Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach
文献类型：期刊论文
| 作者 | Xu, Mingzhu6; Liu, Ronggao1; Chen, Jing M.2,3,6; Liu, Yang1; Shang, Rong1; Ju, Weimin6; Wu, Chaoyang5; Huang, Wenjiang4 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2019-04-01 |
| 卷号 | 224页码:60-73 |
| 关键词 | Leaf chlorophyll content Sentinel-2 Remote sensing PROSAIL model Spectral vegetation indices Leaf area index Winter wheat |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2019.01.039 |
| 通讯作者 | Liu, Ronggao(liurg@igsnrr.ac.cn) |
| 英文摘要 | Leaf chlorophyll content (Chl(Leaf)), which is responsible for light harvesting for photosynthesis, is an important parameter for carbon cycle modeling and agriculture monitoring at regional and global scales. Since the spectral signals of chlorophyll content and leaf area are highly coupled, it is required to remove the effect of the LAI on the retrieval of Chl(Leaf) from satellite data. In this paper, an approach for the retrieval of Chl(Leaf) was proposed. A 2-dimensional matrix-based relationship between Chl(Leaf) and two VIs was established using simulated datasets from the PROSAIL model. The matrix was formed by dividing the two-VI space into m x n cells and assigning the Chl(Leaf) value to each cell. Based on the matrix, the Chl(Leaf) can be retrieved using the two VIs from observations. Three matrices of different VI pairs for retrieving Chl(Leaf) were tested using the PROSAIL simulated data. The results show that the matrix formed with two new VIs, RERI[705] and RERI[783], works best. The results from the matrices of two VIs are better than those from individual VIs as well as from VI ratios. The matrices were successfully used to retrieve the Chl(Leaf) of winter wheat from Sentinel-2 images. The Chl(Leaf) estimations using the RERI[705]-RERI[783] matrix achieves an accuracy of R-2 = 0.70, RMSE = 10.4 mu g/cm(2), and NRMSE = 11.9%. The estimations using the TCARI-OSAVI and the R-740/R-705-R-865/R-665 matrices are also in good agreement with the measured Chl(Leaf) (R-2 > 0.48, RMSE < 13.1 mu g/cm(2), and NRMSE < 15.1%). The matrix-based VI combination approach has the potential for the operational retrieval of Chl(Leaf) from multispectral satellite data. |
| WOS关键词 | RED EDGE POSITION ; AREA INDEX ; REMOTE ESTIMATION ; HYPERSPECTRAL INDEXES ; REFLECTANCE ; CANOPY ; INVERSION ; MODEL ; CROP ; LAI |
| 资助项目 | National Key Research and Development Program of China[2016YFA0600201] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000462421200005 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | National Key Research and Development Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/48705]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Ronggao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Toronto, Dept Geog, Toronto, ON MSS 3G3, Canada 3.Univ Toronto, Program Planning, Toronto, ON MSS 3G3, Canada 4.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 6.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Mingzhu,Liu, Ronggao,Chen, Jing M.,et al. Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach[J]. REMOTE SENSING OF ENVIRONMENT,2019,224:60-73. |
| APA | Xu, Mingzhu.,Liu, Ronggao.,Chen, Jing M..,Liu, Yang.,Shang, Rong.,...&Huang, Wenjiang.(2019).Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach.REMOTE SENSING OF ENVIRONMENT,224,60-73. |
| MLA | Xu, Mingzhu,et al."Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach".REMOTE SENSING OF ENVIRONMENT 224(2019):60-73. |
入库方式： OAI收割
来源：地理科学与资源研究所
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