A SYSTEM WITH PREDICTIVE LEAST-SQUARES MATHEMATICAL-MODELS FOR MONITORING WILDLIFE CONSERVATION SITES USING GIS AND REMOTELY-SENSED DATA

Today there is a worldwide trend towards protecting the environment an d its natural resources. This goal is achieved using different procedu res and techniques. Remote sensing and geographical information system s, however, are two of the most suitable techniques for monitoring, an alysing, and managing Earth resources. Conserved natural areas for wil dlife is one of the most important natural resources that should be ex plored using GIS and RS technologies. In this study, a prototype GIS t hat can integrate remotely-sensed data to monitor conservation areas ( for wildlife) in arid and semi-arid regions is developed. The system u ses TM images and other heuristic information to perform its analysis and prediction. Future change in land-cover is anticipated by mathemat ical models. The mathematical models are developed by this study based on the concepts of least-squares theories and techniques. The system is operational. It is tested using an area in Saudi Arabia. The obtain ed results showed that the system is accurate.