Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques — Oak Academic Publishing
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Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques
Water Resources Management Engineering Department, Faculty of Engineering, Al-Qasim Green University, Babylon, Iraq
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Department of Civil Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden
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Department of Civil Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden
1 Water Resources Management Engineering Department, Faculty of Engineering, Al-Qasim Green University, Babylon, Iraq
2 Department of Civil Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden
3 Department of Civil Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden
The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.
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