Analysis of forest loss by Sentinel-1 SAR time series

Abstract

Synthetic Aperture Radar (SAR) has the advantage of operating regardless of the cloud cover or a lack of light. This makes SAR a potential substitution for optical sensors in various ways. SAR images have been effectively used for detecting the various terrain changes, particularly in comparing the terrain before and after natural disasters. In this paper, we compare SAR images to measure the forest loss rate before and after the fire. we analyze the Gangwon-do forest fire which occurred in 2019. SNAP (Sentinels Application Platform) is used in this paper to process Sentinel-1. Pre-processing, post-processing, color manipulation, cropping image was used in the program. Based on the calculated loss rate, we expect that it can be used for other researches such as flood or debris flow. It would be more accurate by using SAR images.