• 研究报告 •

### 森林冠层叶面积指数遥感反演——以小兴安岭五营林区为例

1. 1 南京信息工程大学气象灾害省部共建教育部重点实验室， 南京 210044； 2南京信息工程大学地理与遥感学院,  南京 210044)
• 出版日期:2015-07-10 发布日期:2015-07-10

### Retrieving forest canopy LAI from remote sensing data: A case study over Wuying forest in the Lesser Khingan.

LIU Zhen-bo1,2**, LIU Jie1,2

1. (1Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China;  2 School of Geography and Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China)
• Online:2015-07-10 Published:2015-07-10

Abstract: In this study, approaches of retrieving forest canopy LAI (leaf area index) were investigated using remote sensing data over Wuying forest in the Lesser Khingan as a case study. We firstly calculated the forest canopy reflectivity using 4-Scale model in combination of MODIS (Moderate Resolution Imaging Spectroradiometer) BRDF (bidirectional reflectance distribution function) product. And then three wellknown vegetation indices (VIs) were obtained from the forest canopy reflectivity. Finally, four models were examined in the forest canopy LAI retrieving using the canopy VIs and onsite canopy LAI measurements. The results showed that the model using quadratic polynomial and simple ratio (SR) VI was  the best LAI retrieving model among the four models. Furthermore, the accuracy of LAI estimate could be improved using canopy reflectivity instead of the whole surface reflectivity, with the coefficient of determination (R2) increasing from 0.38 to 0.54. The mean canopy LAI in the study area ranges from 2.38 to 12.67, with an average of 6.52, and the relatively higher LAI values were found in the deciduous forest area.