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Digital Elevation Model of the Republic of Adygea

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The Republic of Adygea Environment

Part of the book series: The Handbook of Environmental Chemistry ((HEC,volume 106))

Abstract

SRTM 4.0 data with a spatial resolution of 30 m were selected as the basis for the digital elevation model (DEM) for the territory of the Republic of Adygea which was built for the first time. A comparison with different topographic maps of different spatial resolution showed that the elaborated DEM of the Republic of Adygea is very accurate. Slope gradient was calculated for the territory of the Republic, which allowed to show possible applications for agriculture, analysis of hydrological network and different exogenous processes, and planning of road construction. With a variety of landforms and the development of exogenous geological processes, the creation of a DEM of the Republic of Adygea integrated into the GIS is necessary for geomorphological zoning and landscape science, geological and soil erosion studies, construction of visibility zones for telecommunication and GSM companies, carrying out cadastral valuation of land and urban development, risk assessment of landslides and avalanches, planning of wind and solar farms, development of mountain tourism and ski resorts, and many other tasks.

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References

  1. Cayley A (1859) XL. On contour and slope lines. Lond Edinburgh Dublin Philos Mag J Sci 18(120):264–268. https://doi.org/10.1080/14786445908642760

    Article  Google Scholar 

  2. Kirkby MJ, Chorley RJ (1967) Throughflow, overland flow and erosion. Hydrol Sci J 12(3):5–21. https://doi.org/10.1080/02626666709493533

    Article  Google Scholar 

  3. Speight JG (1980) The role of topography in controlling throughflow generation: a discussion. Earth Surf Process 5(2):187–191. https://doi.org/10.1002/esp.3760050209

    Article  Google Scholar 

  4. Geiger R, Aron RH, Todhunter P (1995) The climate near the ground.5th edn. Vieweg+Teubner Verlag, p 528. https://doi.org/10.1007/978-3-322-86582-3

  5. Franklin J (1995) Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients. Prog Phys Geogr 19(4):474–499. https://doi.org/10.1177/030913339501900403

    Article  Google Scholar 

  6. Penck W (1953) Morphological analysis of land forms: a contribution to physical geology. Macmillan, London, p 429

    Google Scholar 

  7. Burbank DW, Anderson RS (2009) Tectonic geomorphology. Wiley, Chichester, p 454

    Google Scholar 

  8. Zhou Q, Lees B, Tang GA (2008) Advances in digital terrain analysis. Springer, Berlin, p 462. https://doi.org/10.1007/978-3-540-77800-4

    Book  Google Scholar 

  9. Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrol Process 5(1):3–30. https://doi.org/10.1002/hyp.3360050103

    Article  Google Scholar 

  10. Miller CL, Laflamme RA (1958) The digital terrain model – theory and application. Photogramm Eng 24(3):433–442

    Google Scholar 

  11. Doyle FJ (1978) Digital terrain models: an overview. Photogramm Eng Remote Sens 44(12):1481–1485

    Google Scholar 

  12. Burrough PA (1986) Principles of geographical information systems for land resources assessment. Clarendon Press, Oxford, p 193

    Google Scholar 

  13. Panin AV, Gelman RN (1997) Experience of the GPS technique application to derive detailed digital terrain models. Geod Cartogr 10:22–27. (in Russian)

    Google Scholar 

  14. Clark RL, Lee R (1998) Development of topographic maps for precision farming with kinematic GPS. Trans ASAE 41(4):909–916. https://doi.org/10.13031/2013.17247

    Article  Google Scholar 

  15. Mikhaylov AP, Chibunichev AG (2016) Photogrammetry. Moscow State University of Geodesy and Cartography, Moscow, p 294. (in Russian)

    Google Scholar 

  16. Jensen JR (1995) Issues involving the creation of digital elevation models and terrain corrected orthoimagery using soft-copy photogrammetry. Geocarto Int 10(1):5–21. https://doi.org/10.1080/10106049509354475

    Article  Google Scholar 

  17. Welch R, Jordan T, Lang H, Murakami H (1998) ASTER as a source for topographic data in the late 1990s. IEEE Trans Geosci Remote Sens 36(4):1282–1289. https://doi.org/10.1109/36.701078

    Article  Google Scholar 

  18. Giles PT, Franklin SE (1996) Comparison of derivative topographic surfaces of a DEM generated from stereoscopic SPOT images with field measurements. Photogramm Eng Remote Sens 62(10):1165–1170

    Google Scholar 

  19. Toutin T (2004) DTM generation from Ikonos in-track stereo images using a 3D physical model. Photogramm Eng Remote Sens 70(6):695–702. https://doi.org/10.14358/PERS.70.6.695

    Article  Google Scholar 

  20. Zebker HA, Werner CL, Rosen PA, Hensley S (1994) Accuracy of topographic maps derived from ERS-1 interferometric radar. IEEE Trans Geosci Remote Sens 32(4):823–836. https://doi.org/10.1109/36.298010

    Article  Google Scholar 

  21. Rabus B, Eineder M, Roth A, Bamler R (2003) The shuttle radar topography mission – a new class of digital elevation models acquired by spaceborne radar. ISPRS J Photogramm Remote Sens 57(4):241–262. https://doi.org/10.1016/S0924-2716(02)00124-7

    Article  Google Scholar 

  22. Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Shaffer S (2007) The shuttle radar topography mission. Rev Geophys 45(2):RG2004. https://doi.org/10.1029/2005RG000183

    Article  Google Scholar 

  23. Wehr A, Lohr U (1999) Airborne laser scanning – an introduction and overview. ISPRS J Photogramm Remote Sens 54(2–3):68–82. https://doi.org/10.1016/S0924-2716(99)00011-8

    Article  Google Scholar 

  24. Lloyd CD, Atkinson PM (2006) Deriving ground surface digital elevation models from LiDAR data with geostatistics. Int J Geogr Inf Sci 20(05):535–563. https://doi.org/10.1080/13658810600607337

    Article  Google Scholar 

  25. Finkl CW, Benedet L, Andrews JL (2005) Interpretation of seabed geomorphology based on spatial analysis of high-density airborne laser bathymetry. J Coast Res 2005(213):501–514. https://doi.org/10.2112/05-756A.1

    Article  Google Scholar 

  26. Laguta AA, Pogorelov AV (2018) Peculiarities of Krasnodar water reservoir silting. Evaluation based on the data of bathymetric surveys. Geograph Bull 4(47):54–66. (in Russian)

    Google Scholar 

  27. Dixon TH, Naraghi M, McNutt MK, Smith SM (1983) Bathymetric prediction from Seasat altimeter data. J Geophys Res Oceans 88(C3):1563–1571. https://doi.org/10.1029/JC088iC03p01563

    Article  Google Scholar 

  28. Sandwell DT, Smith WHF (2001) Bathymetric estimation. In: Satellite altimetry and earth sciences. Academic Press, San Diego, pp 441–458. https://doi.org/10.1016/S0074-6142(01)80157-1

    Chapter  Google Scholar 

  29. Khalugin EI, Zhalkovsky EA, Zhdanov ND (1992) Digital maps. Nedra, Moscow, p 415. (in Russian)

    Google Scholar 

  30. Eklundh L, Mårtensson U (1995) Rapid generation of digital elevation models from topographic maps. Int J Geogr Inf Syst 9(3):329–340. https://doi.org/10.1080/02693799508902040

    Article  Google Scholar 

  31. Miliaresis GC, Argialas DP (1999) Segmentation of physiographic features from the global digital elevation model/GTOPO30. Comput Geosci 25(7):715–728. https://doi.org/10.1016/S0098-3004(99)00025-4

    Article  Google Scholar 

  32. Hastings DA Dunbar PK (1993) Global land one-kilometer base elevation (GLOBE). Digital elevation model, version 1, documentation version 1,0. NGDC key to geophysical records documentation no. 34. National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, 133 pp

    Google Scholar 

  33. Amante C, Eakins BW (2009) ETOPO1 arc-minute global relief model: procedures, data sources and analysis. NOAA technical memorandum NESDIS NGDC-24. National Geophysical Data Center Marine Geology and Geophysics Division, Boulder, p 19

    Google Scholar 

  34. Strakhov VN, Strakhov AV, Stepanova IE, Zhalkovskiy EA (2007) About the substitution of the topographic maps for the linear analytical approximations of the earth surface relief. Geod Cartogr 2:21–25. (in Russian)

    Google Scholar 

  35. Strakhov VN, Strakhov AV, Stepanova IE, Zhalkovskiy EA (2007) About the substitution of the topographic maps for the linear analytical approximations of the earth surface relief. Geod Cartogr 3:33–38. (in Russian)

    Google Scholar 

  36. Wieczorek MA (2015) Gravity and topography of the terrestrial planets. In: Treatise on geophysics, vol 10. 2nd edn. Elsevier, Amsterdam, pp 165–206. https://doi.org/10.1016/B978-0-444-53802-4.00169-X

    Chapter  Google Scholar 

  37. Carter JR (1988) Digital representations of topographic surfaces. Photogramm Eng Remote Sens 54(11):1577–1580

    Google Scholar 

  38. Kumler M (1994) An intensive comparison of triangulated irregular networks (TINs) and digital elevation models (DEMs). Cartographica 31(2):1–99. https://doi.org/10.3138/TM56-74K7-QH1T-8575

    Article  Google Scholar 

  39. Evans IS (1979) Statistical characterization of altitude matrices by computer. An integrated system of terrain analysis and slope mapping. The final report on Grant DA-ERO-591-73-G0040. University of Durham, Durham, 192 pp

    Google Scholar 

  40. Shary PA (1995) Land surface in gravity points classification by a complete system of curvatures. Math Geol 27(3):373–390. https://doi.org/10.1007/BF02084608

    Article  Google Scholar 

  41. Clarke KC (1988) Scale-based simulation of topographic relief. Am Cartogr 15(2):173–181. https://doi.org/10.1559/152304088783887107

    Article  Google Scholar 

  42. Shary PA, Sharaya LS, Mitusov AV (2002) Fundamental quantitative methods of land surface analysis. Geoderma 107(1–2):1–32. https://doi.org/10.1016/S0016-7061(01)00136-7

    Article  Google Scholar 

  43. Evans IS (1972) General geomorphometry, derivatives of altitude, and descriptive statistics. In: Chorley RJ (ed) Spatial analysis in geomorphology. Methuen, London, pp 17–90

    Google Scholar 

  44. Speight JG (1974) A parametric approach to landform regions. Prog Geomorphol Spec Publ 7:213–230

    Google Scholar 

  45. Li Z, Zhu C, Gold C (2004) Digital terrain modeling: principles and methodology. CRC Press, Boca Raton, p 323. https://doi.org/10.1201/9780203357132

    Book  Google Scholar 

  46. Florinsky I (2016) Digital terrain analysis in soil science and geology. Academic Press, Cambridge, p 506

    Google Scholar 

  47. O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vision Graph Image Process 28(3):323–344. https://doi.org/10.1016/S0734-189X(84)80011-0

    Article  Google Scholar 

  48. Martz LW, De Jong E (1988) Catch: a fortran program for measuring catchment area from digital elevation models. Comput Geosci 14(5):627–640. https://doi.org/10.1016/0098-3004(88)90018-0

    Article  Google Scholar 

  49. Freeman TG (1991) Calculating catchment area with divergent flow based on a regular grid. Comput Geosci 17(3):413–422. https://doi.org/10.1016/0098-3004(91)90048-I

    Article  Google Scholar 

  50. Quinn PFBJ, Beven K, Chevallier P, Planchon O (1991) The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrol Process 5(1):59–79. https://doi.org/10.1002/hyp.3360050106

    Article  Google Scholar 

  51. Tarboton DG (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. https://doi.org/10.1029/96WR03137

    Article  Google Scholar 

  52. Zevenbergen LW, Thorne CR (1987) Quantitative analysis of land surface topography. Earth Surf Process Landf 12(1):47–56. https://doi.org/10.1002/esp.3290120107

    Article  Google Scholar 

  53. Skidmore AK (1989) A comparison of techniques for calculating gradient and aspect from a gridded digital elevation model. Int J Geograph Inform Syst 3(4):323–334. https://doi.org/10.1080/02693798908941519

    Article  Google Scholar 

  54. Jones KH (1998) A comparison of algorithms used to compute hill slope as a property of the DEM. Comput Geosci 24(4):315–323. https://doi.org/10.1016/S0098-3004(98)00032-6

    Article  Google Scholar 

  55. Zhou Q, Liu X (2004) Analysis of errors of derived slope and aspect related to DEM data properties. Comput Geosci 30(4):369–378. https://doi.org/10.1016/j.cageo.2003.07.005

    Article  Google Scholar 

  56. Rodríguez JLG, Suárez MCG (2010) Comparison of mathematical algorithms for determining the slope angle in GIS environment. Aqua-LAC 2(2):78–82

    Article  Google Scholar 

  57. Florinsky IV (1998) Accuracy of local topographic variables derived from digital elevation models. Int J Geogr Inf Sci 12(1):47–62. https://doi.org/10.1080/136588198242003

    Article  Google Scholar 

  58. Schmidt J, Evans IS, Brinkmann J (2003) Comparison of polynomial models for land surface curvature calculation. Int J Geogr Inf Sci 17(8):797–814. https://doi.org/10.1080/13658810310001596058

    Article  Google Scholar 

  59. Florinsky IV (2009) Accurate method for derivation of local topographic variables. Geod Cartogr 4:19–23. (in Russian)

    Google Scholar 

  60. Florinsky IV (1998) Derivation of topographic variables from a digital elevation model given by a spheroidal trapezoidal grid. Int J Geogr Inf Sci 12(8):829–852. https://doi.org/10.1080/136588198241527

    Article  Google Scholar 

  61. Wood JD (1996) The geomorphological characterisation of digital elevation models. PhD thesis, University of Leicester, Leicester, 193 pp

    Google Scholar 

  62. Florinsky IV (2002) Errors of signal processing in digital terrain modelling. Int J Geogr Inf Sci 16(5):475–501. https://doi.org/10.1080/13658810210129139

    Article  Google Scholar 

  63. Buzarov AS, Varshanina TP, Kabayan NV, Krasnopolskiy AV, Krasnopolskaya NV, Kuasheva DA, Melnikova TN, Spesivtsev PA, Khachegogu AY, Shebzukhova EA Geography of the Republic of Adygea. Adyghe Republican Book Publishing House, Maykop, p 200. (in Russian)

    Google Scholar 

  64. The Atlas of the Republic of Adygea (2005) Publishing house “Lev Tolstoy”, Maykop, 79 p. (in Russian)

    Google Scholar 

  65. Bedanokov MK, Chich SK, Chetyz DY, Trepet SA, Lebedev SA, Kostianoy AG (2020) Physico-geographical characteristics of the Republic of Adygea. In: Bedanokov MK, Lebedev SA, Kostianoy AG (eds) The Republic of Adygea environment. Springer, Cham

    Google Scholar 

  66. Lebedev SA, Korinevich LA (2020) Development of exogenous geological processes in the territory of the Republic of Adygea. In: Bedanokov MK, Lebedev SA, Kostianoy AG (eds) The Republic of Adygea environment. Springer, Cham

    Google Scholar 

  67. Lebedev SA, Kravchenko PN (2020) Soil degradation in the Republic of Adygea under exogenous geological processes. In: Bedanokov MK, Lebedev SA, Kostianoy AG (eds) The Republic of Adygea environment. Springer, Cham

    Google Scholar 

  68. Khunagov RD, Varshanina TP (2006) Multipurpose national geographic information system of the Republic of Adygea. Vestnik Adygea State Univ 1:262–268. (in Russian)

    Google Scholar 

  69. Varshanina TP, Shekhov ZA, Shtelmakh EV, Getmansky MY (2018) The prospects of use of digital technologies for the solution of theoretical problems of landscape study. In: Landscape geography in the 21st century. Publishing House Printing House “Arial”, Simferopol, pp 95–97. (in Russian)

    Google Scholar 

  70. Orlov TV, Sadkov SA (2015) Investigation of karst relief in the eastern part of Lago-Naki plateau by LIDAR and high-resolution airborn images. Geoecol Eng Geol Hydrogeol Geocryol 4:365–376. (in Russian)

    Google Scholar 

  71. Konstantinov YA, Sinelnikova IE (2018) Organization of engineering and geodetic work in the construction of buildings and structures in the conditions of geodynamic activity of the mountainous part of the Republic of Adygea. In Field of knowledge: questions of the modern stage of development of scientific thought. Individual Entrepreneur Kuzmin Sergey Vladimirovich, Kazan, pp 451–467. (in Russian)

    Google Scholar 

  72. Zhuchkova VK, Rakovskaya EM (2004) Methods of comprehensive physical and geographical research. Publishing Center “Academy”, Moscow, p 368. (in Russian)

    Google Scholar 

  73. Florinsky IV (1998) Combined analysis of digital terrain models and remotely sensed data in landscape investigations. Prog Phys Geogr 22(1):33–60. https://doi.org/10.1177/030913339802200102

    Article  Google Scholar 

  74. Kostianoy AG, Lebedev SA (2014) Three-dimensional digital elevation model of Karashor depression and Altyn Asyr Lake. In: The Turkmen Lake Altyn Asyr and water resources in Turkmenistan. The handbook of environmental chemistry, vol 28. Springer, Berlin, pp 177–196. https://doi.org/10.1007/698_2013_238

    Chapter  Google Scholar 

  75. Teslenko PF, Korotkov BS (1967) Effect of arenaceous intercalations in clays on their compaction. Int Geol Rev 9(5):699–701. https://doi.org/10.1080/00206816709474501

    Article  Google Scholar 

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Acknowledgments

S.A. Lebedev (satellite data processing) was supported in the framework of the Geophysical Center RAS budgetary financing, adopted by the Ministry of Science and Higher Education of the Russian Federation, by the project “Intelligent analysis of big data in the tasks of ecology and environmental protection,” carried out within the Competence Center Program of the National Technological Initiative “Center for the Storage and Analysis of Big Data,” supported by the Ministry of Science and Higher Education of the Russian Federation at the Lomonosov Moscow State University and by the Fund of the National Technological Initiative dated December 11, 2018, No. 13/1251/2018. This work employed facilities and data provided by the Shared Research Facility “Analytical Geomagnetic Data Center” of the Geophysical Center of RAS (http://ckp.gcras.ru/). A.G. Kostianoy was partially supported in the framework of the P.P. Shirshov Institute of Oceanology RAS budgetary financing (Project N 149-2019-0004).

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Authors and Affiliations

  1. Geophysical Center, Russian Academy of Sciences, Moscow, Russian Federation

    Sergey A. Lebedev

  2. Maykop State Technological University, Maykop, The Republic of Adygea, Russian Federation

    Sergey A. Lebedev

  3. Big Data Storage and Analysis Center at the Lomonosov Moscow State University Center for Digital Economy, Moscow, Russian Federation

    Sergey A. Lebedev

  4. P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russian Federation

    Andrey G. Kostianoy

  5. S.Yu. Witte Moscow University, Moscow, Russian Federation

    Andrey G. Kostianoy

  6. Tver State University, Tver, Russian Federation

    Pavel N. Kravchenko

Authors
  1. Sergey A. Lebedev
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  2. Andrey G. Kostianoy
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  3. Pavel N. Kravchenko
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Correspondence to Sergey A. Lebedev .

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Editors and Affiliations

  1. Maykop State Technological University, Maykop, The Republic of Adygea, Russia

    Murat K. Bedanokov

  2. Geophysical Center Russian Academy of Sciences, Moscow, Russia

    Sergey A. Lebedev

  3. P.P. Shirshov Institute of Oceanology Russian Academy of Sciences, Moscow, Russia

    Andrey G. Kostianoy

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Lebedev, S.A., Kostianoy, A.G., Kravchenko, P.N. (2020). Digital Elevation Model of the Republic of Adygea. In: Bedanokov, M.K., Lebedev, S.A., Kostianoy, A.G. (eds) The Republic of Adygea Environment. The Handbook of Environmental Chemistry, vol 106. Springer, Cham. https://doi.org/10.1007/698_2020_656

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