A Comparison of Different Machine Learning Algorithms in the Classification of Impervious Surfaces: Case Study of the Housing Estate Fort Bema in Warsaw (Poland)

A Comparison of Different Machine Learning Algorithms in the Classification of Impervious Surfaces: Case Study of the Housing Estate Fort Bema in Warsaw (Poland)

The aim of this study is to extract impervious surfaces and show their spatial distribution, using different machine learning algorithms. For this purpose, geoprocessing and remote sensing techniques were used and three classification methods for digital images were compared, namely Support Vector M...

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Bibliographic Details
Main Authors: Janusz Sobieraj, Marcos Fernández, Dominik Metelski
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Buildings
Subjects:
support vector machines (SVM)
maximum likelihood (ML)
random trees (RT)
impervious surfaces
land use and land cover (LULC)
normalised difference vegetation index (NDVI)
Online Access:https://www.mdpi.com/2075-5309/12/12/2115

Internet

https://www.mdpi.com/2075-5309/12/12/2115

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