|
|||||
|
|
Thermal bidirectional gap probability model for row crop canopies and validation |
|
| Authors: | |
| Institution: | 1. Research Center for Remote Sensing and GIS, Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing Normal University, Beijing 100875, China 2. LARSIS, Institute of Remote Sensing Application, Chinese Academy of Sciences, Beijing 100101, China 3. Research Center for Remote Sensing and GIS, Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing Normal University, Beijing 100875, China;Department of Geography and Center for Remote Sensing, Bo |
| Abstract: | Based on the row structure model of Kimes and the mean gap probability model in single direction, we develop a bidirectional gap probability model for row crop canopies. A concept of overlap index is introduced in this model to consider the gaps and their correlation between the sun and view directions. Multiangular thermal emission data sets were measured in Shunyi, Beijing, and these data are used in model validation in this paper. By comparison with the Kimes model that does not consider the gap probability, and the model considering the gap in view direction only, it is found that our bidirectional gap probability model fits the field measurements over winter wheat much better. |
| Keywords: | row crop bidirectional gap probability thermal emission hot spot effect |
| 本文献已被 CNKI 万方数据 SpringerLink 等数据库收录！ | |