Geoecological Assessment of the Malyi Khingan Ridge Area Using Land Surface Remote Sensing Data
Mining Ecology and Exploitation of The Earth’s Bowels
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Abstract
The spotlight is on the use of Earth remote sensing data in geoecological assessment of the Malyi Khingan Ridge area in the Far East. Based on the analysis of satellite observations over the Sutara gold placer mining range, the time variation of the disturbed land is determined. It is found that natural recovery of bio-geo-cenosis takes an active part in the process. Using the normalized difference vegetation index (NDVI), the behavior and rates of self-healing of the disturbed lands are assessed. Complete recovery of vegetation in gold placer mining areas up to a level comparable with the adjacent territories takes 7 to 10 years.
Keywords
Earth remote sensing satellite images gold placer mining cluster normalized difference vegetation index self-healingPreview
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References
- 1.Bolsunovsky, M.A., Perspective Directions of Space Earth Remote Sensing Development, Geomatika, 2009, no. 2, pp. 12–15.Google Scholar
- 2.Nosenko, Yu.I., Loshkarev, P.A., Joint Spatially Distributed Earth Remote Sensing Information System–problems, solutions, perspectives, P. 1, Geomatika, 2010, no. 3, pp. 35–42.Google Scholar
- 3.Isaev, A.S., Bartalev, S.A., and Lupyan, E.A., Earth Observations from Satellites as a Unique Instrument to Monitor Russia’s Forests, Herald of the Russian Academy of Sciences, 2014, vol. 84, no. 12, pp. 413–419.CrossRefGoogle Scholar
- 4.Zol’nikov, I.D., Balandin, V.A., and Boguslavsky, A.E., Data Bank and Geodata Geo-Environment of Novosibirsk, Engineering and Geological Problems of Urbanized Territories: Int. Conf. Proc., vol. 2, Ekaterinburg: Akva-Press, 2001.Google Scholar
- 5.Oparin, V.N., Potapov, V.P., Giniyatullina, O.L., Andreeva, N.V., Schastlivtsev, E.L., and Bykova, A.A., Evaluation of Dust Pollution of Air in Kuzbass Coal-Mining Areas in Winter by Data of Remote Earth Sensing, J. Min. Sci., 2014, vol. 50, no. 3, pp. 549–558.CrossRefGoogle Scholar
- 6.Fiziko-geograficheskoe raionirovanie SSSR. Kharakteristika regional’nykh edinits (Physical-Geographical Regionalization of the USSR. Regional Units Characteristics), Gvozdetsky, N.A., Ed., Moscow: Izd. MGU, 1968.Google Scholar
- 7.Fetisov, D.M., Anthropogenic Changes of Natural Landscapes in the Russian Part of the Lesser Khingan, Vestn. DVO RAN, 2008, no. 3, pp. 51–57.Google Scholar
- 8.Kapel’kina, L.P., Natural Revegetation and Remediation of Disturbed Lands of the North, Usp. Sovr. Estest., 2012, no. 11 (1), pp. 98–102.Google Scholar
- 9.Borzuchowski, J., Schulz, K., Retrieval of Leaf Area Index (LAI) and Soil Water Content (WC) Using Hyperspectral Remote Sensing Under Controlled Glass House Conditions for Spring Barley and Sugar Beet, Remote Sensing, 2010, vol. 2, no. 7, pp. 1702–1721.CrossRefGoogle Scholar
- 10.Chadra, A.M., Gosh, G.S., Distantsionnoe zondirovanie i geograficheskie informatsionnye sistemy (Remote Sensing and Geographic Information Systems), Moscow: Tekhnosfera, 2008.Google Scholar
- 11.Cherepanov, A.S., Vegetation Indices, Geomatika, 2011, no. 2, pp. 98–102.Google Scholar
- 12.http:/epizodsspace. no-ip.org/bibl/sutyrina/distantsionnoe/sutyrina-distantsionnoe-2013.pdf.Google Scholar
- 13.Mesyats, S.P., Volkova, E.Yu., Fundamental Regulations for the Strategy of Returning the Damaged Lands from Man-Made Landscapes to Biospheric Fund, GIAB, no. S4-13, pp. 3–11.Google Scholar
- 14.Ozaryan, Yu. A., Integrated Assessment of Technogenic Wasteland of Komsomolsk Mining District Using Vega Satellite Service, Sovr. Prob. Dist. Zond. Zem. Kosm., vol. 13, no. 1, pp. 70–78.Google Scholar
- 15.Chibrik, T.S., El’kin, Yu.A., Formirovanie fitotsenozov na narushennykh promyshlennost’yu zemlyakh (Formation of Plant Communities on Disturbed Industry Lands), Sverdlovsk: Izd. Ural. Univer., 1991.Google Scholar
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