2024
DOI: 10.1002/esp.5985
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The feasibility of using national‐scale datasets for classifying wetlands in Arizona with machine learning

Christopher E. Soulard,
Jessica J. Walker,
Britt W. Smith
et al.

Abstract: The advent of machine learning techniques has led to a proliferation of landscape classification products. These approaches can fill gaps in wetland inventories across the United States (U.S.) provided that large reference datasets are available to develop accurate models. In this study, we tested the feasibility of expediting the classification process by sourcing requisite training and testing data from existing national‐scale land cover maps instead of customized sample sets. We created a single map of wate… Show more

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