potential of modis images and contextual algorithm for active fire detection in the zagross forests, west of iran

moderate resolution imaging spectroradiometer (modis) have been widely used for active fire detection in the world as the specific channels used for the fire detection have made the modis images applicable. the main objective was to explore the capability of modis images for active fire detection in the zagross forests using the modis contextual algorithm. the study was performed in the marivan forests located in the zagross forests, west of iran. details of 20 reference fires occurred in the study areas were acquired and imported to gis. modis images of fire days as well as the previous and past days of fires were collected. the aqua images were obtained from the l1b level, which was suitable for using in this algorithm whereas terra images were obtained from pds format and then preprocessed to the l1b. modis images were processed for active fire detections using modis contextual algorithm. modis active fire detections were compared with reference fires. the results revealed that six reference fires were found. in addition, four fires were detected by images not included in the 20 reference fires. finding the location of these four fires on the 1:25000 topographic maps showed that they have happened in urban areas. the shorter duration and lower temperature of fires during the data acquisition was probably the main reason in failing fire detection. thirty percent of all reference fires were detected which may help to prevent more losses. it can be concluded that modis images provide a valuable source of information concerning the fire activity in the zagross forests; however, the contextual algorithm was not successful in the detection of forest fires. we recommend that modis contextual algorithm can be used in the zagross forests, however, complementary research, should be carried out for development a regional fire detection algorithm in this area.