Arid
DOI10.1117/1.3563569
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
ISSN1931-3195
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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