Features of Visual Decoding of Water Erosion by Remote Sensing Data

  • A. B. Achasov V. N. Karazin Kharkiv National University, 6, Svobody Square, 61022, Kharkiv, Ukraine http://orcid.org/0000-0002-5009-7184
  • А. О. Achasova National Scientific Center «O. N. Sokolovsky Institute of Soil Science and Agrochemistry Research», Tchaikovsky St., 4, 61024, Kharkiv, Ukraine https://orcid.org/0000-0002-6294-2445
Keywords: visual interpretation, remote sensing, soil erosion, linear erosion, buried soil

Abstract

Purpose: analysis of the features of visual decoding of eroded soils and erosion processes according to remote sensing data.

Methods. Remote sensing, field, comparative geographical, historical, cartographic, GIS analysis.

Results. The main attention in the article is paid to the features of visual decoding of linear forms of erosion. Comparative analysis of aerial photographs of 1943 and modern satellite imagery for the Kharkov region shown that in the second half of the 20th century the growth of gullies was almost stopped due to large-scale anti-erosion measures carried out at that time. Currently the main erosion losses occur in sheet erosion and small gully erosion. The article provides a list of decoding features that determine linear forms of erosion in the images. It is shown problems that can arise during automatic decoding. As an example of artifact formations requiring the participation of a human analyst in the decryption process, the so-called "Turkish Wall" is shown, the traces of which can be erroneously diagnosed as a manifestation of linear erosion

Conclusions. Automatic decoding of water erosion processes and an inventory of erosion landforms requires the obligatory monitoring of a qualified analyst to eliminate object identification errors

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Author Biographies

A. B. Achasov, V. N. Karazin Kharkiv National University, 6, Svobody Square, 61022, Kharkiv, Ukraine

DSc (Agriculture), Professor

А. О. Achasova, National Scientific Center «O. N. Sokolovsky Institute of Soil Science and Agrochemistry Research», Tchaikovsky St., 4, 61024, Kharkiv, Ukraine

PhD (Biology), Associate Professor, Senior Researcher of the Laboratory of Soil Protection against Erosion

References

Sartoria, M. Philippidis, G., Ferrari, T., Borrelli, P., Lugato, E., Montanarella, L. & Panagos, P. (2019). A linkage between the biophysical and the economic: Assessing the global market impacts of soil erosion. Land Use Policy. 86. 299-312. https://doi.org/10.1016/j.landusepol.2019.05.014

Аchasova, A. (2020). Modern approaches to environmental and economic estimation of damage from water erosion of soil. Visnyk of V. N. Karazin Kharkiv National University series «Еcоlogy», 22, 8-20. Retrieved from https://doi.org/10.26565/1992-4259-2020-22-01 (in Ukranian).

Outcome document of the Global Symposium on Soil Erosion. (2009). FAO. Rome. Retrieved from http://www.fao.org/3/ca5697en/ca5697en.pdf

Eswaran, H., Lal, R. & Reich, P.F. (2001). Land degradation: an overview. In: Bridges, E.M., Hannam, I.D., Oldeman, L.R., Penning de Vries, F.W.T., Scherr, S.J., Sombatpanit, S. (Eds.), Response to land degradation (pp.20-35). Science Publishers Inc, Enfield, NH, USA.

Balyuk, S. A. & Tovazhnyansky, L. L. (Eds.). (2010). Scientific and applied bases of soil protection from erosion in Ukraine. Kharkiv: NTU "KPI" (in Ukranian).

Panagos, P., Borrelli, P., Poesen, J., Ballabio, C., Lugato, E., Meusburger, K., Montanarella, L. & Alewell, C. (2015). The new assessment of soil loss by water erosion in Europe. Environment Science & Policy, 54, 438–447. https://doi.org/10.1016/j.envsci.2015.08.012

Benavidez, R., Jackson, B., Maxwell, D. & Norton, K. (2018). A review of the (Revised) Universal Soil Loss Equation ((R)USLE): With a view to increasing its global applicability and improving soil loss estimates. Hydrology and Earth System Sciences, 22, 6059–6086. https://doi.org/10.5194/hess-22-6059-2018

Bayramin, U., Denguz, O., Bakan, O., Bayramin, U., Denguz, O., Bakan, O. & Parlak, M. (2003). Soil Erosion Risk Assessment With ICONA Model; Case Study: Beypazari Area. Turkish Journal of Agriculture and Forestry. 27. 105-116.

Luleva, M.I., van de Werff, H., van der Meer, F. & Jetten, V. (2012). Gaps and opportunities in the use of remote sensing for soil erosion assessment. Chemistry: Bulgarian Journal of Science Education, 21 (5), 748-764.

Achasov, A. B., Achasova, A. O., Bulygin, S. Yu., Tikhonenko, D. G. & Astakhov, E. A. (2010). Large-scale mapping of soils by integrated analysis of remote sensing data and digital terrain models. Guidelines. Kharkiv: KhNAU (in Ukranian).

Kuchma, T., Ilienko, T., Syrotenko, O., Tarariko, O., Mynkevych, N. & Mudryk, S. (2013). Guidelines for detection and identification of water erosion in agricultural landscapes according to the data of space survey of high spatial resolution. Kyiv. https://doi.org/10.5281/zenodo.1401255 (in Ukranian).

Seutloali, K.E., Dube, T. & Mutanga, O. (2017). Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei (viewed 06 June 2017). Physics and Chemistry of the Earth. 100, 296-304. https://doi.org/10.1016/j.pce.2016.10.001

Nekos, A. N., Achasov, A. B. & Kochanov, E. O. (2017). Methods of measuring environmental parameters: remote sensing methods. Kharkiv: V. N. Karazin KhNU (in Ukranian).

Beguería, S. (2006). Identifying erosion areas at basin scale using remote sensing data and GIS: a case study in a geologically complex mountain basin in the Spanish Pyrenees. International Journal of Remote SensingInt. 27 (20), 4585-4598. Retrieved from https://www.tandfonline.com/doi/full/10.1080/01431160600735640

Karami, A., Khoorani, A., Noohegar, A., Shamsi, S.R.F. & Moosavi, V. (2015). Gully erosion mapping using object-based and pixel-based image Classification methods. Environmental and Engineering Geoscience, 21 (2), 101–110. https://doi.org/10.2113/gseegeosci.21.2.101

Achasov, A. B., Achasova, A. O., Titenko, A. V., Seliverstov, O. Yu. & Sedov, A. O. (2015). UAV usage for crop estimation. Visnyk of V. N. Karazin Kharkiv National University, series «Еcоlogy», 13, 13-18. Retrieved from https://periodicals.karazin.ua/ecology/article/view/5546 (in Ukranian).

Achasova, A. (2016). Evaluating crop characteristics in the visible range. Retrieved from http://www.50northspatial.org/otsinka-stanu-posiviv/

Achasov, A. B. (2016). Anti-erosion optimization of agrolandscapes: geoinformation approach. Kharkiv: KhNAU Dep. in the State Scientific Library of Ukraine (in Ukranian).

Aerial photography of World War II. Kharkov. Retrieved from http://warfly.ru/?lat=49.983903&lon=36.240807&z=12

Schubert, F. F. & Tuchkov, P. A. (Eds). Military topographic map of the Russian Empire in 1846-1863. M .: 3 versts per inch. Series: XXIV, sheet: 14. Retrieved from http://www.etomesto.ru/shubert-map/24-14/

Museums of "genesis and cartography of soils". (2013). V.V. Dokuchaev Kharkiv National Agrarian University. Retrieved from https://knau.kharkov.ua/muzey-henezusu.html (in Ukranian).

Wheeler, C. (2020). Discovering the context of complex problems. Faces of GIS/esri.com/arcuser. Winter 2020. Retrieved from https://www.esri.com/about/newsroom/arcuser/discovering-the-context-of-complex-problems/

Published
2020-06-03
How to Cite
Achasov, A. B., & AchasovaА. О. (2020). Features of Visual Decoding of Water Erosion by Remote Sensing Data. Man and Environment. Issues of Neoecology, (33), 145-154. https://doi.org/10.26565/1992-4224-2020-33-13