Forest fire analysis with remote sensing data
Forest fires cause major damage to the environment, human health and property, and endanger life. Fires can be monitored and analysed over large areas in a timely and cost-effective manner by using satellite sensor imagery in combination with spatial analysis as provided by Geographical Information Systems (GIS). In this study, the forest area damage caused by a large fire which occurred in the Marmaris, province of Mugla in July 1996 was analysed using satellite sensor images. Digital image processing methods, such as spectral profile analysis, vegetation indices and multispectral classification, were applied to the satellite sensor images acquired before and after the forest fire. Besides the conventional maximum likelihood classification algorithm, a multilayer feed-forward neural network architecture was also used for comparison and evaluation of its effectiveness. A GIS database was constructed from the raster (satellite sensor data), vector (the forest type and topographical maps) and ancillary data (meteorological data). The GIS is being used to develop an information and decision support system to monitor and predict forest fire activity, and to enhance fire management efficiency. This study highlights the deficiencies in the current approach to fire management and emphasizes the need for an improved method along the lines outlined.