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Research Articles

Comprehensive vertical accuracy analysis of freely available DEMs for different landscape types of the Rur catchment, Germany

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Pages 7774-7799 | Received 13 Apr 2021, Accepted 17 Sep 2021, Published online: 05 Oct 2021

References

  • Abrams M, Bailey B, Tsu H, Hato M. 2010. The ASTER global DEM. Photogramm Eng Rem S. 76(4):344–348.
  • Abrams M, Crippen R. 2019. ASTER GDEM V3 (ASTER Global DEM).
  • Airbus Defence and Space. 2020a. Copernicus digital elevation model – Product handbook. [ Airbus Defense & Space; accessed 2021 April 12]. https://spacedata.copernicus.eu/documents/20126/0/GEO1988-CopernicusDEM-SPE-002_ProductHandbook_I1.00.pdf.
  • Airbus Defence and Space. 2020b. Copernicus digital elevation model – Validation report. Airbus Defense & Space; [accessed 2021 April 12]. https://spacedata.copernicus.eu/documents/20126/0/GEO1988-CopernicusDEM-RP-001_ValidationReport_V1.0.pdf.
  • Alganci U, Besol B, Sertel E. 2018. Accuracy assessment of different digital surface models. Isprs Int Geo-Inf. 7(3):114.
  • Altunel AO. 2019. Evaluation of TanDEM-X 90 m digital elevation model. Int J Remote Sens. 40(7):2841–2854.
  • Arbeitsgemeinschaft der Vermessungsverwaltungen der Länder der Bundesrepublik Deutschland. 2017. Produkt- und Qualitätsstandard für Digitale Geländemodell – Version 3.0. German.
  • Baade J, Schmullius C. 2016. TanDEM-X IDEM precision and accuracy assessment based on a large assembly of differential GNSS measurements in Kruger National Park, South Africa. ISPRS J Photogramm. 119:496–508.
  • Becek K, Koppe W, Kutoglu SH. 2016. Evaluation of vertical accuracy of the WorldDEM (TM) using the runway method. Remote Sens. 8(11):934.
  • Berthier E, Brun F. 2019. Karakoram geodetic glacier mass balances between 2008 and 2016: persistence of the anomaly and influence of a large rock avalanche on Siachen Glacier. J Glaciol. 65(251):494–507.
  • Bezirksregierung Köln. 2017. Digital elevation model (DGM1) of the Rur Catchment, based on data from Bezirksregierung Köln [dataset]. CRC/TR32 Database (TR32DB); [accessed 2021 April 12]. https://www.tr32db.uni-koeln.de/data.php?dataID=1690.
  • Bezirksregierung Köln. 2020. Festpunktdaten NW im amtlichen Festpunktinformationssystem (AFIS) [dataset]. Geobasis NRW. German. [accessed 2021 April 12]. https://www.opengeodata.nrw.de/produkte/geobasis/rb/fd/hfp_pl_csv/.
  • Bishop MP, James LA, Shroder JF, Walsh SJ. 2012. Geospatial technologies and digital geomorphological mapping: Concepts, issues and research. Geomorphology. 137(1):5–26.
  • Blaszczyk M, Ignatiuk D, Grabiec M, Kolondra L, Laska M, Decaux L, Jania J, Berthier E, Luks B, Barzycka B, et al. 2019. Quality assessment and glaciological applications of digital elevation models derived from space-borne and aerial images over two tidewater glaciers of Southern Spitsbergen. Remote Sens. 11(9):1121.
  • Bogena HR, Montzka C, Huisman JA, Graf A, Schmidt M, Stockinger M, von Hebel C, Hendricks-Franssen HJ, van der Kruk J, Tappe W, et al. 2018. The TERENO-Rur hydrological observatory: A multiscale multi-compartment research platform for the advancement of hydrological science. Vadose Zone J. 17(1):180055.
  • Buchhorn M, Smets B, Bertels L, De Roos B, Lesiv M, Tesendbazar N-E, Herold M, Fritz S. 2020. Copernicus global land service: Land cover 100m: collection 3: epoch 2019: Globe. 3.0.1 [dataset]. Zenodo. [accessed 2021 March 29]. https://doi.org/10.5281/zenodo.3939050.
  • Crippen R, Buckley S, Agram P, Belz E, Gurrola E, Hensley S, Kobrick M, Lavalle M, Martin J, Neumann M, et al. 2016. Nasadem global elevation model: methods and progress. ISPRS – International archives of the photogrammetry. Remote Sens Spatial Inform Sci. XLI-B4:125–128.
  • Dragut L, Blaschke T. 2006. Automated classification of landform elements using object-based image analysis. Geomorphology. 81(3–4):330–344.
  • Drisya J, Kumar DS. 2016. Comparison of digitally delineated stream networks from different spaceborne digital elevation models: A case study based on two watersheds in South India. Arab J Geosci. 9(18): 710.
  • Earth Observation Research Center and Japan Aerospace Exploration Agency. 2021. ALOS World 3D-30m (AW3D30) Version 3.2/3.1; [accessed 2021 April 12]. https://www.eorc.jaxa.jp/ALOS/en/aw3d30/aw3d30v3.2_product_e_e1.2.pdf.
  • European Environment Agency (EEA). 2014. EU-DEM statistical validation; [accessed 2021 April 12]. https://land.copernicus.eu/user-corner/technical-library/eu-dem-2013-report-on-the-results-of-the-statistical-validation.
  • European Environment Agency (EEA). 2016. European Digital Elevation Model (EU-DEM), version 1.1 [dataset]. [accessed 2021 April 12]. https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1?tab=metadata.
  • Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, et al. 2007. The shuttle radar topography mission. Rev Geophys. 45(2):RG2004.
  • Fenta AA, Kifle A, Gebreyohannes T, Hailu G. 2015. Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrogeol J. 23(1):195–206.
  • Gdulová K, Marešová J, Moudrý V. 2020. Accuracy assessment of the global TanDEM-X digital elevation model in a mountain environment. Remote Sens Environ. 241:111724.
  • Gesch DB. 2018. Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure. Front Earth Sci. 6: 230.
  • Gonzalez-Moradas MDR, Viveen W. 2020. Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the Peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics. Remote Sens Environ. 237: 111509.
  • Graf L, Moreno-de-las-Heras M, Ruiz M, Calsamiglia A, Garcia-Comendador J, Fortesa J, Lopez-Tarazon JA, Estrany J. 2018. Accuracy assessment of digital terrain model dataset sources for hydrogeomorphological modelling in small mediterranean catchments. Remote Sens. 10(12):2014.
  • Grohmann CH. 2018. Evaluation of TanDEM-X DEMs on selected Brazilian sites: Comparison with SRTM, ASTER GDEM and ALOS AW3D30. Remote Sens Environ. 212:121–133.
  • Höhle J, Höhle M. 2009. Accuracy assessment of digital elevation models by means of robust statistical methods. Isprs J Photogramm. 64(4):398–406.
  • Holmes KW, Chadwick OA, Kyriakidis PC. 2000. Error in a USGS 30-meter digital elevation model and its impact on terrain modeling. J Hydrol. 233(1-4):154–173.
  • Hu ZH, Peng JW, Hou YL, Shan J. 2017. Evaluation of recently released open global digital elevation models of Hubei, China. Remote Sens. 9(3):262.
  • Huang LC, Liu L, Jiang LM, Zhang TJ. 2018. Automatic mapping of Thermokarst landforms from remote sensing images using deep learning: a case study in the Northeastern Tibetan Plateau. Remote Sens. 10(12):2067.
  • Ihde, J, Augath W, Sacher M. 2002. The vertical reference system for Europe. In: Drewes H, Dodson AH, Fortes LPS, et al., editors. Vertical reference systems. Berlin, Heidelberg: Springer Berlin Heidelberg; p. 345–350.
  • IT.NRW. 2012. Landwirtschaftszählung in Nordrhein-Westfalen 2010 – Gemeinde- und Kreisstatistik der landwirtschaftlichen Betriebe Betriebsgrößen, Bodennutzung, Viehhaltung, sozialökonomische Betriebstypen, betriebswirtschaftliche Ausrichtung, Arbeitskräfte. Information und Technik Nordrhein-Westfalen (Geschäftsbereich Statistik). Düsseldorf. German.
  • Jarvis A, Reuter H, Nelsen A, Guevara E. 2008. Hole-filled seamless SRTM data V4 [dataset]. International Centre for Tropical Agriculture (CIAT); [accessed 2021 April 12]. http://srtm.csi.cgiar.org.
  • Kalambukattu JG, Kumar S, Raj RA. 2018. Digital soil mapping in a Himalayan watershed using remote sensing and terrain parameters employing artificial neural network model. Environ Earth Sci. 77(5):203.
  • Keys L, Baade J. 2019. Uncertainty in catchment delineations as a result of digital elevation model choice. Hydrology. 6(1):13.
  • Korres W, Reichenau TG, Fiener P, Koyama CN, Bogena HR, Comelissen T, Baatz R, Herbst M, Diekkruger B, Vereecken H, et al. 2015. Spatio-temporal soil moisture patterns - A meta-analysis using plot to catchment scale data. J Hydrol. 520:326–341.
  • Kramm T, Hoffmeister D, Curdt C, Maleki S, Khormali F, Kehl M. 2017. Accuracy assessment of landform classification approaches on different spatial scales for the Iranian Loess Plateau. Isprs Int Geo-Inf. 6(11):366.
  • Kramm T, Hoffmeister D. 2019. A relief dependent evaluation of digital elevation models on different scales for Northern Chile. Isprs Int Geo-Inf. 8(10):430.
  • Kramm T, Hoffmeister D. 2020. Assessing the influence of environmental factors and datasets on soil type prediction with two machine learning algorithms in a heterogeneous area in the Rur catchment, Germany. Geoderma Reg. 22:e00316.
  • Kumar A, Negi HS, Kumar K, Shekhar C. 2020. Accuracy validation and bias assessment for various multi-sensor open-source DEMs in part of the Karakoram region. Remote Sens Lett. 11(10):893–902.
  • Li H, Zhao JY. 2018. Evaluation of the newly released worldwide AW3D30 DEM over typical landforms of China using two global DEMs and ICESat/GLAS data. IEEE J-Stars. 11(11):4430–4440.
  • Liu K, Song CQ, Ke LH, Jiang L, Pan YY, Ma RH. 2019. Global open-access DEM performances in Earth's most rugged region High Mountain Asia: A multi-level assessment. Geomorphology. 338:16–26.
  • Liu ZW, Zhu JJ, Fu HQ, Zhou C, Zuo TY. 2020. Evaluation of the vertical accuracy of open global DEMs over steep terrain regions using ICESat Data: a case study over Hunan Province, China. Sensors. 20(17):4865.
  • Luana SP, Hou XY, Wang YT. 2015. Assessing the accuracy of SRTM DEM and aster GDEM datasets for the Coastal Zone of Shandong Province, Eastern China. Pol Marit Res. 22:15–20.
  • Marques KPP, Dematte JAM, Miller BA, Lepsch IF. 2018. Geomorphometric segmentation of complex slope elements for detailed digital soil mapping in southeast Brazil. Geoderma Reg. 14:e00175.
  • Maune DF. 2007. Digital Elevation model technologies and applications: The DEM users manual, 2nd ed.; American Society for Photogrammetry and Remote Sensing: Bethesda, MD.
  • Mmbando GA, Kleyer M. 2018. Mapping precipitation, temperature, and evapotranspiration in the Mkomazi River Basin, Tanzania. Climate. 6(3):63.
  • Mokarram M, Seif A, Sathyamoorthy D. 2015. Landform classification via fuzzy classification of morphometric parameters computed from digital elevation models: case study on Zagros Mountains. Arab J Geosci. 8(7):4921–4937.
  • Mouratidis A, Ampatzidis D. 2019. European digital elevation model validation against extensive global navigation satellite systems data and comparison with SRTM DEM and ASTER GDEM in Central Macedonia (Greece). Isprs Int Geo-Inf. 8(3):108.
  • Mukherjee S, Joshi PK, Mukherjee S, Ghosh A, Garg RD, Mukhopadhyay A. 2013. Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). Int J Appl Earth Obs. 21:205–217.
  • Nagaveni C, Kumar KP, Ravibabu MV. 2019. Evaluation of TanDEMx and SRTM DEM on watershed simulated runoff estimation. J Earth Syst Sci. 128(1):2.
  • NASA JPL. 2020. NASADEM Merged DEM Global 1 arc second V001 [dataset]. NASA EOSDIS Land Processes DAAC; [accessed 2021 April 12]. https://doi.org/10.5067/MEaSUREs/NASADEM/NASADEM_HGT.001.
  • Pakoksung K, Takagi M. 2021. Assessment and comparison of Digital Elevation Model (DEM) products in varying topographic, land cover regions and its attribute: a case study in Shikoku Island Japan. Model Earth Syst Env. 7:465–484.
  • Pandey P, Manickam S, Bhattacharya A, Ramanathan AL, Singh G, Venkataraman G. 2017. Qualitative and quantitative assessment of TanDEM-X DEM over western Himalayan glaciated terrain. Geocarto Int. 32(4):442–454.
  • Podgorski J, Kinnard C, Petlicki M, Urrutia R. 2019. Performance assessment of TanDEM-X DEM for Mountain Glacier elevation change detection. Remote Sens. 11(2):187.
  • Reuter HI, Nelson A, Jarvis A. 2007. An evaluation of void-filling interpolation methods for SRTM data. Int J Geogr Inf Sci. 21(9):983–1008.
  • Rexer M, Hirt C. 2014. Comparison of free high resolution digital elevation data sets (ASTER GDEM2, SRTM v2.1/v4.1) and validation against accurate heights from the Australian National Gravity Database. Aust J Earth Sci. 61(2):213–226.
  • Rizzoli P, Brautigam B, Kraus T, Martone M, Krieger G. 2012. Relative height error analysis of TanDEM-X elevation data. Isprs J Photogramm. 73:30–38.
  • Rizzoli P, Martone M, Gonzalez C, Wecklich C, Tridon DB, Brautigam B, Bachmann M, Schulze D, Fritz T, Huber M, et al. 2017. Generation and performance assessment of the global TanDEM-X digital elevation model. Isprs J Photogramm. 132:119–139.
  • Rodriguez E, Morris CS, Belz JE, Chapin E, Martin J, Daffer W, Hensley S. 2005. An assessment of the SRTM topographic products, Technical Report JPL D-31639.
  • Rossman NR, Zlotnik VA, Rowe CM. 2018. An approach to hydrogeological modeling of a large system of groundwater-fed lakes and wetlands in the Nebraska Sand Hills, USA. Hydrogeol J. 26(3):881–897.
  • Satge F, Bonnet MP, Timouk F, Calmant S, Pillco R, Molina J, Lavado-Casimiro W, Arsen A, Cretaux JF, Garnier J. 2015. Accuracy assessment of SRTM v4 and ASTER GDEM v2 over the Altiplano watershed using ICESat/GLAS data. Int J Remote Sens. 36(2):465–488.
  • Schlund M, Baron D, Magdon P, Erasmi S. 2019. Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests. Isprs J Photogramm. 147:232–241.
  • Schwanghart W, Groom G, Kuhn NJ, Heckrath G. 2013. Flow network derivation from a high resolution DEM in a low relief, agrarian landscape. Earth Surf Processes Landforms. 38(13):1576–1586.
  • Scilands GmbH. 2010. GMK10 Rur – Terrainfactors [dataset]. CRC/TR32 Database (TR32DB). [accessed 2021 April 12]. https://www.tr32db.uni-koeln.de/data.php?dataID=196.
  • Solberg S, May J, Bogren W, Breidenbach J, Torp T, Gizachew B. 2018. Interferometric SAR DEMs for Forest Change in Uganda 2000-2012. Remote Sens. 10(2):228.
  • Suwandana E, Kawamura K, Sakuno Y, Kustiyanto E, Raharjo B. 2012. Evaluation of ASTER GDEM2 in Comparison with GDEM1, SRTM DEM and Topographic-Map-Derived DEM Using Inundation Area Analysis and RTK-dGPS Data. Remote Sens. 4(8):2419–2431.
  • Tachikawa T, Kaku M, Iwasaki A, Gesch DB, Oimoen MJ, Zhang Z, Danielson JJ, Krieger T, Curtis B, Haase J, et al. 2011. ASTER Global Digital Elevation Model Version 2 - summary of validation results.
  • Tadono T, Shimada M, Murakami H, Takaku J. 2009. Calibration of PRISM and AVNIR-2 Onboard ALOS “Daichi”. IEEE T Geosci Remote. 47(12):4042–4050.
  • Takaku J, Tadono T, Tsutsui K. 2014. Generation of high resolution global DSM from ALOS PRISM. Int Arch Photogramm Remote Sens Spatial. XL-4:243–248.
  • Thomas J, Joseph S, Thrivikramji KP, Arunkumar KS. 2014. Sensitivity of digital elevation models: The scenario from two tropical mountain river basins of the Western Ghats, India. Geosci Front. 5(6):893–909.
  • Tian JJ, Schneider T, Straub C, Kugler F, Reinartz P. 2017. Exploring digital surface models from nine different sensors for forest monitoring and change detection. Remote Sens. 9(3):287.
  • Ullmann T, Sauerbrey J, Hoffmeister D, May SM, Baumhauer R, Bubenzer O. 2019. Assessing Spatiotemporal Variations of Sentinel-1 InSAR Coherence at Different Time Scales over the Atacama Desert (Chile) between 2015 and 2018. Remote Sens. 11(24):2960.
  • Uuemaa E, Ahi S, Montibeller B, Muru M, Kmoch A. 2020. Vertical Accuracy of Freely Available Global Digital Elevation Models (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM). Remote Sens. 12(21):3482.
  • Vassilaki DI, Stamos AA. 2020. TanDEM-X DEM: Comparative performance review employing LIDAR data and DSMs. Isprs J Photogramm. 160:33–50.
  • Waldhoff G, Lussem U, Bareth G. 2017. Multi-Data Approach for remote sensing-based regional crop rotation mapping: A case study for the Rur catchment, Germany. Int J Appl Earth Obs. 61:55–69.
  • Waldhoff G, Lussem U. 2016. Enhanced land use classification of 2015 for the Rur catchment – Update [dataset]. CRC/TR32 Database (TR32DB); [accessed 2021 April 12].
  • Walk J, Stauch G, Reyers M, Vasquez P, Sepulveda FA, Bartz M, Hoffmeister D, Bruckner H, Lehmkuhl F. 2020. Gradients in climate, geology, and topography affecting coastal alluvial fan morphodynamics in hyperarid regions – The Atacama perspective. Global Planet Change. 185:102994.
  • Wessel B, Huber M, Wohlfart C, Marschalk U, Kosmann D, Roth A. 2018. Accuracy assessment of the global TanDEM-X digital elevation model with GPS data. Isprs J Photogramm. 139:171–182.
  • Wessel B. 2016. TanDEM-X ground segment – DEM products specification document. Oberpfaffenhofen, Germany: Earth Observation Center.
  • Weydahl DJ, Sagstuen J, Dick OB, Ronning H. 2007. SRTM DEM accuracy assessment over vegetated areas in Norway. Int J Remote Sens. 28(16):3513–3527.
  • Wilson JP. 2018. Environmental applications of digital terrain modeling. 1st ed. Hoboken, NJ: Wiley-Blackwell.
  • Yahaya SI, El Azzab D. 2019. Vertical accuracy assessment of global digital elevation models and validation of gravity database heights in Niger. Int J Remote Sens. 40(20):7966–7985.
  • Yap L, Kande LH, Nouayou R, Kamguia J, Ngouh NA, Makuate MB. 2019. Vertical accuracy evaluation of freely available latest high-resolution (30 m) global digital elevation models over Cameroon (Central Africa) with GPS/leveling ground control points. Int J Digit Earth. 12(5):500–524.
  • Zhang KQ, Gann D, Ross M, Robertson Q, Sarmiento J, Santana S, Rhome J, Fritz C. 2019. Accuracy assessment of ASTER, SRTM, ALOS, and TDX DEMs for Hispaniola and implications for mapping vulnerability to coastal flooding. Remote Sens Environ. 225:290–306.
  • Zhao SM, Cheng WM, Zhou CH, Chen X, Zhang SF, Zhou ZP, Liu HJ, Chai HX. 2011. Accuracy assessment of the ASTER GDEM and SRTM3 DEM: an example in the Loess Plateau and North China Plain of China. Int J Remote Sens. 32(23):8081–8093.

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