Remotely sensed imagery has an enhanced capability of extracting information about small image structures (both artificial and natural objects). Fast, low cost, accurate and spatially rich data can be acquired via remote sensing technology. For this reason, satellite image mapping is quite common technique and image maps provide a great contribution to cartography and Geographic Information Sys...

The main aim of this study is to investigate the suitability of 1) combining map data derived from the Landsat satellite and other sources with statistical methods for analyzing habitat selection and making probability maps for large areas, and 2) testing a sampling design where volunteers arbitrarily select a walking route within specific areas for conducting transects surveys of wildlife. We ...

An algorithm for lossy compression of scanned map images is proposed. The algorithm is based on color quantization, efficient statistical context tree modeling and arithmetic coding. The ratedistortion performance is evaluated on a set of scanned maps and compared to JPEG2000 lossy compression algorithm, and to ECW, which is a commercially available solution for compression of satellite and aer...

there are various methods and models for land evaluation. these methods are classified according to the number of used resources. the best resources capabilities or potentials and land use can be found by analyzing one of the main resources, in the lands close relations to ecologic resources exist. soil has a great potential for introducing the studied region specifications. hence, it challenge...

Image segmentation is a major research area due to its extensive usage and application in the area of computer vision. It is the basis of Image analysis and understanding. Satellite Image segmentation is a challenging and tough task due to the inherent nature of the image. A wide variety of various segmentation techniques for colour satellite images have been developed. Here, we come up with an...