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Enhancing Reproducibility and Replicability in Remote Sensing Deep Learning R...
Many issues can reduce the reproducibility and replicability of deep learning (DL) research and application in remote sensing, including the complexity and customizability of... -
Forest Type Differentiation Using GLAD Phenology Metrics, Land Surface Parame...
This study investigates the mapping of forest community types for the entire state of West Virginia, United States, using Global Land Analysis and Discovery (GLAD) Phenology... -
Is high spatial resolution DEM data necessary for mapping palustrine wetlands?
Digital elevation models (DEMs) have been found to be an effective data source for automated mapping of wetlands. However, it is unclear whether high spatial resolution DEMs,... -
Large-Area, High Spatial Resolution Land Cover Mapping Using Random Forests, ...
Despite the need for quality land cover information, large-area, high spatial resolution land cover mapping has proven to be a difficult task for a variety of reasons including... -
Thematic Classification Accuracy Assessment with Inherently Uncertain Boundar...
Accuracy assessment is one of the most important components of both applied and research-oriented remote sensing projects. For mapped classes that have sharp and easily... -
Mapping the Topographic Features of Mining-Related Valley Fills Using Mask R-...
Modern elevation-determining remote sensing technologies such as light-detection and ranging (LiDAR) produce a wealth of topographic information that is increasingly being used...