Reproduction of Remote Sensing Image Using Supervised Mode of Learning Using Artificial Neural Network
DOI:
https://doi.org/10.24297/ijct.v13i9.2356Keywords:
Light Detection and Ranging (LIDAR), Geographic Information System (GIS), Artificial Neural Network (ANN), Mean Square Error (MSE), Matrix Laboratory (MATLAB), Support Vector Machines (SVM).Abstract
Remote sensing is the science of gathering information from a location that is distant from the source. Image analysis is the technique of extracting and interpreting meaningful information from a remotely sensed image. The information from an image may be extracted with the help of computer software or be visually considered. Images like such can be acquired in the form of aerial photograph, a multispectral satellite image, Light Detection and Ranging data, a radar data or a thermal image. Remote sensing is a dynamic technical field of endeavor. This paper is based on the technique involved in mapping of Geographic Information System projects.