Assessment of forest vegetation potential of reclaimed areas after ilmenite mining using the remote earth sensing method

dc.citation.epage20
dc.citation.issue1
dc.citation.journalTitleЕкологічні проблеми
dc.citation.spage14
dc.citation.volume9
dc.contributor.affiliationZhytomyr Polytechnic State University
dc.contributor.authorShomko, Olha
dc.contributor.authorDavydova, Iryna
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-05-07T09:02:36Z
dc.date.created2024-02-27
dc.date.issued2024-02-27
dc.description.abstractThe mining of ilmenite has irreversible negative environmental impacts on the ecosystem of the area where mining companies operate. First of all, it leads to disturbance of the soil and vegetation layer, changes in the natural landscape, formation of depression sinkholes, which causes changes in water flow and water distribution in the mining area, lowering of groundwater levels, pollution of the atmosphere, soil and water bodies, and loss of species diversity of flora and fauna. In general, the mining process lasts for decades, during which time the territory is subject to irreversible changes and disturbances and requires high-quality restoration after the completion of ilmenite mining. The article suggests a methodology for assessing the forest vegetation potential of soils in areas disturbed by ilmenite mining using remote earth sensing (RES). Based on satellite images and spectral characteristics, we determined the parameters of soil type and moisture, as well as the vegetation and moisture index of the forest vegetation layer The results of the remote earth sensing were compared with the results of laboratory analyzes of soil samples from the territory operated by the branch of the Irshansk Mining and Processing Plant of PJSC UMCC. Normalized Difference Vegetation Index, Normalized Difference Moisture Index, soil type and moisture were calculated and identified using QGIS software from data obtained from free-access satellite images. The results showed that a combination of laboratory and remote sensing methods can be quite effective for studying areas disturbed by mining activities and the state of their recovery after reclamation.
dc.format.extent14-20
dc.format.pages7
dc.identifier.citationShomko O. Assessment of forest vegetation potential of reclaimed areas after ilmenite mining using the remote earth sensing method / Olha Shomko, Iryna Davydova // Environmental Problems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 1. — P. 14–20.
dc.identifier.citationenShomko O. Assessment of forest vegetation potential of reclaimed areas after ilmenite mining using the remote earth sensing method / Olha Shomko, Iryna Davydova // Environmental Problems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 1. — P. 14–20.
dc.identifier.doidoi.org/10.23939/ep2024.01.014
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/64508
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofЕкологічні проблеми, 1 (9), 2024
dc.relation.ispartofEnvironmental Problems, 1 (9), 2024
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dc.relation.referencesenFAO Digital Soil Map of the World (DSMW). (2024). Retrieved from https://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/446ed430-8383-11db-b9b2-000d939bc5d8
dc.relation.referencesenFurdychko, O. I., Drebot, O. I., Kuchma, T. L., & Ilienko, T. V.(2019). Otsinka ekosystemnykh posluh lisiv za danymy dystantsiinoho zonduvannia Zemli. Ahroekolohichnyi zhurnal, 4, 6–16. doi: https://doi.org/10.33730/2077-4893.4.2019.189436.
dc.relation.referencesenIvaniuk, H. (2017) Siri lisovi grunty u riznykh klasyfikatsiinykh systemakh. Visnyk Lvivskoho universytetu. Seria heohrafichna, 51, 120–134. Retrieved from http://nbuv.gov.ua/UJRN/VLNU_Geograf_2017_51_15
dc.relation.referencesenKshetri, T. B. (2018). NDVI, NDBI, Calculating using Landsat 7,8. Retrieved from https://www.researchgate.net/publication/327971920
dc.relation.referencesenLastovicka, J., Svec, P., Paluba, D., Kobliuk, N., Svoboda, J., Hladky, R., & Stych, P. (2020). Sentinel-2 Data in an Evaluation of the Impact of the Disturbances on Forest Vegetation. Remote Sensing, 12(12), 1914. doi: https://doi.org/10.3390/rs12121914
dc.relation.referencesenLavkulich, L. M., & Arocena, J. M. (2011). Luvisolic soils of Canada: Genesis, distribution, andclassifi cation. Sanadian Journal of Soil Science, 91(5), 781–806. doi: https://doi.org/10.4141/cjss2011-014
dc.relation.referencesenMacdonald, S. E., Landhäusser, S. M., Skousen, J., Franklin, J., Frouz, J., Hall, S., Jacobs, D. F., & Quideau, S. (2015). Forest restoration following surface mining disturbance: challenges and solutions. New Forests, 46, 703–732. doi: https://doi.org/10.1007/s11056-015-9506-4
dc.relation.referencesenRoy, D. P., Kovalskyy, V., Zhang, H. K., Vermote, E. F., Yan, L., Kumar, S. S., & Egorov, A. (2016). Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sensing of Environment, 185, 57–70. doi: https://doi.org/10.1016/j.rse.2015.12.024
dc.relation.referencesenPankiv, Z. P. (2017). Grunty Ukrainy: navchalno-metodychnyi posibnyk. Lviv: LNU imeni Avana Franka.
dc.relation.referencesenShao, Y, Xu, Q, & Wei, X. (2023). Progress of Mine Land Reclamation and Ecological Restoration Research Based on Bibliometric Analysis. Sustainability, 15(13), 10458. doi: https://doi.org/10.3390/su151310458
dc.relation.referencesenShomko, O. M., & Davydova, I. V. (2022). Fizyko-mekhanichnyi sklad gruntiv rekultyvovanykh terytorii pislia vydobuvannia ilmenitu na Zhytomyrskomu Polissi. Tekhnichna inzheneria, 1(89), 166–175. doi: https://doi.org/10.26642/ten-2022-1(89)-166-175
dc.relation.referencesenSobue, S., Tochigi, Y., Kawamura, K., Ikehata, Y., Segami, G., Sugita, N., Hamamoto, K., & Kuroiwa, K. (2023). Jaxa earth observation dashboard with COG and WMS/WMTSS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-4/W7-2023, 209–216. doi: https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-209-2023
dc.relation.referencesenSoil Classification Working Group (1998). The Canadian System of Soil Classification, 3rd ed. Agriculture and Agri Food Canada Publication, Ottawa.
dc.relation.urihttps://doi.org/10.1080/00207233.2022.2152254
dc.relation.urihttps://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/446ed430-8383-11db-b9b2-000d939bc5d8
dc.relation.urihttps://doi.org/10.33730/2077-4893.4.2019.189436
dc.relation.urihttp://nbuv.gov.ua/UJRN/VLNU_Geograf_2017_51_15
dc.relation.urihttps://www.researchgate.net/publication/327971920
dc.relation.urihttps://doi.org/10.3390/rs12121914
dc.relation.urihttps://doi.org/10.4141/cjss2011-014
dc.relation.urihttps://doi.org/10.1007/s11056-015-9506-4
dc.relation.urihttps://doi.org/10.1016/j.rse.2015.12.024
dc.relation.urihttps://doi.org/10.3390/su151310458
dc.relation.urihttps://doi.org/10.26642/ten-2022-1(89)-166-175
dc.relation.urihttps://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-209-2023
dc.rights.holder© Національний університет “Львівська політехніка”, 2024
dc.rights.holder© Shomko O., Davydova I., 2024
dc.subjectRES
dc.subjectsoil type
dc.subjectmoisture
dc.subjectNDVI
dc.subjectNDMI
dc.titleAssessment of forest vegetation potential of reclaimed areas after ilmenite mining using the remote earth sensing method
dc.typeArticle

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