Changing patterns and reduction in agricultural land are among the fundamental problems that impacts food security in developing regions like India. Rapid economic growth coupled with increasing populations and changes in climatic patterns are among the main factors impacting availability of agricultural land. On a macroscopic scale, due to the lack of good quality data, governments do not have...

Many researchers conducted the effort for improving the classification accuracy of satellite image. Most of the study has used optical spectral information of each pixel for image classification. By applying this method for high resolution satellite image, number of class became increase. This situation was remarkable for objects in urban area. In this study, we propose the method for extractin...

Automatic image classification often fails at separating a large number of land cover classes that punctually may present similar spectral reflectances. To improve the classification accuracy in such situations, multi-temporal satellite data has proven to be valuable auxiliary information. In this paper, we present a study exploring the usefulness of intra-annual satellite images timeseries for...

Mega-city analysis with very high resolution (VHR) satellite images has been drawing increasing interest in the fields of city planning and social investigation. It is known that accurate land-use, urban density, and population distribution information is the key to mega-city monitoring and environmental studies. Therefore, how to generate land-use, urban density, and population distribution ma...

The growing use of Geographic Information Systems (GIS) has led to new research opportunities in the application of satellite imagery to urban analysis. The information content of such images is a function of the combined influence of the radiometric, spatial, and spectral resolution of the sensor. The different bands of satellite sensors are recorded synchronously so that their pixels may be p...

For land cover classification and urban area analysis remote sensing techniques are gaining more importance. Numerous remote sensing techniques have been developed for analyzing the satellite images. The launch of Worldview-2 satellite with resolution of 0.5 m signaled the advent of high resolution satellite images. Such images offer an exciting possibility for feature extraction as well as com...

In this paper we have proposed a symmetric, positive semi definite kernel function for support vector machine classifier. Pixel classification is a form of supervised image segmentation where the actual object classes present in the image are known a priori. In case of satellite image, this prior information plays a huge role to estimate the actual statistics of different land covers. The state...

Preparation of land cover / land use maps for large areas, based on automatic classification of high-resolution satellite data is the objective of many application programmes, e.g. GSE Land Monitoring Services. The crucial point for this kind of activity is to apply optimal classification approach, which will ensure high class recognition accuracy and classification repeatability. Among differe...

This paper investigates the image-based characterization of the land mobile satellite (LMS) channel. For a comprehensive multi-satellite model, a traditional measurementbased approach is not feasible due to the lack of available satellites at all possible orbital positions and the drawbacks of the measurement system when a high gain tracking antenna is involved (e.g. Ka/Ku band). To overcome th...