Measuring Maritime Forest Loss (2012–2022) in a roadless Coastal Barrier Resources System Unit with Multi-Sensor Object-Based Image Analysis, Outer Banks, North Carolina.
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Keywords: Coastal Barrier Resources Act, residential development, deforestation, geomorphology, remote sensing, Object-Based Image Analysis, LULC change, lidar, NAIP
Abstract Type: Paper Abstract
Authors:
Ryley C Harris, Virginia Tech
Lisa M Kennedy, Virginia Tech Department of Geography
Thomas R Allen, Old Dominion University
Thomas Crawford, Virginia Tech
Valerie A Thomas, Virginia Tech
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Abstract
Coastal economies rely heavily on ecotourism to sustain livelihoods, while ongoing ecosystem disturbance driven by residential and commercial development threatens coastal land and biological resources. Coastal barriers also protect inland areas from storms and provide critical habitats for aquatic and terrestrial plants and animals. Our study area includes a 19km stretch of remote, roadless barrier island on the northern Outer Banks that encompasses private ownership and conservation areas and easements. The Coastal Barrier Resources Act has been largely ineffective in preventing development in the roadless area, resulting in the fragmentation of maritime forests and filling of estuarine ecosystems, thereby reducing biodiversity and flood mitigation capacity. This research quantified land cover change since 2012 using a remote sensing approach—multi-sensor object-based image analysis—with inputs including airborne lidar data and NAIP aerial photography. We measured changes in vegetation cover and deforestation patterns within the study area, also examining other land cover changes and data sets relevant to development to identify the drivers of vegetation loss/change and changes in sediment distribution. Our findings can assist with policies related to the regulation of development in risky and flood-prone areas and can pinpoint areas in greatest need of conservation.
Measuring Maritime Forest Loss (2012–2022) in a roadless Coastal Barrier Resources System Unit with Multi-Sensor Object-Based Image Analysis, Outer Banks, North Carolina.
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Paper Abstract