4 research outputs found
DESCRIBING THE VERTICAL STRUCTURE OF INFORMAL SETTLEMENTS ON THE BASIS OF LIDAR DATA – A CASE STUDY FOR <i>FAVELAS</i> (SLUMS) IN SAO PAULO CITY
Cadastral mapping of favela’s agglomerated buildings in informal settlements at Level of Detail 1 (LoD1) usually requires specific surveys and extensive manual data processing. Therefore, there is a demand for including the favelas in the city map production on the basis of Lidar surveys, as well as the detection of their vertical growth. However, the currently developed algorithms for automatically extracting buildings from airborne Lidar data have mainly been tested only for regular building reconstruction. This study aims to develop a Lidar data processing pipeline enabling to compute metrics related to intraurban informal settlements. To do so, we present a procedure to generate favela’s buildings delineation, height, floors’ number and built area and apply them to six case studies in favela typo-morphologies. We conducted an exploratory analysis in order to obtain the adequate parameters of the processing pipeline and its evaluation, using open source, free license and self-developed software. The results are compared to reference data from the manual stereo plotting, achieving a quality index in the building reconstruction about 70%. We also calculated the growth density, measured by gross Floor Area Ratio index inside settlement, revealing values from 29% to 74% considering different time periods
RECONSTRUCTION OF BUILDING OUTLINES IN DENSE URBAN AREAS BASED ON LIDAR DATA AND ADDRESS POINTS
The paper presents a comprehensive method for automated extraction and delineation of building outlines in densely built-up areas.
A novel approach to outline reconstruction is the use of geocoded building address points. They give information about building
location thus highly reduce task complexity. Reconstruction process is executed on 3D point clouds acquired by airborne laser
scanner. The method consists of three steps: building detection, delineation and contours refinement. The algorithm is tested against
a data set that presents the old market town and its surroundings. The results are discussed and evaluated by comparison to reference
cadastral data
QUALITY ANALYSIS ON 3D BUIDLING MODELS RECONSTRUCTED FROM UAV IMAGERY
Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard
platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal
solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce
labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from
different sensors (e.g. airborne laser scanning), a proper quality assessment is necessary. The objective of this paper is thus to
evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation
process is conducted threefold: (1) comparing generated SfM point cloud to ALS data; (2) computing internal consistency measures
of the reconstruction process; (3) analysing the deviation of Check Points identified on building roofs and measured with a
tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The
assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the
accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component
THERMAL TEXTURE SELECTION AND CORRECTION FOR BUILDING FACADE INSPECTION BASED ON THERMAL RADIANT CHARACTERISTICS
An automatic building façade thermal texture mapping approach, using uncooled thermal camera data, is proposed in this paper. First, a shutter-less radiometric thermal camera calibration method is implemented to remove the large offset deviations caused by changing ambient environment. Then, a 3D façade model is generated from a RGB image sequence using structure-from-motion (SfM) techniques. Subsequently, for each triangle in the 3D model, the optimal texture is selected by taking into consideration local image scale, object incident angle, image viewing angle as well as occlusions. Afterwards, the selected textures can be further corrected using thermal radiant characteristics. Finally, the Gauss filter outperforms the voted texture strategy at the seams smoothing and thus for instance helping to reduce the false alarm rate in façade thermal leakages detection. Our approach is evaluated on a building row façade located at Dresden, Germany