Estimation of High-Resolution Fractional Tree Cover Using Landsat Time-Series Observations
文献类型：期刊论文
| 作者 | Chen, Jilong2; Liu, Yang; Liu, Ronggao; Wei, Xuexin2 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2023-10-17 |
| 卷号 | 61页码:4409411 |
| 关键词 | Forest fractional tree cover high resolution time-series observations |
| DOI | 10.1109/TGRS.2023.3323641 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | High-resolution fractional tree cover mapping allows for the representation of spatial details of tree distribution and contributes to forest ecosystem monitoring and modeling. However, the estimation of tree cover at high resolution is challenging, especially in sparsely tree-covered and mountainous areas interfered with background signals (e.g., soil, grass, and water) and terrain shadow. This article presents a fractional tree cover estimation algorithm from Landsat time-series observations at 30-m resolution, with the effects of background and terrain shadow reduced. The seasonal profiles of vegetation index and surface reflectance were constructed from multiyear Landsat data. Three phenological metrics were extracted from the seasonal profiles as input features for tree cover estimation. The training data were collected from the European Space Agency (ESA) WorldCover product and used to calibrate a feedforward neural network model to predict cover fractions. This algorithm extracted the tree cover of major forest types, including boreal, temperate, tropical dry, and moist forests. It also captured the sparse tree cover in areas containing mixtures of tree crowns and grass, bare soil, crop, impervious surface, and water. In two dense montane forest areas, the tree cover fractions on shady and sunny slopes were estimated consistently. The estimation results were evaluated through the reference samples generated from Google submeter-resolution image classification. The values of R-squared (R-2), root-mean-square error (RMSE), and mean absolute error (MAE) reached 0.78, 15.71%, and 11.09%, respectively. The proposed algorithm can be applied to monitor tree cover in spatially fragmented forest areas and sparse forests. |
| WOS关键词 | CONTINUOUS FIELDS ; WOODY COVER ; FOREST ; REFLECTANCE ; PRODUCTS ; AVHRR ; NDVI ; ALGORITHM ; SAVANNA ; SURFACE |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:001090483200006 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/199478]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Jilong,Liu, Yang,Liu, Ronggao,et al. Estimation of High-Resolution Fractional Tree Cover Using Landsat Time-Series Observations[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2023,61:4409411. |
| APA | Chen, Jilong,Liu, Yang,Liu, Ronggao,&Wei, Xuexin.(2023).Estimation of High-Resolution Fractional Tree Cover Using Landsat Time-Series Observations.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61,4409411. |
| MLA | Chen, Jilong,et al."Estimation of High-Resolution Fractional Tree Cover Using Landsat Time-Series Observations".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023):4409411. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。