Spatially continuous surface air temperature (SAT) is of great significance for various research areas in geospatial communities, and it can be reconstructed by the SAT estimation models that integrate accurate point measurements at ground sites with wall-to-wall datasets derived from remotely sensed observations spaceborne instruments. As land (LST) strongly correlates SAT, are typically devel...

Urban sprawl is one of the main problems that threaten the limited highly fertile land in the Nile Delta of Egypt. In this research, satellite images Landsat TM 1993, ETM+ 2001 and Egypt Sat-1, 2009 has been used to study the urban sprawl and its impact on agricultural land in Qalubiya Governorate. Maximum likelihood supervised classification and post-classification change detection techniques ...

Researchers have noted that current water quality protection strategies, like nutrient management plans, lack a sound hydrological underpinning for pollutant transport processes. This is especially true for areas like the northeastern U.S. where copious research has shown that variable source area hydrology largely governs runoff generation. The goal of this study was to develop a scientificall...

Abstract A super-large ensemble simulation dataset with 110 members has been produced by the fully coupled model FGOALS-g3 developed researchers at Institute of Atmospheric Physics, Chinese Academy Sciences. This is first large simulations a climate system modeling center. The largest realizations up to now worldwide in terms single-model initial-condition ensembles. Each member includes histor...

Abstract. Surface air temperature (SAT) is a key indicator of global warming and plays an important role in glacier melting. On the Tibetan Plateau (TP), there exists large number glaciers. However, station SAT observations on these glaciers are extremely scarce, moreover available ones characterized by short time series, which substantively hinder our deep understanding dynamics due to climate...

The major aim of processing satellite images is to prepare topical and effectivemaps. The selection of appropriate classification methods plays an important role. Amongvarious methods existing for image classification, artificial neural network method is ofhigh accuracy. In present study, TM images of 1987, and ETM+ images of 2000 and 2006were analyzed using artificial fuzzy ARTMAP neural netwo...