A DEM upscaling method with integrating valley lines based on HASM

Mingwei ZHAO, Xiaoxiao JU, Na ZHAO, Chun WANG, Yan XU, Xiaoran WU, Weitao LI

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Front. Earth Sci. ›› 2024, Vol. 18 ›› Issue (3) : 509-525. DOI: 10.1007/s11707-022-1068-0
RESEARCH ARTICLE

A DEM upscaling method with integrating valley lines based on HASM

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Abstract

A new digital elevation model (DEM) upscaling method based on high accuracy surface modeling (HASM) is proposed by combining the elevation information of DEM and the valley lines extracted from DEM with different flow accumulation thresholds. The proposed method has several advantages over traditional DEM upscaling methods. First, the HASM ensures the smoothness of the upscaled DEM. Secondly, several DEMs with different topographic details can be obtained using the same DEM grid size by incorporating the valley lines with different flow accumulation thresholds. The Jiuyuangou watershed in China’s Loess Plateau was used as a case study. A DEM with a grid size of 5 m obtained from the local surveying and mapping department was used to verify the proposed DEM upscaling method. We established the surface complexity index to describe the complexity of the topographic surface and quantified the differences in the topographic features obtained from different upscaling results. The results show that topography becomes more generalized as grid size and flow accumulation threshold increase. At a large DEM grid size, an increase in the flow accumulation threshold increases the difference in elevation values in different grids, increasing the surface complexity index. This study provides a new DEM upscaling method suitable for quantifying topography.

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Keywords

DEM / upscaling / HASM / flow accumulation threshold / surface complexity index

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Mingwei ZHAO, Xiaoxiao JU, Na ZHAO, Chun WANG, Yan XU, Xiaoran WU, Weitao LI. A DEM upscaling method with integrating valley lines based on HASM. Front. Earth Sci., 2024, 18(3): 509‒525 https://doi.org/10.1007/s11707-022-1068-0

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Acknowledgments

We are thankful for all of the helpful comments provided by the reviewers. This research was supported by Anhui Province Universities Outstanding Talented Person Support Project (No. gxyq2022097); Major Project of Natural Science Research of Anhui Provincial Department of Education (Nos. 2022AH040150, KJ2021ZD0130, KJ2021ZD0131); the National Natural Science Foundation of China (Grant No. 42071374); the guiding plan project of Chuzhou Science and Technology Bureau (No. 2021ZD008); “113” Industry Innovation Team of Chuzhou City in Anhui Province.

Competing interests

The authors declare that they have no competing interests.

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