Title: Forest fire identification method of UAV remote sensing image based on FCM clustering algorithm

Authors: Peiran Li; Yuqing Tan; Wei He; Haifeng Zhang; Zhanlan Xie

Addresses: State Grid Qinghai Electric Power Company, Xi'ning, 810008, China ' Qinghai Sanxin Rural Power Co., Ltd., Xi'ning, 810000, China ' Guoluo Power Supply Company of State Grid Qinghai Electric Power Company, Guoluo, 814000, China ' Guoluo Power Supply Company of State Grid Qinghai Electric Power Company, Guoluo, 814000, China ' Qinghai Sanxin Rural Power Co., Ltd., Xi'ning, 810000, China

Abstract: In order to overcome the problems of low recognition accuracy and speed in traditional forest fire recognition methods, the paper proposes a forest fire recognition method based on unmanned aerial vehicle remote sensing images using FCM clustering algorithm. Firstly, the FCM clustering algorithm is used to cluster and segment the target RGB pixels in unmanned aerial vehicle remote sensing images. Secondly, according to the calculation rules of the LPB algorithm, the flame characteristics of forest fires are calculated. Finally, the optimal hyperplane of SVM is used to judge whether the target RGB pixels in the remote sensing image are fire pixels, and the forest fire recognition method can be obtained after traversing all pixels. The experimental results show that the fire location identified by this method is completely consistent with the actual situation, and the recognition rate can reach a maximum of 52 frames/s.

Keywords: FCM clustering algorithm; UAV remote sensing image; forest fire awareness; flame characteristics.

DOI: 10.1504/IJRIS.2025.146936

International Journal of Reasoning-based Intelligent Systems, 2025 Vol.17 No.2, pp.114 - 121

Received: 01 Feb 2023
Accepted: 15 May 2023
Published online: 27 Jun 2025 *

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