Objective Forest ecological quality reflects the ecological quality of forests from an ecological perspective, measuring the comprehensive capacity of forests to improve the ecological environment, maintain ecological balance, and provide ecological functions and services. Utilizing medium and high-resolution multisource remote sensing data, we aim to acquire crucial indicator information that characterizes forest ecological quality at a large-scale level. Based on this foundation, our objective is to analyze the forest ecological quality status in the 40 coastal counties of Fujian Province of eastern China.
Method Firstly, the primary data source utilized was 2 m resolution multisource remote sensing data. The bi-level scale-sets model (BSM) was employed to determine the optimal segmentation scale, integrating multiple classifiers to create an algorithm set. The best classification algorithm for forest type extraction was automatically selected. This approach was complemented by the use of Sentinel remote sensing data in 2020 and fine forest classification products, resulting in an optimized fine-scale distribution map of coastal forests in Fujian Province for year 2020. Secondly, forest age was estimated using disturbance onset time features derived from the LandTrendr algorithm. Additionally, GEDI crown height products were used to obtain the canopy height distribution map of coastal forests. Building upon the extraction of key forest quality indicators through remote sensing methods, a principal component analysis was conducted on eight forest ecological quality assessment indicators obtained through remote sensing. This led to a comprehensive assessment of forest ecological quality for the coastal counties of Fujian Province.
Result In 2020, approximately 50% of the 40 coastal counties in Fujian’s coastal zone exhibited a favorable level of forest ecological quality. Among them, Xianyou County, Minhou County, Nan’an City, Xiapu County, Zherong County, as well as the districts of Haicang, Siming, Jimei, and Tong’an in Xiamen, demonstrated excellent forest ecological quality. On the other hand, counties with relatively poor forest ecological quality included Huian County, Xiuyu District, Shishi City, Fu’an City, Pingtan Experimental Zone, and Zhao’an County.
Conclusion Utilizing high and medium-resolution multisource remote sensing data, the advantages of remote sensing large-scale monitoring have been leveraged to provide an objective assessment of the forest ecological quality in the 40 coastal counties of Fujian Province. The research findings reveal that there is considerable room for improvement in the forest ecological quality of the coastal counties in Fujian Province in 2020. Addressing the existing issues calls for the implementation of appropriate forest management measures to enhance the forest ecological quality.
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