Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China
文献类型：期刊论文
| 作者 | Xia, Haoming1,2 ; Zhao, Wei1; Li, Ainong1; Bian, Jinhu1,3; Zhang, Zhengjian1,3
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| 刊名 | REMOTE SENSING
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| 出版日期 | 2017 |
| 卷号 | 9期号:1页码:doi:10.3390/rs9010031 |
| 关键词 | wetland subpixel inundation percentage (SIP) Landsat-8 unmanned aerial vehicle (UAV) linear spectral unmixing (LSU) regression tree (RT) artificial neural networks (ANN) Zoige Plateau |
| ISSN号 | 2072-4292 |
| 通讯作者 | Ainong Li |
| 英文摘要 | Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data. A reference subpixel inundation percentage (SIP) map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m). The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU), Artificial neural networks (ANN), and Regression tree (RT)). Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R-2 = 0.933, RMSE = 8.73%) compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R-2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Remote Sensing |
| 研究领域[WOS] | Remote Sensing |
| 关键词[WOS] | DIFFERENCE WATER INDEX ; NEURAL-NETWORK ; TIME-SERIES ; IMPERVIOUS SURFACES ; IMAGE-ANALYSIS ; VEGETATION ; DYNAMICS ; FEATURES ; MODELS ; COVER |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000395492600031 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/18530]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 作者单位 | 1.Chinese Acad Sci, Inst Mt Hazards & Environm, Res Ctr Digital Mt & Remote Sensing Applicat, Chengdu 610041, Peoples R China 2.Henan Univ, Coll Environm & Planning, Key Lab Geospatial Technol Middle & Lower Yellow, Kaifeng 475004, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xia, Haoming,Zhao, Wei,Li, Ainong,et al. Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China[J]. REMOTE SENSING,2017,9(1):doi:10.3390/rs9010031. |
| APA | Xia, Haoming,Zhao, Wei,Li, Ainong,Bian, Jinhu,&Zhang, Zhengjian.(2017).Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China.REMOTE SENSING,9(1),doi:10.3390/rs9010031. |
| MLA | Xia, Haoming,et al."Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China".REMOTE SENSING 9.1(2017):doi:10.3390/rs9010031. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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