38 citations as recorded by crossref.

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2. 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
3. Generalized deep learning model for photovoltaic module segmentation from satellite and aerial imagery G. García et al. 10.1016/j.solener.2024.112539
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5. 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
6. PV Identifier: Extraction of small-scale distributed photovoltaics in complex environments from high spatial resolution remote sensing images N. Lu et al. 10.1016/j.apenergy.2024.123311
7. The Use of Drone Photo Material to Classify the Purity of Photovoltaic Panels Based on Statistical Classifiers T. Czarnecki & K. Bloch 10.3390/s22020483
8. 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
9. Geospatial assessment of rooftop solar photovoltaic potential using multi-source remote sensing data H. Jiang et al. 10.1016/j.egyai.2022.100185
10. 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
11. Application of photovoltaics on different types of land in China: Opportunities, status and challenges C. Song et al. 10.1016/j.rser.2023.114146
12. 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
13. FEPVNet: A Network with Adaptive Strategies for Cross-Scale Mapping of Photovoltaic Panels from Multi-Source Images B. Su et al. 10.3390/rs15092469
14. GIScience can facilitate the development of solar cities for energy transition R. Zhu et al. 10.1016/j.adapen.2023.100129
15. Deep solar PV refiner: A detail-oriented deep learning network for refined segmentation of photovoltaic areas from satellite imagery R. Zhu et al. 10.1016/j.jag.2022.103134
16. A solar panel dataset of very high resolution satellite imagery to support the Sustainable Development Goals C. Clark & F. Pacifici 10.1038/s41597-023-02539-8
17. An Information Extraction Method for Industrial and Commercial Rooftop Photovoltaics Based on GaoFen-7 Remote Sensing Images H. Tao et al. 10.3390/rs15245744
18. Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China H. Jiang et al. 10.1016/j.oceaneng.2023.115914
19. Assessment of the large-scale extraction of photovoltaic (PV) panels with a workflow based on artificial neural networks and algorithmic postprocessing of vectorization results M. Manso-Callejo et al. 10.1016/j.jag.2023.103563
20. 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
21. 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
22. Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine H. Zhang et al. 10.3390/rs15153712
23. Multi-Resolution Segmentation of Solar Photovoltaic Systems Using Deep Learning M. Kleebauer et al. 10.3390/rs15245687
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25. Multi-sourced data modelling of spatially heterogenous life-cycle carbon mitigation from installed rooftop photovoltaics: A case study in Singapore R. Zhu et al. 10.1016/j.apenergy.2024.122957
26. Deep learning for photovoltaic panels segmentation K. Bouzaachane et al. 10.23939/mmc2023.03.638
27. Detecting Photovoltaic Panels in Aerial Images by Means of Characterising Colours D. Marletta et al. 10.3390/technologies11060174
28. Comprehensive analysis of tropical rooftop PV project: A case study in nanning X. Wang et al. 10.1016/j.heliyon.2023.e14131
29. PYS: A classification and extraction model of photovoltaics for providing more detailed data to support photovoltaic sustainable development D. Chen et al. 10.1016/j.seta.2023.103578
30. 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
31. 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
32. Extracting Photovoltaic Panels From Heterogeneous Remote Sensing Images With Spatial and Spectral Differences Z. Zhao et al. 10.1109/JSTARS.2024.3369660
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34. 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
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37. General generative AI-based image augmentation method for robust rooftop PV segmentation H. Tan et al. 10.1016/j.apenergy.2024.123554
38. Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery H. Jiang et al. 10.5194/essd-13-5389-2021