黑河流域叶面积指数的遥感估算  

THE ESTIMATION OF LAI IN HEIHE RIVER BASIN USING REMOTELY SENSED DATA

作　　者：方秀琴[1] 张万昌[1] 刘三超[1] 

机构地区：[1]南京大学国际地球科学研究所,南京210093

出　　处：《国土资源遥感》2004年第1期27-31,共5页Remote Sensing for Land & Resources

基　　金：国家重点基础研究发展项目(2001CB309404);海外青年学者合作研究基金(40128001);教育部科学技术重点项目(2001)。

摘　　要：研究利用Landsat7ETM+遥感数据获取黑河流域植被叶面积指数(LAI)空间分布的可行性。该研究是基于黑河流域分布式水文模型的一个重要输入项———LAI空间分布数据的需要而产生的。文章在详尽的野外观测数据基础上,分别探究实测LAI与同时相ETM+3、4、5、7波段反射率及相关植被指数(SR、NDVI、ARVI、RSR、SAV I、PVI、GESAVI)的相关关系,率定最佳的LAI遥感反演及其空间分布方案。研究发现,针对特定的自然条件,将研究区分为植被覆盖度小的稀疏立地和覆盖度大的密集立地,分别采用土壤调节植被指数(SAVI)和大气阻抗植被指数(ARVI)进行2种林地的LAI估算最为可靠,在此基础上,提出黑河地区LAI估算及其空间分布的遥感制图方案。The aim of this paper is to investigate the feasibility of using Landsat 7 ETM^+ data to estimate Leaf Area Index (LAI).The investigation is prompted by the need of obtaining spatially distributed data on LAI which serve as an important input for distributive hydrological modeling of Heihe Basin. Using detailed field data of Zhangye Oasis and Qilian Mountain collected in September 2002, the authors investigated the relationship between contemporary field data and remotely sensed ETM^+ data, which include ETM^+ 3, 4, 5, 7 and some vegetation indices such as Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Atmospherically Resistant Vegetation Index (ARVI), Reduced Simple Ratio (RSR), Perpendicular Vegetation Index (PVI), Soil-Adjusted Vegetation Index (SAVI) and Generalized Soil-Adjusted Vegetation Index (GESAVI). The best approach to the estimation of LAI was found on the basis of statistical analysis. According to the specific natural conditions of Heihe Basin, it is thought that the most reliable method should be the division of the study area into sparse stands and dense stands, with SAVI used in the estimation of LAI in the former stands and ARVI in the latter stands. In such a way, the estimation and spatial mapping of LAI of the whole study area can be completed.

关 键 词：叶面积指数 遥感 估算 黑河流域 LAI 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] Q948[自动化与计算机技术—控制科学与工程]