Assessment of the Forest Fire Risk and Its Indicating Significances in Zhaoqing City Based on Landsat Time-Series Images
Author:
Zhou Xia1, Yang Ji12ORCID, Niu Kunlong123, Zou Bishan4, Lu Minjian4, Wang Chongyang12ORCID, Wei Jiayi1, Liu Wei5, Yang Chuanxun1, Huang Haoling1
Affiliation:
1. Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangdong Engineering Technology Center for Remote Sensing Big Data Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China 2. Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China 3. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China 4. Guangdong Xijiang Forest Farm, Zhaoqing 526020, China 5. Guangdong Climate Center, Guangzhou 510080, China
Abstract
An efficient monitoring of forest fire risk and its dynamic changes is an important way to prevent and reduce forest fire hazards. This study integrated the ignition effect of fire sources and the impact of landform into the calculation of forest fire risk using digital-terrain-slope factor, and developed an optimized forest fire risk model (fire-potential-index slope, FPIS). Combined with Landsat 8 satellite images, the study retrieved and analyzed the variations of forest fire risk in Zhaoqing City, Guangdong province, for four consecutive periods in the dry season, 2019. It was found that the high forest fire risk area was mainly distributed in the valley plains of Huaiji district, Fengkai district and Guangning district, the depressions of the Sihui district, and mountain-edge areas of Dinghu district and Gaoyao district, and accounted for 8.9% on 20 October but expanded to 19.89% on 7 December 2019. However, the further trend analysis indicated that the forest fire risk with significant increasing trend only accounted for 6.42% in Zhaoqing. Compared to the single high forest fire risk results, the changing trend results effectively narrowed the key areas for forest fire prevention (2.48%–12.47%) given the actual forest fires in the city. For the four forest fire events (Lingshan mountain, Hukeng industrial area, Xiangang county and Huangniuling ridge forest fires), it was found that the forest fire risk with significant increasing trend in these regions accounted for 26.63%, 35.84%, 54.6% and 73.47%, respectively, which further proved that the forest fire risk changing trend had a better indicated significance for real forest fire events than the high forest fire risk results itself (1.89%–71.69%). This study suggested that the forest fire risk increasing trend could be well used to reduce the probability of misjudgment and improve the accuracy of the early-warning areas when predicting forest fires.
Funder
Guangdong Forestry Science and Technology Innovation Project Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory GDAS’ Project of Science and Technology Development Guangzhou Basic and Applied Basic Research Foundation
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