|
Estimation of forest parameters through Fuzzy classification of TM Data
 Maisam Toosi M.sc. Student, Dept. of Remote Sensing Eng. Email: maisam_toosi@yahoo.com M. J. Valadan Zouj Assistant Professor, Dept. of Remote Sensing Eng. Email: valadan_zouj@kntu.ac.ir Address: faculty of Geodesy and Geomatic Eng., K. N. TOOSI University of Technology Vali Asr St., Vanak Sq., Tehran, Iran, Post Box: 15875-15433 Fax: ++98 21 878 6213, Tel: ++ 98 21 877 9473-5 Abstract Several studies have investigated the utility of Landsat 5 TM imagery to estimate forest parameters such as stand composition and density. Regression equations have generally been used to relate these parameters to the radiance responses of the TM channels. Such method is not feasible in highly complex landscapes, where forest mixtures and terrain irregularities may obscure the existence of simple relationships. In the current paper a fuzzy approach to the problem is presented. First, some typical forest plots with known features are spectrally identified. A maximum likelihood fuzzy classification is apply to the study image, so as to derive fuzzy membership grades for all pixels with respect to the typical plots. Finally, these grades are used to compute the estimates of the forest parameters by a weighted average strategy. One TM scene and accurate ground references taken in summer 1987 was utilitilized for the testing. For comparison results first, with PCI Geomatica software (8.1 ver) with supervise classification with maximum likelihood approach were used. Also this image has investigated by fuzzy approach for the testing. The first results statistically are quite encouraging. |