Uniting Forest Inventory and Remote Sensing Data to Assess Forest Composition and Structure in Tropical Mountain Regions

量化和预测森林分布对持续气候变化的反应需要关于物种分布和森林组成的准确数据。这些数据通常是从以地块为基础的森林清查调查中收集的。然而，这种办法在交通不便或地形困难的地区极为有限。因此，缺乏数据，因此对热带山区系统如何应对气候变化了解甚少。这一巨大的知识差距对我们预测从全球到地方规模的环境变化的未来影响的能力以及从生物群落分布和碳经济到地方生物多样性和生态系统服务的因素具有重大影响。利用高分辨率遥感数据，得出在较难进入的地区进行和解释森林评估的新方法。该项目将整合现有的数据与实地研究，并将适合来自广泛背景的学生，从地理，通过生态学到环境科学。然而，必须对森林和山区地形的实地考察以及对在对比空间尺度上理解模式和过程的热情。目标：1）利用现有森林清查数据对与中央山脉环境变化相关的山地热带森林组成的空间变化进行分类; 2）确定样地组成数据与卫星图像和航空摄影遥感数据之间的关系; 3）利用地面清查并辅以三维激光扫描确定一个子集样地的结构特征; 4）通过结合上述目标1-3的结果，开发远程森林结构和组成评估方法。

Quantifying and predicting the response of forest distribution to on-going climatic changes requires accurate data on species distribution and forest composition. Such data are typically gathered from plot-based forest inventory surveys. However, this approach is extremely limited in areas with poor access or difficult terrain. Consequently, there is poor data availability and hence little understanding, of how tropical mountain systems will respond to climate change. This significant knowledge gap has major implications for our ability to predict future impacts of environmental change from global to local scales and for factors spanning from biome distribution and carbon economy to local biodiversity and ecosystem services.This project will combine plot-level forest inventory data with aerial photographs and high-resolution remote sensing data to derive new methods for conducting and interpreting forest assessments in less accessible regions. The project will integrate existing data with field-based research and would suit students from a wide range of backgrounds, spanning from geography, through ecology to environmental science. An enthusiasm for fieldwork in forests and mountain terrain and for understanding pattern and process at contrasting spatial scales is a must, however. Objectives:1) To classify spatial variation in montane tropical forest composition associated with environmental variation across the central mountain range using existing forest inventory data.2) To identify relationships between plot compositional data and remote sensing data from satellite imagery and aerial photography.3) To determine structural characteristics of a subset of plots using ground based inventory augmented with 3D laser scanning.4) To develop methods for remote forest structural and compositional assessment by combining outcomes of objectives 1-3, above.