Title :
A physically based approach in retrieving vegetation Leaf Area Index from Landsat surface reflectance data
Author :
Ganguly, Sangram ; Nemani, Ramakrishna R. ; Knyazikhin, Yuri ; Wang, Weile ; Hashimoto, Hirofumi ; Votava, Peter ; Michaelis, Andrew ; Milesi, Cristina ; Dungan, Jennifer L. ; Melton, Forrest S. ; Myneni, Ranga B.
Author_Institution :
NASA Ames Res. Center, Moffett Field, CA, USA
Abstract :
In this study, we aim to generate global 30-m Leaf Area Index (LAI) from Landsat surface reflectance data using the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). Furthermore, canopy spectral invariants introduce an efficient way for incorporating multiple bands for retrieving LAI. We incorporate a 3-band retrieval scheme including the Red, NIR and SWIR bands, the SWIR band being specifically useful in low LAI regions and thus compensating for background effects. The initial results have satisfactory agreement with MODIS LAI, although with spatially more detailed structure and variability. A future exercise will be to introduce field measured LAI estimates to minimize the differences between model-simulated LAI´s and in-situ observations.
Keywords :
atmospheric boundary layer; geophysical signal processing; radiative transfer; reflectivity; vegetation; Landsat surface reflectance data; MODIS LAI; bidirectional reflectance factor; canopy spectral invariants; radiative transfer theory; vegetation leaf area index; Biological system modeling; Earth; Indexes; MODIS; Reflectivity; Remote sensing; Satellites; LANDSAT; MODIS; canopy spectral invariants; leaf area index; scaling;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on
Conference_Location :
Reykjavik
Print_ISBN :
978-1-4244-8906-0
Electronic_ISBN :
978-1-4244-8907-7
DOI :
10.1109/WHISPERS.2010.5594875