Title :
Remotely sensed estimate of biomass carbon stocks in Xilingol grassland using MODIS NDVI data
Author :
Bao Gang ; Hasituya ; Hugejiletu ; Yuhai Bao
Author_Institution :
Inner Mongolia Key Lab. of Remote Sensing & Geographic Inf. Syst., Inner Mongolia Normal Univ., Huhhot, China
Abstract :
Accurate estimate of grassland biomass carbon stock is very important to carbon cycling and rational utilization of grassland resources. The natural ecosystem of Xilingol grassland has traditionally been the source of the most productive and highest quality grass in northern China. Based on the plant growing season MODIS-NDVI and Meteorological data, the present study employed the CASA model and plants withered loss model to estimate the above-ground carbon stocks of Xilingol grassland in 2002, 2005, 2009, and further calculate the below-ground biomass carbon stock according to the proportion of above-ground and under-ground biomass. The validation result indicates that the model achieved the reasonable results with an accuracy of 92.47%. Generally, the biomass carbon stocks in Xilingol grassland experienced a decreasing trend from 2002 to 2009., with a total carbon stock of 8.68, 8.09 and 7.61Tg (1Tg=1×1012g) in 2002, 2005, and 2009, respectively, and the corresponding below-ground biomass carbon stock was 40.64, 37.48 and 36.04Tg in three study years, which is approximately five times about the above-ground.
Keywords :
carbon capture and storage; remote sensing; vegetation; AD 2002 to 2009; CASA model; MODIS NDVI data; Xilingol grassland; above-ground biomass; biomass carbon stocks; grassland biomass carbon stock; grassland resources; meteorological data; natural ecosystem; northern China; plant growing season; remotely sensed estimate; under-ground biomass; Accuracy; Biological system modeling; Biomass; Carbon; Data models; Remote sensing; Vegetation mapping; Xilingol grassland; biomass carbon stocks; estimate;
Conference_Titel :
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location :
Shengyang
Print_ISBN :
978-1-4799-2564-3
DOI :
10.1109/MEC.2013.6885149