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Abstract <p>High resolution and accurate Digital Surface Model (DSM) is a basic requirement for applications in smart cities such as flood management, infrastructure planning, digital twin, airflow analysis, telecom infrastructure planning, traffic management, solar potential analysis and many of such applications. However, it is very difficult to obtain a <i>cost effective</i> DSM without very high-resolution satellite data. Prime objective of this study is to generate a state-of-the-art DSM using very high-resolution satellite data over an Indian city, and to evaluate its accuracy with reference to Ground Control Points (GCP). In this study, stereo data from Worldview-3 mission is acquired at 30 cm spatial resolution. Satellite data is used as an input to generate very high resolution DSM using one of the approaches of satellite photogrammetry. Output DSM is generated at a grid interval of 30 cm and DSM has achieved a remarkable vertical accuracy of ~1.2 m as evaluated against extensive set of reference Ground Control Points (GCPs). In this study, the basic approach of generating highly accurate VHR DSM over Gandhinagar city, its validation, major limitations and potential applications in smart city modelling and digital twin are discussed. This study is useful in generating the actionable insights and paves a way for sustainable development in future.</p> Highlights <p><UnorderedList Mark="Bullet"> <ItemContent> <p>Study demonstrates the generation of very high resolution and accurate DEM in dense urban Indian city using satellite data.</p> </ItemContent> <ItemContent> <p>Study clearly outlines the approach to generate this state of the art DEM at 30CM spatial resolution.</p> </ItemContent> <ItemContent> <p>Study includes the thorough validation of the generated DEM over well spread GCP points. Hence, demonstrates the accuracy of the generated DEM.</p> </ItemContent> <ItemContent> <p>Study discusses the potential applications of generated DEM in management of smart cities towards sustainable development.</p> </ItemContent> </UnorderedList></p>

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Generation of state-of-the-art digital surface model over an urban Indian city, validation and usefulness for digital twin

  • 期刊论文

  • 发表日期：

    2026年3月2日

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  • Jai Singla

摘要

Abstract

High resolution and accurate Digital Surface Model (DSM) is a basic requirement for applications in smart cities such as flood management, infrastructure planning, digital twin, airflow analysis, telecom infrastructure planning, traffic management, solar potential analysis and many of such applications. However, it is very difficult to obtain a cost effective DSM without very high-resolution satellite data. Prime objective of this study is to generate a state-of-the-art DSM using very high-resolution satellite data over an Indian city, and to evaluate its accuracy with reference to Ground Control Points (GCP). In this study, stereo data from Worldview-3 mission is acquired at 30 cm spatial resolution. Satellite data is used as an input to generate very high resolution DSM using one of the approaches of satellite photogrammetry. Output DSM is generated at a grid interval of 30 cm and DSM has achieved a remarkable vertical accuracy of ~1.2 m as evaluated against extensive set of reference Ground Control Points (GCPs). In this study, the basic approach of generating highly accurate VHR DSM over Gandhinagar city, its validation, major limitations and potential applications in smart city modelling and digital twin are discussed. This study is useful in generating the actionable insights and paves a way for sustainable development in future.

Highlights

Study demonstrates the generation of very high resolution and accurate DEM in dense urban Indian city using satellite data.

Study clearly outlines the approach to generate this state of the art DEM at 30CM spatial resolution.

Study includes the thorough validation of the generated DEM over well spread GCP points. Hence, demonstrates the accuracy of the generated DEM.

Study discusses the potential applications of generated DEM in management of smart cities towards sustainable development.