Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1117/1.3563569 |
Object-based classification of semi-arid wetlands | |
Halabisky, Meghan1; Moskal, L. Monika1; Hall, Sonia A.2 | |
通讯作者 | Halabisky, Meghan |
来源期刊 | JOURNAL OF APPLIED REMOTE SENSING
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ISSN | 1931-3195 |
出版年 | 2011 |
卷号 | 5 |
英文摘要 | Wetlands are valuable ecosystems that benefit society. However, throughout history wetlands have been converted to other land uses. For this reason, timely wetland maps are necessary for developing strategies to protect wetland habitat. The goal of this research was to develop a time-efficient, automated, low-cost method to map wetlands in a semi-arid landscape that could be scaled up for use at a county or state level, and could lay the groundwork for expanding to forested areas. Therefore, it was critical that the research project contain two components: accurate automated feature extraction and the use of low-cost imagery. For that reason, we tested the effectiveness of geographic object-based image analysis (GEOBIA) to delineate and classify wetlands using freely available true color aerial photographs provided through the National Agriculture Inventory Program. The GEOBIA method produced an overall accuracy of 89% (khat = 0.81), despite the absence of infrared spectral data. GEOBIA provides the automation that can save significant resources when scaled up while still providing sufficient spatial resolution and accuracy to be useful to state and local resource managers and policymakers. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3563569] |
英文关键词 | semi-arid wetlands geographic object-based image analysis segmentation GEOBIA/OBIA feature extraction aerial photography |
类型 | Article |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000289546600002 |
WOS关键词 | AERIAL-PHOTOGRAPHY ; ECOSYSTEM SERVICES ; IMAGES |
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/2XILL650/168820 |
作者单位 | 1.Univ Washington, Sch Forest Resources, Remote Sensing & Geospatial Anal Lab, Seattle, WA 98195 USA; 2.Nature Conservancy, Wenatchee, WA 98801 USA |
推荐引用方式 GB/T 7714 | Halabisky, Meghan,Moskal, L. Monika,Hall, Sonia A.. Object-based classification of semi-arid wetlands[J],2011,5. |
APA | Halabisky, Meghan,Moskal, L. Monika,&Hall, Sonia A..(2011).Object-based classification of semi-arid wetlands.JOURNAL OF APPLIED REMOTE SENSING,5. |
MLA | Halabisky, Meghan,et al."Object-based classification of semi-arid wetlands".JOURNAL OF APPLIED REMOTE SENSING 5(2011). |
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