Using Land-Use Change, Soil Characteristics, and a Semi-Automated On-Line GIS Database to Inventory Carolina Bays

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• 作者：Dana G. Sullivan ; Jeffrey G. White ; Michael J. Vepraskas
• 关键词：Carolina Bay ; Wetland ; Land ; use change ; Remote sensing ; Inventory ; Geographic information system (GIS) ; Landsat ; Image analysis and classification
• 刊名：Wetlands
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：37
• 期：1
• 页码：89-98
• 全文大小：
• 刊物主题：Freshwater & Marine Ecology; Environmental Management; Ecology; Hydrogeology; Coastal Sciences; Landscape Ecology;
• 出版者：Springer Netherlands
• ISSN：1943-6246
• 卷排序：37

文摘

Carolina Bay wetlands are common in the southeastern US Coastal Plain and important to water quality, carbon sequestration, and habitat. Only South Carolina and Georgia have statewide inventories. We developed and evaluated a novel way to identify and delineate Bays using Bay-dense Bladen County, NC as a testbed. We posited that Bay land use had changed in the past 40 years and that Bays comprise a small subset of their surrounding soils. We classified decadal Landsat images as forest, agriculture, urban, and water. We used 812 previously delineated Bays to identify common Bay soils. From areas with common Bay soils and land-use change, we identified 548 new Bays and delineated them using a semi-automated on-line digitization tool. We saved new Bays to a Google Fusion Table for download and integration within a GIS. To gauge accuracy, Bays were scored on soils, land-use change, wetland delineation, and landscape position. Potential errors included omission of some small Bays (3.3–14.6 % of total Bay area) and commission of misclassified Bays (11 % of 1360 Bays), an estimated overall accuracy of 74 to 86 %. With 1360 delineated Bays, we estimated that as many as 478 have not yet been identified. These are most likely <5.76 ha.