Quantifying multi-decadal change of planted forest cover using airborne LiDAR and Landsat imagery
文献类型：期刊论文
| 作者 | Wang, Xiaoyi1; Huang, Huabing1; Gong, Peng1; Biging, Gregory S.1; Xin, Qinchuan1; Chen, Yanlei1; Yang, Jun1; Liu, Caixia1 |
| 刊名 | Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 8期号:1 |
| 关键词 | MUTUAL INFORMATION SIFT |
| 通讯作者 | Huang, Huabing (huanghb@radi.ac.cn) |
| 英文摘要 | Continuous monitoring of forest cover condition is key to understanding the carbon dynamics of forest ecosystems. This paper addresses how to integrate single-year airborne LiDAR and time-series Landsat imagery to derive forest cover change information. LiDAR data were used to extract forest cover at the sub-pixel level of Landsat for a single year, and the Landtrendr algorithm was applied to Landsat spectral data to explore the temporal information of forest cover change. Four different approaches were employed to model the relationship between forest cover and Landsat spectral data. The result shows incorporating the historic information using the temporal trajectory fitting process could infuse the model with better prediction power. Random forest modeling performs the best for quantitative forest cover estimation. Temporal trajectory fitting with random forest model shows the best agreement with validation data (R2= 0.82 and RMSE = 5.19%). We applied our approach to Youyu county in Shanxi province of China, as part of the Three North Shelter Forest Program, to map multi-decadal forest cover dynamics. With the availability of global time-series Landsat imagery and affordable airborne LiDAR data, the approach we developed has the potential to derive large-scale forest cover dynamics. © 2016 by the authors; licensee MDPI, Basel, Switzerland. |
| 学科主题 | Remote Sensing |
| 类目[WOS] | Remote Sensing |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20160701945611 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39237]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (CAS), Beijing, China 2. Department of Environmental Sciences, Policy and Management, University of California, Berkeley, CA, United States 3. Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China 4. Joint Center for Global Change Studies, Beijing, China 5. School of Geography and Planning, Sun Yat-sen University, Guangzhou, China |
| 推荐引用方式 GB/T 7714 | Wang, Xiaoyi,Huang, Huabing,Gong, Peng,et al. Quantifying multi-decadal change of planted forest cover using airborne LiDAR and Landsat imagery[J]. Remote Sensing,2016,8(1). |
| APA | Wang, Xiaoyi.,Huang, Huabing.,Gong, Peng.,Biging, Gregory S..,Xin, Qinchuan.,...&Liu, Caixia.(2016).Quantifying multi-decadal change of planted forest cover using airborne LiDAR and Landsat imagery.Remote Sensing,8(1). |
| MLA | Wang, Xiaoyi,et al."Quantifying multi-decadal change of planted forest cover using airborne LiDAR and Landsat imagery".Remote Sensing 8.1(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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