%0 Generic %A Palmer, Diane %A Koumpli, Elena %A Cole, Ian %A Gottschalg, Ralph %A Betts, Thomas %D 2019 %T Supplementary Information Files for "A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry" %U https://repository.lboro.ac.uk/articles/dataset/Supplementary_Information_Files_for_A_GIS-Based_Method_for_Identification_of_Wide_Area_Rooftop_Suitability_for_Minimum_Size_PV_Systems_Using_LiDAR_Data_and_Photogrammetry_/8937815 %R 10.17028/rd.lboro.8937815.v1 %2 https://repository.lboro.ac.uk/ndownloader/files/16334825 %2 https://repository.lboro.ac.uk/ndownloader/files/16334828 %2 https://repository.lboro.ac.uk/ndownloader/files/16334831 %2 https://repository.lboro.ac.uk/ndownloader/files/16334834 %2 https://repository.lboro.ac.uk/ndownloader/files/16334837 %2 https://repository.lboro.ac.uk/ndownloader/files/16334840 %2 https://repository.lboro.ac.uk/ndownloader/files/16334843 %2 https://repository.lboro.ac.uk/ndownloader/files/16334846 %2 https://repository.lboro.ac.uk/ndownloader/files/16334849 %2 https://repository.lboro.ac.uk/ndownloader/files/16334852 %2 https://repository.lboro.ac.uk/ndownloader/files/16334855 %2 https://repository.lboro.ac.uk/ndownloader/files/16334858 %2 https://repository.lboro.ac.uk/ndownloader/files/16334861 %2 https://repository.lboro.ac.uk/ndownloader/files/16334864 %K Solar %K LiDAR %K Rooftop Photovoltaics %K Building Characteristics %K Wide-Area Solar Yield %K Engineering not elsewhere classified %X Supplementary Information Files for "A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry"

Abstract:
Knowledge of roof geometry and physical features is essential for evaluation of the impact of multiple rooftop solar photovoltaic (PV) system installations on local electricity networks. The paper starts by listing current methods used and stating their strengths and weaknesses. No current method is capable of delivering accurate results with publicly available input data. Hence a different approach is developed, based on slope and aspect using aircraft-based Light Detection and Ranging (LiDAR) data, building footprint data, GIS (Geographical Information Systems) tools, and aerial photographs. It assesses each roof’s suitability for PV deployment. That is, the characteristics of each roof are examined for fitting of at least a minimum size solar power system. In this way the minimum potential solar yield for region or city may be obtained. Accuracy is determined by ground-truthing against a database of 886 household systems. This is the largest validation of a rooftop assessment method to date. The method is flexible with few prior assumptions. It can generate data for various PV scenarios and future analyses.
%I Loughborough University