Remotely Sensed Data Processing on Grids by Using GreenLand Web Based Platform

Abstract

Developing applications for analyzing and processing different remotely sensed data is very important for environmental predictions and management strategies. Applications focusing on environmental and natural resource monitoring need large data sets to be processed and fast response to actions. These requirements mostly imply high computing power that can be achieved through the parallel and distributed capabilities provided by the Grid infrastructure. This paper presents the GreenLand application as a user friendly web based platform for the use of environmental specialists engaging remote sensing applications using Grid computing technology. Theoretical concepts and basic functionalities of GreenLand platform were tested in two detailed case studies: a land cover/use determination analysis in Istanbul (Turkey) by conducting vegetation indices and density slice classification on Landsat 5 Thematic Mapper (TM) imagery, and the retrieval of large remote sensing products datasets (The Moderate Resolution Imaging Spectroradiometer (MODIS)) for the entire Black Sea Catchment. All the results of different image processing scenarios used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea Catchment (BSC) area.