A Geoscience-Aware Network (GASlumNet) Combining UNet and ConvNeXt for Slum Mapping

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Lu, Wei;Hu, Yunfeng;Peng, Feifei;Feng, Zhiming;Yang, Yanzhao;...

通讯作者：

Hu, YF

作者机构：

[Hu, YF; Lu, Wei; Hu, Yunfeng; Feng, Zhiming; Yang, Yanzhao] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

[Hu, YF; Lu, Wei; Hu, Yunfeng; Feng, Zhiming; Yang, Yanzhao] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.

[Peng, Feifei] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.

[Peng, Feifei] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.

通讯机构：

[Hu, YF ] C

Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.

Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.

语种：

英文

关键词：

slum mapping;deep learning;geoscience-aware paradigm;semantic segmentation;remote sensing

期刊：

Remote Sensing

ISSN：

2072-4292

年：

2024

卷：

期：

DOI：

10.3390/rs16020260

基金类别：

Network Security and Information Program of the Chinese Academy of Sciences

机构署名：

本校为其他机构

院系归属：

城市与环境科学学院

摘要：

Approximately 1 billion people worldwide currently inhabit slum areas. The UN Sustainable Development Goal (SDG 11.1) underscores the imperative of upgrading all slums by 2030 to ensure adequate housing for everyone. Geo-locations of slums help local governments with upgrading slums and alleviating urban poverty. Remote sensing (RS) technology, with its excellent Earth observation capabilities, can play an important role in slum mapping. Deep learning (DL)-based RS information extraction methods have attracted a lot of attention. Currently, DL-based slum mapping studies typically uses three op...

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A Geoscience-Aware Network (GASlumNet) Combining UNet and ConvNeXt for Slum Mapping

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