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Identification of Roof Surfaces from LiDAR Cloud Points by GIS Tools: A Case Study of Lučenec, Slovakia

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  • Marcela Bindzarova Gergelova

    (Institute of Geodesy, Cartography and Geographical Information Systems, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

  • Slavomir Labant

    (Institute of Geodesy, Cartography and Geographical Information Systems, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

  • Stefan Kuzevic

    (Institute of Earth Resources Ecology, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

  • Zofia Kuzevicova

    (Institute of Geodesy, Cartography and Geographical Information Systems, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

  • Henrieta Pavolova

    (Institute of Earth Resources Ecology, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

Abstract

The identification of roof surfaces is characterized by a sequence of several processing steps. The boundary detection of different types of roof is realized from light detection and ranging (LiDAR) cloud points and can confirm the real boundary of the roof. In the process of processing LiDAR data, shortcomings have been found regarding the inappropriate classification of points (class 6 “buildings”) concerning the roofs (the points of the building facade were marked as outliers and reclassified). In cases of insufficient point density, there is a problem with not being able to capture either the roof boundary or small roof objects, along with the possible occurrence of gaps inside the roof areas. This study proposes a processing procedure in a geographic information system (GIS) environment that advocates the identification of roof surfaces based on the LiDAR point cloud. We created the contours of a roof surface boundary with a simplified regular shape. From 824 roofs in the studied area, six different types of roof were selected, which this study presents in detail. The expected result of the study is the generation of segments inside the roof boundary. The study also includes the visualization of the outcomes of the spatial analyses of the identified roof surfaces, which forms the basis for determining the potential of solar systems with respect to green roofs for the development of smart city buildings.

Suggested Citation

  • Marcela Bindzarova Gergelova & Slavomir Labant & Stefan Kuzevic & Zofia Kuzevicova & Henrieta Pavolova, 2020. "Identification of Roof Surfaces from LiDAR Cloud Points by GIS Tools: A Case Study of Lučenec, Slovakia," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6847-:d:402936
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    References listed on IDEAS

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    1. Israel Griol-Barres & Sergio Milla & Antonio Cebrián & Huaan Fan & Jose Millet, 2020. "Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing," Sustainability, MDPI, vol. 12(19), pages 1-22, September.
    2. Marcela Bindzarova Gergelova & Slavomir Labant & Jozef Mizak & Pavel Sustek & Lubomir Leicher, 2021. "Inventory of Locations of Old Mining Works Using LiDAR Data: A Case Study in Slovakia," Sustainability, MDPI, vol. 13(12), pages 1-21, June.

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