Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 4, pp. 128-137

Application of remote information and GIS technologies to create digital soil map (by the example of the plain and foothill parts of Kabardino-Balkaria)

R.Kh. Tembotov 1 , O.N. Gorobtsova 1 , F.V. Gedgafova 1 , T.S. Uligova 1 , E.M. Khakunova 1 
1 Tembotov Institute of Ecology of Mountain Territories RAS, Nalchik, Russia
Accepted: 28.07.2022
DOI: 10.21046/2070-7401-2022-19-4-128-137
The article shows the effectiveness of applying a methodology for creating digital soil maps that combines the actual material on soils (training sample) and remote sensing data processed using geostatistical methods. The technique was applied to form a model of the structure of the soil cover on the example of the plain-foothill part of Kabardino-Balkaria. Stepwise discriminant analysis was used to process combined data on the spatial dynamics of the properties of various types and subtypes of soils and further modeling. The obtained results indicate that all 11 studied soil subtypes are well recognized in the created model. The recognition quality is 74–100 %, and the overall quality of the discriminant model is 85 %, which allows us to consider the created digital soil map as quite adequate. Unlike conventional digitized versions of paper soil maps, the created information product is a cartographic model, which is a database that can be updated and supplemented, thereby increasing its reliability. Digital version of the traditional soil map, based on a combination of field data and remote information, is an effective tool for land management, development of agricultural technologies and soil protection measures.
Keywords: digital soil map, discriminant analysis, remote sensing data, digital elevation model, bioclimatic characteristics
Full text

References:

  1. Vekshina V. N., The development of digital models of the soil cover in the western part of Bol’shezemel’skaya tundra, Byulleten’ Pochvennogo instituta imeni V. V. Dokuchaeva, 2019, Vol. 99, pp. 21–46 (in Russian), DOI: 10.19047/0136-1694-2019-99-21-46.
  2. Gavrilyuk E. A., Ershov D. V., Methodology of joint processing of multi-season Landsat-TM images and creation of a map of terrestrial ecosystems of the Moscow region based on them, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 4, pp. 15–23 (in Russian).
  3. Zheltukhin A. S., Puzachenko Yu. G., Sandlerskii R. B., The quality of animal habitats estimated from track activity and remote sensing data, Contemporary Problems of Ecology, 2009, Vol. 2, No. 3, pp. 176–184.
  4. Klassifikatsiya i diagnostika pochv SSSR (Classification and diagnostics of soils of the USSR), Moscow: Kolos, 1977, 280 p. (in Russian).
  5. Kozlov D. N., Traditions and innovations in large-scale soil cartography, In: Tsifrovaya pochvennaya kartografiya: teoreticheskie i eksperimental’nye issledovaniya, Moscow: Pochvennyi institut im. V. V. Dokuchaeva, 2012, pp. 35–57 (in Russian).
  6. Konyushkova M. V., Kozlov D. N., Automated analysis of the geographic distribution of chernozem-like dark-colored soils in the Northern Caspian lowland on the basis of space-borne imagery (the case study at the Dzhanybek research station), Aridnye ekosistemy, 2010, Vol. 16, No. 5(45), pp. 46–56 (in Russian).
  7. Krenke A. N., Otobrazhenie faktorov formirovaniya komponentov landshafta na osnove tematicheskikh kart, distantsionnoi informatsii i trekhmernoi modeli rel’efa: Diss. kand. biol. nauk (Mapping factors of the formation of landscape components based on thematic maps, remote information and a three-dimensional relief model, Cand. biol. sci. thesis), Moscow: IG RAN, 2011, 128 p. (in Russian).
  8. Krenke A. N., Puzachenko Yu. G., Building a landscape cover map based on remote information, Ekologicheskoe planirovanie i upravlenie, 2008, Vol. 2, No. 7, pp. 10–25 (in Russian).
  9. Molchanov E. N., Pochvennyi pokrov Kabardino-Balkarskoi ASSR: Poyasnitel’naya zapiska k Pochvennoi karte Kabardino-Balkarskoi ASSR (Soil cover of the Kabardino-Balkarian ASSR: Explanatory note to the Soil Map of the Kabardino-Balkarian ASSR), Moscow: GUGK SSSR, 1990, 22 p. (in Russian).
  10. Popov S. Yu., Experience of creating a geobotanical map using discriminant analysis of field vegetation description and remote sensing data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 1, pp. 25–35 (in Russian), DOI: 10.21046/2070-7401-2016-13-1-25-35.
  11. Puzachenko M. Yu., Puzachenko Yu. G., Kozlov D. N., Fedyaeva M. V., The mapping of the thickness of organic matter and humus horizons of soils and bogs in the southern taiga (Valdai Hills) on the basis of dugital elevation model and remote sensing data (Landsat-7), Issledovanie Zemli iz kosmosa, 2006, No. 4, pp. 70–79 (in Russian).
  12. Puzachenko Yu. G., Onufrenya I. A., Aleshchenko G. M., Analyses of hierarchic organization of the relief, Izvestiya Rossiiskoi akademii nauk. Ser. geograficheskaya, 2002, No. 4, pp. 29–38 (in Russian).
  13. Puzachenko Yu. G., Zheltukhin A. S., Sandlerskiy R. B., Analyzing spatial-temporal dynamics of the ecological niche: a marten (Martes Martes) population case study, Zhurnal obshchei biologii, 2010, Vol. 71, No. 6, pp. 467–487 (in Russian).
  14. Razumov V. V., Kurdanov Kh. A., Razumova L. A., Krokhmal A. G., Batyrbekova L. M., Ekosistemy gor Tsentral’nogo Kavkaza i zdorov’e cheloveka (Ecosystems of the Central Caucasus mountains and human health), Moscow: Ileksa, Stavropol: Stavropol’servisshkola, 2003, 448 p. (in Russian).
  15. Rukhovich D. I., Vil’chevskaya E. V., Kalinina N. V., Koroleva P. V., Wagner V. B., Problems of using digitized thematic maps on the territory of the former Soviet Union upon the creation of the “Soils of Russia” geographic information system, Pochvovedenie, 2011, No. 9, pp. 1043–1045 (in Russian).
  16. Savin I. Yu., Usage of satellite data for soil mapping: modern tendencies and problems, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 6, pp. 29–39 (in Russian), DOI: 10.21046/2070-7401-2016-13-6-29-39.
  17. Sandlerskii R. B., Termodinamicheskie kharakteristiki yuzhno-taezhnykh biogeotsenozov na osnove distantsionnoi informatsii (yug Valdaiskoi vozvyshennosti, Tsentral’no-lesnoi zapovednik): Dis. kand. biol. nauk (Thermodynamic characteristics of Southern Taiga biogeocenoses based on remote information (south of the Valdai Upland, Central Forest Reserve), Cand. biol. sci. thesis), Moscow: IPEE RAN, 2013, 269 p. (in Russian).
  18. Sokolov V. E., Tembotov A. K., Pozvonochnye Kavkaza. Mlekopitayushchie. Nasekomoyadnye (Vertebrates of the Caucasus. Mammals. Insectivores), Moscow: Nauka, 1989, 547 p. (in Russian).
  19. Ali R. R., Kotb M. M., Use of Satellite Data and GIS for Soil Mapping and Capability Assessment, Nature and Science, 2010, Issue 8, No. 8, pp. 104–115.
  20. Boettinger J., Ramsey R., Bodily J., Cole N., Kienast-Brown S., Nield S., Saunders A., Stum A., Landsat spectral data for digital soil mapping, A. E. Hartemink, A. McBratney, M. Mendonça-Santos (eds.), 2008, pp. 193–202, DOI: 10.1007/978-1-4020-8592-5_16.
  21. Browning D. M., Duniway M. C., Digital Soil Mapping in the Absence of Field Training Data: A Case Study Using Terrain Attributes and Semiautomated Soil Signature Derivation to Distinguish Ecological Potential, Applied and Environmental Soil Science, 2011, Art. No. 421904, 12 p., DOI: 10.1155/2011/421904.
  22. Elbeih S. F., Evaluation of agricultural expansion areas in the Egyptian deserts: A review using remote sensing and GIS, Egyptian J. Remote Sensing and Space Science, 2021, Vol. 24, Issue 3, No. 2, pp. 889–906, DOI: 10.1016/j.ejrs.2021.10.004.
  23. Fick S., Hijmans R., WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas, Intern. J. Climatology, 2017, Vol. 37, No. 2, DOI: 10.1002/joc.5086.
  24. Liping Y., Xingmin M., Xiaoqiang Z., SRTM DEM and its application advances, Intern. J. Remote Sensing, 2011, Vol. 32, No. 14, pp. 3875–3896, DOI: 10.1080/01431161003786016.
  25. Minasny B., Digital soil mapping: A brief history and some lessons, Geoderma, 2016, Vol. 264, pp. 301–311, DOI: 10.1016/j.geoderma.2015.07.017.
  26. Puzachenko Yu. G., Sandlersky R. B., Svirejeva-Hopkins A., Estimation of thermodynamic parameters of the biosphere, based on remote sensing, Ecological Modelling, 2011, Vol. 222, No. 16, pp. 2913–2923, DOI: 10.1016/j.ecolmodel.2011.05.011.
  27. Saunders A. M., Boettinger J. L., Incorporating classification trees into a pedogenic understanding raster classification methodology, Green River Basin, Wyoming, USA, Digital Soil Mapping: An Introductory Perspective, Amsterdam: Elsevier, 2007, pp. 389–399.