Evaluation of classification algorithms in the Google Earth Engine platform for the identification and change detection of rural and periurban buildings from very high-resolution images

Evaluation of classification algorithms in the Google Earth Engine platform for the identification and change detection of rural and periurban buildings from very high-resolution images

Building change detection based on remote sensing imagery is a key task for land management and planning e.g., detection of illegal settlements, updating land records and disaster response. Under the post- classification comparison approach, this research aimed to evaluate the feasibility of several...

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Bibliographic Details
Main Authors: Alejandro Coca-Castro, Maycol A. Zaraza-Aguilera, Yilsey T. Benavides-Miranda, Yeimy M. Montilla-Montilla, Heidy B. Posada-Fandiño, Angie L. Avendaño-Gomez, Hernando A. Hernández-Hamon, Sonia C. Garzón-Martinez, Carlos A. Franco-Prieto
Format: Article
Language:English
Published: Universitat Politécnica de Valencia 2021-07-01
Series:Revista de Teledetección
Subjects:
clasificación
construcciones
catastro
computación en la nube
aprendizaje de máquinas
aprendizaje profundo
Online Access:https://polipapers.upv.es/index.php/raet/article/view/15026

Internet

https://polipapers.upv.es/index.php/raet/article/view/15026

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