IMHE OpenIR
Retrieval of grassland aboveground biomass through inversion of the PROSAIL model with MODIS imagery
He Li1,2; Li Ainong1; Yin Gaofei1,3; Nan Xi1; Bian Jinhu1
2019
Source PublicationRemote Sensing
ISSN0
EISSN2072-4292
Volume11Issue:13Pages:1597
SubtypeArticle
Contribution Rank1
AbstractThe estimation of aboveground biomass (AGB), an important indicator of grassland production, is crucial for evaluating livestock carrying capacity, understanding the response and feedback to climate change, and achieving sustainable development. Most existing grassland AGB estimation studies were based on empirical methods, in which field measurements are indispensable, hindering their operational use. This study proposed a novel physically-based grassland AGB retrieval method through the inversion of PROSAIL model against MCD43A4 imagery. This method relies on the basic understanding that grassland is herbaceous, and therefore AGB can be represented as the product of leaf dry matter content (Cm) and leaf area index (LAI), i.e., AGB = Cm × LAI. First, the PROSAIL model was parameterized according to the literature regarding grassland parameters retrieval, then Cm and LAI were retrieved using a lookup table (LUT) algorithm, finally, the retrieved Cm and LAI were multiplied to obtain the AGB. The method was assessed in Zoige Plateau, China. Results show that it could reproduce the reference AGB map, which is generated by upscaling the field measurements, in terms of magnitude (with RMSE and R-RMSE of 60.06 gm-2 and 18.1%, respectively) and spatial distribution. The estimated AGB time series also agreed reasonably well with the expected temporal dynamic trends of the grassland in our study area. The greatest advantage of our method is its fully physical nature, i.e., no field measurement is needed. Our method has the potential for operational monitoring of grassland AGB at regional and even larger scales. © 2019 by the authors.
KeywordAgriculture Climate change Plants (botany) Table lookup
DOI10.3390/rs11131597
Indexed ByEI
Language英语
EI Accession NumberAccession number:20192807167471
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/26624
Collection中国科学院水利部成都山地灾害与环境研究所
Corresponding AuthorLi Ainong
Affiliation1.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu;610041, China;
2.University of Chinese Academy of Sciences, Beijing;100049, China;
3.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu;610031, China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
He Li,Li Ainong,Yin Gaofei,et al. Retrieval of grassland aboveground biomass through inversion of the PROSAIL model with MODIS imagery[J]. Remote Sensing,2019,11(13):1597.
APA He Li,Li Ainong,Yin Gaofei,Nan Xi,&Bian Jinhu.(2019).Retrieval of grassland aboveground biomass through inversion of the PROSAIL model with MODIS imagery.Remote Sensing,11(13),1597.
MLA He Li,et al."Retrieval of grassland aboveground biomass through inversion of the PROSAIL model with MODIS imagery".Remote Sensing 11.13(2019):1597.
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