Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.rse.2016.02.040 |
Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011) | |
Halabisky, Meghan1; Moskal, L. Monika1; Gillespie, Alan2; Hannam, Michael3 | |
通讯作者 | Halabisky, Meghan |
来源期刊 | REMOTE SENSING OF ENVIRONMENT
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ISSN | 0034-4257 |
EISSN | 1879-0704 |
出版年 | 2016 |
卷号 | 177页码:171-183 |
英文摘要 | Wetlands are valuable ecosystems for maintaining biodiversity, but are vulnerable to climate change and land conversion. Despite their importance, wetland hydrology is poorly understood as few tools exist to monitor their hydrologic regime at a landscape scale. This is especially true when monitoring hydrologic change at scales below 30 m, the resolution of one Landsat pixel. To address this, we used spectral mixture analysis (SMA) of a time series of Landsat satellite imagery to reconstruct surface-water hydrographs for 750 wetlands in Douglas County, Washington State, USA, from 1984 to 2011. SMA estimates the fractional abundance of spectra representing physically meaningful materials, known as spectral endmembers, which comprise a mixed pixel, thus providing sub-pixel estimates of surface water extent Endmembers for water and sage steppe were selected directly from each image scene in the Landsat time series, whereas endmembers for salt and wetland vegetation were derived from a mean spectral signature of selected dates spanning the 1984-2011 timeframe. This method worked well (R-2 = 0.99) for even small wetlands (<1800 m(2)) providing a wall-to-wall dataset of reconstructed surface-water hydrographs for wetlands across our study area. We have validated this method only in semi-arid regions. Further research is necessary to extend its validity to other environments. This method can be used to better understand the role of hydrology in wetland ecosystems and as a monitoring tool to identify wetlands undergoing abnormal change. (C) 2016 Elsevier Inc. All rights reserved. |
英文关键词 | Time series Landsat Wetlands Hydrology Hydroperiod High resolution OBIA Object-based image analysis Hydrograph Monitoring Sub-pixel |
类型 | Article |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000373550100015 |
WOS关键词 | FORESTED WETLANDS ; PRAIRIE WETLANDS ; CLIMATE-CHANGE ; CLASSIFICATION ; LIDAR ; HYDROPERIOD ; BATHYMETRY ; INUNDATION ; SERVICES ; SYSTEM |
WOS类目 | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/195998 |
作者单位 | 1.Univ Washington, Sch Environm & Forest Sci, Seattle, WA 98195 USA; 2.Univ Washington, Dept Earth & Space Sci, Seattle, WA 98195 USA; 3.Smithsonian Environm Res Ctr, POB 28, Edgewater, MD 21037 USA |
推荐引用方式 GB/T 7714 | Halabisky, Meghan,Moskal, L. Monika,Gillespie, Alan,et al. Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011)[J],2016,177:171-183. |
APA | Halabisky, Meghan,Moskal, L. Monika,Gillespie, Alan,&Hannam, Michael.(2016).Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011).REMOTE SENSING OF ENVIRONMENT,177,171-183. |
MLA | Halabisky, Meghan,et al."Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011)".REMOTE SENSING OF ENVIRONMENT 177(2016):171-183. |
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文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
Reconstructing semi-(3302KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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