Fractional vegetation cover estimation algorithm for Chinese GF-1 wide field view data
文献类型：期刊论文
| 作者 | Jia, Kun1; Liang, Shunlin1; Gu, Xingfa1; Baret, F.1; Wei, Xiangqin1; Wang, Xiaoxia1; Yao, Yunjun1; Yang, Linqing1; Li, Yuwei1 |
| 刊名 | Remote Sensing of Environment
 |
| 出版日期 | 2016 |
| 卷号 | 177页码:184-191 |
| 关键词 | CROP CLASSIFICATION SATELLITE DATA THEMATIC MAPPER SOUTH-AMERICA FOREST COVER TM DATA PLANTATIONS IMAGERY CHINA MODEL |
| 通讯作者 | Jia, Kun (jiakun@bnu.edu.cn) |
| 英文摘要 | Wide field view (WFV) sensor on board the Chinese GF-1, the first satellite of the China High-resolution Earth Observation System, is acquiring multi-spectral data with decametric spatial resolution, high temporal resolution and wide coverage, which are valuable data sources for environment monitoring. The objective of this study is to develop a general and reliable fractional vegetation cover (FVC) estimation algorithm for GF-1 WFV data under various land surface conditions. The algorithm is expected to estimate FVC from GF-1 WFV reflectance data with spatial resolution of 16 m and temporal resolution of four dates. The proposed algorithm is based on training back propagation neural networks (NNs) using PROSPECT + SAIL radiative transfer model simulations for GF-1 WFV canopy reflectance and corresponding FVC values. Green, red and near-infrared bands' reflectances of GF-1 WFV data are the input variables of the NNs, as well as the corresponding FVC is the output variable, and finally 842,400 simulated samples covering various land surface conditions are used for training the NNs. A case study in Weichang County of China, having abundant land cover types, was conducted to validate the performance of the proposed FVC estimation algorithm for GF-1 WFV data. The validation results showed that the proposed algorithm worked effectively and generated reasonable FVC estimates with R2= 0.790 and root mean square error of 0.073 based on the field survey data. The proposed algorithm can be operated without prior knowledge on the land cover and has the potential for routine production of high quality FVC products using GF-1 WFV surface reflectance data. © 2016 Elsevier Inc. |
| 学科主题 | Environmental Sciences & Ecology; Remote Sensing; Imaging Science & Photographic Technology |
| 类目[WOS] | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20160902037988 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39416]  |
| 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, School of Geography, Beijing Normal University, Beijing, China 2. Department of Geographical Sciences, University of Maryland, College Park, MD, United States 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 4. INRA-EMMAH UMR, Avignon, France |
| 推荐引用方式 GB/T 7714 | Jia, Kun,Liang, Shunlin,Gu, Xingfa,et al. Fractional vegetation cover estimation algorithm for Chinese GF-1 wide field view data[J]. Remote Sensing of Environment,2016,177:184-191. |
| APA | Jia, Kun.,Liang, Shunlin.,Gu, Xingfa.,Baret, F..,Wei, Xiangqin.,...&Li, Yuwei.(2016).Fractional vegetation cover estimation algorithm for Chinese GF-1 wide field view data.Remote Sensing of Environment,177,184-191. |
| MLA | Jia, Kun,et al."Fractional vegetation cover estimation algorithm for Chinese GF-1 wide field view data".Remote Sensing of Environment 177(2016):184-191. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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