46 citations as recorded by crossref.

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5. The Use of Drone Photo Material to Classify the Purity of Photovoltaic Panels Based on Statistical Classifiers T. Czarnecki & K. Bloch 10.3390/s22020483
6. Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images H. Mao et al. 10.1016/j.rser.2023.113276
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8. High-resolution solar panel detection in Sfax, Tunisia: A UNet-Based approach M. Bouaziz et al. 10.1016/j.renene.2024.121171
9. GIScience can facilitate the development of solar cities for energy transition R. Zhu et al. 10.1016/j.adapen.2023.100129
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11. Impact of Deep Convolutional Neural Network Structure on Photovoltaic Array Extraction from High Spatial Resolution Remote Sensing Images L. Li et al. 10.3390/rs15184554
12. Combined Hybrid Neural Networks and Swarm Intelligence Optimization Algorithms for Photovoltaic Panel Segmentation From Remote Sensing Images X. Zhang et al. 10.1109/ACCESS.2024.3406551
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15. Mapping national-scale photovoltaic power stations using a novel enhanced photovoltaic index and evaluating carbon reduction benefits J. Wang et al. 10.1016/j.enconman.2024.118894
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19. Characterization and mapping of photovoltaic solar power plants by Landsat imagery and random forest: A case study in Gansu Province, China X. Wang et al. 10.1016/j.jclepro.2023.138015
20. PVNet: A novel semantic segmentation model for extracting high-quality photovoltaic panels in large-scale systems from high-resolution remote sensing imagery J. Wang et al. 10.1016/j.jag.2023.103309
21. Toward global rooftop PV detection with Deep Active Learning M. Zech et al. 10.1016/j.adapen.2024.100191
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23. A Downscaling Methodology for Extracting Photovoltaic Plants with Remote Sensing Data: From Feature Optimized Random Forest to Improved HRNet Y. Wang et al. 10.3390/rs15204931
24. Data Augmentation with Generative Adversarial Network for Solar Panel Segmentation from Remote Sensing Images J. Lekavičius & V. Gružauskas 10.3390/en17133204
25. Remote-sensing extraction and carbon emission reduction benefit assessment for centralized photovoltaic power plants in Agrivoltaic systems C. Huang et al. 10.1016/j.apenergy.2024.123585
26. Mapping of Utility-Scale Solar Panel Areas From 2000 to 2022 in China Using Google Earth Engine X. Lyu et al. 10.1109/JSTARS.2024.3468627
27. High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles H. Jiang et al. 10.1016/j.apenergy.2023.121553
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29. Exploration of determinants underlying regional disparity in rooftop photovoltaic adoption: A case study in Nagoya, Japan L. Tao et al. 10.1016/j.apenergy.2024.123469
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34. An Information Extraction Method for Industrial and Commercial Rooftop Photovoltaics Based on GaoFen-7 Remote Sensing Images H. Tao et al. 10.3390/rs15245744
35. Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China H. Jiang et al. 10.1016/j.oceaneng.2023.115914
36. Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine H. Zhang et al. 10.3390/rs15153712
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39. Detecting Photovoltaic Panels in Aerial Images by Means of Characterising Colours D. Marletta et al. 10.3390/technologies11060174
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41. Extracting Photovoltaic Panels From Heterogeneous Remote Sensing Images With Spatial and Spectral Differences Z. Zhao et al. 10.1109/JSTARS.2024.3369660
42. Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning Y. Chen et al. 10.1016/j.rse.2024.114100
43. Vectorization Method for Remote Sensing Object Segmentation Based on Frame Field Learning: A Case Study of Greenhouses L. Yao et al. 10.1109/TGRS.2024.3403425
44. A Novel Framework for Solar Panel Segmentation From Remote Sensing Images: Utilizing Chebyshev Transformer and Hyperspectral Decomposition H. Gasparyan et al. 10.1109/TGRS.2024.3386402
45. General generative AI-based image augmentation method for robust rooftop PV segmentation H. Tan et al. 10.1016/j.apenergy.2024.123554
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