森林生态系统是生物多样性最丰富的陆地生态系统，分布范围广泛且多在地形复杂地区。样地调查是森林生物多样性监测的有效手段，但其很难客观全面地对较大范围森林生物多样性进行监测。高分辨率（空间、光谱、垂直、时间）的遥感数据为解决这一难题提供了契机。本课题拟从森林生物多样性多尺度地面调查出发，利用塔吊和机载平台获取的激光雷达和高光谱等高分辨率遥感数据反演森林树种多样性和结构多样性等监测指标，发展基于遥感数据森林多样性监测指标的计算方法，并验证生物多样性与生产力的关系。拟选取浙江古田山国家级自然保护区为项目核心研究区，并将发展的算法在邻近的安徽省岭南省级自然保护区进行验证。本研究为森林生物多样性指标的遥感获取提供算法支持，为更大范围的森林生物多样性遥感监测提供参考。

With wide distribution especially in mountainous areas, forest ecosystem has the most abundant biodiversity in terrestrial ecosystems. The field survey is efficient for forest biodiversity monitoring, but it is hard to carry out continuously in large area. Remote sensing data with high spatial, spectrum, vertical and temporal resolution provide the capability to monitor forest biodiversity in large area. With the multi-scale field survey of forest biodiversity, this subject develops methods to calculate forest species and structure diversity indices base on remote sensing data, which include Lidar and hyperspectral data acquired from airborne and tower crane platforms. Then explore the relationship between remote sensing estimated biodiversity indices and forest productivity. We plan to take the Gutian Mountain national nature reserve in Zhejiang province as intensive study site to develop algorithms. Then these developed algorithms will be verified in the nearby Lingnan nature reserve in Anhui province. This study will support the algorithm development of forest biodiversity assessment using remote sensing data, and provide technical support for forest biodiversity monitoring using remote sensing in large area.