A Typical Application of Distributed Rooftop Photovoltaic Survey Based on Satellite Remote Sensing in Jiangsu Province
As global demand for renewable energy continues to grow, distributed rooftop photovoltaic (PV) power generation has garnered increasing attention as a clean and efficient form of energy utilization. Jiangsu Province, as a key base for China’s PV industry, holds significant strategic importance in the development and utilization of distributed rooftop PV systems. This paper presents a typical application of satellite remote sensing data for a comprehensive survey of distributed rooftop PV in Jiangsu Province. First, high-resolution satellite remote sensing imagery, combined with advanced image processing technologies, is used to accurately identify and extract building rooftops across the province. Second, by integrating multi-source remote sensing data, a scientific and feasible method is established to assess the potential for distributed rooftop solar PV generation in urban areas. This method not only considers the planar area of building rooftops but also analyzes detailed rooftop characteristics such as slope, orientation, and solar radiation parameters, enabling a refined evaluation of rooftop PV potential. Finally, the suitability of distributed rooftop PV systems is analyzed for various building types. This study provides crucial data support for the development of distributed rooftop PV systems in Jiangsu Province and offers valuable references for similar projects in other regions. By implementing this research, we aim to promote the widespread application of distributed rooftop PV systems in Jiangsu and nationwide. The study highlights the immense potential of satellite remote sensing technology in distributed rooftop PV surveys, offering new ideas and methods for future energy management and planning. It contributes to optimizing the energy structure and achieving sustainable development goals.
Authors
- Yongheng Shang (ORCID: https://orcid.org/0000-0001-8550-6710)
- Zilun Zhang (ORCID: https://orcid.org/0009-0008-5961-5970)
- Yuhao Wang (ORCID: https://orcid.org/0009-0000-0255-2413)
- Shuiguang Deng (ORCID: https://orcid.org/0000-0001-5015-6095)
- Jianwei Yin (ORCID: https://orcid.org/0000-0003-4703-7348)
- Chao Cai (ORCID: https://orcid.org/0000-0003-1995-4739)
- Yi Xu (ORCID: https://orcid.org/0000-0002-3503-3086)
- Jun Han (ORCID: https://orcid.org/0000-0003-2387-7932)
Institutions
- Ningbo University (CN)
- Zhejiang University of Science and Technology (CN)
- Zhejiang University (CN)
Publication Details
- Published
- 2025-06-20
- DOI
- https://doi.org/10.1109/eee64897.2025.11162796
- Citations
- 1
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 1.30