Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4057-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4057-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
06 Sep 2022
Data description paper |
| 06 Sep 2022
| 06 Sep 2022
Vectorized dataset of roadside noise barriers in China using street view imagery
Zhen Qian
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Jiangsu Provincial Key Laboratory for NSLSCS, School of Mathematical Science, Nanjing Normal University, Nanjing 210023, China
Yue Yang
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Teng Zhong
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Fan Zhang
Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Rui Zhu
Department of Land Surveying and Geo-Informatics, The Hong Kong
Polytechnic University, Kowloon, Hong Kong, China
Kai Zhang
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Zhixin Zhang
College of Geography & Marine, Nanjing University, Nanjing, P.O. Box 2100913, China
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
Zhuo Sun
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Peilong Ma
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Guonian Lü
Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Yu Ye
Department of Architecture, College of Architecture and Urban Planning, Tongji University, China
Jinyue Yan
Future Energy Center, Malardalen University, 72123 Vasteras, Sweden
Department of Chemical Engineering, KTH Royal Institute of
Technology, Stockholm 10044, Sweden
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Cited
13 citations as recorded by crossref.
- Carbon mitigation potential afforded by rooftop photovoltaic in China Z. Zhang et al. 10.1038/s41467-023-38079-3
- Estimating urban noise along road network from street view imagery J. Huang et al. 10.1080/13658816.2023.2274475
- Integrating Renewable Energy in Transportation: Challenges, Solutions, and Future Prospects on Photovoltaic Noise Barriers Q. Wu et al. 10.3390/su16062358
- Estimation of urban-scale photovoltaic potential: A deep learning-based approach for constructing three-dimensional building models from optical remote sensing imagery L. Yan et al. 10.1016/j.scs.2023.104515
- 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
- Street-level imagery analytics and applications F. Zhang et al. 10.1016/j.isprsjprs.2023.04.005
- Integrating photovoltaic noise barriers and electric vehicle charging stations for sustainable city transportation K. Zhang et al. 10.1016/j.scs.2023.104996
- Documentation strategy for facilitating the reproducibility of geo-simulation experiments Z. Zhu et al. 10.1016/j.envsoft.2023.105687
- Iterative integration of deep learning in hybrid Earth surface system modelling M. Chen et al. 10.1038/s43017-023-00452-7
- Power generation assessment of photovoltaic noise barriers across 52 major Chinese cities K. Zhang et al. 10.1016/j.apenergy.2024.122839
- Improving the Performance of Automated Rooftop Extraction through Geospatial Stratified and Optimized Sampling Z. Sun et al. 10.3390/rs14194961
- Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges M. Chen et al. 10.1016/j.earscirev.2023.104438
- GIScience can facilitate the development of solar cities for energy transition R. Zhu et al. 10.1016/j.adapen.2023.100129
13 citations as recorded by crossref.
- Carbon mitigation potential afforded by rooftop photovoltaic in China Z. Zhang et al. 10.1038/s41467-023-38079-3
- Estimating urban noise along road network from street view imagery J. Huang et al. 10.1080/13658816.2023.2274475
- Integrating Renewable Energy in Transportation: Challenges, Solutions, and Future Prospects on Photovoltaic Noise Barriers Q. Wu et al. 10.3390/su16062358
- Estimation of urban-scale photovoltaic potential: A deep learning-based approach for constructing three-dimensional building models from optical remote sensing imagery L. Yan et al. 10.1016/j.scs.2023.104515
- 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
- Street-level imagery analytics and applications F. Zhang et al. 10.1016/j.isprsjprs.2023.04.005
- Integrating photovoltaic noise barriers and electric vehicle charging stations for sustainable city transportation K. Zhang et al. 10.1016/j.scs.2023.104996
- Documentation strategy for facilitating the reproducibility of geo-simulation experiments Z. Zhu et al. 10.1016/j.envsoft.2023.105687
- Iterative integration of deep learning in hybrid Earth surface system modelling M. Chen et al. 10.1038/s43017-023-00452-7
- Power generation assessment of photovoltaic noise barriers across 52 major Chinese cities K. Zhang et al. 10.1016/j.apenergy.2024.122839
- Improving the Performance of Automated Rooftop Extraction through Geospatial Stratified and Optimized Sampling Z. Sun et al. 10.3390/rs14194961
- Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges M. Chen et al. 10.1016/j.earscirev.2023.104438
- GIScience can facilitate the development of solar cities for energy transition R. Zhu et al. 10.1016/j.adapen.2023.100129
Latest update: 25 Apr 2024
Short summary
Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable. This study provides the first reliable and nationwide vectorized RNB dataset with street view imagery in China. The generated RNB dataset is evaluated in terms of two aspects, i.e., the detection accuracy and the completeness and positional accuracy. The method is based on a developed geospatial artificial intelligence framework.
Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable....
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