Research Progress in Monitoring Arbor Moisture Content via Image Processing Technology: A Case Study of Typical Trees in Central Yunnan

Na Li; Enju Sun; Xiaojie Ma; Zhengrui Pu; Wenquan Chen; Zhongliang Gao

doi:10.6919/ICJE.202605_12(5).0010

Authors

Na Li
Enju Sun
Xiaojie Ma
Zhengrui Pu
Wenquan Chen
Zhongliang Gao

DOI:

https://doi.org/10.6919/ICJE.202605_12(5).0010

Keywords:

Image Processing; Arbor Moisture Content; Forest Combustibles.

Abstract

The moisture content of arbor trees is a core indicator that reflects the dryness of forest combustibles and evaluates forest fire risk levels. Traditional methods for measuring moisture content have limitations such as time consumption, strong destructiveness, and difficulty in large-scale popularization. In contrast, image processing technology has gradually become an important method for rapid vegetation moisture monitoring due to its advantages of non-contact, low cost, high efficiency, and easy automated monitoring. This paper systematically reviews the research progress on the inversion of plant moisture content using image processing technology at home and abroad, summarizes the application rules of image features including color, texture and morphology, and reviews the research status of image monitoring for the moisture content of arbor trees and forest combustibles in forestry. The aim is to provide a reference for dynamic forest fire risk monitoring, rapid assessment of combustible moisture content and related academic research in central Yunnan.

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