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An Improved Forest Fire Monitoring Algorithm With Three-Dimensional Otsu

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成果类型:
期刊论文
作者:
Deng, Zhao;Zhang, Gui
通讯作者:
Zhang, G.
作者机构:
[Zhang, Gui; Deng, Zhao] Cent South Univ Forestry & Technol, Sch Forestry, Changsha 410004, Peoples R China.
通讯机构:
[Zhang, G.] S
School of Forestry, China
语种:
英文
关键词:
3D Otsu algorithm;adaptive dynamic threshold;brightness temperature;forest fires monitoring;Himawari-8 geostationary satellite;image segmentation
期刊:
IEEE ACCESS
ISSN:
2169-3536
年:
2021
卷:
9
页码:
118367-118378
基金类别:
This work was supported in part by the Science and Technology Innovation Platform and Talent Plan Project of Hunan Province under Grant 2017TP1022, and in part by the Emergency Management Science and Technology Project of Hunan Province under Grant 2020YJ007.
机构署名:
本校为第一机构
院系归属:
林学院
摘要:
Forest fires can destroy millions of acres of land at shockingly fast speeds. The forest fire points identification algorithm is the most critical step in the forest fire monitoring process. Most traditional forest fire monitoring methods use fixed thresholds, ignoring background pixels, and have low recognition rates, which could lead to many problems, such as false reporting and low recognition rate. This paper proposes and tests an adaptive forest fire points identification algorithm using Himawari-8 data. By calculating the three-dimensional histogram of brightness temperature, an adaptive...

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