On the topographic entity-oriented digital elevation model construction method for urban area land surface

Abstract

Human activity transforms a land surface into a complex surface where artificial and natural landforms coexist and continuous and emergent landforms merge. In this background, the problems of conventional digital elevation models (DEMs), such as morphological distortion, complicated updates, and lack of information, are increasingly prominent. This study proposes a new idea of DEM construction based on the concept of geographic ontology. First, landforms with common features are abstracted into a certain type of topographic entity based on their morphologies and semantics. For each type of topographic entity, a DEM was constructed independently based on the available elevation information and other information about the semantics and spatial relationships. Second, individual DEMs were merged into a complete DEM following certain rules. A 1 km² area located in the suburb of Nanjing, Jiangsu Province, China, was selected as the experimental area. The effectiveness of the model construction method proposed in this study was verified. The results show that the DEM constructed according to the idea of this study has a significantly better performance than the conventional DEMs. The constructed DEM in this study can well represent ground objects, such as slopes, farmland, and ditches. In particular, the constructed DEM ensures the morphological accuracy of the ground objects.

Graphical abstract

Keywords

topographic entity / DEM / urban area / artificial strip terrain / morphological accuracy

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Acknowledgments

We are thankful for all of the helpful comments provided by the reviewers. This study was supported by National Natural Science Foundation of China (Grant Nos. 41701450 & 41930102), Program of Provincial Natural Science Foundation of Anhui (No. 1808085QD103), Key Project of Natural Science Research of Anhui Provincial Department of Education (KJ2020A0722), Grant from State Key Laboratory of Resources and Environmental Information System in 2018, Key Project of Research and Development in Chuzhou Science and Technology Program (No. 2020ZG016), Jiangsu Planned Projects for Postdoctoral Research Funds (No. 2018K144C), China Postdoctoral Science Foundation (No. 2018M642146), and Anhui Province Universities Outstanding Talented Person Support Project (No. gxyq2019093).

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