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Open AccessArticle

Object-Based Image Procedures for Assessing the Solar Energy Photovoltaic Potential of Heterogeneous Rooftops Using Airborne LiDAR and Orthophoto

1
The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer-Sheva 85105, Israel
2
Structural Engineering Dept., Faculty of Engineering Sciences, Ben-Gurion University of the Negev, Beer-Sheva 85105, Israel
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(2), 223; https://doi.org/10.3390/rs12020223
Received: 6 December 2019 / Revised: 5 January 2020 / Accepted: 6 January 2020 / Published: 9 January 2020
Available renewable energy resources play a vital role in fulfilling the energy demands of the increasing global population. To create a sustainable urban environment with the use of renewable energy in human habitats, a precise estimation of solar energy on building roofs is essential. The primary goal of this paper is to develop a procedure for measuring the rooftop solar energy photovoltaic potential over a heterogeneous urban environment that allows the estimation of solar energy yields on flat and pitched roof surfaces at different slopes and in different directions, along with multi-segment roofs on a single building. Because of the complex geometry of roofs, very high-resolution data, such as ortho-rectified aerial photography (orthophotos), and LiDAR data have been used to generate a new object-based algorithm to classify buildings. An overall accuracy index and a Kappa index of agreement (KIA) of 97.39% and 0.95, respectively, were achieved. The paper also develops a new model to create an aspect-slope map, which combines slope orientation with the gradient of the slope and uses it to demonstrate the collective results. This study allows the assessment of solar energy yields through defining solar irradiances in units of pixels over a specific time period. It might be beneficial in terms of more efficient measurements for solar panel installations and more accurate calculations of solar radiation for residents and commercial energy investors. View Full-Text
Keywords: object-based image analysis; segmentation; LiDAR; orthophoto; aspect-slope map; solar energy photovoltaic potential object-based image analysis; segmentation; LiDAR; orthophoto; aspect-slope map; solar energy photovoltaic potential
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MDPI and ACS Style

Tiwari, A.; Meir, I.A.; Karnieli, A. Object-Based Image Procedures for Assessing the Solar Energy Photovoltaic Potential of Heterogeneous Rooftops Using Airborne LiDAR and Orthophoto. Remote Sens. 2020, 12, 223.

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