Fine-scale remote sensing monitoring and interpretation of large-scene vegetation health in the Jiuzhai Valley biosphere reserve: A case study of the Changhai pilot zone
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摘要: 在自然过程、地质灾害和人为扰动的交织影响下,生物圈保护区植被健康风险提升,如何从复杂大场景精准提取与识别植被健康信息面临技术挑战。文章充分利用遥感技术宏观、客观与定量的优势,选取九寨沟生物圈保护区长海试验区为例,提出了一种集特征提取和随机森林的大场景植被健康遥感精细监测方法,实现了典型生物圈保护区不健康树木的信息提取与目标识别。结果表明: 应用光谱特征和纹理特征相结合的随机森林分类方法,在高分辨率遥感影像中可以精细提取森林中零散分布的不健康树木; 红绿指数、归一化植被指数、红边波段、红光波段相关性和修正的土壤调整植被指数是遥感植被健康信息提取的典型特征; 长海实验区植被健康状况总体较好,不健康树木占比0.23%,同时地质灾害对不健康树木空间分布有正向作用。研究不仅为九寨沟生物圈保护区植被健康诊断提供了第一手科学数据,而且对我国其他生物圈保护区的生态安全遥感监测具有推广价值。
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关键词:
- 遥感 /
- 植被健康 /
- 特征提取 /
- 特征重要性 /
- WorldView-2
Abstract: Under the intertwined effects of natural processes, geological disasters, and human disturbances, the health risks of vegetation in biosphere reserves have increased. Accurately extracting and identifying vegetation health information from complex large scenes faces technical challenges. This study investigated the Changhai pilot zone of the Jiuzhai Valley biosphere reserve by leveraging the macro, objective, and quantitative advantages of remote sensing technology. It proposed a fine-scale remote sensing monitoring method integrated with feature extraction and random forest for large-scene vegetation health, achieving the information extraction and target identification of unhealthy trees in typical biosphere reserves. The results show that: ① The random forest classification method combined with spectral and texture features can accurately extract unhealthy trees scattered in forests from high-resolution remote sensing images; ② The red-green ratio index, normalized difference vegetation index, correlation between red-edge and red bands, and corrected soil-adjusted vegetation index constitute typical features for extracting vegetation health information from remote sensing images; ③ The Changhai pilot zone exhibits a generally fair vegetation health status, with unhealthy trees accounting for 0.23%, and geological disasters exert positive effects on the spatial distribution of unhealthy trees. This study provides primary scientific data for vegetation health diagnosis of the Jiuzhai Valley biosphere reserve while showing generalization value for the remote sensing monitoring of ecological security in other biosphere reserves of China.-
Key words:
- remote sensing /
- vegetation health /
- feature extraction /
- feature importance /
- WorldView-2
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