIS. Land use types of 1993, land use types of 2005 and 2011 and land use capability classes were compared. As the result of the comparison urbanization and unintended use increased in I., II. and III. class lands. In 1984 agricultural land has 24313.76 ha while, this amount decreased to 10120.96 ha in 2005 and 6960.69 ha in 2011. On the other hand, while non-agricultural area was 1893.36 in 1984, this area increased to 6301.66 ha in 2005 and 7917.73 ha in 2011. In addition, this study showed that to determine and to monitory for large areas‟ land cover and land use trend, remote sensing and geographic information system techniques have important role to generate accoriance and fast

  17. 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.

  18. Estimating surface turbulent heat fluxes from land surface temperature and soil moisture using the particle batch smoother

    Science.gov (United States)

    Lu, Yang; Dong, Jianzhi; Steele-Dunne, Susan; van de Giesen, Nick

    2016-04-01

    This study is focused on estimating surface sensible and latent heat fluxes from land surface temperature (LST) time series and soil moisture observations. Surface turbulent heat fluxes interact with the overlying atmosphere and play a crucial role in meteorology, hydrology and other climate-related fields, but in-situ measurements are costly and difficult. It has been demonstrated that the time series of LST contains information of energy partitioning and that surface turbulent heat fluxes can be determined from assimilation of LST. These studies are mainly based on two assumptions: (1) a monthly value of bulk heat transfer coefficient under neutral conditions (CHN) which scales the sum of the fluxes, and (2) an evaporation fraction (EF) which stays constant during the near-peak hours of the day. Previous studies have applied variational and ensemble approaches to this problem. Here the newly developed particle batch smoother (PBS) algorithm is adopted to test its capability in this application. The PBS can be seen as an extension of the standard particle filter (PF) in which the states and parameters within a fix window are updated in a batch using all observations in the window. The aim of this study is two-fold. First, the PBS is used to assimilate only LST time series into the force-restore model to estimate fluxes. Second, a simple soil water transfer scheme is introduced to evaluate the benefit of assimilating soil moisture observations simultaneously. The experiments are implemented using the First ISLSCP (International Satellite Land Surface Climatology Project) (FIFE) data. It is shown that the restored LST time series using PBS agrees very well with observations, and that assimilating LST significantly improved the flux estimation at both daily and half-hourly time scales. When soil moisture is introduced to further constrain EF, the accuracy of estimated EF is greatly improved. Furthermore, the RMSEs of retrieved fluxes are effectively reduced at both

  19. Quantifying Surface Energy Flux Estimation Uncertainty Using Land Surface Temperature Observations

    Science.gov (United States)

    French, A. N.; Hunsaker, D.; Thorp, K.; Bronson, K. F.

    2015-12-01

    Remote sensing with thermal infrared is widely recognized as good way to estimate surface heat fluxes, map crop water use, and detect water-stressed vegetation. When combined with net radiation and soil heat flux data, observations of sensible heat fluxes derived from surface temperatures (LST) are indicative of instantaneous evapotranspiration (ET). There are, however, substantial reasons LST data may not provide the best way to estimate of ET. For example, it is well known that observations and models of LST, air temperature, or estimates of transport resistances may be so inaccurate that physically based model nevertheless yield non-meaningful results. Furthermore, using visible and near infrared remote sensing observations collected at the same time as LST often yield physically plausible results because they are constrained by less dynamic surface conditions such as green fractional cover. Although sensitivity studies exist that help identify likely sources of error and uncertainty, ET studies typically do not provide a way to assess the relative importance of modeling ET with and without LST inputs. To better quantify model benefits and degradations due to LST observational inaccuracies, a Bayesian uncertainty study was undertaken using data collected in remote sensing experiments at Maricopa, Arizona. Visible, near infrared and thermal infrared data were obtained from an airborne platform. The prior probability distribution of ET estimates were modeled using fractional cover, local weather data and a Penman-Monteith mode, while the likelihood of LST data was modeled from a two-source energy balance model. Thus the posterior probabilities of ET represented the value added by using LST data. Results from an ET study over cotton grown in 2014 and 2015 showed significantly reduced ET confidence intervals when LST data were incorporated.

  20. Exploiting Surface Albedos Products to Bridge the Gap Between Remote Sensing Information and Climate Models

    Science.gov (United States)

    Pinty, Bernard; Andredakis, Ioannis; Clerici, Marco; Kaminski, Thomas; Taberner, Malcolm; Stephen, Plummer

    2011-01-01

    We present results from the application of an inversion method conducted using MODIS derived broadband visible and near-infrared surface albedo products. This contribution is an extension of earlier efforts to optimally retrieve land surface fluxes and associated two- stream model parameters based on the Joint Research Centre Two-stream Inversion Package (JRC-TIP). The discussion focuses on products (based on the mean and one-sigma values of the Probability Distribution Functions (PDFs)) obtained during the summer and winter and highlight specific issues related to snowy conditions. This paper discusses the retrieved model parameters including the effective Leaf Area Index (LAI), the background brightness and the scattering efficiency of the vegetation elements. The spatial and seasonal changes exhibited by these parameters agree with common knowledge and underscore the richness of the high quality surface albedo data sets. At the same time, the opportunity to generate global maps of new products, such as the background albedo, underscores the advantages of using state of the art algorithmic approaches capable of fully exploiting accurate satellite remote sensing datasets. The detailed analyses of the retrieval uncertainties highlight the central role and contribution of the LAI, the main process parameter to interpret radiation transfer observations over vegetated surfaces. The posterior covariance matrix of the uncertainties is further exploited to quantify the knowledge gain from the ingestion of MODIS surface albedo products. The estimation of the radiation fluxes that are absorbed, transmitted and scattered by the vegetation layer and its background is achieved on the basis of the retrieved PDFs of the model parameters. The propagation of uncertainties from the observations to the model parameters is achieved via the Hessian of the cost function and yields a covariance matrix of posterior parameter uncertainties. This matrix is propagated to the radiation

  1. A synthesis of remote sensing and local knowledge approaches in land degradation assessment in the Bawku East District, Ghana

    Science.gov (United States)

    Yiran, G. A. B.; Kusimi, J. M.; Kufogbe, S. K.

    2012-02-01

    A greater percentage of Northern Ghana is under threat of land degradation and is negatively impacting on the well-being of the people owing to deforestation, increasing incidence of drought, indiscriminate bush burning and desertification. The problem is becoming severe with serious implications on the livelihoods of the people as the land is the major resource from which they eke their living. Reversing land degradation requires sustainable land use planning which should be based on detailed up-to-date information on landscape attributes. This information can be generated through remote sensing analytical studies. Therefore, an attempt has been made in this study to collect data for planning by employing remote sensing techniques and ground truthing. The analysis included satellite image classification and change detection between Landsat images captured in 1989, 1999 and 2006. The images were classified into the following classes: water bodies, close savannah woodland, open savannah woodland, grassland/unharvested farmland, exposed soil, burnt scars, and settlement. Change detection performed between the 1989 and 1999 and 1989 and 2006 showed that the environment is deteriorating. Land covers such as close savannah woodland, open savannah woodland and exposed soil diminished over the period whereas settlement and water bodies increased. The grassland/unharvested farmland showed high increases because the images were captured at the time that some farms were still crops or crop residue. Urbanization, land clearing for farming, over grazing, firewood fetching and bush burning were identified as some of the underlying forces of vegetal cover degradation. The socio-cultural beliefs and practices of the people also influenced land cover change as sacred groves as well as medicinal plants are preserved. Local knowledge is recognized and used in the area but it is not properly integrated with scientific knowledge for effective planning for sustainable land management

  2. Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

    Science.gov (United States)

    2015-09-21

    rain gauges to measure precipitation , and 1 internal mini-flume to measure runoff . 9 Fig. 8. Processed fluxes measured at the two eddy...SECURITY CLASSIFICATION OF: Arid and semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface...semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface conditions, including soil moisture

  3. Monitoring Multidecadal satellite earth observation of soil moisture products through land surface reanalysis

    NARCIS (Netherlands)

    Albergel, C.; Dorigo, W.; Balsamo, G.; Sabatar, J; de Rosnay, P.; Isaksen, I; Brocca, L; de Jeu, R.A.M.; Wagner, W.

    2013-01-01

    Soil moisture from ERA-Land, a revised version of the land surface components of the European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim), is used to monitor at a global scale the consistency of a new microwave based multi-satellite surface soil moisture date set

  4. A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

    Directory of Open Access Journals (Sweden)

    Neha Joshi

    2016-01-01

    Full Text Available The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

  5. Channel Storage change: a new remote sensed surface water measurement

    Science.gov (United States)

    Coss, S. P.; Durand, M. T.; Yi, Y.; Guo, Q.; Shum, C. K.; Allen, G. H.; Pavelsky, T.

    2017-12-01

    Here we present river channel storage change (CSC) measurements for 17 major world rivers from 2002-2016. We combined interpolated daily 1 km resolution Global River Radar Altimeter Time Series (GRRATS) river surface elevation data with static widths from the global river Global River Widths from Landsat (GRWL) dataset, to generate preliminary channel storage measurements. CSC is a previously unmeasured component of the terrestrial water balance It is a fundamental Earth science quantity with global bearing on floodplains, ecology, and geochemistry. CSC calculations require only remote sensed data, making them an ideal tool for studying remote regions where hydrological data is not easily accessible. CSC is uniquely suited to determine the role of hydrologic and hydraulic controls in basins with strong seasonal cycles (freeze-up and break-up). The cumulative CSC anomaly can impart spatial details that discharge measurements cannot. With this new measurement, we may be able to determine critical hydrological and hydraulic controls on rapidly changing systems like Arctic rivers. Results for Mississippi River indicate that peak CSC anomaly was the highest in 2011 (12.6 km3) and minimum CSC anomaly was in 2012 (-12.2 km3). Peak CSC has most frequently occurs in May (5 years), but has come as late in the year as July, and as early as January. Results for the Yukon River indicate that peak CSC anomaly was the highest in 2013 (13.9 km3) and minimum CSC anomaly was in 2010 (-14.2 km3). Peak CSC has most frequently come in early to mid-June (4-18), but has occurred in May (19-31) four years in the study period (three of the last 6 years) and once on April 30th.

  6. 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.

  7. Land surface cleanup of plutonium at the Nevada Test Site

    International Nuclear Information System (INIS)

    Ebeling, L.L.; Evans, R.B.; Walsh, E.J.

    1991-01-01

    The Nevada Test Site (NTS) covers approximately 3300 km 2 of high desert and is located approximately 100 km northwest of Las Vegas, Nevada. Soil contaminated by plutonium exists on the NTS and surrounding areas from safety tests conducted in the 1950s and 1960s. About 150 curies of contamination have been measured over 1200 hectares of land surface. Most contamination is found in the top 5 cm of soil but may be found as deep as 25 cm. The cost of conventional removal and disposal of the full soil volume has been estimated at over $500,000,000. This study is directed toward minimizing the volume of waste which must be further processed and disposed of by precisely controlling soil removal depth. The following soil removal machines were demonstrated at the NTS: (1) a CMI Corporation Model PR-500FL pavement profiler, (2) a CMI Corporation Model TR-225B trimmer reclaimer, (3) a Caterpillar Model 623 elevating scraper equipped with laser depth control, (4) a Caterpillar Model 14G motor grader equipped with laser depth control, (5) a Caterpillar Model 637 auger scraper, and (6) a XCR Series Guzzler vacuum truck. The most effective removal technique tested was the pavement profiler, which provided for dust control and precisely removed thin layers of soil. Soil removal with the motor grader and paddle scraper generated unacceptable dust levels, even after the soil was extensively watered. The vacuum truck was ineffective because of its limited intake volume which is a function of its small intake size, its weak intake force, and the tendency of its filters to clog

  8. Urban surface energy fluxes based on remotely-sensed data and micrometeorological measurements over the Kansai area, Japan

    Science.gov (United States)

    Sukeyasu, T.; Ueyama, M.; Ando, T.; Kosugi, Y.; Kominami, Y.

    2017-12-01

    The urban heat island is associated with land cover changes and increases in anthropogenic heat fluxes. Clear understanding of the surface energy budget at urban area is the most important for evaluating the urban heat island. In this study, we develop a model based on remotely-sensed data for the Kansai area in Japan and clarify temporal transitions and spatial distributions of the surface energy flux from 2000 to 2016. The model calculated the surface energy fluxes based on various satellite and GIS products. The model used land surface temperature, surface emissivity, air temperature, albedo, downward shortwave radiation and land cover/use type from the moderate resolution imaging spectroradiometer (MODIS) under cloud free skies from 2000 to 2016 over the Kansai area in Japan (34 to 35 ° N, 135 to 136 ° E). Net radiation was estimated by a radiation budget of upward/downward shortwave and longwave radiation. Sensible heat flux was estimated by a bulk aerodynamic method. Anthropogenic heat flux was estimated by the inventory data. Latent heat flux was examined with residues of the energy budget and parameterization of bulk transfer coefficients. We validated the model using observed fluxes from five eddy-covariance measurement sites: three urban sites and two forested sites. The estimated net radiation roughly agreed with the observations, but the sensible heat flux were underestimated. Based on the modeled spatial distributions of the fluxes, the daytime net radiation in the forested area was larger than those in the urban area, owing to higher albedo and land surface temperatures in the urban area than the forested area. The estimated anthropogenic heat flux was high in the summer and winter periods due to increases in energy-requirements.

  9. Hydrological response to land cover changes and human activities in arid regions using a geographic information system and remote sensing.

    Directory of Open Access Journals (Sweden)

    Shereif H Mahmoud

    Full Text Available The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities.

  10. Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005.

    Science.gov (United States)

    Dewan, Ashraf M; Yamaguchi, Yasushi

    2009-03-01

    This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

  11. Monitoring land and water uses in the Columbia Plateau using remote-sensing computer analysis and integration techniques

    International Nuclear Information System (INIS)

    Leonhart, L.S.; Wukelic, G.E.; Foote, H.P.; Blair, S.C.

    1983-09-01

    This study successfully utilized advanced, remote-sensing computer-analysis techniques to quantify and map land- and water-use trends potentially relevant to siting, developing, and operating a high-level national, nuclear waste repository on the US Department of Energy's Hanford Site in eastern Washington State. Specifically, using a variety of digital data bases (primarily multidate LANDSAT data) and digital analysis programs, the study produced unique numerical data and integrated data reference maps relevant to regional (Columbia Plateau) and localized (Pasco Basin) hydrologic considerations associated with developing such a facility. Because all study data developed are in digital form, they can be called upon to contribute to future reference repository location monitoring and reporting efforts, as well as to be utilized in other US Department of Energy programmatic areas having technical and/or environmental interest in the Columbia Plateau region. The results obtained indicate that multidate digital LANDSAT data provide an inexpensive, up-to-date, and accurate data base and reference map of natural and cultural features existing in any region. These data can be (1) computer enhanced to highlight selected surface features of interest; (2) processed/analyzed to provide regional land cover/use information and trend data; and (3) combined with other line and point data files to accommodate interactive, correlative analyses and integrated colorgraphic displays to aid interpretation and modeling efforts. Once the digital base is established, selected site information can be assessed immediately, various forms of data can be accessed concurrently or separately, and data sets may be displayed or mapped at any scale. Available editing software provides the opportunity to generate credible scenarios for a site while preserving the actual data base. 6 references

  12. Remote sensing and GIS analyses for emergency manouvering and forced landing areas definition as a support for general aviation flights

    Science.gov (United States)

    Skocki, Krzysztof

    2016-08-01

    This paper summarizes the preliminary analyses of using existing remote sensing data, medium and high-resolution satellite and airborne data to define safe emergency landing and maneuvering areas to be used by small aircrafts operating from small airports and airfields in Poland. The pilots need to know such places in the interest of safe flight operations. In common practice, flying instructors typically show the student pilot fields around the airfield supposed to be suitable for emergency or precautionary landing (or ditching) in the initial phase of the training. Although it looks to cover the most basic needs, the problem still exists in relation to guest pilots. To fill this gap, the unified safety map document covering the safe emergency areas around the airfields is proposed in this research. Use of satellite high resolution data, as well as aerial photos, infrastructure information, with use of GIS tools (like buffer zones, distance, equal-time circles or position lines) enable to check the terrain around selected airfields and define possible areas suitable for emergency operations. In the second phase of work, selected areas will be described in terms of easy navigation, possible infrastructure around them, rescue possibilities, radio signal coverage, and others. The selected areas should be also checked for typical cover and surface hardness and stability (eg. with use of moisture estimation on the base of middle-resolution satellite data). Its planned to prepare one combined and separate sheets of the final map for various aircraft characteristics (`classes' of small Cessna-related, big Cessna-related, fast low-wing Diamond-like, two-engine Piper-like). The presented concept should highly increase the safety operations for small aviation in secondary airports and airfields, where the information available is limited. There is also a possibility to make a similar maps for `cruise', which means the areas with dense traffic between the airports/airfields.

  13. Land development, land use, and urban sprawl in Puerto Rico integrating remote sensing and population census data.

    Science.gov (United States)

    Sebastian Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez

    2007-01-01

    The island of Puerto Rico has both a high population density and a long history of ineffective land use planning. This study integrates geospatial technology and population census data to understand how people use and develop the lands. We define three new regions for Puerto Rico: Urban (16%), Densely Populated Rural (36%), and Sparsely Populated Rural (48%). Eleven...

  14. Assessing the influence of groundwater and land surface scheme in the modelling of land surface-atmosphere feedbacks over the FIFE area in Kansas, USA

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Højmark Rasmussen, Søren; Drews, Martin

    2016-01-01

    The land surface-atmosphere interaction is described differently in large scale surface schemes of regional climate models and small scale spatially distributed hydrological models. In particular, the hydrological models include the influence of shallow groundwater on evapotranspiration during dry...... by HIRHAM simulated precipitation. The last two simulations include iv) a standard HIRHAM simulation, and v) a fully coupled HIRHAM-MIKE SHE simulation locally replacing the land surface scheme by MIKE SHE for the FIFE area, while HIRHAM in standard configuration is used for the remaining model area...

  15. Characteristics of Eurasian snowmelt and its impacts on the land surface and surface climate

    Science.gov (United States)

    Ye, Kunhui; Lau, Ngar-Cheung

    2018-03-01

    The local hydrological and climatic impacts of Eurasian snowmelt are studied using advanced land surface and atmospheric data. It is found that intense melting of snow is located at mid-high latitudes in April and May. Snowmelt plays an important role in determining the seasonal cycles of surface runoff and soil moisture (SM). Specifically, melting is accompanied by sharp responses in surface runoff and surface SM while the impacts are delayed for deeper-layer of soil. This is particularly significant in the western sector of Eurasia. On interannual timescales, the responses of various surface parameters to snowmelt in the same month are rather significant. However, the persistence of surface SM anomalies is weak due to the strong soil evaporation anomalies and surplus of surface energy for evaporation. Strong impacts on the sensible heat flux, planetary boundary layer height and precipitation in the next month following the melting of snow are identified in west Russia and Siberia. Downward propagation of surface SM anomalies is observed and a positive evaporation-convection feedback is identified in west Russia. However, the subsequent impacts on the local convective precipitation in late spring-summer and its contribution to the total precipitation are seemingly weak. The atmospheric water vapor convergence has strong control over the total precipitation anomalies. Overall, snowmelt-produced SM anomalies are not found to significantly impact the late spring-summer local climate anomalies in Northern Eurasia. Therefore, the delayed remote-responses of atmospheric circulation and climate to the melting of Eurasian snow may be only possible near the melting period.

  16. A Remote Sensing Approach for Regional-Scale Mapping of Agricultural Land-Use Systems Based on NDVI Time Series

    Directory of Open Access Journals (Sweden)

    Beatriz Bellón

    2017-06-01

    Full Text Available In response to the need for generic remote sensing tools to support large-scale agricultural monitoring, we present a new approach for regional-scale mapping of agricultural land-use systems (ALUS based on object-based Normalized Difference Vegetation Index (NDVI time series analysis. The approach consists of two main steps. First, to obtain relatively homogeneous land units in terms of phenological patterns, a principal component analysis (PCA is applied to an annual MODIS NDVI time series, and an automatic segmentation is performed on the resulting high-order principal component images. Second, the resulting land units are classified into the crop agriculture domain or the livestock domain based on their land-cover characteristics. The crop agriculture domain land units are further classified into different cropping systems based on the correspondence of their NDVI temporal profiles with the phenological patterns associated with the cropping systems of the study area. A map of the main ALUS of the Brazilian state of Tocantins was produced for the 2013–2014 growing season with the new approach, and a significant coherence was observed between the spatial distribution of the cropping systems in the final ALUS map and in a reference map extracted from the official agricultural statistics of the Brazilian Institute of Geography and Statistics (IBGE. This study shows the potential of remote sensing techniques to provide valuable baseline spatial information for supporting agricultural monitoring and for large-scale land-use systems analysis.

  17. Improvement of a land surface model for accurate prediction of surface energy and water balances

    International Nuclear Information System (INIS)

    Katata, Genki

    2009-02-01

    In order to predict energy and water balances between the biosphere and atmosphere accurately, sophisticated schemes to calculate evaporation and adsorption processes in the soil and cloud (fog) water deposition on vegetation were implemented in the one-dimensional atmosphere-soil-vegetation model including CO 2 exchange process (SOLVEG2). Performance tests in arid areas showed that the above schemes have a significant effect on surface energy and water balances. The framework of the above schemes incorporated in the SOLVEG2 and instruction for running the model are documented. With further modifications of the model to implement the carbon exchanges between the vegetation and soil, deposition processes of materials on the land surface, vegetation stress-growth-dynamics etc., the model is suited to evaluate an effect of environmental loads to ecosystems by atmospheric pollutants and radioactive substances under climate changes such as global warming and drought. (author)

  18. Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

    Science.gov (United States)

    Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; Blyth, Eleanor; de Roo, Ad; DöLl, Petra; Ek, Mike; Famiglietti, James; Gochis, David; van de Giesen, Nick; Houser, Paul; Jaffé, Peter R.; Kollet, Stefan; Lehner, Bernhard; Lettenmaier, Dennis P.; Peters-Lidard, Christa; Sivapalan, Murugesu; Sheffield, Justin; Wade, Andrew; Whitehead, Paul

    2011-05-01

    Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (˜10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a "grand challenge" to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

  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. Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

    Science.gov (United States)

    Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James; hide

    2011-01-01

    Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

  1. Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

    Science.gov (United States)

    Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

    2018-05-01

    Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data

  2. Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

    Science.gov (United States)

    Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

    2018-02-01

    We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

  3. Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

    2010-01-01

    Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

  4. Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

    Directory of Open Access Journals (Sweden)

    Gemma Simó

    2016-10-01

    Full Text Available Land Surface Temperature (LST as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean, with an area of about 1 km 2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area.

  5. Land surface evapotranspiration modelling at the regional scale

    Science.gov (United States)

    Raffelli, Giulia; Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Gisolo, Davide; Provenzale, Antonello

    2017-04-01

    minimal point of soil moisture that plant requires not to wilt); the field capacity (i.e. the maximum amount of water content that a soil can held); the available water content (AWC), obtained as the difference between field capacity and wilting point. Furthermore, the model considers 15 different ID of land use, with a resolution of 250 m. The model was then tested by a direct comparison with experimental data. First, the modelled water content from the surface down to 65 cm of soil depth was compared to the measured one with a Time Domain Reflectometry (TDR) in Grugliasco (TO), a non-irrigated flat permanent meadow, for years 2006-2008. Here, the soil is sandy with a slope of about 1%. Then, considering three corn farms located in the Cuneo district, the goodness of modelled irrigations was verified. The soil texture of the three farms, analysed according to the USDA criteria, is loam or silty-loam. In particular, we compared the number of irrigations done by the farmers with the ones given by the model, which irrigates as soon as the plant reaches an imposed level of water stress. We also compared the irrigation turn given by the model with the farmers' one. Then we compared the modelled water content with the one measured before and after the irrigation. We observed that the modelled irrigation occurred when the measured water content was close to the modelled wilting point. In both test cases, the model seems to reflect quite well the real behaviour of water content.

  6. Atmospheric sensitivity to land surface changes: comparing the impact of albedo, roughness, and evaporative resistance on near-surface air temperature using an idealized land model.

    Science.gov (United States)

    Lague, M. M.; Swann, A. L. S.; Bonan, G. B.

    2017-12-01

    Past studies have demonstrated how changes in vegetation can impact the atmosphere; however, it is often difficult to identify the exact physical pathway through which vegetation changes drive an atmospheric response. Surface properties (such as vegetation color, or height) control surface energy fluxes, which feed back on the atmosphere on both local and global scales by modifying temperatures, cloud cover, and energy gradients. Understanding how land surface properties influence energy fluxes is crucial for improving our understanding of how vegetation change - past, present, and future - impacts the atmosphere, global climate, and people. We explore the sensitivity of the atmosphere to perturbations of three land surface properties - albedo, roughness, and evaporative resistance - using an idealized land model coupled to an Earth System Model. We derive a relationship telling us how large a change in each surface property is required to drive a local 0.1 K change in 2m air temperature. Using this idealized framework, we are able to separate the influence on the atmosphere of each individual surface property. We demonstrate that the impact of each surface property on the atmosphere is spatially variable - that is, a similar change in vegetation can have different climate impacts if made in different locations. This analysis not only improves our understanding of how the land system can influence climate, but also provides us with a set of theoretical limits on the potential climate impact of arbitrary vegetation change (natural or anthropogenic).

  7. Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation

    Directory of Open Access Journals (Sweden)

    Mukesh Singh Boori

    2016-12-01

    Full Text Available This data article contains data related to the research article entitled “Global land cover classification based on microwave polarization and gradient ratio (MPGR” [1] and “Microwave polarization and gradient ratio (MPGR for global land surface phenology” [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E. This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE, digital elevation model (DEM and Brightness Temperature (BT information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

  8. Source Apportionment of Annual Water Pollution Loads in River Basins by Remote-Sensed Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-08-01

    Full Text Available In this study, in order to determine the efficiency of estimating annual water pollution loads from remote-sensed land cover classification and ground-observed hydrological data, an empirical model was investigated. Remote sensing data imagery from National Oceanic and Atmospheric Administration (NOAA Advanced Very High Resolution Radiometer were applied to an 11 year (1994–2004 water quality dataset for 30 different rivers in Japan. Six water quality indicators—total nitrogen (TN, total phosphorus (TP, biochemical oxygen demand (BOD, chemical oxygen demand (COD, and dissolved oxygen (DO—were examined by using the observed river water quality data and generated land cover map. The TN, TP, BOD, COD, and DO loads were estimated for the 30 river basins using the empirical model. Calibration (1994–1999 and validation (2000–2004 results showed that the proposed simulation technique was useful for predicting water pollution loads in the river basins. We found that vegetation land cover had a larger impact on TP export into all rivers. Urban areas had a very small impact on DO export into rivers, but a relatively large impact on BOD and TN export. The results indicate that the application of land cover data generated from the remote-sensed imagery could give a useful interpretation about the river water quality.

  9. Challenges and opportunities in land surface modelling of savanna ecosystems

    Directory of Open Access Journals (Sweden)

    R. Whitley

    2017-10-01

    Full Text Available The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs, which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model

  10. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season

    Directory of Open Access Journals (Sweden)

    Sadroddin Alavipanah

    2015-04-01

    Full Text Available The Urban Heat Island (UHI is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST and Land Use Land Cover (LULC, MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i the cooling effect accrued from urban vegetation tended to be non-linear; and (ii a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

  11. Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

    KAUST Repository

    Zampieri, Matteo; Serpetzoglou, Efthymios; Anagnostou, Emmanouil N.; Nikolopoulos, Efthymios I.; Papadopoulos, Anastasios

    2012-01-01

    Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions

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

    Science.gov (United States)

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

    2017-05-01

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

  13. A Method for Retrieving Daily Land Surface Albedo from Space at 30-m Resolution

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2015-08-01

    Full Text Available Land surface albedo data with high spatio-temporal resolution are increasingly important for scientific studies addressing spatially and/or temporally small-scale phenomena, such as urban heat islands and urban land surface energy balance. Our previous study derived albedo data with 2–4-day and 30-m temporal and spatial resolution that have better spatio-temporal resolution than existing albedo data, but do not completely satisfy the requirements for monitoring high-frequency land surface changes at the small scale. Downscaling technology provides a chance to further improve the albedo data spatio-temporal resolution and accuracy. This paper introduces a method that combines downscaling technology for land surface reflectance with an empirical method of deriving land surface albedo. Firstly, downscaling daily MODIS land surface reflectance data (MOD09GA from 500 m to 30 m on the basis of HJ-1A/B BRDF data with 2–4-day and 30-m temporal and spatial resolution is performed: this is the key step in the improved method. Subsequently, the daily 30-m land surface albedo data are derived by an empirical method combining prior knowledge of the MODIS BRDF product and the downscaled daily 30-m reflectance. Validation of albedo data obtained using the proposed method shows that the new method has both improved spatio-temporal resolution and good accuracy (a total absolute accuracy of 0.022 and a total root mean squared error at six sites of 0.028.

  14. Assessment of Land Surface Complexity In Relation To Information Capacity and the Fractal Dimension in Different Landform Regions Using Landsat Data

    International Nuclear Information System (INIS)

    Hong, Wang Xu; Huijie, Qin; Zhe, Zhang; Fei, Li

    2014-01-01

    Remote sensing images are highly structured, and contiguous pixels of space domain have strong correlations that contain abundant information on land surface structure features and land surface electromagnetic radiation features. The information capacity model, which is a quality evaluation model based on a multi-dimensional histogram, includes local correlations within different pixels. Thus, the information capacity can illustrate land surface structural information more objectively and effectively than other single-pixel calculation models. Our results reveal that the information capacity value correlates well with the meaningful grey level of remote sensing imagery. This high correlation is related to the complexity of terrestrial surface landscapes. Therefore, information capacity, as applied to geoscience, is introduced in this study to demonstrate the spatial differentiation of information capacity of different landform regions. Generally, the information capacity of a mountain is large and is followed in decreasing order by those of the hills and the plains. Moreover, the correlation between information capacity and the fractal dimension is analysed. Based on the results of this study, it can be concluded that the level of correlation for information capacity and the fractal dimension is high, and the correlation coefficient for the basic landform areas and the loess landform areas is 0.874 and 0.825, respectively. Finally, this paper proposes that information capacity be used as a new reference index for geoscientific analysis in quantitative research on the characteristics of land surface complexity

  15. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

    2017-12-01

    Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

  16. Engineering of Surface Chemistry for Enhanced Sensitivity in Nanoporous Interferometric Sensing Platforms.

    Science.gov (United States)

    Law, Cheryl Suwen; Sylvia, Georgina M; Nemati, Madieh; Yu, Jingxian; Losic, Dusan; Abell, Andrew D; Santos, Abel

    2017-03-15

    We explore new approaches to engineering the surface chemistry of interferometric sensing platforms based on nanoporous anodic alumina (NAA) and reflectometric interference spectroscopy (RIfS). Two surface engineering strategies are presented, namely (i) selective chemical functionalization of the inner surface of NAA pores with amine-terminated thiol molecules and (ii) selective chemical functionalization of the top surface of NAA with dithiol molecules. The strong molecular interaction of Au 3+ ions with thiol-containing functional molecules of alkane chain or peptide character provides a model sensing system with which to assess the sensitivity of these NAA platforms by both molecular feature and surface engineering. Changes in the effective optical thickness of the functionalized NAA photonic films (i.e., sensing principle), in response to gold ions, are monitored in real-time by RIfS. 6-Amino-1-hexanethiol (inner surface) and 1,6-hexanedithiol (top surface), the most sensitive functional molecules from approaches i and ii, respectively, were combined into a third sensing strategy whereby the NAA platforms are functionalized on both the top and inner surfaces concurrently. Engineering of the surface according to this approach resulted in an additive enhancement in sensitivity of up to 5-fold compared to previously reported systems. This study advances the rational engineering of surface chemistry for interferometric sensing on nanoporous platforms with potential applications for real-time monitoring of multiple analytes in dynamic environments.

  17. 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

    The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface

  18. Using NOAA-AVHRR estimates of land surface temperature for regional agrometeoro[lo]gical modelling

    NARCIS (Netherlands)

    Wit, de A.J.W.; Boogaard, H.L.; Diepen, van C.A.

    2004-01-01

    This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature

  19. Detecting moisture status of pecan orchards and the potential of remotely-sensed surface reflectance data

    Science.gov (United States)

    Othman, Yahia Abdelrahman

    Demand for New Mexico's limited water resources coupled with periodic drought has increased the need to schedule irrigation of pecan orchards based on tree water status. The overall goal of this research was to develop advanced tree water status sensing techniques to optimize irrigation scheduling of pecan orchards. To achieve this goal, I conducted three studies in the La Mancha and Leyendecker orchards, both mature pecan orchards located in the Mesilla Valley, New Mexico. In the first study, I screened leaf-level physiological changes that occurred during cyclic irrigation to determine parameters that best represented changes in plant moisture status. Then, I linked plant physiological changes to remotely-sensed surface reflectance data derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+). In the second study, I assessed the impact of water deficits that developed during the flood irrigation dry-down cycles on photosynthesis (A) and gas exchange and established preliminary water deficit thresholds of midday stem water potential (Psi smd) critical to A and gas exchange of pecans. In a third study, I investigated whether hyperspectral data obtained from a handheld spectroradiometer and multispectral remotely-sensed data derived from Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI) could detect moisture status in pecans during cyclic flood irrigations. I conducted the first study simultaneously in both orchards. Leaf-level physiological responses and remotely-sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Midday stem water potential was the best leaf-level physiological response to detect moisture status in pecans. Multiple linear regression between Psismd and vegetation indices revealed a significant relationship (R 2 = 0.54) in both orchards. Accordingly, I concluded that remotely-sensed multispectral data form Landsat TMETM+ holds promise for detecting the moisture

  20. Impacts of land cover transitions on surface temperature in China based on satellite observations

    Science.gov (United States)

    Zhang, Yuzhen; Liang, Shunlin

    2018-02-01

    China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short

  1. Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

    Science.gov (United States)

    Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

    2017-04-01

    Split Based Approach (MSBA) is used in order to focus on surface water areas automatically and facilitate the estimation of class models for water and non-water areas. A Finite Mixture Model is employed as the underlying statistical model to produce probabilistic maps. Subsequently, bilateral filtering is applied to take into account spatial neighborhood relationships in the generation of final map. The elimination of shadows effect is performed in a post-processing step. The processing chain is tested on three case studies. The first case is a flood event in central Ireland, the second case is located in Yorkshire county / Great Britain, and the third test case covers a recent flood event in northern Italy. The tests showed that the modified SBA step and the Finite Mixture Models can be applied for the automatic surface water detection in a variety of test cases. An evaluation again Copernicus products derived from very-high resolution imagery was performed, and showed a high overall accuracy and F-measure of the obtained maps. This evaluation also showed that the use of probability maps and bilateral filtering improved the accuracy of classification results significantly. Based on this quantitative evaluation, it is concluded that the processing chain can be applied for flood mapping from Sentinel-1 data. To estimate robust statistical distributions the method requires sufficient surface waters areas in the observed zone and sufficient contrast between surface waters and other land use classes. Ongoing research addresses the fusion of Sentinel-1 and passive remote sensing data (e.g. Sentinel-2) in order to reduce the current shortcomings in the developed processing chain. In this work, fusion is performed at the feature level to better account for the difference image properties of SAR and optical sensors. Further, the processing chain is currently being optimized in terms of calculation time for a further integration as a flood mapping service on the A2S (Alsace Aval

  2. Comparison of two perturbation methods to estimate the land surface modeling uncertainty

    Science.gov (United States)

    Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

    2007-12-01

    In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

  3. DMPD: Innate immune sensing of pathogens and danger signals by cell surface Toll-likereceptors. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17275324 Innate immune sensing of pathogens and danger signals by cell surface Toll... Show Innate immune sensing of pathogens and danger signals by cell surface Toll-likereceptors. PubmedID 172...75324 Title Innate immune sensing of pathogens and danger signals by cell surface

  4. Land Surface Process and Air Quality Research and Applications at MSFC

    Science.gov (United States)

    Quattrochi, Dale; Khan, Maudood

    2007-01-01

    This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.

  5. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-06-01

    Full Text Available This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

  6. Fiber optic corrosion sensing for bridges and roadway surfaces

    Science.gov (United States)

    Fuhr, Peter L.; Ambrose, Timothy P.; Huston, Dryver R.; McPadden, Adam P.

    1995-04-01

    In this paper we report the development of a fiber optic corrosion sensing system that complements and/or surpasses the capabilities of conventional corrosion sensing techniques. The sensing system is based on evanescent wave phenomena and in the configured sensor allows for the detection of general corrosion on and within materials. Based on the authors' experience installing may kilometers of fiberoptic sensors into large civil structures such as multistory buildings, hydroelectric dams, and railway/roadway bridges, we are (currently) embedding these sensors into bridge test members -- limited structures that are being subjected to accelerated corrosion testing conditions. Three Vermont Agency of Transportation bridges, one in a low salt use region, one in a medium salt use region, and the third in a high salt use region, are being selected and will be instrumented with these embedded fiber optic corrosion sensors. Monitoring of chloride penetration and rebar corrosion status will be measured during the course of a longitudinal study. The specific sensing mechanism and design for robustness (to allow survival of the embedding process during repaving of the bridges) are discussed and laboratory and initial field results are presented.

  7. Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

    Science.gov (United States)

    Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

    2016-01-01

    The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial

  8. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MYD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  9. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MOD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  10. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MYD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  11. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MOD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  12. Impacts of surface gold mining on land use systems in Western Ghana.

    Science.gov (United States)

    Schueler, Vivian; Kuemmerle, Tobias; Schröder, Hilmar

    2011-07-01

    Land use conflicts are becoming increasingly apparent from local to global scales. Surface gold mining is an extreme source of such a conflict, but mining impacts on local livelihoods often remain unclear. Our goal here was to assess land cover change due to gold surface mining in Western Ghana, one of the world's leading gold mining regions, and to study how these changes affected land use systems. We used Landsat satellite images from 1986-2002 to map land cover change and field interviews with farmers to understand the livelihood implications of mining-related land cover change. Our results showed that surface mining resulted in deforestation (58%), a substantial loss of farmland (45%) within mining concessions, and widespread spill-over effects as relocated farmers expand farmland into forests. This points to rapidly eroding livelihood foundations, suggesting that the environmental and social costs of Ghana's gold boom may be much higher than previously thought.

  13. Instantaneous heat flux flowing into piston top-land surface of D.I. diesel engine; DI diesel kikan no piston top land bu eno shunji netsuryusoku

    Energy Technology Data Exchange (ETDEWEB)

    Taguma, M [Zexel Corp., Tokyo (Japan); Inui, M; Enomoto, Y; Hagihara, Y [Musashi Institute of Technology, Tokyo (Japan); Koyama, T [Mitsubishi Motors Co., Tokyo (Japan)

    1997-10-01

    The thermal loads of the piston top-land surface in D.I. diesel engine during actual operation is not cleared. The authors fixed thin film thermocouples in the top-land center of a standard piston, and measured the instantaneous heat fluxes in that place. As a result, the authors made clear the thermal loads of the piston top-land surface in a cycle, and confirmed presence of the flame inflow to the piston top-land center. In addition, the authors made clear the thermal loads of the piston top-land surface in EGR operation. 4 refs., 8 figs.

  14. Impact of the Sun on Remote Sensing of Sea Surface Salinity from Space

    National Research Council Canada - National Science Library

    Le Vine, David M; Abraham, Saji; Wentz, F; Lagerloef, G. S

    2005-01-01

    ... to monitor soil moisture and sea surface salinity. Radiation from the sun can impact passive remote sensing systems in several ways, including line-of-sight radiation that comes directly from the sun and enters through antenna side lobes...

  15. The impact of implementing the bare essentials of surface transfer land surface scheme into the BMRC GCM

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Z.L. [Univ. of Arizona, Tucson, AZ (United States); Pitman, A.J. [Macquarie Univ., Sydney (Australia); McAvaney, B. [Bureau of Meterology Research Centre, Melbourne (Australia)] [and others

    1995-07-01

    This study describes the first order impacts of incorporating a complex land-surface scheme, the bare essentials of surface transfer (BEST), into the Australian Bureau of Meteorology Research Centre (BMRC) global atmospheric general circulation model (GCM). Land seasonal climatologies averaged over the last six years of integrations after equilibrium from the GCM with BEST and without BEST (the control) are compared. The modeled results are evaluated with comprehensive sources of data, including the layer-cloud climatologies project (ISCCP) data from 1983 to 1991 and the surface-observed global data of Warrent et al., a five-year climatology of surface albedo estimated from earth radiation budget experiment (ERBE) top-of-the-atmosphere (TOA) radiative fluxes, global grid point datasets of precipitation, and the climatological analyses of surface evaporation and albedo. Emphasis is placed on the surface evaluation of simulations of land-surface conditions such as surface roughness, surface albedo and the surface wetness factor, and on their effects on surface evaporation, precipitation, layer-cloud and surface temperature. The improvements due to the inclusion of BEST are: a realistic geographical distribution of surface roughness, a decrease in surface albedo over areas with seasonal snow cover, an an increase in surface albedo over snow-free land. The simulated reduction in surface evaporation due, in part, to the bio-physical control of vegetation, is also consistent with the previous studies. Since the control climate has a dry bias, the overall simulations from the GCM with BEST are degraded, except for significant improvements for the northern winter hemisphere because of the realistic vegetation-masking effects. The implications of our results for synergistic developments of other aspects of model parameterization schemes such as boundary layer dynamics, clouds, convection and rainfall are discussed. 82 refs., 9 figs., 3 tabs.

  16. LAND SURFACE TEMPERATURES ESTIMATED ON GROUNDOBSERVED DATA AND SATELLITE IMAGES, DURING THE VEGETATION PERIOD IN THE OLTENIA PLAIN

    Directory of Open Access Journals (Sweden)

    ONŢEL IRINA

    2015-03-01

    Full Text Available The purpose of this study is to analyze the land surface temperatures by using climatological and remote sensing data during the vegetation period in the Oltenia Plain. The data used in this study refer both to climatological data (namely monthly and seasonal air and soil temperatures, and to remote sensing data delivered by MODIS Land Surface Temperature (LST, with a spatial resolution of 1 km. The analyzed period spans from 2000 to 2013 and the vegetation period considered is April-September. As main results, there were observed four years with high temperatures, namely 2000 (20.4oC-air T, 24.6oC soil T, and 26oC LST, 2003 (20.2oC air T, 23.9oC soil T and 24.5oC LST, 2007 (20.5oC air T, 24.3oC soil T and 25oC LST and 2012 (21.3oC air T, 25.7oC soil T and 26.5oC LST. The correlations between air temperature, soil temperature and LST were statisticaly significant. The diference between air temperature and soil temperature values ranked within 3-4oC, while the difference between soil temperature and land surface temperature obtained from MODIS images was about 0.8oC. Spatially, the highest temperatures were recorded on the Leu-Rotunda Field, the Caracal Plain and the Nedeia Field, and pretty high variations of observed temperatures seemed to depend on vegetation cover. The MODIS images represent one of the most important types of satellite data available for free, which can be successfully used in determining the climatic parameters and can help to predict the changes in plant activity, due to weather phenomena.

  17. Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece

    Directory of Open Access Journals (Sweden)

    Ioannis Manakos

    2014-12-01

    Full Text Available The National Geomatics Center of China (NGCC produced Global Land Cover (GlobalLand30 maps with 30 m spatial resolution for the years 2000 and 2009–2010, responding to the need for harmonized, accurate, and high-resolution global land cover data. This study aims to assess the mapping accuracy of the land surface water layer of GlobalLand30 for 2009–2010. A representative Mediterranean region, situated in Greece, is considered as the case study area, with 2009 as the reference year. The assessment is realized through an object-based comparison of the GlobalLand30 water layer with the ground truth and visually interpreted data from the Hellenic Cadastre fine spatial resolution (0.5 m orthophoto map layer. GlobCover 2009, GlobCorine 2009, and GLCNMO 2008 corresponding thematic layers are utilized to show and quantify the progress brought along with the increment of the spatial resolution, from 500 m to 300 m and finally to 30 m with the newly produced GlobalLand30 maps. GlobalLand30 detected land surface water areas show a 91.9% overlap with the reference data, while the coarser resolution products are restricted to lower accuracies. Validation is extended to the drainage network elements, i.e., rivers and streams, where GlobalLand30 outperforms the other global map products, as well.

  18. On the measurement of the surface energy budget over a land ...

    Indian Academy of Sciences (India)

    The measurement of surface energy balance over a land surface in an open area in Bangalore is reported. Measurements of all variables needed to calculate the surface energy balance on time scales longer than a week are made. Components of radiative fluxes are measured while sensible and latent heat fluxes are ...

  19. Optimal land use/cover classification using remote sensing imagery for hydrological modelling in a Himalayan watershed

    NARCIS (Netherlands)

    Sameer Saran,; Sterk, G.; Kumar, S.

    2007-01-01

    Land use/cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into

  20. REMOTE SENSING AND SURFACE ENERGY FLUX MODELS TO DERIVE EVAPOTRANSPIRATION AND CROP COEFFICIENT

    Directory of Open Access Journals (Sweden)

    Salvatore Barbagallo

    2008-06-01

    Full Text Available Remote sensing techniques using high resolution satellite images provide opportunities to evaluate daily crop water use and its spatial and temporal distribution on a field by field basis. Mapping this indicator with pixels of few meters of size on extend areas allows to characterize different processes and parameters. Satellite data on vegetation reflectance, integrated with in field measurements of canopy coverage features and the monitoring of energy fluxes through the soil-plant-atmosphere system, allow to estimate conventional irrigation components (ET, Kc thus improving irrigation strategies. In the study, satellite potential evapotranspiration (ETp and crop coefficient (Kc maps of orange orchards are derived using semi-empirical approaches between reflectance data from IKONOS imagery and ground measurements of vegetation features. The monitoring of energy fluxes through the orchard allows to estimate actual crop evapotranspiration (ETa using energy balance and the Surface Renewal theory. The approach indicates substantial promise as an efficient, accurate and relatively inexpensive procedure to predict actual ET fluxes and Kc from irrigated lands.

  1. Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

    Science.gov (United States)

    Grant, G.; Gallaher, D. W.

    2017-12-01

    New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

  2. On the utility of land surface models for agricultural drought monitoring

    Directory of Open Access Journals (Sweden)

    W. T. Crow

    2012-09-01

    Full Text Available The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

  3. 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.

  4. Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing.

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2007-09-01

    Full Text Available Land degradation is of great concern in South Africa particularly in the Inkomati catchment. Here a mosaic of different land use types such as plantation agriculture, subsistence farming, irrigated commercial farming, rural and urban settlements...

  5. Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

    Science.gov (United States)

    Xu, L.

    1994-01-01

    A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

  6. Monitoring Urbanization-Related Land Cover Change on the U.S. Great Plains and Impacts on Remotely Sensed Vegetation Dynamics

    Science.gov (United States)

    Krehbiel, C. P.; Jackson, T.; Henebry, G. M.

    2014-12-01

    Earth is currently in an era of rapid urban growth with >50% of global population living in urban areas. Urbanization occurs alongside urban population growth, as cities expand to meet the demands of increasing population. Consequently, there is a need for remote sensing research to detect, monitor, and measure urbanization and its impacts on the biosphere. Here we used MODIS and Landsat data products to (1) detect urbanization-related land cover changes, (2) investigate urbanization-related impacts on land surface phenology (LSP) across rural to urban gradients and (3) explore fractional vegetation and impervious surface area regionally across the US Great Plains and within 14 cities in this region. We used the NLCD Percent Impervious Surface Area (%ISA) and Land Cover Type (LCT) products from 2001, 2006, and 2011 for 30m classification of the peri-urban environment. We investigated the impacts of urbanization-related land cover change on urban LSP at 30m resolution using the NDVI product from Web Enabled Landsat Data (http://weld.cr.usgs.gov) with accumulated growing degree-days calculated from first-order weather stations. We fitted convex quadratic LSP models to a decade (2003-2012) of observations to yield these phenometrics: modeled peak NDVI, time (thermal and calendar) to modeled peak, duration of season (DOS), and model fit. We compared our results to NDVI from MODIS NBAR (500m) and we explored the utility of 4 μm radiance (MODIS band 23) at 1 km resolution to characterize fractional vegetation dynamics in and around urbanized areas. Across all 14 cities we found increases in urbanized area (>25 %ISA) exceeding 10% from 2001-2011. Using LSP phenometrics, we were able to detect changes from cropland to suburban LCTs. In general we found negative relationships between DOS and distance from city center. We found a distinct seasonal cycle of MIR radiance over cropland LCTs due to the spectral contrast between bare soils and green vegetation.

  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. Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes

    Directory of Open Access Journals (Sweden)

    Heinz Gallaun

    2015-09-01

    Full Text Available Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.

  9. Remote Sensing Time Series to Evaluate Direct Land Use Change of Recent Expanded Sugarcane Crop in Brazil

    Directory of Open Access Journals (Sweden)

    Marcio Pupin Mello

    2012-04-01

    Full Text Available The use of biofuels to mitigate global carbon emissions is highly dependent on direct and indirect land use changes (LUC. The direct LUC (dLUC can be accurately evaluated using remote sensing images. In this work we evaluated the dLUC of about 4 million hectares of sugarcane expanded from 2005 to 2010 in the South-central region of Brazil. This region has a favorable climate for rain-fed sugarcane, a great potential for agriculture expansion without deforestation, and is currently responsible for almost 90% of Brazilian’s sugarcane production. An available thematic map of sugarcane along with MODIS and Landast images, acquired from 2000 to 2009, were used to evaluate the land use prior to the conversion to sugarcane. A systematic sampling procedure was adopted and the land use identification prior to sugarcane, for each sample, was performed using a web tool developed to visualize both the MODIS time series and the multitemporal Landsat images. Considering 2000 as reference year, it was observed that sugarcane expanded: 69.7% on pasture land; 25.0% on annual crops; 0.6% on forest; while 3.4% was sugarcane land under crop rotation. The results clearly show that the dLUC of recent sugarcane expansion has occurred on more than 99% of either pasture or agriculture land.

  10. The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

    Science.gov (United States)

    Wang, N.; Yang, R.

    2018-04-01

    Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

  11. Microclimatic models. Estimation of components of the energy balance over land surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Heikinheimo, M.; Venaelaeinen, A.; Tourula, T. [Finnish Meteorological Inst., Helsinki (Finland). Air Quality Dept.

    1996-12-31

    Climates at regional scale are strongly dependent on the interaction between atmosphere and its lower boundary, the oceans and the land surface mosaic. Land surfaces influence climate through their albedo, and the aerodynamic roughness, the processes of the biosphere and many soil hydrological properties; all these factors vary considerably geographically. Land surfaces receive a certain portion of the solar irradiance depending on the cloudiness, atmospheric transparency and surface albedo. Short-wave solar irradiance is the source of the heat energy exchange at the earth`s surface and also regulates many biological processes, e.g. photosynthesis. Methods for estimating solar irradiance, atmospheric transparency and surface albedo were reviewed during the course of this project. The solar energy at earth`s surface is consumed for heating the soil and the lower atmosphere. Where moisture is available, evaporation is one of the key components of the surface energy balance, because the conversion of liquid water into water vapour consumes heat. The evaporation process was studied by carrying out field experiments and testing parameterisation for a cultivated agricultural surface and for lakes. The micrometeorological study over lakes was carried out as part of the international `Northern Hemisphere Climatic Processes Experiment` (NOPEX/BAHC) in Sweden. These studies have been aimed at a better understanding of the energy exchange processes of the earth`s surface-atmosphere boundary for a more accurate and realistic parameterisation of the land surface in atmospheric models

  12. Microclimatic models. Estimation of components of the energy balance over land surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Heikinheimo, M; Venaelaeinen, A; Tourula, T [Finnish Meteorological Inst., Helsinki (Finland). Air Quality Dept.

    1997-12-31

    Climates at regional scale are strongly dependent on the interaction between atmosphere and its lower boundary, the oceans and the land surface mosaic. Land surfaces influence climate through their albedo, and the aerodynamic roughness, the processes of the biosphere and many soil hydrological properties; all these factors vary considerably geographically. Land surfaces receive a certain portion of the solar irradiance depending on the cloudiness, atmospheric transparency and surface albedo. Short-wave solar irradiance is the source of the heat energy exchange at the earth`s surface and also regulates many biological processes, e.g. photosynthesis. Methods for estimating solar irradiance, atmospheric transparency and surface albedo were reviewed during the course of this project. The solar energy at earth`s surface is consumed for heating the soil and the lower atmosphere. Where moisture is available, evaporation is one of the key components of the surface energy balance, because the conversion of liquid water into water vapour consumes heat. The evaporation process was studied by carrying out field experiments and testing parameterisation for a cultivated agricultural surface and for lakes. The micrometeorological study over lakes was carried out as part of the international `Northern Hemisphere Climatic Processes Experiment` (NOPEX/BAHC) in Sweden. These studies have been aimed at a better understanding of the energy exchange processes of the earth`s surface-atmosphere boundary for a more accurate and realistic parameterisation of the land surface in atmospheric models

  13. Land

    NARCIS (Netherlands)

    C.A. Hunsberger (Carol); Tom P. Evans

    2012-01-01

    textabstractPressure on land resources has increased during recent years despite international goals to improve their management. The fourth Global Environment Outlook (UNEP 2007) highlighted the unprecedented land-use changes created by a burgeoning population, economic development and

  14. The GLORIE Campaign: Assessment of the Capabilities of Airborne GNSS-R for Land Remote Sensing.

    Science.gov (United States)

    Mangiarotti, S.; Motte, E.; Zribi, M., Sr.; Fanise, P., Sr.

    2015-12-01

    In June and July 2015 an intensive flight campaign was conducted over the south west of France to test the sensitivity of Global Navigation Satellite System Reflectometry (GNSS-R) to the geophysical parameters of continental surfaces. Namely, the parameters of interest were soil moisture, soil roughness, plant water content, forest biomass and level of inland water bodies and rivers. We used the GLORI polarimetric GNSS-R instrument, collecting raw 10MSPS 2-bit IQ direct (RHCP, zenith) and reflected (RHCP and LHCP, nadir) signals at GPS L1 frequency aboard the ATR-42 aircraft of the SAFIRE fleet. Simultaneous measurement of aircraft attitude and position were recorded. The flight plan included flyovers of several areas of interests, with collocated ground truth measurements of soil moisture, soil roughness, cultivated biomass, and forest biomass. Also flyovers of ponds, lakes and river were included for power calibration and altimetry retrievals. In total, 6 flights were performed between June 19th and July 6th, representing more than 15 hours of raw data. A conventional GNSS-R processing of the data was performed in order to compute the direct and reflected complex waveforms. A preliminary data analysis based on the variations of the ratio of reflected maximum correlation amplitude in the LHCP antenna to direct maximum correlated amplitude shows measurements sensitivity to soil type, land use and incidence angle. Also, first altimetric retrievals using phase-delay techniques shows very promising results over calm waters. Current work is ongoing in order to fit the observed polarimetric measurements with innovative bistatic scattering models capable of taking into account complex geometries and land use configurations.

  15. Integrated nanohole array surface plasmon resonance sensing device using a dual-wavelength source

    International Nuclear Information System (INIS)

    Escobedo, C; Vincent, S; Choudhury, A I K; Campbell, J; Gordon, R; Brolo, A G; Sinton, D

    2011-01-01

    In this paper, we demonstrate a compact integrated nanohole array-based surface plasmon resonance sensing device. The unit includes a LED light source, driving circuitry, CCD detector, microfluidic network and computer interface, all assembled from readily available commercial components. A dual-wavelength LED scheme was implemented to increase spectral diversity and isolate intensity variations to be expected in the field. The prototype shows bulk sensitivity of 266 pixel intensity units/RIU and a limit of detection of 6 × 10 −4 RIU. Surface binding tests were performed, demonstrating functionality as a surface-based sensing system. This work is particularly relevant for low-cost point-of-care applications, especially those involving multiple tests and field studies. While nanohole arrays have been applied to many sensing applications, and their suitability to device integration is well established, this is the first demonstration of a fully integrated nanohole array-based sensing device.

  16. Performance evaluation for different sensing surface of BICELLs bio-transducers for dry eye biomarkers

    Science.gov (United States)

    Laguna, M. F.; Holgado, M.; Santamaría, B.; López, A.; Maigler, M.; Lavín, A.; de Vicente, J.; Soria, J.; Suarez, T.; Bardina, C.; Jara, M.; Sanza, F. J.; Casquel, R.; Otón, A.; Riesgo, T.

    2015-03-01

    Biophotonic Sensing Cells (BICELLs) are demonstrated to be an efficient technology for label-free biosensing and in concrete for evaluating dry eye diseases. The main advantage of BICELLs is its capability to be used by dropping directly a tear into the sensing surface without the need of complex microfluidics systems. Among this advantage, compact Point of Care read-out device is employed with the capability of evaluating different types of BICELLs packaged on Biochip-Kits that can be fabricated by using different sensing surfaces material. In this paper, we evaluate the performance of the combination of three sensing surface materials: (3-Glycidyloxypropyl) trimethoxysilane (GPTMS), SU-8 resist and Nitrocellulose (NC) for two different biomarkers relevant for dry eye diseases: PRDX-5 and ANXA-11.

  17. Land use and land cover change detection at Mirzapur Union of Gazipur District of Bangladesh using remote sensing and GIS technology

    International Nuclear Information System (INIS)

    Yesmin, R; Mohiuddin, A S M; Uddin, M J; Shahid, M A

    2014-01-01

    A study was conducted with a view to identify and quantify the changes in land use and land cover occurred during the last 20 years at Mirzapur Union of Gazipur district of Bangladesh using remote sensing and GIS technologies. Two LANDSAT TM images of 1989 and 2009 with 30mx30m spatial resolution were used to determine the temporal land cover changes. Subsequently, a ground verification was done in the study site. The study revealed that forest cover was decreased by 20.29 % and settlement area was found to increase by 28.64% and water bodies was decreased by 6.25 %. In the same period of time, bare land was found to increase by 20.91 % due to the effect of clearing of forest area which is not replanted again. A lot of new infrastructures has been built by this time. Population pressure becomes double enhancing the deforestation of Sal (Shorea robusta). Most prominent features are the emergence of brick fields and various industries. Thus, the above study demonstrated the usefulness of RS and GIS technology regarding resource management and urban planning

  18. Detection of Land Use/Land Cover Changes and Urban Sprawl in Al-Khobar, Saudi Arabia: An Analysis of Multi-Temporal Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Muhammad Tauhidur Rahman

    2016-02-01

    Full Text Available While several studies examined land use and land cover changes in the central and western parts of Saudi Arabia, this study is the first to use remote sensing data to examine the decadal land cover changes in Saudi Arabia’s eastern coastal city of Al-Khobar between 1990 and 2013. Specifically, it utilized ISODATA classification method to classify Landsat TM, ETM+, and OLI data collected from 1990, 2001, and 2013 and then detected changes in the land cover within the study area. It then measured urban sprawl by calculating the relative Shannon’s entropy index values for the three years. With overall classification accuracies greater than 85%, the results show that urban built-up areas increased by 117% between 1990 and 2001 and 43.51% from 2001 to 2013. Vegetation increased by 110% from 1990 to 2001 and by 52% between 2001 and 2013. The entropy index values of 0.700 (1990, 0.779 (2001, and 0.840 (2013 indicates a high rate of urban sprawl and the city dispersing near the outskirts and towards the neighboring cities of Dhahran and Dammam. Future studies should examine the current challenges faced by the city’s residents due to urban expansion and attempt to find ways to resolve them in the near future.

  19. 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

    2017-11-01

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

  20. Rain detection over land surfaces using passive microwave satellite data

    NARCIS (Netherlands)

    Bauer, P.; Burose, D.; Schulz, J.

    2002-01-01

    An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

  1. Surface soil moisture retrievals from remote sensing: Current status, products & future trends

    Science.gov (United States)

    Petropoulos, George P.; Ireland, Gareth; Barrett, Brian

    Advances in Earth Observation (EO) technology, particularly over the last two decades, have shown that soil moisture content (SMC) can be measured to some degree or other by all regions of the electromagnetic spectrum, and a variety of techniques have been proposed to facilitate this purpose. In this review we provide a synthesis of the efforts made during the last 20 years or so towards the estimation of surface SMC exploiting EO imagery, with a particular emphasis on retrievals from microwave sensors. Rather than replicating previous overview works, we provide a comprehensive and critical exploration of all the major approaches employed for retrieving SMC in a range of different global ecosystems. In this framework, we consider the newest techniques developed within optical and thermal infrared remote sensing, active and passive microwave domains, as well as assimilation or synergistic approaches. Future trends and prospects of EO for the accurate determination of SMC from space are subject to key challenges, some of which are identified and discussed within. It is evident from this review that there is potential for more accurate estimation of SMC exploiting EO technology, particularly so, by exploring the use of synergistic approaches between a variety of EO instruments. Given the importance of SMC in Earth's land surface interactions and to a large range of applications, one can appreciate that its accurate estimation is critical in addressing key scientific and practical challenges in today's world such as food security, sustainable planning and management of water resources. The launch of new, more sophisticated satellites strengthens the development of innovative research approaches and scientific inventions that will result in a range of pioneering and ground-breaking advancements in the retrievals of soil moisture from space.

  2. Optimal use of land surface temperature data to detect changes in tropical forest cover

    Science.gov (United States)

    Van Leeuwen, T. T.; Frank, A. J.; Jin, Y.; Smyth, P.; Goulden, M.; van der Werf, G.; Randerson, J. T.

    2011-12-01

    Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the build up of atmospheric CO2. Here we examined different ways to use remotely sensed land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05×0.05 degree Terra MODerate Resolution Imaging Spectroradiometer (MODIS) observations of LST and PRODES (Program for the Estimation of Deforestation in the Brazilian Amazon) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10×10 degree included most of the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (~1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pan-tropical deforestation classifiers. Combined with the normalized difference vegetation index (NDVI), a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST difference decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES. The use of day-night LST differences may be particularly valuable for use with satellites that do not have spectral bands that allow for the estimation of NDVI or other vegetation indices.

  3. NODC Standard Format Coastal Ocean Wave and Current (F181) Data from the Atlantic Remote Sensing Land/Ocean Experiment (ARSLOE) (1980) (NODC Accession 0014202)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains time series coastal ocean wave and current data collected during the Atlantic Remote Sensing Land/Ocean Experiment (ARSLOE). ARSLOE was...

  4. A Surface-Mounted Rotor State Sensing System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A surface-mounted instrumentation system for measuring rotor blade motions on rotorcraft, for use both in flight and in wind tunnel testing, is proposed for...

  5. Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K; Zhang, H

    2005-12-01

    This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and

  6. Comparative influence of land and sea surfaces on the Sahelian drought: a numerical study

    Directory of Open Access Journals (Sweden)

    Arona Diedhiou

    Full Text Available The aim of this work is to compare the relative impact of land and sea surface anomalies on Sahel rainfall and to describe the associated anomalies in the atmospheric general circulation. This sensitivity study was done with the Météo-France climate model: ARPEGE. The sensitivity to land surface conditions consists of changes in the management of water and heat exchanges by vegetation cover and bare soil. The sensitivity to ocean surfaces consists in forcing the lower boundary of the model with worldwide composite sea surface temperature (SST anomalies obtained from the difference between 4 dry Sahel years and 4 wet Sahel years observed since 1970. For each case, the spatiotemporal variability of the simulated rainfall anomaly and changes in the modelled tropical easterly jet (TEJ and African easterly jet (AEJ are discussed. The global changes in land surface evaporation have caused a rainfall deficit over the Sahel and over the Guinea Coast. No significant changes in the simulated TEJ and an enhancement of the AEJ are found; at the surface, the energy budget and the hydrological cycle are substantially modified. On the other hand, SST anomalies induce a negative rainfall anomaly over the Sahel and a positive rainfall anomaly to the south of this area. The rainfall deficit due to those anomalies is consistent with previous diagnostic and sensitivity studies. The TEJ is weaker and the AEJ is stronger than in the reference. The composite impact of SST and land surfaces anomalies is also analyzed: the simulated rainfall anomaly is similar to the observed mean African drought patterns. This work suggests that large-scale variations of surface conditions may have a substantial influence on Sahel rainfall and shows the importance of land surface parameterization in climate change modelling. In addition, it points out the interest in accurately considering the land and sea surfaces conditions in sensitivity studies on Sahel rainfall.

  7. Comparative influence of land and sea surfaces on the Sahelian drought: a numerical study

    Directory of Open Access Journals (Sweden)

    A. Diedhiou

    1996-01-01

    Full Text Available The aim of this work is to compare the relative impact of land and sea surface anomalies on Sahel rainfall and to describe the associated anomalies in the atmospheric general circulation. This sensitivity study was done with the Météo-France climate model: ARPEGE. The sensitivity to land surface conditions consists of changes in the management of water and heat exchanges by vegetation cover and bare soil. The sensitivity to ocean surfaces consists in forcing the lower boundary of the model with worldwide composite sea surface temperature (SST anomalies obtained from the difference between 4 dry Sahel years and 4 wet Sahel years observed since 1970. For each case, the spatiotemporal variability of the simulated rainfall anomaly and changes in the modelled tropical easterly jet (TEJ and African easterly jet (AEJ are discussed. The global changes in land surface evaporation have caused a rainfall deficit over the Sahel and over the Guinea Coast. No significant changes in the simulated TEJ and an enhancement of the AEJ are found; at the surface, the energy budget and the hydrological cycle are substantially modified. On the other hand, SST anomalies induce a negative rainfall anomaly over the Sahel and a positive rainfall anomaly to the south of this area. The rainfall deficit due to those anomalies is consistent with previous diagnostic and sensitivity studies. The TEJ is weaker and the AEJ is stronger than in the reference. The composite impact of SST and land surfaces anomalies is also analyzed: the simulated rainfall anomaly is similar to the observed mean African drought patterns. This work suggests that large-scale variations of surface conditions may have a substantial influence on Sahel rainfall and shows the importance of land surface parameterization in climate change modelling. In addition, it points out the interest in accurately considering the land and sea surfaces conditions in sensitivity studies on Sahel rainfall.

  8. Impacts of Land Use on Surface Water Quality in a Subtropical River Basin: A Case Study of the Dongjiang River Basin, Southeastern China

    Directory of Open Access Journals (Sweden)

    Jiao Ding

    2015-08-01

    Full Text Available Understanding the relationship between land use and surface water quality is necessary for effective water management. We estimated the impacts of catchment-wide land use on water quality during the dry and rainy seasons in the Dongjiang River basin, using remote sensing, geographic information systems and multivariate statistical techniques. The results showed that the 83 sites can be divided into three groups representing different land use types: forest, agriculture and urban. Water quality parameters exhibited significant variations between the urban-dominated and forest-dominated sites. The proportion of forested land was positively associated with dissolved oxygen concentration but negatively associated with water temperature, electrical conductivity, permanganate index, total phosphorus, total nitrogen, ammonia nitrogen, nitrate nitrogen and chlorophyll-a. The proportion of urban land was strongly positively associated with total nitrogen and ammonia nitrogen concentrations. Forested and urban land use had stronger impacts on water quality in the dry season than in the rainy season. However, agricultural land use did not have a significant impact on water quality. Our study indicates that urban land use was the key factor affecting water quality change, and limiting point-source waste discharge in urban areas during the dry season would be critical for improving water quality in the study area.

  9. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-01-01

    Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

  10. Ion-step method for surface potential sensing of silicon nanowires

    NARCIS (Netherlands)

    Chen, S.; van Nieuwkasteele, Jan William; van den Berg, Albert; Eijkel, Jan C.T.

    2016-01-01

    This paper presents a novel stimulus-response method for surface potential sensing of silicon nanowire (Si NW) field-effect transistors. When an "ion-step" from low to high ionic strength is given as a stimulus to the gate oxide surface, an increase of double layer capacitance is therefore expected.

  11. Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

    Science.gov (United States)

    Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

    2017-12-01

    Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land gr