{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:21:59Z","timestamp":1783938119648,"version":"3.55.0"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,1,9]],"date-time":"2020-01-09T00:00:00Z","timestamp":1578528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs12020223","type":"journal-article","created":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T04:06:51Z","timestamp":1578629211000},"page":"223","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Object-Based Image Procedures for Assessing the Solar Energy Photovoltaic Potential of Heterogeneous Rooftops Using Airborne LiDAR and Orthophoto"],"prefix":"10.3390","volume":"12","author":[{"given":"Arti","family":"Tiwari","sequence":"first","affiliation":[{"name":"The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer-Sheva 85105, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8427-5789","authenticated-orcid":false,"given":"Isaac A.","family":"Meir","sequence":"additional","affiliation":[{"name":"Structural Engineering Dept., Faculty of Engineering Sciences, Ben-Gurion University of the Negev, Beer-Sheva 85105, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8065-9793","authenticated-orcid":false,"given":"Arnon","family":"Karnieli","sequence":"additional","affiliation":[{"name":"The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer-Sheva 85105, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,9]]},"reference":[{"key":"ref_1","unstructured":"Olejarnik, P. (2013). IEA World Energy Outlook 2013, International Energy Agency."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1016\/j.rser.2005.12.002","article-title":"Spatial mapping of renewable energy potential","volume":"11","author":"Ramachandra","year":"2007","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.erss.2019.01.008","article-title":"Energy transitions or additions?: Why a transition from fossil fuels requires more than the growth of renewable energy","volume":"51","author":"York","year":"2019","journal-title":"Energy Res. Soc. Sci."},{"key":"ref_4","unstructured":"De L\u2019\u00c9nergie, C.M. (2014). 2014 World Energy Issues Monitor, World Energy Council."},{"key":"ref_5","unstructured":"IRENA (2019). Renewable Capacity Statistics 2019, International Renewable Energy Agency (IRENA)."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1016\/j.apenergy.2012.08.042","article-title":"Rating of roofs\u2019 surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data","volume":"102","author":"Seme","year":"2013","journal-title":"Appl. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.energy.2018.05.014","article-title":"Solar driven net zero emission electricity supply with negligible carbon cost: Israel as a case study for Sun Belt countries","volume":"155","author":"Solomon","year":"2018","journal-title":"Energy"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"D\u2019Adamo, I. (2018). The profitability of residential photovoltaic systems. A new scheme of subsidies based on the price of CO2 in a developed PV market. Soc. Sci., 7.","DOI":"10.3390\/socsci7090148"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1080\/17512549.2016.1275982","article-title":"Performance study of building integrated photovoltaic modules","volume":"12","author":"Karthick","year":"2018","journal-title":"Adv. Build. Energy Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3820","DOI":"10.1016\/j.jclepro.2015.07.117","article-title":"Automated registration of potential locations for solar energy production with Light Detection and Ranging (LiDAR) and small format photogrammetry","volume":"112","author":"Enyedi","year":"2016","journal-title":"J. Clean. Prod."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.rser.2013.03.010","article-title":"Solar photovoltaic and thermal technology and applications in China","volume":"23","author":"Fang","year":"2013","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rser.2013.10.021","article-title":"Green building research-current status and future agenda: A review","volume":"30","author":"Zuo","year":"2014","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1007\/s10479-011-1009-x","article-title":"Evaluation of photovoltaic cells in a multi-criteria decision making process","volume":"199","author":"Lamata","year":"2012","journal-title":"Ann. Oper. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.energy.2013.12.066","article-title":"Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data","volume":"66","author":"Seme","year":"2014","journal-title":"Energy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2206","DOI":"10.1016\/j.renene.2009.02.021","article-title":"Assessment of photovoltaic potential in urban areas using open-source solar radiation tools","volume":"34","author":"Hofierka","year":"2009","journal-title":"Renew. Energy"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.solener.2011.09.031","article-title":"Photovoltaic potential in a Lisbon suburb using LiDAR data","volume":"86","author":"Brito","year":"2012","journal-title":"Sol. Energy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.envsoft.2014.11.019","article-title":"An open-source 3D solar radiation model integrated with a 3D Geographic Information System","volume":"64","author":"Liang","year":"2015","journal-title":"Environ. Model. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Palmero-Marrero, A.I., and Oliveira, A.C. (2010). Research on heating and cooling requirements of buildings with solar louvre devices. Advances in Building Energy Research, Taylor & Francis Group.","DOI":"10.3763\/aber.2009.0401"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.cageo.2012.10.010","article-title":"GPU-based roofs\u2019 solar potential estimation using LiDAR data","volume":"52","year":"2013","journal-title":"Comput. Geosci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.solener.2015.03.044","article-title":"Evaluation of photovoltaic integration potential in a village","volume":"121","author":"Mavromatidis","year":"2015","journal-title":"Sol. Energy"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.enbuild.2015.01.051","article-title":"Evolutionary-driven search for solar building models using LiDAR data","volume":"92","author":"Bizjak","year":"2015","journal-title":"Energy Build."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.apenergy.2015.06.043","article-title":"A review on sustainable construction management strategies for monitoring, diagnosing, and retrofitting the building\u2019s dynamic energy performance: Focused on the operation and maintenance phase","volume":"155","author":"Hong","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_23","unstructured":"Carneiro, C., Morello, E., Ratti, C., and Golay, F. (2009). Solar radiation over the urban texture: Lidar data and image processing techniques for environmental analysis at city scale. Lect. Notes Geoinf. Cartogr., 319\u2013340."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.solener.2013.08.036","article-title":"Solar energy potential on roofs and facades in an urban landscape","volume":"97","author":"Redweik","year":"2013","journal-title":"Sol. Energy"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1016\/j.solener.2006.12.007","article-title":"Potential of solar electricity generation in the European Union member states and candidate countries","volume":"81","author":"Huld","year":"2007","journal-title":"Sol. Energy"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Neteler, M., and Mitasova, H. (2008). Open Source GIS: A GRASS GIS Approach, Springer.","DOI":"10.1007\/978-0-387-68574-8"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.scs.2013.01.002","article-title":"Methodology for estimating solar potential on multiple building rooftops for photovoltaic systems","volume":"8","author":"Kodysh","year":"2013","journal-title":"Sustain. Cities Soc."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.apenergy.2014.02.076","article-title":"Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)","volume":"124","author":"Jacques","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.apgeog.2014.03.008","article-title":"Applications of solar mapping in the urban environment","volume":"51","author":"Santos","year":"2014","journal-title":"Appl. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.enbuild.2016.08.025","article-title":"A pixel-based approach to estimation of solar energy potential on building roofs","volume":"129","author":"Li","year":"2016","journal-title":"Energy Build."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.enbuild.2016.12.070","article-title":"Estimating solar energy potentials on pitched roofs","volume":"139","author":"Li","year":"2017","journal-title":"Energy Build."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"17212","DOI":"10.3390\/rs71215877","article-title":"Estimating roof solar energy potential in the downtown area using a GPU-accelerated solar radiation model and airborne LiDAR data","volume":"7","author":"Huang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"401","DOI":"10.3934\/energy.2015.3.401","article-title":"An automated model for rooftop PV systems assessment in ArcGIS using LIDAR","volume":"3","author":"Calvert","year":"2015","journal-title":"AIMS Energy"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.renene.2016.07.003","article-title":"Estimation of Hong Kong\u2019s solar energy potential using GIS and remote sensing technologies","volume":"99","author":"Wong","year":"2016","journal-title":"Renew. Energy"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.renene.2017.04.025","article-title":"Rooftop solar potential based on LiDAR data: Bottom-up assessment at neighbourhood level","volume":"111","author":"Suomalainen","year":"2017","journal-title":"Renew. Energy"},{"key":"ref_36","unstructured":"Guide, U. (2009). eCognition Developer 8: Whats New, Trimble Navigation Limited."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"711","DOI":"10.2113\/gsecongeo.78.4.711","article-title":"Use of Landsat multispectral scanner data for the definition of limonitic exposures in heavily vegetated areas (Montana, Idaho)","volume":"78","author":"Segal","year":"1983","journal-title":"Econ. Geol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.3390\/rs2102369","article-title":"Applicability of green-red vegetation index for remote sensing of vegetation phenology","volume":"2","author":"Motohka","year":"2010","journal-title":"Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0034-4257(01)00295-4","article-title":"Status of land cover classification accuracy assessment","volume":"80","author":"Foody","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_41","unstructured":"Fu, P., and Rich, P.M. (1999, January 26\u201330). Design and implementation of the solar analyst: An ArcView extension for modeling solar radiation at landscape scales. Proceedings of the Nineteenth Annual ESRI User Conference, San Diego, CA, USA."},{"key":"ref_42","unstructured":"Fu, P., and Rich, P.M. (1999). The Solar Analyst 1.0 User Manual, Helios Environmental Modeling Institute."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1080\/02757259009532119","article-title":"Characterizing plant canopies with hemispherical photographs","volume":"5","author":"Rich","year":"1990","journal-title":"Remote Sens. Rev."},{"key":"ref_44","unstructured":"(2019, November 21). Esri ArcGIS Help 10.1: Area Solar Radiation (Spatial Analyst). Available online: http:\/\/resources.arcgis.com\/en\/help\/main\/10.1\/index.html#\/Area_Solar_Radiation\/009z000000t5000000\/."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/2\/223\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:42:33Z","timestamp":1760362953000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/2\/223"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,9]]},"references-count":44,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2020,1]]}},"alternative-id":["rs12020223"],"URL":"https:\/\/doi.org\/10.3390\/rs12020223","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,9]]}}}