Automatic mapping of urban green spaces using a geospatial neural network

Automatic mapping of urban green spaces using a geospatial neural network

Detailed and precise urban green spaces (UGS) maps provide essential data for the sustainable urban development and related studies (e.g. heatwave events, heat related health risk, urban flooding, urban biodiversity and ecosystem services). However, remote sensing of mapping UGS is challenging due t...

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Bibliographic Details
Main Authors: Yang Chen, Qihao Weng, Luliang Tang, Qinhuo Liu, Xia Zhang, Muhammad Bilal
Format: Article
Language:English
Published: Taylor & Francis Group 2021-05-01
Series:GIScience & Remote Sensing
Subjects:
urban green spaces
remote-sensing imagery
crowdsourcing
geospatial big data
deep learning
sdg 11.7
urban areas
Online Access:http://dx.doi.org/10.1080/15481603.2021.1933367

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