Monitoring of urban forests using 3D spatial indices based on ALS point clouds: a city-level analysis

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Monitoring of urban forests using 3D spatial indices based on LiDAR point clouds and voxel approach

Modern cities face challenges in responding to the needs of diverse groups, therefore urban space must be appropriately shaped to be as resident-friendly as possible. Particular attention needs to be paid to urban vegetation, which is an essential component of a suitable quality of life. Research to date has often relied on two- dimensional (2D) mapping of urban vegetation using remote sensing imagery and vegetation indicators, where greenery is evenly distributed regardless of the cubature. However, in reality, vegetation’s spatial and vertical structure varies, and the layers often overlap. In the current paper concerning Luxembourg City, we propose a novel 3D method exploring such indices as Vegetation 3D Density (V3DI) and Vegetation Volume to Building Volume (VV2BV). The goal of the study is to investigate the spatial relationship between the volume of vege- tation and of buildings in the rapidly developing Luxembourg City. The vegetation volume was calculated using airborne laser scanning point clouds (ALS LiDAR) processed into voxels (0.5 m). The volume of the buildings was calculated based on the results of 3D ALS LiDAR point cloud modelling. Proposed spatial indices were estimated for districts, for cadastral parcels, in a cell grid of 100 m and for each building individually, using a 100 m buffer. We found that in 2019, urban forests covered 1689 ha of Luxembourg City, accounting for 33 per cent of the entire administrative area. The 3D GIS analyses show that the total volume of vegetation (> 1.0 m above ground) was about 40 million m3, equating to 328 m3 of greenery per resident. The V3DI produced a value of 0.77 m3/m2. The overall VV2BV(%) index calculated for Luxembourg was 41.6 per cent. Only five districts of Luxembourg were characterized by a high value for the VV2BV index, which indicates areas with a high level of green infrastructure to contribute to health and a better quality of life

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 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 m3/m2 (2001) to 0.9 m3/m2 (2010) to 1.09 m3/m2 (2019). Further, the increase in the volume of 3 buildings between 2001–2019 was +16 million m . The general trend of changes in the cubic capacity of buildings per resident shows a decrease from 522 m3/resident in 2001, to 460 m3/resident in 2019, which, with the simultaneous appearance of new buildings and fast population growth, represents the dynamic development of the city.SusDEen