Document Type : Original Research Paper
Authors
Department of Geomatics, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran
Abstract
Background and Objectives: The urbanization occurs everywhere, especially in developing countries and is the process of changing the social order and transforming the landscape of a city. However, urbanization always leads to the growth of slums or informal settlements. The development of urban areas with dense and complex slum areas requires extensive planning and very accurate and reliable information. The process of collecting data using traditional methods is time-consuming and expensive.
Methods: Remote sensing is used to identify, identify and monitor slum settlements in space and time and better understand the physical effects of slums. But due to the complexities of the slum areas and the spatial resolution of satellite images, it is not possible to use satellite images to prepare accurate maps with high details. With the emergence of unmanned aerial vehicle (UAV) as an imaging platform and the use of these images for aerial photogrammetric mapping of UAVs, its applications in various fields have increased day by day. Due to their portability, accuracy, low cost, and high imaging speed, UAVs have attracted attention in many research fields to obtain the latest information about target areas. Due to the use of non-metric cameras in UAV photogrammetry, camera calibration is necessary is carried out in the UAV image processing software using the bundle adjustment technique. However, the conventional aerial photogrammetry imaging structure, i.e. obtaining vertical images with overlaps, due to the dependence between the camera calibration parameters and the external orientation parameters of the camera, cannot achieve high accuracy in the 3D maps. In addition, due to the low height of UAV images, more hidden areas are created in the 3D photogrammetric model. In this research, vertical and oblique UAV images with angles of 30 and 45 degrees were used to prepare a three-dimensional map of the slum area with high density and complexity, and the accuracy of the vertical and oblique images was evaluated using control points in the study area.
Findings: The high resolution of UAV images and the generated orthomosaic makes it possible to recognize details and provides a better understanding of the earth's features. For example, walls with a thickness of ten centimeters and power lines with a thickness of two centimeters can be seen. As a result, urban planners can determine the boundaries of buildings with high accuracy and produce cadastral maps with high accuracy. Oblique images are distinguished by a wider field of view than vertical images. It is also possible to see areas hidden under obstacles such as plants, buildings and narrow alleys. This feature provides high accuracy that can be used in projects that require detailed descriptions, such as cultural heritage protection projects and urban projects that require details such as building facades and height estimates.
Conclusion: In this research, vertical and oblique UAV images were used to prepare a 3D map of the slum area, and based on the results, the total error of oblique images is 6.2 and 8.3 cm for oblique images with angles of 30 and 45 degrees, respectively. While the total error of vertical images is equal to 16.1 cm. This comparison shows the superiority of the accuracy of oblique images compared to vertical images.
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© 2024 The Author(s). This is an open-access article distributed under the terms and conditions of the Creative Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/)
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