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Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object based classification approachesAuthor(s): Dacia M. Meneguzzo; Greg C. Liknes; Mark D. Nelson
Source: Environmental Monitoring and Assessment. 185: 6261-6275.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionDiscrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis--[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA.
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CitationMeneguzzo, Dacia M.; Liknes, Greg C.; Nelson, Mark D. 2013. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object based classification approaches. Environmental Monitoring and Assessment. 185: 6261-6275.
KeywordsTrees outside forests, Forest inventory, Tree cover, Aerial photography, Object-based image analysis, Independent component analysis
- Research Activities in Support of High-Resolution Land Cover Mapping in the North Central United States
- A framework for reporting tree cover attributes in agricultural landscapes
- Image-based change estimation for land cover and land use monitoring
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