Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural netw...

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Bibliographic Details
Main Author: Lee, Saro (auth)
Other Authors: Jung, Hyung-Sup (auth)
Format: Electronic Book Chapter
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
Subjects:
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GIS
Online Access:DOAB: download the publication
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Description
Summary:As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
Physical Description:1 electronic resource (438 p.)
ISBN:books978-3-03921-216-3
9783039212156
9783039212163
Access:Open Access