Paper
11 October 2023 Extraction of burned area and monitoring of vegetation restoration in Qipan Mountain
Yuntao Ma, Mingyi Yang, Shufang Gong
Author Affiliations +
Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128004J (2023) https://doi.org/10.1117/12.3003960
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China
Abstract
In this paper, the burned area of Qipan Mountain was selected as the research area where a fire disaster occurred on April 17, 2019. The data of OLI from Landsat-eight were selected as research data. The remote sensing index of NDVI, NBR and dNBR were used to analyze the burned area. The burned area was extracted, and the fire severity was graded through visual interpretation and threshold segmentation. The following conclusions were drawn from the research: (1) The spectral characteristics of the burned area were distinctly different in the NIR band and SWIR band compared with other types of ground objects. The remote sensing index composed of NIR band and SWIR band could accurately extracted the burned area. (2) The most accurate remote sensing remote index for extracting the burned area was dNBR, with an extraction accuracy of more than 90%. (3) The burned area was graded into four levels according to the damage degree. They were the unburned, the lightly burned, the moderately burned, and the severely burned. The area of the fire severity levels covered separately 367.9 hm2, 443.9 hm2, 309.9 hm2 and 268.8 hm2. (4) The vegetation in different fire severity levels was recovered variously after the fire disaster. Two years later, the vegetation throughout the fire area had been restored about 30% and the severely burned areas had disappeared completely.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yuntao Ma, Mingyi Yang, and Shufang Gong "Extraction of burned area and monitoring of vegetation restoration in Qipan Mountain", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128004J (11 October 2023); https://doi.org/10.1117/12.3003960
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KEYWORDS
Remote sensing

Forest fires

Fire

Vegetation

Short wave infrared radiation

Near infrared

Earth observing sensors

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