Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data
Solar energy, as a clean and renewable resource is becoming increasingly important in the global context of climate change and energy crisis. Utilization of solar energy in urban areas is of great importance in urban energy planning, environmental conservation, and sustainable development. However,...
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doaj-a93bcf6cf2de4a1584adff4625c9c6d62020-11-24T23:50:17ZengMDPI AGRemote Sensing2072-42922015-12-01712172121723310.3390/rs71215877rs71215877Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR DataYan Huang0Zuoqi Chen1Bin Wu2Liang Chen3Weiqing Mao4Feng Zhao5Jianping Wu6Junhan Wu7Bailang Yu8Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaSchool of Geographic Sciences, East China Normal University, Shanghai 200241, ChinaShanghai Surveying and Mapping Institute, 419 Wuning Rd, Shanghai 200063, ChinaShanghai Surveying and Mapping Institute, 419 Wuning Rd, Shanghai 200063, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, ChinaSolar energy, as a clean and renewable resource is becoming increasingly important in the global context of climate change and energy crisis. Utilization of solar energy in urban areas is of great importance in urban energy planning, environmental conservation, and sustainable development. However, available spaces for solar panel installation in cities are quite limited except for building roofs. Furthermore, complex urban 3D morphology greatly affects sunlit patterns on building roofs, especially in downtown areas, which makes the determination of roof solar energy potential a challenging task. The object of this study is to estimate the solar radiation on building roofs in an urban area in Shanghai, China, and select suitable spaces for installing solar panels that can effectively utilize solar energy. A Graphic Processing Unit (GPU)-based solar radiation model named SHORTWAVE-C simulating direct and non-direct solar radiation intensity was developed by adding the capability of considering cloud influence into the previous SHORTWAVE model. Airborne Light Detection and Ranging (LiDAR) data was used as the input of the SHORTWAVE-C model and to investigate the morphological characteristics of the study area. The results show that the SHORTWAVE-C model can accurately estimate the solar radiation intensity in a complex urban environment under cloudy conditions, and the GPU acceleration method can reduce the computation time by up to 46%. Two sites with different building densities and rooftop structures were selected to illustrate the influence of urban morphology on the solar radiation and solar illumination duration. Based on the findings, an object-based method was implemented to identify suitable places for rooftop solar panel installation that can fully utilize the solar energy potential. Our study provides useful strategic guidelines for the selection and assessment of roof solar energy potential for urban energy planning.http://www.mdpi.com/2072-4292/7/12/15877solar radiationurban arearoof planesLiDARGPU |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yan Huang Zuoqi Chen Bin Wu Liang Chen Weiqing Mao Feng Zhao Jianping Wu Junhan Wu Bailang Yu |
spellingShingle |
Yan Huang Zuoqi Chen Bin Wu Liang Chen Weiqing Mao Feng Zhao Jianping Wu Junhan Wu Bailang Yu Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data Remote Sensing solar radiation urban area roof planes LiDAR GPU |
author_facet |
Yan Huang Zuoqi Chen Bin Wu Liang Chen Weiqing Mao Feng Zhao Jianping Wu Junhan Wu Bailang Yu |
author_sort |
Yan Huang |
title |
Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data |
title_short |
Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data |
title_full |
Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data |
title_fullStr |
Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data |
title_full_unstemmed |
Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data |
title_sort |
estimating roof solar energy potential in the downtown area using a gpu-accelerated solar radiation model and airborne lidar data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2015-12-01 |
description |
Solar energy, as a clean and renewable resource is becoming increasingly important in the global context of climate change and energy crisis. Utilization of solar energy in urban areas is of great importance in urban energy planning, environmental conservation, and sustainable development. However, available spaces for solar panel installation in cities are quite limited except for building roofs. Furthermore, complex urban 3D morphology greatly affects sunlit patterns on building roofs, especially in downtown areas, which makes the determination of roof solar energy potential a challenging task. The object of this study is to estimate the solar radiation on building roofs in an urban area in Shanghai, China, and select suitable spaces for installing solar panels that can effectively utilize solar energy. A Graphic Processing Unit (GPU)-based solar radiation model named SHORTWAVE-C simulating direct and non-direct solar radiation intensity was developed by adding the capability of considering cloud influence into the previous SHORTWAVE model. Airborne Light Detection and Ranging (LiDAR) data was used as the input of the SHORTWAVE-C model and to investigate the morphological characteristics of the study area. The results show that the SHORTWAVE-C model can accurately estimate the solar radiation intensity in a complex urban environment under cloudy conditions, and the GPU acceleration method can reduce the computation time by up to 46%. Two sites with different building densities and rooftop structures were selected to illustrate the influence of urban morphology on the solar radiation and solar illumination duration. Based on the findings, an object-based method was implemented to identify suitable places for rooftop solar panel installation that can fully utilize the solar energy potential. Our study provides useful strategic guidelines for the selection and assessment of roof solar energy potential for urban energy planning. |
topic |
solar radiation urban area roof planes LiDAR GPU |
url |
http://www.mdpi.com/2072-4292/7/12/15877 |
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