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 Number 4 Number 5
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, 2021, Vol. 18, No. 3, pp. 214-225

Assessment of vegetation cover flooding in the republics of Mari El and Chuvashia in case of Cheboksary Reservoir rise to a mark of 68 m with the use of remote sensing

O.N. Vorobiev 1 , E.A. Kurbanov 1 
1 Volga State University of Technology, Yoshkar-Ola, Russia
Accepted: 02.06.2021
DOI: 10.21046/2070-7401-2021-18-3-214-225
Construction of hydroelectric dams in river basins is an alternative option to generate “clean” energy, which is demanded in domestic and international markets. On the other hand, this type of projects negatively affects the riparian vegetation ecosystems. The paper evaluates potential loss of forest ecosystems along the Cheboksary Reservoir with the use of Sentinel-2 satellite imagery and DEM (Digital Elevation Model) in case of a possible rise of Cheboksary Dam’s water level from 63 m to the initially designed 68 m. The study area includes vegetation cover along the right and left banks of the Volga River, taking into account its bed’s width in the borders of the republics of Mari El and Chuvashia in 2020. We used Isodata unsupervised classification of satellite images for the assessment of land cover on the study area. Identification of 8 land (vegetation) cover classes on the thematic map was carried out on the basis of the available forest inventory and field research data, gathered in the study area in 2012–2019. Evaluation of the land cover classes by the Jeffreys – Matusita distance showed their high spectral separability. Overall accuracy of the 2020 thematic map was 0.88. The classification results of the possible flooded territory showed that forest stands (pine 6.8 %, birch 27.5 % and mixed deciduous 27.6 %) can be lost to a greater extent in terms of area. This is followed by young stand/shrubs (18.6 %) and water bodies (10.5 %). In case Cheboksary Dam’s water level rises to 68 m, Mari El may lose 4.5 times more lands than Chuvashia. The research results can be used for regional assessments (environmental, social and economic) of the consequences of a possible increase in the level of the Cheboksary Reservoir.
Keywords: Cheboksary Reservoir, forest ecosystems, Sentinel-2, DEM, NDWI, Isodata
Full text

References:

  1. Buzin V. A., Goroshkova N. I., Strizhenok A. V., Maximum ICE-JAM water levels on the northern rivers of Russia under conditions of climate change and anthropogenic impact on the ice jamming process, Russian Meteorology and Hydrology, 2014, Vol. 39, No. 12, pp. 823–827.
  2. Voitko P. F., Use of Mari El republic forests for building and exploitation of artificial water objects, Vestnik Mariiskogo gosudarstvennogo universiteta. Ser.: Les. Ekologiya. Prirodopol’zovanie, 2009, No. 3, pp. 75–83 (in Russian).
  3. Vorobiev O. N., Kurbanov E. A., Polevshchikova Yu. A., Lezhnin S. A., Prostranstvenno-vremennoi analiz dinamiki lesnogo pokrova v Srednem Povolzh’e po sputnikovym dannym (Spatio-temporal analyses of forest cover dynamics in Middle Volga region on the base of satellite data), Kurbanov E. A. (ed.), Yoshkar-Ola: Volgatech, 2019, 200 p. (in Russian).
  4. Zharko V. O., Bartalev S. A., Egorov V. A., Investigation of forest growing stock volume estimation possibilities over Russian Primorsky Krai region using Proba-V satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 1, pp. 157–168 (in Russian), DOI: 10.21046/2070-7401-2018-15-1-157-168.
  5. Kurbanov E. A., Vorob’ev O. N., Distantsionnye metody v lesnom khozyaistve (Remote sensing in forestry), Yoshkar-Ola: PGTU, 2020, 266 p. (in Russian).
  6. Kurbanov E. A., Vorob’ev O. N., Retrospective analysis of vegetation cover loss in Republics of Mari El and Chuvashia after flooding of Cheboksarskaya dam from Landsat/MSS data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 1, pp. 127–137 (in Russian), DOI: 10.21046/2070-7401-2021-18-1-127-137.
  7. Kurbatova I. E., Space monitoring of the coastal zone of the Krasnodar reservoir, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2008, Vol. 2, Issue 5, pp. 523–528 (in Russian).
  8. Lyushvin P. V., Zyryanov V. N., Egorov S. N., Kukharskii A. V., Polonskii V. F., Korshenko A. N., Lobov A. L., Space monitoring of the coastal zone of the Krasnodar reservoir impact of peak releases from the Volgograd hydrological power on the ecology of the North-West Caspian, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2006, No. 2, pp. 121–129 (in Russian).
  9. Terekhov A. G., Abayev N. N., Lagutin E. I., Satellite monitoring of the Sardoba Reservoir in Syr Darya River basin (Uzbekistan) before and after a dam collapses on May 1, 2020, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 3, pp. 255–260 (in Russian), DOI: 10.21046/2070-7401-2020-17-3-255-260.
  10. Abarca-Del-Rio R., CrÉtaux J.-F., Berge-Nguyen M., Maisongrande P., Does Lake Titicaca still control the Lake Poopó system water levels? An investigation using satellite altimetry and MODIS data (2000–2009), Remote Sensing Letters, 2012, Vol. 3, pp. 707–714, available at: https://doi.org/10.1080/01431161.2012.667884.
  11. Chuvieco E., Fundamentals of satellite remote sensing: an environmental approach, Second Edition, Boca Raton; London; New York: CRC Press Taylor and Francis, 2016, 468 p.
  12. Cooley S. W., Smith L. C., Stepan L., Mascaro J., Tracking dynamic northern surface water changes with high-frequency planet CubeSat imagery, Remote Sensing, 2017, Vol. 9, No. 12, Art. No. 1306, available at: https://doi.org/10.3390/rs9121306.
  13. Di Baldassarre G., Montanari A., Lins H., Koutsoyiannis D., Brandimarte L., Blöschl G., Flood fatalities in Africa: from diagnosis to mitigation, Geophysical Research Letters, 2010, Vol. 37, Issue 22, Art. No. L22402, available at: https://doi.org/10.1029/2010GL045467.
  14. Feloni E., Mousadis I., Baltas E., Flood vulnerability assessment using a GIS-based multi-criteria approach — The case of Attica region, J. Flood Risk Management, 2019, No. 13, pp. 1–15, available at: https://doi.org/10.1111/jfr3.12563.
  15. Jarihani A. A., Callow J. N., McVicar T. R., Van Niel T. G., Larsen J. R., Satellite-derived Digital Elevation Model (DEM) selection, preparation and correction for hydrodynamic modelling in large, low-gradient and data-sparse catchments, J. Hydrology, 2015, Vol. 524, pp. 489–506, available at: https://doi.org/10.1016/j.jhydrol.2015.02.049.
  16. Macfarlane W. W., Gilbert J. T., Gilbert J. D., Saunders W. C., Hough-Snee N., Hafen C., Wheaton J. M., Bennet S. N., What are the conditions of riparian ecosystems? Identifying impaired floodplain ecosystems across the Western U. S. using the riparian condition assessment (RCA) tool, Environmental Management, 2018, Vol. 62, pp. 548–570, available at: https://doi.org/10.1007/s00267-018-1061-2.
  17. Madsen H., Lawrence D., Lang M., Martinkova M., Kjeldsen T. R., Review of trend analysis and climate change projections of extreme precipitation and floods in Europe, J. Hydrology, 2014, Vol. 519, pp. 3634–3650, available at: https://doi.org/10.1016/j.jhydrol.2014.11.003.
  18. McFeeters S. K., The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, Intern. J. Remote Sensing, 1996, Vol. 17, No. 7, pp. 1425–1432, available at: https://doi.org/10.1080/01431169608948714.
  19. Momm H. G., Bingner R. L., Yuan Y., Locke M. A., Wells R. R., Spatial characterization of riparian buffer effects on sediment loads from watershed systems, J. Environmental Quality, 2014, Vol. 43, No. 5, pp. 1736–1753, available at: https://doi.org/10.2134/jeq2013.10.0413.
  20. Ricci G. F., Romano G., Leronni V., Gentile F., Effect of check dams on riparian vegetation cover: A multiscale approach based on field measurements and satellite images for Leaf Area Index assessment, Science of the Total Environment, 2019, Vol. 657, No. 20, pp. 827–838, available at: https://doi.org/10.1016/j.scitotenv.2018.12.081.
  21. Rokni K., Ahmad A., Selamat A., Hazini S., Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery, Remote Sensing, 2014, Vol. 6, pp. 4173–4189, available at: https://doi.org/10.3390/rs6054173.
  22. Shawky M., Moussa A., Hassan Q. K., El-Sheimy N., Pixel-based geometric assessment of channel networks/orders derived from Global Spaceborne Digital Elevation Models, Remote Sensing, 2019, Vol. 11, No. 3, Art. No. 235, available at: https://doi.org/10.3390/rs11030235.
  23. Shi W., Wang B., Tian Y., Accuracy analysis of Digital Elevation Model relating to spatial resolution and terrain slope by Bilinear Interpolation, Mathematical Geosciences, 2014, Vol. 46, pp. 445–481, available at: https://doi.org/10.1007/s11004-013-9508-8.
  24. Stanislawski L. V., Survila K., Wendel J., Liu Y., Buttenfield B. P., An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions, Cartography and Geographic Information Science, 2018, Vol. 45, No. 4, pp. 319–328, available at: https://doi.org/10.1080/15230406.2017.1337524.
  25. Vaze J., Teng J., Spencer G., Impact of DEM accuracy and resolution on topographic indices, Environmental Modelling and Software, 2010, Vol. 25, pp. 1086–1098, available at: https://doi.org/10.1016/j.envsoft.2010.03.014.