Estimation of Growth Rate of Davanagere District using Multispectral Image using ENVI 4.7

"Remote sensing (RS) in earth’s perspective is the process of obtaining information about the earth surface features without being in direct contact with it, but using on board camera systems or sensors from the satellite platform. The data collected by these sensors are in the form of Electro Magnetic Energy (EME) which are emitted or reflected by the object at different wavelengths depending upon the object’s physical properties. In addition, objects emit radiation depending upon their temperature and emissivity. Every pixel of the digital RS data represents an average value of the EM energy and is recorded as a Digital Number (DN) ranging from 0 to 255 in 8-bit data format. The recorded energy at different wavelengths follows a pattern which is the characteristic of the object and is known as the spectral signature of the object of class. This paper focuses mainly on urban environment and its classification. The urban context is highly complex, as cities consist of a large number of structures of different size and shapes. Most of the conditions and processes are related to space. Thus, for measuring, analyzing and classifying the urban context panchromatic high-resolution data from urban areas using morphological and neural approaches is investigated. As one data source, remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their changes over time, at various spatial and temporal scales. The proposed approach is applied in experiments on high-resolution US remote sensing data from urban areas. "