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 | |
刊名 | Remote Sensing |
2019 | |
卷号 | 11期号:13页码:1597 |
关键词 | Agriculture Climate change Plants (botany) Table lookup |
ISSN号 | 0 |
DOI | 10.3390/rs11131597 |
产权排序 | 1 |
文献子类 | Article |
英文摘要 | The 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. |
电子版国际标准刊号 | 2072-4292 |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.imde.ac.cn/handle/131551/26624] |
专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
通讯作者 | Li Ainong |
作者单位 | 1.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 |
推荐引用方式 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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