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Using MODIS time series data to estimate aboveground biomass and its spatio-temporal variation in Inner Mongolia’s grassland between 2001 and 2011.

Authors :
Gao, Tian
Xu, Bin
Yang, Xiuchun
Jin, Yunxiang
Ma, Hailong
Li, Jinya
Yu, Haida
Source :
International Journal of Remote Sensing. Nov2013, Vol. 34 Issue 21, p7796-7810. 15p. 3 Charts, 6 Graphs, 2 Maps.
Publication Year :
2013

Abstract

It is critical to understanding grassland biomass and its dynamics to study regional carbon cycles and the sustainable use of grassland resources. In this study, we estimated aboveground biomass (AGB) and its spatio-temporal pattern for Inner Mongolia’s grassland between 2001 and 2011 using field samples, Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index (MODIS-NDVI) time series data, and statistical models based on the relationship between NDVI and AGB. We also explored possible relationships between the spatio-temporal pattern of AGB and climatic factors. The following results were obtained: (1) AGB averaged 19.1 Tg C (1 Tg = 1012 g) over a total area of 66.01 × 104 km2between 2001 and 2011 and experienced a general fluctuation (coefficient of variation = 9.43%), with no significant trend over time (R2 = 0.05,p > 0.05). (2) The mean AGB density was 28.9 g C m−2 over the whole study area during the 11 year period, and it decreased from the northeastern part of the grassland to the southwestern part, exhibiting large spatial heterogeneity. (3) The AGB variation over the 11 year period was closely coupled with the pattern of precipitation from January to July, but we did not find a significant relationship between AGB and the corresponding temperature changes. Precipitation was also an important factor in the spatial pattern of AGB over the study area (R2 = 0.41,p< 0.001), while temperature seemed to be a minor factor (R2 = 0.14,p< 0.001). A moisture index that combined the effects of precipitation and temperature explained more variation in AGB than did precipitation alone (R2 = 0.45,p< 0.001). Our findings suggest that establishing separate statistical models for different vegetation conditions may reduce the uncertainty of AGB estimation on a large spatial scale. This study provides support for grassland administration for livestock production and the assessment of carbon storage in Inner Mongolia. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01431161
Volume :
34
Issue :
21
Database :
Academic Search Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
90274087
Full Text :
https://doi.org/10.1080/01431161.2013.823000