Supervised/ Unsupervised Classification of LULC using remotely Sensed Data for Coimbatore city, India

The Landuse / Landcover system espoused by almost all Organisations and scientists, engineers and remote sensing community who are involved in mapping of earth surface features, is a system which is derived from the united States Geological Survey (USGS) LULC classification system. The application of RS and GIS involves determining of homogeneous zones, trend analysis of land use integration of new area changes or change detection etc., National Remote Sensing Agency(NRSA) Govt. of India has devised a generalized LULC classification system respect to the Indian conditions based on the various categories of Earth surface features , resolution of available satellite data, capabilities of sensors and present and future applications. The profusion information of the earth surface offered by the high resolution satellite images for remote sensing applications. Using change detection methodologies to extract the target changes in the areas from high resolution images and rapidly update geodatabase information processing. Traditionally, classification approaches have focused on per-pixel technologies. Pixels within areas assumed to be automatically homogeneous are analyzed independently. These new sources of high spatial resolution image will increase the amount of information attainable on land cover. Significance is that the data can be acquired by our eyes and the energy can be analyzed. But satellites are capable of collecting data beyond the visible band also However, the traditional method of change detection are not suitable for high resolution remote sensing images. To overcome the limitations of traditional pixel-level change detection of high resolution remote sensing images, based on georeferencing and analysis method, this paper presents a unsullied way of multi-scale amalgamation for the high resolution remote sensing images change detection. Experiment shows that this method has a stronger advantage than the traditional pixel-level method of high resolution remote sensing image change detection. General terms Landcover, Landuse, Analysis, Indian conditions