Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the...

Land use is a dynamic phenomenon that changes with time and space due to anthropogenic pressure and development. Evaluating the existing land use and its periodic change is useful for urban planners, policy makers and natural resource managers. Land use and land cover changes in Mekelle City, Ethiopia (north east Africa) over a period of 25 years was studied using remotely sensed data. Multi te...

Using satellite imagery for the study of Earth's resources is attended by manyresearchers. In fact, the various phenomena have different spectral response inelectromagnetic radiation. One major application of satellite data is the classification ofland cover. In recent years, a number of classification algorithms have been developed forclassification of remote sensing data. One of the most nota...

nowadays, remote sensing comes under the title of management method for precision farming. for provision of the land cover and therefore land use map use must be made of satellite images. for an assessment of the type of agricultural crops it is required to have satellite images of high resolution. from specifications of the satellite images one is to produce maps with varied scales. in this re...

An artificial neural network is a system based on the operation of biological neural networks, in other words, is an emulation of biological neural system. Artificial Neural Networks or simply Neural Networks are powerful general purpose computing tools. They have become popular in the analysis of remotely sensed data, particularly in classification or feature extraction from image data more ac...

The primary objective of this research is to predict and analyze the future urban growth of Dhaka City using the Landsat satellite images of 1989, 1999 and 2009. Dhaka City Corporation (DCC) and its surrounding impact areas have been selected as the study area. At the beginning, a fisher supervised classification method has been applied to prepare the base maps with five land cover classes. In ...

Phrases Clumped 0.62 high spectral resolution 0.56 sea surface temperature S 0.39 emissivity Abstract Phrases Clumped -0.54 full Landsat Thematic Map -0.52 land cover -0.44 Synthetic Aperture Radar -0.43 data sets -0.38 classifications Abstract Phrases Clumped -0.68 High Resolution Radiomete -0.50 difference vegetation ind -0.44 real time -0.38 satellite data Abstract Phrases Clumped -0.59 radi...

A global poverty map has been produced at 30 arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have be...

The CARTO-CHANGE project addresses the harmonization of existing land cover data (Advanced CORINE LC, CORINE LC and GLOBCOVER) and thereby two aspects: Firstly, the cartographic and statistical comparison of land cover information across different scales and resolutions, and secondly the timely identification of candidate land cover changes by using land cover and land use information derived f...