Land-Use Classification using Finite Element Machines

Satellite images have been used in a number of applications, both in the academy and in the industry. One critical purpose concerns the land-use classification, which aims at automatically identifying different land-use applications, which range from economy and environmental monitoring to resources...

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Bibliographic Details
Published inIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium pp. 7316 - 7319
Main Authors Pereira, D.R., Papa, J.P., Papa, L.P., Pisani, R.J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2018
Subjects
Earth
Finite element analysis
Finite Element Machines
Forestry
Land-use classification
Remote sensing
Roads
Satellites
Training
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Summary:Satellite images have been used in a number of applications, both in the academy and in the industry. One critical purpose concerns the land-use classification, which aims at automatically identifying different land-use applications, which range from economy and environmental monitoring to resources planning. In this paper, we introduce a new machine learning technique called Finite Element Machines (FEMa) in the context of land-use classification using satellite images. We show that FEMa can obtain results that are comparable to some state-of-the-art techniques in the literature.
ISSN:2153-7003
DOI:10.1109/IGARSS.2018.8519252