Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis
Understanding how, where, and when a city is expanding can inform better ways to make our cities more resilient, sustainable, and equitable. This paper explores urban volumetry using the Building 3D Density Index (B3DI) in 2001, 2010, 2019, and quantifies changes in the volume of buildings and urban...
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| Format: | Article |
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MDPI AG
2020-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/21/3668 |
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| author | Karolina Zięba-Kulawik Konrad Skoczylas Ahmed Mustafa Piotr Wężyk Philippe Gerber Jacques Teller Hichem Omrani |
| author_facet | Karolina Zięba-Kulawik Konrad Skoczylas Ahmed Mustafa Piotr Wężyk Philippe Gerber Jacques Teller Hichem Omrani |
| author_sort | Karolina Zięba-Kulawik |
| collection | DOAJ |
| description | Understanding how, where, and when a city is expanding can inform better ways to make our cities more resilient, sustainable, and equitable. This paper explores urban volumetry using the Building 3D Density Index (B3DI) in 2001, 2010, 2019, and quantifies changes in the volume of buildings and urban expansion in Luxembourg City over the last two decades. For this purpose, we use airborne laser scanning (ALS) point cloud (2019) and geographic object-based image analysis (GEOBIA) of aerial orthophotos (2001, 2010) to extract 3D models, footprints of buildings and calculate the volume of individual buildings and B3DI in the frame of a 100 × 100 m grid, at the level of parcels, districts, and city scale. Findings indicate that the B3DI has notably increased in the past 20 years from 0.77 m<sup>3</sup>/m<sup>2</sup> (2001) to 0.9 m<sup>3</sup>/m<sup>2</sup> (2010) to 1.09 m<sup>3</sup>/m<sup>2</sup> (2019). Further, the increase in the volume of buildings between 2001–2019 was +16 million m<sup>3</sup>. The general trend of changes in the cubic capacity of buildings per resident shows a decrease from 522 m<sup>3</sup>/resident in 2001, to 460 m<sup>3</sup>/resident in 2019, which, with the simultaneous appearance of new buildings and fast population growth, represents the dynamic development of the city. |
| first_indexed | 2024-03-10T14:59:46Z |
| format | Article |
| id | doaj.art-5db77a476f05438b974999c38c5926e4 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:59:46Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5db77a476f05438b974999c38c5926e42023-11-20T20:17:39ZengMDPI AGRemote Sensing2072-42922020-11-011221366810.3390/rs12213668Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level AnalysisKarolina Zięba-Kulawik0Konrad Skoczylas1Ahmed Mustafa2Piotr Wężyk3Philippe Gerber4Jacques Teller5Hichem Omrani6Department of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, PolandUrban Development and Mobility Department, Luxembourg Institute of Socio-Economic Research, L-4366 Esch-sur-Alzette, LuxembourgUrban Systems Lab, The New School, New York, NY 10003, USADepartment of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, PolandUrban Development and Mobility Department, Luxembourg Institute of Socio-Economic Research, L-4366 Esch-sur-Alzette, LuxembourgLEMA, Urban and Environmental Engineering Department, Liège University, 4000 Liège, BelgiumUrban Development and Mobility Department, Luxembourg Institute of Socio-Economic Research, L-4366 Esch-sur-Alzette, LuxembourgUnderstanding how, where, and when a city is expanding can inform better ways to make our cities more resilient, sustainable, and equitable. This paper explores urban volumetry using the Building 3D Density Index (B3DI) in 2001, 2010, 2019, and quantifies changes in the volume of buildings and urban expansion in Luxembourg City over the last two decades. For this purpose, we use airborne laser scanning (ALS) point cloud (2019) and geographic object-based image analysis (GEOBIA) of aerial orthophotos (2001, 2010) to extract 3D models, footprints of buildings and calculate the volume of individual buildings and B3DI in the frame of a 100 × 100 m grid, at the level of parcels, districts, and city scale. Findings indicate that the B3DI has notably increased in the past 20 years from 0.77 m<sup>3</sup>/m<sup>2</sup> (2001) to 0.9 m<sup>3</sup>/m<sup>2</sup> (2010) to 1.09 m<sup>3</sup>/m<sup>2</sup> (2019). Further, the increase in the volume of buildings between 2001–2019 was +16 million m<sup>3</sup>. The general trend of changes in the cubic capacity of buildings per resident shows a decrease from 522 m<sup>3</sup>/resident in 2001, to 460 m<sup>3</sup>/resident in 2019, which, with the simultaneous appearance of new buildings and fast population growth, represents the dynamic development of the city.https://www.mdpi.com/2072-4292/12/21/3668buildings 3D densityGEOBIALiDARCIR aerial orthophotosbuilding footprint |
| spellingShingle | Karolina Zięba-Kulawik Konrad Skoczylas Ahmed Mustafa Piotr Wężyk Philippe Gerber Jacques Teller Hichem Omrani Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis Remote Sensing buildings 3D density GEOBIA LiDAR CIR aerial orthophotos building footprint |
| title | Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis |
| title_full | Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis |
| title_fullStr | Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis |
| title_full_unstemmed | Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis |
| title_short | Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis |
| title_sort | spatiotemporal changes in 3d building density with lidar and geobia a city level analysis |
| topic | buildings 3D density GEOBIA LiDAR CIR aerial orthophotos building footprint |
| url | https://www.mdpi.com/2072-4292/12/21/3668 |
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