Titlebook: Remote Sensing Applications in Environmental Research; Prashant K. Srivastava,Saumitra Mukherjee,Tanvir I Book 2014 Springer International

GROSS

Remote Estimation of Land Surface Temperature for Different LULC Features of a Moist Deciduous Tropi covered with vegetation show minimum temperatures; while barren and exposed land shows high values. Built-up land generally has higher LST, but when dispersed in small pockets in the forests, the LST value decreases as revealed in the results.

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2194-9204 development.Applicable to natural disaster management.Inclu.Remote Sensing Applications in Environmental Research .is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in

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DAUNT

Sensitivity Exploration of SimSphere Land Surface Model Towards Its Use for Operational Products Devtural processes of the Earth as well as how the different components of the Earth system interplay. However, before applying any modelling approach in performing any kind of analysis or operation, a variety of validatory tests needs to be executed to evaluate the adequacy of the developed “model” in

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Remote Estimation of Land Surface Temperature for Different LULC Features of a Moist Deciduous Tropiurface emissivity for a moist deciduous tropical forest area of Munger forests (Bihar, India). Surface emissivity values derived from NDVI are directly used for LST estimation. LST varies spatially due to the complexity of land surface cover features and helps in land-use/land-cover profiling. Areas

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Geospatial Strategy for Estimation of Soil Organic Carbon in Tropical Wildlife Reserven the research area of the global carbon cycle as it is the largest terrestrial carbon pool. Geospatial and various forest inventory approaches were used during study for statistical correlation between estimated and predicted value. Remote sensing plays a vital role in spatial data acquisition of t

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A Comparative Assessment Between the Application of Fuzzy Unordered Rules Induction Algorithm and J4ensemble technique) in comparison with Decision Tree model for spatial prediction of shallow landslides in the Lang Son city area (Vietnam). First, a landslide inventory map was constructed from various sources. Then, the landslide inventory was randomly partitioned into 70 % for training the models