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Posts
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
Scale parameter estimation based on the spatial and spectral statistics in high spatial resolution image segmentation
Published in Journal of Geo-information Science, 2016
Recommended citation: Ming D P, Zhou W, Wang M. Scale parameter estimation based on the spatial and spectral statistics in high spatial resolution image segmentation. Journal of Geo-information Science, 2016, 18(5):622-631.
Applying Spatial Statistics into Remote Sensing Pattern Recognition: with Case Study of Cropland Extraction Based on GeOBIA
Published in Acta Geodaetica Et Cartographica Sinica, 2016
Recommended citation: Ming D, Qiu Y, Zhou W. Applying Spatial Statistics into Remote Sensing Pattern Recognition: with Case Study of Cropland Extraction Based on GeOBIA. Acta Geodaetica Et Cartographica Sinica, 2016, 45(7):825-833.
Stratified Object-Oriented Image Classification Based on Remote Sensing Image Scene Division
Published in Journal of Spectroscopy, 2018
Recommended citation: Zhou W, Ming D, Xu L, Bao H, Wang M. Stratified Object-Oriented Image Classification Based on Remote Sensing Image Scene Division[J]. Journal of Spectroscopy, 2018(1):1-11. (IF: 1.81)
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Cultivated land extraction based on image region division and scale estimation
Published in Journal of Geo-information Science, 2018
Recommended citation: Zhou W, Ming D P, Yan P F. Cultivated land extraction based on image region division and scale estimation. Journal of Geo-information Science, 2018, 20(7):1014-1025.
Coupling relationship among scale parameter, segmentation accuracy, and classification accuracy in GeOBIA
Published in Photogrammetric Engineering & Remote Sensing, 2018
Recommended citation: Ming D, Zhou W, Xu L, et al. Coupling relationship among scale parameter, segmentation accuracy, and classification accuracy in GeOBIA[J]. Photogrammetric Engineering & Remote Sensing, 2018, 84(11): 681-693. (IF: 1.47)
Applying Spatial Statistics to Evaluate the Accuracy of Remote Sensing Image Classification
Published in Journal of Geomatics, 2019
Recommended citation: Ming D, Qiu Y, Zhou W. Applying Spatial Statistics to Evaluate the Accuracy of Remote Sensing Image Classification. Journal of Geomatics. 2019, 44(1): 1-5. (IF: 1.64)
Farmland Extraction from High Spatial Resolution Remote Sensing Images Based on Stratified Scale Pre-Estimation
Published in Remote Sensing, 2019
Recommended citation: Xu L, Ming D, Zhou W, Hanqing Bao, Yangyang Chen, Xiao Ling. Farmland Extraction from High Spatial Resolution Remote Sensing Images Based on Stratified Scale Pre-Estimation. Remote Sensing. 2019, 11(2), 108.
Urban functional zone fine division with VHR remote sensing image based on SO-CNN
Published in Remote Sensing, 2019
Recommended citation: Ming D, Zhou W, Xu L, et al. Urban functional zone fine division with VHR remote sensing image based on SO-CNN. Remote Sensing. 2019, 11(12), 1460. (IF: 5.7)
SO–CNN based urban functional zone fine division with VHR remote sensing image
Published in Remote Sensing of Environment, 2020
Recommended citation: Zhou W, Ming D, Lv X, et al. SO–CNN based urban functional zone fine division with VHR remote sensing image[J]. Remote Sensing of Environment, 2020, 236: 111458.
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BTS: a binary tree sampling strategy for object identification based on deep learning
Published in International journal of geographical information science, 2022
Recommended citation: Lv, X., Shao, Z., Huang, X., Zhou, W., Ming, D., Wang, J., & Tong, C. BTS: a binary tree sampling strategy for object identification based on deep learning. International journal of geographical information science, 36(4), 822-848.
Identifying Urban Functional Regions from High-Resolution Satellite Images Using a Context-Aware Segmentation Network
Published in Remote Sensing, 2022
Recommended citation: Zhao, W., Li, M., Wu, C., Zhou, W., & Chu, G. Identifying Urban Functional Regions from High-Resolution Satellite Images Using a Context-Aware Segmentation Network. Remote Sensing, 14(16), 3996.
Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information
Published in Remote Sensing of Environment, 2023
Recommended citation: Zhou W, Persello C, Li M, Stein A. Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information. Remote Sensing of Environment, 2023, 297: 113767.
Cross-Domain Urban Land Use Classification Via Scene-Wise Unsupervised Multi-Source Domain Adaptation With Transformer
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024
Recommended citation: Li M, Zhang C, Zhao W, Zhou W. Cross-Domain Urban Land Use Classification Via Scene-Wise Unsupervised Multi-Source Domain Adaptation With Transformer. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.
Hierarchical building use classification from multiple modalities with a multi-label multimodal transformer network
Published in International Journal of Applied Earth Observation and Geoinformation, 2024
Recommended citation: Zhou W, Persello C, Stein A. Hierarchical building use classification from multiple modalities with a multi-label multimodal transformer network[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 132: 104038.
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Building hierarchical use classification based on multiple data sources with a multi-label multimodal transformer network
Published in EGU General Assembly 2024, 2024
Recommended citation: Zhou W, Persello C, Stein A. Building hierarchical use classification based on multiple data sources with a multi-label multimodal transformer network, EGU General Assembly 2024, Vienna, Austria, 14-19 Apr 2024, EGU24-12472.
Toward 3D hedonic price model for vertically developed cities using street view images and machine learning methods
Published in Habitat International, 2025
Recommended citation: Ying Y., Dai S., Koeva M., Kuffer M., Persello C., Zhou W., Zevenbergen J. Toward 3D hedonic price model for vertically developed cities using street view images and machine learning methods. Habitat International 156 (2025): 103288.
Urban livability evaluation based on multimodal deep learning fusing multiple remote sensing images and geospatial textual data
Published in Remote Sensing of Environment, 2025
Recommended citation: Zhou W, et al. Urban livability evaluation based on multimodal deep learning fusing multiple remote sensing images and geospatial textual data[J]. Remote Sensing of Environment. (Major review)
talks
teaching
Postdoctoral Research Associate
Research Position, University of Illinois Urbana-Champaign, 2024
Postdoctoral Research Associate in the Department of Geography and GIS, focusing on urban research using multiple geospatial data, GeoAI, and GIS.