Artificial neural networks in geospatial analysis
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Date
2017-04-05
Authors
Gopal, Sucharita
Version
OA Version
Citation
Sucharita Gopal. 2017. "Artificial Neural Networks in Geospatial Analysis." In: The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. Edited by Douglas Richardson, Noel Castree, Michael F. Goodchild, Audrey Kobayashi, Weidong Liu, and Richard A. Marston. DOI: 10.1002/9781118786352.wbieg0322
Abstract
Artificial neural networks are computational models widely used in geospatial analysis for data classification, change detection, clustering, function approximation, and forecasting or prediction. There are many types of neural networks based on learning paradigm and network architectures. Their use is expected to grow with increasing availability of massive data from remote sensing and mobile platforms.
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License
© 2017 John Wiley & Sons, Ltd. Published 2017 by John Wiley & Sons, Ltd