摘要
The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ecosystems.HJ-1A/B satellite data combined with field measurement data was used for the estimation of shrub AGB and carbon storage in the Mu Us desert,China.The correlations of shrub AGB and spectral reflectance of four bands as well as their combined vegetation indexes were respectively analyzed and stepwise regression analysis was employed to establish AGB prediction equation.The prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than others.Shrub AGB and carbon storage were mapped using the RVI based prediction model in final.The statistics showed the western Mu Us desert has relatively high AGB and carbon storage,and that the gross shrub carton storage in Mu Us desert reaches 16 799 200 t,which has greatly contributed to the carbon fixation in northern China.
The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ecosystems.HJ-1A/B satellite data combined with field measurement data was used for the estimation of shrub AGB and carbon storage in the Mu Us desert,China.The correlations of shrub AGB and spectral reflectance of four bands as well as their combined vegetation indexes were respectively analyzed and stepwise regression analysis was employed to establish AGB prediction equation.The prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than others.Shrub AGB and carbon storage were mapped using the RVI based prediction model in final.The statistics showed the western Mu Us desert has relatively high AGB and carbon storage,and that the gross shrub carton storage in Mu Us desert reaches 16 799 200 t,which has greatly contributed to the carbon fixation in northern China.
作者
XU Min 1,2,CAO ChunXiang 1,TONG QingXi 1,LI ZengYuan 3,ZHANG Hao 1,HE QiSheng 1,2,GAO MengXu 1,2,ZHAO Jian 1,2,ZHENG Sheng 1,2,CHEN Wei 1,2 & ZHENG LanFen 1 1State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China
2 Graduate School of the Chinese Academy of Sciences,Beijing 100049,China
3 Research Institute of Forest Resources and Information Techniques,Chinese Academy of Forestry,Beijing 10009,China
基金
supported by the National Basic Research Program of China("973"Project)(Grant No.2007CB714404)
the National Natural Science Foundation of China(Grant No.40871173)
the Special Grantfor Prevention and Treatment of Infectious Diseases(2008ZX10004-012)
