Use of vegetation indexes and PCA method with remote sensing data for the classification of burnt areas according to how many times they have been burnt

Abstract

The objective of this study was to process multitemporal satellite data in order to detect burnt areas and classify these areas according to how many times they have been burnt. The area of study is situated in Western Peloponnese near the site of Ancient Olympia. In 1986, 1998 and 2000 three big fires have burnt more than 500.000.000 m2 of forest and rural land in the broader area. In order to detect the vegetation changes and classify the burnt areas for the period 1984-1999 we used the following multitemporal satellite images: A Landsat 5 TM cloud free subscene, acquired on July 27 1984, A Landsat 5 TM cloud free subscene, acquired on September 18 1986, A Landsat 7 ETM cloud free subscene, acquired on July 28 1999, We applied the NDVI (Normalized Difference Vegetation Index) to all the satellite images. Then, we created two new images with two bands each. one using the vegetation indexes images of 1986 and 1984 and a second one using the vegetation indexes images of 1999 and 1986. Then, we applied the PCA method to the new images. After the fires of 1986, 1998 and 2000 local authorities have mapped the burnt areas using traditional methods. With joint use of the thematic maps and the above produced images of Principal Components we managed to classify the burnt areas according to how many times the have been burnt. The general conclusion is that we can use satellite data with the vegetation indexes PCA method for the accurate mapping of burnt areas and the vegetation monitoring. Burnt areas for more than twice cannot be regenerated on its own so the classification of the burnt areas according to how many times they have been burnt is very important in order to locate the areas that needs reforestation.