Forest fire identification method of UAV remote sensing image based on FCM clustering algorithm
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.
Authors
- Wei He (ORCID: https://orcid.org/0000-0003-2357-7673)
- Yuqing Tan (ORCID: https://orcid.org/0000-0003-2906-0026)
- Haifeng Zhang (ORCID: https://orcid.org/0000-0001-5883-9720)
- Peiran Li (ORCID: https://orcid.org/0000-0003-4234-0292)
- Zhanlan Xie
Institutions
- State Grid Corporation of China (China) (CN)
- Shanghai Electric (China) (CN)
- Ningxia Water Conservancy (CN)
Publication Details
- Journal
- International Journal of Reasoning-based Intelligent Systems
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1504/ijris.2025.146936
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 0.00