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

Front. Earth Sci. ›› 2024, Vol. 18 ›› Issue (3) : 509 -525.

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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 DOI:10.1007/s11707-022-1068-0

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References

[1]

Aguilar F J, Aguera F, Aguilar M A, Carvajal F (2005). Effects of terrain morphology, sampling density, and interpolation methods on grid DEM accuracy.Photogramm Eng Remote Sensing, 71(7): 805–816

[2]

Ai T, Li J (2010). A DEM generalization by minor valley branch detection and grid filling.ISPRS J Photogramm Remote Sens, 65(2): 198–207

[3]

Ai T, Liu Y, Huang Y (2007). The hierarchical watershed partitioning and generalization of river network.Acta Geodetica Cartograph Sin, 36(2): 231–236,243

[4]

BurroughP A, McDonnell R A, LloydC D (1988). Principles of Geographical Information Systems. New York: Oxford University Press

[5]

Chen C F, Yue T X, Li Y Y (2012). A high speed method of SMTS.Comput Geosci, 41: 64–71

[6]

Chen C, Li Y (2013). An orthogonal least-square-based method for DEM generalization.Int J Geogr Inf Sci, 27(1): 154–167

[7]

Chen Y, Ma T, Chen X, Chen Z, Yang C, Lin C, Shan L (2016). A new DEM generalization method based on watershed and tree structure.PLoS One, 11(8): e0159798

[8]

Chen Z, Ma X, Yu W, Wu L (2020). An integrated graph Laplacian downsample (IGLD)-based method for DEM generalization.Earth Sci Inform, 13(4): 973–987

[9]

Fisher P F (1991). Firest experiments in viewshed uncertainty-The accuracy of the viewshed area.Photogramm Eng Remote Sensing, 57(10): 1321–1327

[10]

Horritt M S, Bates P D (2001). Effects of spatial resolution on a raster based model of flood flow.J Hydrol (Amst), 253(1–4): 239–249

[11]

Jenson S K, Domingue J O (1988). Extracting topographic structure from digital elevation data for geographic information-system analysis.Photogramm Eng Remote Sensing, 54(11): 1593–1600

[12]

Kawabata D, Bandibas J (2009). Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN).Geomorphology, 113(1–2): 97–109

[13]

Li J H, Chen W J (2005). A rule-based method for mapping Canada’s wetlands using optical, radar and DEM data.Int J Remote Sens, 26(22): 5051–5069

[14]

Lin W T, Chou W C, Lin C Y, Huang P H, Tsai J S (2006). Automated suitable drainage network extraction from digital elevation models in Taiwan’s upstream watersheds.Hydrol Processes, 20(2): 289–306

[15]

Liu X (2008). Airborne LiDAR for DEM generation: some critical issues.Prog Phys Geogr, 32(1): 31–49

[16]

Ma T, Chen Y, Hua Y, Chen Z, Chen X, Lin C, Yang C (2017). DEM generalization with profile simplification in four directions.Earth Sci Inform, 10(1): 29–39

[17]

Murphy P N C, Ogilvie J, Meng F R, Arp P (2008). Stream network modelling using lidar and photogrammetric digital elevation models: a comparison and field verification.Hydrol Processes, 22(12): 1747–1754

[18]

O’Callaghan J F, Mark D M (1984). The extraction of drainage networks from digital elevation data.Comput Vis Graph Image Process, 28(3): 323–344

[19]

Raposo P (2020). Variable DEM generalization using local entropy for terrain representation through scale.Intern J Cartograph, 6(1): 99–120

[20]

Schoorl J M, Sonneveld M P W, Veldkamp A (2000). Three-dimensional landscape process modelling: the effect of DEM resolution.Earth Surf Process Landf, 25(9): 1025–1034

[21]

Tang G (2014). Progress of DEM and digital terrain analysis in China.Acta Geogr Sin, 69(9): 1305–1325

[22]

Tarboton D G (1997). A new method for the determination of flow directions and upslope areas in grid digital elevation models.Water Resour Res, 33(2): 309–319

[23]

Tarboton D G, Bras R L, Rodriguez-Iturbe I (1991). On the extraction of channel networks from digital elevation data.Hydrol Processes, 5(1): 81–100

[24]

Tribe A (1992). Automated recognition of valley lines and drainage networks from grid digital electation models–a review and a new method.J Hydrol (Amst), 139(1–4): 263–293

[25]

Turcotte R, Fortin J P, Rousseau A N, Massicotte S, Villeneuve J P (2001). Determination of the drainage structure of a watershed using a digital elevation model and a digital river and lake network.J Hydrol (Amst), 240(3–4): 225–242

[26]

Vaze J, Teng J, Spencer G (2010). Impact of DEM accuracy and resolution on topographic indices.Environ Model Softw, 25(10): 1086–1098

[27]

Weibel R (1992). Models and experiments for adaptive computer-assisted terrain generalization.Cartogr Geogr Inf Syst, 19(3): 133–153

[28]

Wolock D M, McCabe G J (2000). Differences in topographic characteristics computed from 100- and 1000-m resolution digital elevation model data.Hydrol Processes, 14(6): 987–1002

[29]

Wu Q, Chen Y, Wilson J P, Liu X, Li H (2019). An effective parallelization algorithm for DEM generalization based on CUDA.Environ Model Softw, 114: 64–74

[30]

Xiong L Y, Li S J, Hu G H, Wang K, Chen M, Zhu A X, Tang G A (2023). Past rainfall-driven erosion on the Chinese loess plateau inferred from archaeological evidence from Wucheng City, Shanxi.Commun Earth Environ, 4(1): 4

[31]

Xiong L, Li S, Tang G, Strobl J (2022). Geomorphometry and terrain analysis: data, methods, platforms and applications.Earth Sci Rev, 233: 104191

[32]

Xiong L, Tang G, Yang X, Li F (2021). Geomorphology-oriented digital terrain analysis: progress and perspectives.J Geogr Sci, 31(3): 456–476

[33]

YueT X (2011). Surface Modeling: High Accuracy and High Speed Methods. Calabasas: CRC Press

[34]

Yue T X, Chen C F, Li B L (2010). An adaptive method of high accuracy surface modeling and its application to simulating elevation surface.Trans GIS, 14(5): 615–630

[35]

Yue T X, Du Z P, Song D J, Gong Y (2007). A new method of surface modeling and its application to DEM construction.Geomorphology, 91(1–2): 161–172

[36]

Yue T X, Liu Y, Zhao M W, Du Z P, Zhao N (2016). A fundamental theorem of Earth’s surface modelling.Environ Earth Sci, 75(9): 751

[37]

Yue T X, Zhao N, Liu Y, Wang Y, Zhang B, Du Z P, Fan Z, Shi W, Chen C, Zhao M, Song D, Wang S, Song Y, Yan C, Li Q, Sun X, Zhang L, Tian Y, Wang W, Wang Y, Ma S, Huang H, Lu Y, Wang Q, Wang C, Wang Y, Lu M, Zhou W, Liu Y, Yin X, Wang Z, Bao Z, Zhao M, Zhao Y, Jiao Y, Naseer U, Fan B, Li S, Yang Y, Wilson J P (2020). A fundamental theorem for eco-environmental surface modelling and its applications.Sci China Earth Sci, 63(8): 1092–1112

[38]

Zhang R, Bian S, Li H (2021). RSPCN: super-resolution of digital elevation model based on recursive sub-pixel convolutional neural networks.ISPRS Int J Geoinf, 10(8): 501

[39]

Zhao N, Yue T X, Zhao M W, Du Z P, Fan Z M, Chen C F (2014). Sensitivity studies of a high accuracy surface modeling method.Sci China Earth Sci, 57(10): 2386–2396

[40]

Zhou A, Chen Y, Wilson J P, Su H, Xiong Z, Cheng Q (2021). An enhanced double-filter deep residual neural network for generating super resolution DEMs.Remote Sens (Basel), 13(16): 3089

[41]

Zhou Q, Chen Y (2011). Generalization of DEM for terrain analysis using a compound method.ISPRS J Photogramm Remote Sens, 66(1): 38–45

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