Cross-Domain Urban Land Use Classification via Scenewise Unsupervised Multisource Domain Adaptation With Transformer-Reference-Cited by-同舟云学术

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Cross-Domain Urban Land Use Classification via Scenewise Unsupervised Multisource Domain Adaptation With Transformer

Published:2024 Issue: Volume:17 Page:10051-10066
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Li Mengmeng¹^ORCID,Zhang Congcong¹,Zhao Wufan²^ORCID,Zhou Wen³^ORCID

Affiliation:

1. Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China

2. Urban Governance and Design Thrust, Society Hub, The Hong Kong University of Science and Technology, Guangzhou, China

3. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province, China

Fujian Science and Technology Plan Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10529516.pdf?arnumber=10529516

Reference54 articles.

1. Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018

2. Knowledge-guided land pattern depiction for urban land use mapping: A case study of Chinese cities

3. Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery

4. Open-source data-driven urban land-use mapping integrating point-line-polygon semantic objects: A case study of Chinese cities

5. Domain Adaptation via a Task-Specific Classifier Framework for Remote Sensing Cross-Scene Classification

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