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Survey of Slum Housing Characteristics Using Drones: An Experiment in the Alto das Pombas Community, Salvador de Bahia/Brazil

Joice Genaro Gomes
Joice Genaro Gomes
 et 
Julio Cesar Pedrassoli
Julio Cesar Pedrassoli
   | 30 sept. 2021
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Publié en ligne: 30 sept. 2021
Pages: 169 - 182
Reçu: 22 juin 2021
DOI: https://doi.org/10.2478/quageo-2021-0031
Mots clés
© 2021 Joice Genaro Gomes et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Risky situations example.
Risky situations example.

Fig. 2

Salvador de Bahia and the Alto das Pombas Census Sector.
Salvador de Bahia and the Alto das Pombas Census Sector.

Fig. 3

3D model of the study generated by drone: Alto das Pombas Community.
3D model of the study generated by drone: Alto das Pombas Community.

Fig. 4

Terrain slope below the houses in the study area of Alto das Pombas, in Salvador/Bahia.
Terrain slope below the houses in the study area of Alto das Pombas, in Salvador/Bahia.

Fig. 5

The zonal mean calculation for slope and building height.
The zonal mean calculation for slope and building height.

Fig. 6

Spatial patterns of buildings distributed by the number of floors, Alto das Pombas Salvador/Bahia.
Spatial patterns of buildings distributed by the number of floors, Alto das Pombas Salvador/Bahia.

Fig. 7

3D model with buildings distributed by the number of floors.
3D model with buildings distributed by the number of floors.

Fig. 8

Google Earth a and drone b. Detailing the spacing between buildings, and roof cover type.
Google Earth a and drone b. Detailing the spacing between buildings, and roof cover type.

Fig. 9

Google Earth a drone b. Unprotected stairways and slabs became visible.
Google Earth a drone b. Unprotected stairways and slabs became visible.

Fig. 10

Identification of dwellings been enlarged and with apparent unprotected slabs/stairs.
Identification of dwellings been enlarged and with apparent unprotected slabs/stairs.

Examples of geo-data possible to get with UAVs (drones). Adapted from Gevaert et al. 2018.

Acquired directly from drone footage Indirectly acquired from drone footage Not captured with the drone – need for other sources
Road System Land Use/Cover Population counts and another census information
Building boundaries Waste dumping sites Income, etc.
Vegetation Urban infrastructure Administrative boundaries
Surface models (DSM) Contextual Information Security of tenure
Terrain models (DTM) Attributes of the features, such as: roof type, number of floors, building material, etc. Temperature of materials and surfaces (not with conventional cameras)

Drone collected data during the flight above the census sector in Alto das Pombas, Salvador/Bahia.

Physical characteristics of the dwellings Potentials and limitations of the drone imagery
Buildings’ land slopes Using the terrain model, generated from the image processing, a map was prepared that indicates the slope of the terrain where each building is located. Information is available on Figure 4.
Building floors From the terrain and surface models, it was possible to identify the approximate number of floors of each dwelling. Information is available on Figure 6.
Spacing between buildings It is possible to identify and measure approximate spacing between buildings, as shown in Figures 8.
Unprotected exposed slabs and stairs It was possible to identify the dwellings that visually presented these characteristics. Information is present in Figure 9.
Width of internal roads It is possible to delineate the width and type of internal roads (whether staircases or not), the type of paving, as per examples in Figures 3 and 4.
Type of roof covering It is possible to identify the type of roof coverage of the buildings, as per examples in Figures 8 and 9.
Dwelling in expansion It was possible to identify the dwellings that were visually enlarging. Information is present in Figure 10.
External coating of the dwellings It was not possible to clearly identify the type of covering of the buildings. It is suggested to conduct new flights with different altitudes, and different camera angles on the drone.
eISSN:
2081-6383
Langue:
Anglais
Périodicité:
4 fois par an
Sujets de la revue:
Geosciences, Geography
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