Remote sensing-based assessment of vegetation damage by a strong typhoon (Meranti) in Xiamen Island, China

Remote sensing is a cost-effective tool for assessing vegetation damage by typhoon events at various scales. Taking Xiamen Island, southeastern China, as a study case, this paper aimed to assess and analyze the vegetation damage caused by Typhoon Meranti landfalling on September 15, 2016, using two high spatial resolution remote sensing images before and after the typhoon event. Seven severely damaged vegetation regions were selected based on the classification of vegetation types and visual interpretation of the images. Regression analysis was used to correct seasonal variation of the two high-solution images before and after typhoon. The vegetation area of the whole of Xiamen Island and the selected seven regions before and after typhoon were then calculated, respectively. Two spectral vegetation indicators, normalized difference vegetation index (NDVI) and fractional vegetation coverage (FVC), were also retrieved for the whole island and the seven regions. By comparing the difference in NDVI values before and after the typhoon of the two high spatial resolution images, we analyzed the most affected vegetation areas, as well as the most seriously damaged vegetation species. The typhoon has caused a decrease in vegetation area by 95.1 ha across the whole Xiamen Island. The mean NDVI and FVC decreased by 0.209 and 13 percentage points, respectively. While, in the seven selected severely damaged areas, the mean NDVI decreased by 0.356–0.444 and FVC decreased by 27–42 percentage points. The visual inspection showed that the tone of typhoon-damaged vegetation became darker, the patches of damaged vegetation became smaller and more fragmented, and the gap between vegetation canopies became larger. The most affected vegetation areas occurred in the southeastern hilly area, Jinshang and Hubin South Roads, as well as the Wuyuan Bay area. The most seriously damaged vegetation type is broad-leaved trees, especially the species, Acacia confusa, Delonix regia, Bauhinia variegata, Chorisia speciosa, Ficus benjamina and F. Concinna.