Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data
文献类型：期刊论文
| 作者 | Sun, Xiaofang2; Li, Bai3; Du, Zhengping4; Li, Guicai1; Fan, Zemeng4 ; Wang, Meng2; Yue, Tianxiang4
|
| 刊名 | GEOCARTO INTERNATIONAL
 |
| 出版日期 | 2019-08-23 |
| 页码 | 16 |
| 关键词 | Aboveground biomass high accuracy surface modelling mapping |
| ISSN号 | 1010-6049 |
| DOI | 10.1080/10106049.2019.1655799 |
| 通讯作者 | Wang, Meng(wangmeng@qfnu.edu.cn) |
| 英文摘要 | An accurate estimation of forest aboveground biomass (AGB) is important for carbon accounting. In this study, six methods, including partial least squares regression, regression kriging, k-nearest neighbour, support vector machines, random forest and high accuracy surface modelling (HASM), were used to simulate forest AGB. Forest AGB was mapped by combining Geoscience Laser Altimeter System data, optical imagery and field inventory data. The Normalized Difference Vegetation Index (NDVI) and Wide Dynamic Range Vegetation Index (WDRVI0.2) of September and October, which had a stronger correlation with forest AGB than that of the peak growing season, were selected as predictor variables, along with tree cover percentage and three GLAS-derived parameters. The results of the different methods were evaluated. The HASM model had the best modelling accuracy (small MAE, RMSE, NRMSE, RMSV and NMSE and large R-2). A forest AGB map of the study area was generated using the optimal model. |
| WOS关键词 | TROPICAL FOREST ; SPATIAL-DISTRIBUTION ; VEGETATION ; PREDICTION ; IMAGERY ; LIDAR ; UNCERTAINTY ; COMBINATION ; STOCK ; GLAS |
| 资助项目 | National Key Research and Development Program of China[2016YFA0600204] ; National Natural Science Foundation of China[41501428] ; National Natural Science Foundation of China[41421001] ; National Natural Science Foundation of China[41590844] ; National Natural Science Foundation of China[41371400] ; Natural Science Foundation of Shandong Province, China[ZR2017BD010] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000484060700001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Shandong Province, China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/69635]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Meng |
| 作者单位 | 1.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing, Peoples R China 2.Qufu Normal Univ, Coll Geog & Tourism, Rizhao, Peoples R China 3.Forestry Bur Suining Cty, Shaoyang, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Xiaofang,Li, Bai,Du, Zhengping,et al. Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data[J]. GEOCARTO INTERNATIONAL,2019:16. |
| APA | Sun, Xiaofang.,Li, Bai.,Du, Zhengping.,Li, Guicai.,Fan, Zemeng.,...&Yue, Tianxiang.(2019).Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data.GEOCARTO INTERNATIONAL,16. |
| MLA | Sun, Xiaofang,et al."Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data".GEOCARTO INTERNATIONAL (2019):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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