Investigetion of Possibility of Forest Type Classification using ASTER data From Terra (Case Study: Field 38 in Northern Forests of Country)

Nowaday, satellite data are the main tools of cycle measurement for collecting information and preparation of maps.Attempt was made ,in addition to the presentation of a method for expansion of the forest in mountainous areas and classification of the forest type, to study the above-mentioned satellite information ability in this research by the use of this type of information. In this study, data from 12 th of June, 2004 related to 38 districts of the country's north forests were used. Initially, data quality and available errors with respect to type and their amount were studied Then, they were used to correct errors resulted from ups and down of Digital Elevation Model (DEM) using 102 point as ground control points (GCP) with the accuracy of less than 0/8 for use in the action of the geometric images match simultaneously. Next, by the use of methods of achieving ratio, filtering and analyzing main elements of new artificial bands of the collecting and classification in the form of one step or multi-step supervision were done by the strategies of the minimum distance of parallel piped, maximum likelihood, mahalanobis distance, spectoral anglemapper, binary encoding, neural net and density slicing. By selction of training areas of the given classes and by the help of the minimum and maximum diagrams and average of these areas for each class in each band, the best channel to enter the classification and achieving the best results were selected. Afterwards, by separation of forest category from non-forest one, action was taken to prepare a map, so that the accuracy of the resulted maps of the classification by the strategies of the parallel piped and minimum distance of mahalanobis, among other algorithms, was more than the others, This suggests that ASTER data, according to the applied method, do not have a relatively good capability to study and examine the forest classification in this mountainous area.