DocumentCode :
576636
Title :
Hyperspectral vegetation indices for crop chlorophyll estimation: Assessment, modeling and validation
Author :
Lin, Peirong ; Qin, Qiming ; Dong, Heng ; Meng, Qingye
Author_Institution :
Inst. of Remote Sensing & GIS, Peking Univ., Beijing, China
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
4841
Lastpage :
4844
Abstract :
This study summarizes 12 spectral indices for chlorophyll inversion, including traditional multi-spectral indices and newly published indices constructed based on “Red Edge” (680-750nm) and “Double-Peak” in red edge region. Among them, some are good candidates to resist Leaf Area Index (LAI) variations, but some are not. By using forward model simulations and in-situ measurements data, we systematically tested these indices and picked out the best one which (1) has the highest sensitivity to chlorophyll; (2) has the best resistance to LAI variation. Then predictive equations were developed from simulated data and validated using winter wheat ground measurement data collected in 2011, Yucheng Station at Chinese Academy of Sciences.
Keywords :
crops; vegetation mapping; Chinese Academy of Sciences; LAI variation; Yucheng Station; chlorophyll inversion; crop chlorophyll estimation; double-peak; forward model simulations; hyperspectral vegetation indices; leaf area index variations; multispectral indices; red edge region; winter wheat ground measurement data; Agriculture; Hyperspectral imaging; Indexes; Mathematical model; Reflectivity; Vegetation mapping; Leaf Area Index (LAI); chlorophyll content; hyperspectral remote sensing; red edge; spectral indices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352529
Filename :
6352529
Link To Document :
بازگشت