Journal of Spatial Analysis

Forest fire is one of the important problems in Iran which is caused by different factors such as human and natural factors. One of these factors is climate conditions that can be created by heat wave and special circulation of atmospheric phenomena. Occurrence of forest fire in north of Iran have different impacts on environment such as destruction of natural. According to the position of Iran in the dry climate zone provides required conditions for this hazard. Unfortunately,every year thousands of hectares of precious green cover is burned. Forest fires have harmful effects on human life directly,or in directly and lead to environmental destruction and pollution, global warming, loss of vegetation, and dry soil erosion. As a result, research on forest fires will become necessary. The study region is Mazandaran province forests located  in north of Iran with area of  23756.4 square Kilometers.The main object of this study is to detect the forest fires using satellite data and associated analysis with synoptic approach based on weather maps.

To detect fire in the study area different satellite data such as  synchronized and geostationary satellite data were used. In this study, MODIS satellite imagery and global algorithm detection of fire to detect fire in the forest and meadows of Mazandaran province were used. The climate data including weather station data and weather map were used. Other data include data of LST and vegetation products of MODIS. In order to downscale the global data an appropriate threshold was defined. In the proposed method,  After geometric correction and radiometric the cloud mask was removed, And then fire potential was identified with different thresholds and tests. Three fire episodes of  Savadkooh 2006, Noor , 2009 , and Behshahr, 2010 were selected for study.

Results showed  a threshold value of 310 ° K for MODIS sensor band 22 is good for a global scale. Cold and small fires are not detected, Therefore Local threshold was used. In addition, surface temperature and vegetation mapping , chlorophyll amount of vegetation were used before and after the fire episode.It became apparent that the amount of chlorophyll was reduced and the temperature was increased after the fire.

   The synoptic maps of the fire day showed a low pressure over the region and mid level systems indicated the advection of warm air over the area. Surface stations showed the increase of temperature and reduction of moisture during the fire days over the long period mean values.

According to the results of the study the ground level data accompanied the upper level images and pressure patterns.

Universal high performance of fire detection algorithm was used  to identify areas of forest fires Using MODIS satellite images and global algorithm modified to suit the characteristics of the study area fire detection. Then three of the fires were identified with this method. The algorithms with MODIS images and weather data together indicated the validity of the study and performance of this algorithm to identify the location of fire in the study region. Therefore the method of this study can be used in other areas to detect forest fires.