Spatial clustering has been widely applied in various applications, especially in remote sensing technology. Clustering the geographical nature of the remote sensing imagery is challenging due to its wide and dense spatial distribution. Renowned clustering algorithms such as k-means and other probabilistic clustering algorithms have been reported in the literature. However, they are not robust ...

Hyperspectral Imagery Sensing (HIS) is widely gained tremendous popularity in many research areas such as remotely sensed satellite imaging and aerial reconnaissance. HIS is an important technique with the measurement, analysis, and interpretation of spectra acquired sensing scene an airborne or satellite sensor. The development of sensor technology brought the developing of collecting image da...

Dimension reduction (DR) refers to removing data from a given set, in such a way as to have the possibility of extricating desired intelligent messages embedded in that set, by making an appropriate analysis of the remaining smaller set. Remote sensing is a means of collecting data about objects without coming in contact with them. These two ideas have been quantified in many ways; and they are...

Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate...

In the recent years we are witness of the permanent change in the climate. There a lot of regions victim of rainfalls and fires caused undesired landslides, defoliation and destruction of the landscapes. These phenomena pertain to climatologically destructive factors which have different manifestation during the seasons. Along with the progress of space technology, and the maturity of remote se...

Sharing spatial data derived from remote sensing is a very significant thing. Grid computing and Web Service technology provides fundamental support for it. In this paper we mainly discuss architecture and middleware of sharing spatial data derived from remote sensing and processing. Because middleware of automatically transferring and task execution on grid is the key of the architecture, we s...