Mapping and Monitoring of Land Cover/Land Use (LCLU) Changes in the Crozon Peninsula (Brittany, France) from 2007 to 2018 by Machine Learning Algorithms (Support Vector Machine, Random Forest, and Convolutional Neural Network) and by Post-classification Comparison (PCC)

Mapping and Monitoring of Land Cover/Land Use (LCLU) Changes in the Crozon Peninsula (Brittany, France) from 2007 to 2018 by Machine Learning Algorithms (Support Vector Machine, Random Forest, and Convolutional Neural Network) and by Post-classification Comparison (PCC)

Land cover/land use (LCLU) is currently a very important topic, especially for coastal areas that connect the land and the coast and tend to change frequently. LCLU plays a crucial role in land and territory planning and management tasks. This study aims to complement information on the types and ra...

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Bibliographic Details
Main Authors: Guanyao Xie, Simona Niculescu
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Remote Sensing
Subjects:
remote sensing
machine learning
GEOBIA
CNN
land cover/land use
SPOT 5
Online Access:https://www.mdpi.com/2072-4292/13/19/3899

Internet

https://www.mdpi.com/2072-4292/13/19/3899

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