| Quantitative Estimation of Biomass of Alpine Grasslands Using Hyperspectral Remote Sensing | |
Bo Kong1 ; Huan Yu2,3; Rongxiang Du2; Qing Wang4
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| 2019 | |
| Source Publication | RANGELAND ECOLOGY & MANAGEMENT
 |
| ISSN | 1550-7424 |
| EISSN | 1551-5028 |
| Volume | 72Issue:2Pages:336-346 |
| Subtype | Article |
| Contribution Rank | 1 |
| Abstract | In order to promote the application of hyperspectral remote sensing in the quantification of grassland areas' physiological and biochemical parameters, based on the spectral characteristics of ground measurements, the dry AGB and multisensor satellite remote sensing data, including such methods as correlation analysis, scaling up, and regression analysis, were used to establish a multiscale remote sensing inversion model for the alpine grassland biomass. The feasibility and effectiveness of the model were verified by the remote sensing estimation of a time-space sequence biomass of a plateau grassland in northern Tibet. The results showed that, in the ground spectral characteristic parameters of the grassland's biomass, the original wave bands of 550, 680, 860, and 900 nm, as well as their combination form, had a good correlation with biomass. Also, the remote sensing biomass estimation model established on the basis of the two spectral characteristics (VI2 and Normalized Difference Vegetation Index [NDVI]) had a high inversion accuracy and was easy to realize, with a fitting R-2 of 0.869 and an F test value of 92.6. The biomass remote sensing estimate after scale transformation had a standard deviation of 53.9 kg/ha from the fitting model established by MODIS NDVI, and the estimation accuracy was 89%. Therefore, it displayed the ability to realize the estimation of large-scale and long-time sequence remote sensing biomass. The verification of the model's accuracy, comparison of the existing research results of predecessors, and analysis of the regional development background demonstrated the effectiveness and feasibility of this method. (C) 2018 The Society for Range Management. Published by Elsevier Inc. All rights reserved. |
| Keyword | alpine grassland biomass hyperspectral remote sensing multiscale spectral characteristic parameters |
| DOI | 10.1016/j.rama.2018.10.005 |
| Indexed By | SCI |
| Language | 英语 |
| Quartile | 4区 |
| TOP | 否 |
| WOS ID | WOS:000460292800015 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imde.ac.cn/handle/131551/25320 |
| Collection | 数字山地与遥感应用中心 |
| Corresponding Author | Huan Yu |
| Affiliation | 1.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, 610041; 2.College of Earth Sciences, Chengdu University of Technology, 610059; 3.Key Laboratory of Geoscience Spatial Information Technology of Ministry of Land and Resources, Chengdu University of Technology, Chengdu, China; 4.Department of Geography and Environmental Resources, Southern Illinois University, Carbondale, IL 62901, USA |
| First 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 | Bo Kong,Huan Yu,Rongxiang Du,et al. Quantitative Estimation of Biomass of Alpine Grasslands Using Hyperspectral Remote Sensing[J]. RANGELAND ECOLOGY & MANAGEMENT,2019,72(2):336-346. |
| APA | Bo Kong,Huan Yu,Rongxiang Du,&Qing Wang.(2019).Quantitative Estimation of Biomass of Alpine Grasslands Using Hyperspectral Remote Sensing.RANGELAND ECOLOGY & MANAGEMENT,72(2),336-346. |
| MLA | Bo Kong,et al."Quantitative Estimation of Biomass of Alpine Grasslands Using Hyperspectral Remote Sensing".RANGELAND ECOLOGY & MANAGEMENT 72.2(2019):336-346. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Quantitative Estimat（4376KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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