Title :
Estimating terrestrial Vegetation Primary Productivity using satellite SAR data
Author :
Gao, Shuai ; Niu, Zheng ; Wu, Mingquan ; Liu, Chenzhou
Author_Institution :
State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing Applic., Beijing, China
Abstract :
A new GPP/NPP model driven by the satellite SAR data was introduced in this paper. It was based on the light use efficiency theory and was referred to the MODIS model for the value of the maximum light use efficiency of different vegetation types. The model was testified in the HEIHE area with ENVISAT-SAR data and showed its feasibility to estimate GPP/NPP. Firstly, the driving factors such as PAR, T_scalar, W_scalar were calculated based on the algorithm and meteorological observation data. Then, the LUT algorithm using the MIMICS model was introduced and validated for its effectiveness to estimate LAI. Finally, the GPP was obtained based on the model and compared with the ground flux observation and MODIS product. The results reveal a potential possibility that the satellite SAR data could be used for the GPP/NPP estimation.
Keywords :
remote sensing by radar; synthetic aperture radar; vegetation; vegetation mapping; ENVISAT-SAR data; GPP/NPP estimation; GPP/NPP model; HEIHE area; LUT algorithm; MIMICS model; MODIS model; MODIS product; PAR; T_scalar; W_scalar; ground flux observation; light use efficiency theory; maximum light use efficiency; meteorological observation data; satellite SAR data; terrestrial vegetation primary productivity; vegetation types; Agriculture; Biological system modeling; MODIS; Productivity; Remote sensing; Synthetic aperture radar; Vegetation mapping; ENVISAT/ASAR; FLUX; GPP; LAI;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6352744