Evaluating cellulose absorption index(CAI) for non-photosynthetic biomass estimation in the desert steppe of Inner Mongolia  

作　　者：REN HongRui ZHOU GuangSheng ZHANG Feng ZHANG XinShi 

机构地区：[1]State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China [2]Graduate University of Chinese Academy of Sciences, Beijing 100049, China [3]Chinese Academy of Meteorological Sciences, Beijing 100081, China

出　　处：《Chinese Science Bulletin》2012年第14期1716-1722,共7页

基　　金：supported by the National Basic Research Program of China (2010CB951303);the National Natural Science Foundation of China (90711001 and 40971123)

摘　　要：Accurate estimation of non-photosynthetic biomass is critical for modeling carbon dynamics within grassland ecosystems.We evaluated the cellulose absorption index(CAI),widely used for monitoring non-photosynthetic vegetation coverage,for non-photosynthetic biomass estimation.Our analysis was based on in situ hyperspectral measurements,during the growing seasons of 2009 and 2010,in the desert steppe of Inner Mongolia.ASD(Analytical Spectral Device)-derived and Hyperion-derived CAI were found to be effective for non-photosynthetic biomass estimation,yielding relative error(RE) values of 26.4% and 26.6%,respectively.The combination of MODIS(Moderate Resolution Imaging Spectroradiometer)-derived(MODIS2 MODIS5)/(MODIS2 +MODIS5) and(MODIS6 MODIS7)/(MODIS6 +MODIS7) showed a high multiple correlation(multiple correlation coefficient,r=0.884) with ASD-derived CAI.A predictive model involving the two MODIS indices gave greater accuracy(RE=28.9%) than the TM(Landsat Thematic Mapper)-derived indices.The latter were the normalized difference index(NDI),the soil adjusted corn residue index(SACRI),and the modified soil adjusted crop residue index(MSACRI).These indices yielded RE values of more than 42%.Our conclusions have great significance for the estimation of regional non-photosynthetic biomass in grasslands,based on remotely sensed data.Accurate estimation of non-photosynthetic biomass is critical for modeling carbon dynamics within grassland ecosystems. We evaluated the cellulose absorption index （CAI）, widely used for monitoring non-photosynthetic vegetation coverage, for non-photosynthetic biomass estimation. Our analysis was based on in situ hyperspectral measurements, during the growing seasons of 2009 and 2010, in the desert steppe of Inner Mongolia. ASD （Analytical Spectral Device）-derived and Hyperion-derived CAI were found to be effective for non-photosynthetic biomass estimation, yielding relative error （RE） values of 26.4% and 26.6%, respectively. The combination of MODIS （Moderate Resolution Imaging Spectroradiometer）-derived （MODIS2- MODISs）/（MODIS2＋MODISs） and （MODIS6-MODIST）/（MODISt＋MODIST） showed a high multiple correlation （multiple cor- relation coefficient, r=- 0.884） with ASD-derived CAI. A predictive model involving the two MODIS indices gave greater accura- cy （RE=28.9%） than the TM （Landsat Thematic Mapper）-derived indices. The latter were the normalized difference index （ND1）, the soil adjusted corn residue index （SACRI）, and the modified soil adjusted crop residue index （MSACRI）. These indices yielded RE values of more than 42%. Our conclusions have great significance for the estimation of regional non-photosynthetic biomass in grasslands, based on remotely sensed data.

关 键 词：光合作用 荒漠草原 吸收指数 生物量 CAI 纤维素 内蒙古 中分辨率成像光谱仪 

分 类 号：S812[农业科学—草业科学] Q945.11[农业科学—畜牧学]