112 citations as recorded by crossref.

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14. Large-Scale Foundation Model Enhanced Few-Shot Learning for Open-Pit Minefield Extraction M. Shao et al. https://doi.org/10.1109/LGRS.2023.3342215
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27. Modeling the effects of urban park 3D environmental features on bird diversity with interpretable machine learning: A case study of Harbin, northeastern China C. Ding et al. https://doi.org/10.1016/j.avrs.2025.100304
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29. Urban green space landscape patterns and preterm birth: a multicenter cohort study of over one million births in Chengdu, China J. Yin et al. https://doi.org/10.1016/j.envres.2026.124811
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34. HR-UVFormer: A Top-Down and Multimodal Hierarchical Extraction Approach for Urban Villages X. Tan et al. https://doi.org/10.1109/TGRS.2024.3387022
35. Assessing Supply and Demand Discrepancies of Urban Green Space in High-Density Built-Up Areas Based on Vitality Impacts: Evidence from Beijing’s Central Districts, China J. Han et al. https://doi.org/10.3390/su17114828
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39. Re-Net: Multibranch Network With Structural Reparameterization for Landslide Detection in Optical Imagery R. Zhang et al. https://doi.org/10.1109/JSTARS.2023.3344720
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41. Quantifying the nonlinear interactions of 2D/3D building and green space morphology on land surface temperature across different urban functional zones H. Luo et al. https://doi.org/10.1016/j.scs.2026.107175
42. Mapping priority zones for urban heat mitigation in Shanghai: Heat risk vs. shelter provision W. Qian et al. https://doi.org/10.1016/j.compenvurbsys.2025.102330
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44. Impact of Internal and External Landscape Patterns on Urban Greenspace Cooling Effects: Analysis from Maximum and Accumulative Perspectives L. Tang et al. https://doi.org/10.3390/buildings15040573
45. Fully Convolutional Spectral–Spatial Fusion Network Integrating Supervised Contrastive Learning for Hyperspectral Image Classification Y. Shen et al. https://doi.org/10.1109/JSTARS.2023.3319587
46. Modeling Urban-Vegetation Aboveground Carbon by Integrating Spectral–Textural Features with Tree Height and Canopy Cover Ratio Using Machine Learning Y. Fang et al. https://doi.org/10.3390/f16091381
47. Improved YOLOv5s for Small Ship Detection With Optical Remote Sensing Images Z. Liu et al. https://doi.org/10.1109/LGRS.2023.3319025
48. OTCFM: A Sea Surface Temperature Prediction Method Integrating Multi-Scale Periodic Features L. Fan et al. https://doi.org/10.1109/ACCESS.2024.3425514
49. Attention-based deep learning framework for urban flood damage and risk assessment with improved flood prediction and land use segmentation Z. Situ et al. https://doi.org/10.1016/j.ijdrr.2024.105165
50. Enclosed by Walls, Embraced by Trees: Effects of Indoor Residential Crowding and Outdoor Green Space on Mental Health X. Wang et al. https://doi.org/10.1177/0739456X261432155
51. TDFNet: twice decoding V-Mamba-CNN Fusion features for building extraction W. Wang et al. https://doi.org/10.1080/10095020.2025.2514812
52. Novel Enhanced UNet for Change Detection Using Multimodal Remote Sensing Image Z. Lv et al. https://doi.org/10.1109/LGRS.2023.3325439
53. Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network Z. Xu & S. Zhao https://doi.org/10.1038/s41597-023-02844-2
54. Detecting Long-Term Spatiotemporal Dynamics of Urban Green Spaces with Training Sample Migration Method M. Wang et al. https://doi.org/10.3390/rs17081426
55. Automatic topology and capacity generation framework for urban drainage systems with deep learning-based land use segmentation and hydrological characterization Q. Zhong et al. https://doi.org/10.1016/j.jhydrol.2024.131766
56. Exploring the Impact of Park and Surrounding Environments on Violent Crime in Wuhan: An XGBoost-SHAP Approach S. Lin et al. https://doi.org/10.1007/s12061-025-09710-1
57. The cooling effects of urban waterbodies and their driving forces in China N. Hu et al. https://doi.org/10.1016/j.ecolind.2023.111200
58. Crowd detection using Very-Fine-Resolution satellite imagery T. Xiao et al. https://doi.org/10.1016/j.isprsjprs.2026.01.001
59. Identifying Key Variables Influencing User Satisfaction in Urban Waterfront Greenways: A Case Study of Shenyang, China W. Shan et al. https://doi.org/10.1080/10549811.2026.2646684
60. Urban green space extraction from BJ-2 remote sensing image based SegFormer semantic segmentation model Y. Guo et al. https://doi.org/10.1080/07038992.2024.2439835
61. Spatial Differentiation of Thermal–Ecological Environmental Responses in High-Density Central Subway-Hub Blocks and Their Associations with Built-Environment Characteristics G. Wang et al. https://doi.org/10.3390/land15040658
62. Scale matters: How spatial resolution impacts remote sensing based urban green space mapping? Z. Hu et al. https://doi.org/10.1016/j.jag.2024.104178
63. A detection of street trees and green space: Understanding contribution of urban trees to climate change mitigation X. Lian et al. https://doi.org/10.1016/j.ufug.2024.128561
64. LGCANet: Local–Global and Change-Aware Network via Segment Anything Model for Remote Sensing Images Change Detection K. Jiang & C. Wu https://doi.org/10.1109/TGRS.2025.3582784
65. A Very High-Resolution Urban Green Space from the Fusion of Microsatellite, SAR, and MSI Images F. Ramdani https://doi.org/10.3390/rs16081366
66. The impact of 2D/3D building morphology and green spaces on urban heat environments: Relative contributions, interaction and marginal effects D. Bai et al. https://doi.org/10.1016/j.ecolind.2025.114296
67. Deep learning in urban green space extraction in remote sensing: a comprehensive systematic review Y. Huang et al. https://doi.org/10.1080/01431161.2024.2424511
68. A Framework for Analyzing Spatial Heterogeneity and Influencing Factors of Campus Green Space in Xi’an, China Z. Zang et al. https://doi.org/10.1007/s11769-025-1524-3
69. A Novel Hybrid Method for Urban Green Space Segmentation from High-Resolution Remote Sensing Images W. Wang et al. https://doi.org/10.3390/rs15235472
70. UTFNet: Uncertainty-Guided Trustworthy Fusion Network for RGB-Thermal Semantic Segmentation Q. Wang et al. https://doi.org/10.1109/LGRS.2023.3322452
71. Micro-scale diurnal thermal regimes and heat-carbon spatial decoupling in the downtown of Beijing Y. Liu et al. https://doi.org/10.1016/j.uclim.2026.102848
72. Reconstructing urban vegetation evolution in China using multimodal deep learning and 30-years Landsat archive Y. Han et al. https://doi.org/10.1016/j.ufug.2024.128582
73. The impact of Urban residential areas on bird diversity: A case study from Harbin, Northeast China Y. Dong et al. https://doi.org/10.1016/j.habitatint.2025.103463
74. Mapping Urban Functional Areas Using Multisource Remote Sensing Images and Open Big Data Y. Chen et al. https://doi.org/10.1109/JSTARS.2023.3308051
75. Efficient Rural Building Segmentation via a Multilevel Decoding Network B. Xu et al. https://doi.org/10.1109/JSTARS.2023.3344210
76. A Lightweight Change Detection Network Based on Feature Interleaved Fusion and Bistage Decoding M. Wang et al. https://doi.org/10.1109/JSTARS.2023.3344635
77. A multi-scale feature fusion framework for urban functional zone identification using automatic ensemble learning method Y. Wang et al. https://doi.org/10.3389/frsc.2026.1736773
78. Urban vegetation productivity under climate change and increasing urbanization: Insights from both urban-rural comparison and trend analysis for global cities J. Chen et al. https://doi.org/10.1016/j.ufug.2025.128950
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