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Precise coastal shoreline mapping is essential for monitoring changes in erosion rates, surface hydrology, and ecosystem structure and function. Monitoring water bodies in the Arctic National Wildlife...
Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural...
Remote sensing techniques provide efficient and cost-effective approach to monitor the expansion of built-up area, in comparison to other traditional approaches. For extracting built-up class, one of ...
Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the para...
Heavy metal stress will induce the change of the bio-parameters like chlorophyll, nitrogen and water content of rice. In this paper, we analyzed the traditional spectral index which has strong relatio...
Soil Organic Carbon (SOC) has been identified as one of the major C sinks in the global carbon cycle, of which the exact size and spatial distribution are still difficult to determine quantitatively....
Considering a forest cover (Balsam Fir with various densities) we analyze the sensitivity of several vegetation indices to ozone absorption using physical simulations in the spectral bands of MODIS,...
Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) covers a wide spectral region with 14 bands from visible to the thermal infrared. The different band ranges can be capable of d...
While high-resolution remote sensing images have increased application possibilities for urban studies, the large number of shadow areas has created challenges to processing and extracting informati...
Abstract: The Tibetan Plateau holds clues to understanding the dynamics and mechanisms associated with continental growth. Part of the region is characterized by zones of ophiolitic melange believed t...
Prediction of stellar atmospheric parameters from spectra, spectral indices and spectral lines using machine learning。
DIFFERENTIAL SPECTRAL INDICES OF RADIO SPURS BETWEEN 38,408 AND 1420 MHz。

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