Title :
Models for estimating Leaf Area Index of different crops using hyperspectral data
Author :
Dong, Heng ; QIN, Qiming ; You, Lin ; Sui, Xinxin ; Li, Jun ; Jiang, Hongbo ; Wang, Jinliang ; Feng, Haixia ; Sun, Hongmei
Author_Institution :
Inst. of Remote Sensing & Geographic Inf. Syst., Peking Univ., Beijing, China
Abstract :
Leaf Area Index (LAI) is a very important parameter in the area of vegetation quantitative remote sensing. Large range of LAI can reflect the change of eco-system. This article has discussed whether the crop type is a factor to impact the leaf area index retrieval. We choose four types of crops in our research and Hyperspectral Data and leaf area index of these crops were measured. Then the LAI retrieval models were established, which demonstrate the relationships between SVI and LAI. Finally the conclusion can be made that the type of crop is a factor impacting the LAI retrieval. For different crops, the best models are not the same. But the little difference of R2 can be omitted. The SR is the best spectral vegetation index for LAI retrieval.
Keywords :
crops; information retrieval; spectral analysis; vegetation mapping; LAI retrieval model; SVI; crop type; crops; hyperspectral data; leaf area index; spectral vegetation index; vegetation quantitative remote sensing; Agriculture; Biological system modeling; Indexes; Reflectivity; Remote sensing; Strontium; Vegetation; Hyperspectral Data; LAI retrieval; Remote sensing;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5653735