Semantic Segmentation Deep Learning for Extracting Surface Mine Extents from Historic Topographic Maps

Semantic Segmentation Deep Learning for Extracting Surface Mine Extents from Historic Topographic Maps

Historic topographic maps, which are georeferenced and made publicly available by the United States Geological Survey (USGS) and the National Map’s Historical Topographic Map Collection (HTMC), are a valuable source of historic land cover and land use (LCLU) information that could be used to expand...

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Bibliographic Details
Main Authors: Aaron E. Maxwell, Michelle S. Bester, Luis A. Guillen, Christopher A. Ramezan, Dennis J. Carpinello, Yiting Fan, Faith M. Hartley, Shannon M. Maynard, Jaimee L. Pyron
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
semantic segmentation
UNet
deep learning
convolutional neural networks
topographic maps
feature extraction
Online Access:https://www.mdpi.com/2072-4292/12/24/4145

Internet

https://www.mdpi.com/2072-4292/12/24/4145

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