IMHE OpenIR  > 数字山地与遥感应用中心
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
Source PublicationREMOTE SENSING
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 x 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.
Keywordaboveground biomass (AGB) grassland PROSAIL MCD43A4
Indexed BySCI
WOS IDWOS:000477049000088
Citation statistics
Document Type期刊论文
Corresponding AuthorLi, Ainong
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 100049, Sichuan, Peoples R China;
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China;
3.Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 610031, Sichuan, Peoples R 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.
Files in This Item:
File Name/Size DocType Version Access License
remotesensing-11-015(3721KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[He, Li]'s Articles
[Li, Ainong]'s Articles
[Yin, Gaofei]'s Articles
Baidu academic
Similar articles in Baidu academic
[He, Li]'s Articles
[Li, Ainong]'s Articles
[Yin, Gaofei]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[He, Li]'s Articles
[Li, Ainong]'s Articles
[Yin, Gaofei]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: remotesensing-11-01597.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.