A Decision Rule and Machine Learning-Based Hybrid Approach for Automated Land-Cover Type Local Climate Zones (LCZs) Mapping Using Multi-Source Remote Sensing Data

A Decision Rule and Machine Learning-Based Hybrid Approach for Automated Land-Cover Type Local Climate Zones (LCZs) Mapping Using Multi-Source Remote Sensing Data

This article presents a streamlined, automated classification method to map land-cover-type local climate zones (LCZs). Using a two-phase hybrid approach, we first generated training samples through universal decision rules and subsequently, a machine learning (ML) algorithm was trained on the gener...

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Bibliographic Details
Main Authors: Md Didarul Islam, Liping Di, Chen Zhang, Ruixin Yang, John J. Qu, Daniel Tong, Liying Guo, Li Lin, Aran Pandey
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Local climate zones (LCZs)
machine learning (ML)
multisource remotely sensed data
vegetation mapping
Online Access:https://ieeexplore.ieee.org/document/10494866/

Internet

https://ieeexplore.ieee.org/document/10494866/

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