Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.
Conserv Biol. 2012 Oct;26(5):840-50. doi: 10.1111/j.1523-1739.2012.01869.x. Epub 2012 Jun 25.
Airborne lidar is a remote-sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three-dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape-level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first-and-last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar- and field-measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar-measured vegetation height (R(2) = 0.50, p < 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground-truthing and its timing relative to acquisition of lidar data.
机载激光雷达在生态和保护研究中越来越重要,因为它能够对三维植被结构进行特征描述。如果可以将植物物种多样性和组成的不同方面与植被结构相关联,那么就有可能对植物群落进行景观水平的评估。我们检验了这种可能性,研究对象是葡萄牙南部的地中海栎林,这里生物多样性丰富,但也受到威胁。我们比较了为栓皮栎(Quercus suber)和阿尔及利亚栎(Quercus canariensis)林采集的 31 个样地的离散的、首次和末次回波激光雷达数据集与野外数据,以测试激光雷达是否可以用于预测植被的垂直结构、物种多样性和群落类型。激光雷达和实地测量的结构数据具有显著的相关性(高达 r = 0.85)。森林物种的多样性与激光雷达测量的植被高度显著相关(R² = 0.50,p < 0.001)。物种数据的聚类和排序表明存在 2 种主要的森林类型,可以基于激光雷达数据以 89%的准确率进行区分。激光雷达可以广泛应用于栖息地制图和栖息地状况评估(例如,支持欧洲物种和栖息地指令[92/43/EEC])。然而,需要特别注意调查设计的问题:激光雷达点的密度、地面实况的地理空间精度及其与激光雷达数据采集的时间关系。