Usage of the earth remote sensing data for the assessment of surface water area dynamics on the basis of Iziaslav district of Khmelnytsky region, Ukraine

dc.citation.epage58
dc.citation.issue91
dc.citation.journalTitleГеодезія, картографія і аерофотознімання
dc.citation.spage51
dc.contributor.affiliationЖитомирський національний агроекологічний університет
dc.contributor.affiliationІнститут сільського господарства Полісся НААНУ
dc.contributor.affiliationPolissia National University
dc.contributor.affiliationInstitute for Agriculture of Polissia NAAS
dc.contributor.authorДребот, О. В.
dc.contributor.authorЗубова, О. В.
dc.contributor.authorХант, Г. О.
dc.contributor.authorЛук’яненко, О. П.
dc.contributor.authorЧерняк, Я. В.
dc.contributor.authorСавчук, О. І.
dc.contributor.authorDrebot, O. V.
dc.contributor.authorZubova, O. V.
dc.contributor.authorKhant, G. O.
dc.contributor.authorLukianenko, O. P.
dc.contributor.authorCherniak, Ya. V.
dc.contributor.authorSavchuk, O. I.
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-03-02T08:01:40Z
dc.date.available2023-03-02T08:01:40Z
dc.date.created2020-03-12
dc.date.issued2020-03-12
dc.description.abstractВстановлено, що проблема зникнення відкритих водойм та використання даних дистанційного зондування землі для їх моніторингу є актуальною та слабко висвітленою у сучасній вітчизняній та зарубіжній науковій літературі. Також визначено необхідність комплексного методичного підходу її вирішення. Метою досліджень є вивчення динаміки площ поверхневих вод протягом тривалого періоду часу в межах Ізяславського району Хмельницької області на основі програмного аналізу космічних знімків та результатів натурних обстежень ключових дослідних ділянок. Використано методику обробки растрових космічних знімків за допомогою програмного забезпечення QGIS. Проведено обстеження в натурі (на місцевості) зниклих водойм станом на 1975, 1989, 2001, 2018 роки. Виконано збір та аналіз багатоспектральних знімків дистанційного зондування землі супутником Landsat станом на 1975, 1984, 1989, 2001, 2018 роки в межах досліджуваної території. Встановлено кількість доступних знімків, кількість знімків, придатних до використання для дослідження, а також кількість якісних знімків із хмарністю <3 %. Виконано спектральний аналіз території району за допомогою встановлених показників натурних обстежень та програмного забезпечення QGIS. На основі розрахунків спектральних індексів NDWI та NDTI сформовано картосхеми, за якими отримано наявні площі водних поверхонь. Встановлено порогові значення спектральних індексів для класифікації складових растрового зображення досліджуваної території. Вивчено зміну площ поверхневих замкнутих водних об’єктів протягом 1975–2018 років. Визначено, що загальна площа водного плеса водних об’єктів зменшилась із 2933 га до 1499 га, на 48 %. Встановлено залежність впливу температурного фактору на площу поверхневих вод. Дослідження виконано на основі багаторічних даних за допомогою сучасних методів обробки космічних знімків. Представлені результати дослідження можна використати для подальшого моніторингу території та розширення досліджень у межах інших адміністративно-територіальних одиниць, зокрема для формування рішень щодо використання земельного ресурсу, розроблення стратегічних напрямів подолання екологічних проблем землекористування, встановлення критичних індикаторів землекористування в умовах змін клімату, моніторингу стану прибережних захисних смуг та охоронних зон водних об’єктів.
dc.description.abstractIt’s been established that the problem of disappearing of open water body and the use of Earth remote sensing data for their monitoring is relevant and poorly covered in current Ukrainian and foreign scientific studies. The necessity of complex solution method has been also determined. The purpose of this paper is to study the dynamics of surface water area over a 45-year period (over a long period of time) across the Iziaslav district of Khmelnytsky on the basis of programming analysis of satellite imagery and the results from field surveys at key research sites. In this study, the freely available QGIS software was used to process satellite imagery. Field surveys (implied on the ground) took place at water bodies which disappeared in 1975, 1989, 2001, 2018. Multispectral LANDSAT imagery of remote sensing from 1975, 1984, 1989, 2001, 2018 were acquired and analyzed across the study region. Highquality images with cloud coverage of <3 % have been selected to support this research, as well as the quantity of all available images. Spectral analysis of the district territory has been performed with the help of special indicators of field surveys and QGIS software. The mapping of available water surface areas has been performed on the basis of the calculations of the spectral indices of NDWI and NDTI. Threshold values of the spectral indices for the classification of raster image components of the studied area are determined. Total changes in open water surface area between 1975 and 2018 have been quantified. It has been noted that total surface water area has decreased from 2933 hectares to 1499 hectares, a decrease of 48 %. The impact of warmer air temperatures on disappearing water bodies has been specified. The research has been conducted on the basis of long-term data with the help of modern methods of satellite imagery processing. The results of the given research can be used for further territory monitoring and further researches within other administrative-territorial units, in particular for making decisions on land use, developing strategic directions of overcoming environmental problems of land use, setting threshold indicators of land use in climate changing conditions, coastal and water bodies buffer zones monitoring.
dc.format.extent51-58
dc.format.pages8
dc.identifier.citationUsage of the earth remote sensing data for the assessment of surface water area dynamics on the basis of Iziaslav district of Khmelnytsky region, Ukraine / O. V. Drebot, O. V. Zubova, G. O. Khant, O. P. Lukianenko, Ya. V. Cherniak, O. I. Savchuk // Geodesy, cartography and aerial photography. — Lviv : Lviv Politechnic Publishing House, 2020. — No 91. — P. 51–58.
dc.identifier.citationenUsage of the earth remote sensing data for the assessment of surface water area dynamics on the basis of Iziaslav district of Khmelnytsky region, Ukraine / O. V. Drebot, O. V. Zubova, G. O. Khant, O. P. Lukianenko, Ya. V. Cherniak, O. I. Savchuk // Geodesy, cartography and aerial photography. — Lviv : Lviv Politechnic Publishing House, 2020. — No 91. — P. 51–58.
dc.identifier.doidoi.org/10.23939/istcgcap2020.91.051
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/57447
dc.language.isoen
dc.publisherВидавництво Національного університету “Львівська політехніка”
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofГеодезія, картографія і аерофотознімання, 91, 2020
dc.relation.ispartofGeodesy, cartography and aerial photography, 91, 2020
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dc.relation.referencesena Landsat 8 scene of Nepal. Sensors, 18(8), 2580. DOI: 10.3390/s18082580. Retrieved from
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dc.relation.referencesenLower Mekong River Basin. Remote Sensing, 11(23), 2872.
dc.relation.referencesenAnand, A., Krishnan, P., Kantharajan, G., & Babu, D. E.
dc.relation.referencesen(2020). Assessing the water spread area available for
dc.relation.referencesenfish culture and fish production potential in inland lentic
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dc.relation.referencesenhttp://www.sciencedirect.com/science/article/pii/S2352938519301272 (Accessed: 04.12.2019).
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dc.relation.referencesenDescription of the data array of daily air
dc.relation.referencesentemperature and precipitation at meteorological
dc.relation.referencesenstations in Russia and in the former USSR (TTTR).
dc.relation.referencesen(in Russian). Retrieved from http://meteo.ru/data/162-temperature-precipitation#opisanie-massivadannykh. (Accessed: 29.01.2020).
dc.relation.referencesenBurshtynska, Kh., Malanii, O., & Shevchuk, V. (2010).
dc.relation.referencesenMonitoring of deformation processes of the river
dc.relation.referencesenbeds. Modern achievements of geodetic science and
dc.relation.referencesenproduction, 1(19), 216–226. UDK 528.92. (in Ukrainian).
dc.relation.referencesenCole, C. J., Friesen, B. A., Wilson, E. M., Wilds, S. R.,
dc.relation.referencesen& Noble, S. M. (2015). Use of satellite images to
dc.relation.referencesendetermine surface-water cover during the flood
dc.relation.referencesenevent of September 13, 2013, in Lyons and western
dc.relation.referencesenLongmont, Colorado (No. 2015–1042). US
dc.relation.referencesenGeological Survey. DOI: 10.3133/ofr20151042/.
dc.relation.referencesenRetrieved from https://pubs.er.usgs.gov/publication/ofr20151042 (Accessed: 28.11.2019).
dc.relation.referencesenCrist, E. P., & Cicone, R. C. (1984). A physically-based
dc.relation.referencesentransformation of Thematic Mapper data – The
dc.relation.referencesenTM Tasseled Cap. IEEE Transactions on
dc.relation.referencesenGeoscience and Remote sensing, (3), 256–263.
dc.relation.referencesenDOI: 10.1109/TGRS.1984.350619. Retrieved from
dc.relation.referencesenhttps://ieeexplore.ieee.org/document/4157507
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dc.relation.referencesenDecree of the Cabinet of Ministers of Ukraine (2017).
dc.relation.referencesenOn Approving the Concept of State Climate Change
dc.relation.referencesenPolicy Implementation until 2030 of 6 December 2017 # 878-r. Uryadovij portal. (in Ukrainian).
dc.relation.referencesenRetrieved from https://www.kmu.gov.ua/npas/249573705 . (Accessed: 21.12.2019).
dc.relation.referencesenDrebot, O., Kudryk, A. & Lukianenko O. (2018).
dc.relation.referencesenMethodological framework for data generation in a
dc.relation.referencesenGIS-environment during agricultural land area
dc.relation.referencesenmanagement based on the landscape approach.
dc.relation.referencesenGeodesy, Cartography and Aeriel Photography, 87, 58–64. DOI: 10.23939/istcgcap2018.01.058.
dc.relation.referencesenEl-Asmar, H. M., Hereher, M. E., & El Kafrawy, S. B. (2013). Surface area change detection of the Burullus
dc.relation.referencesenLagoon, North of the Nile Delta, Egypt, using water
dc.relation.referencesenindices: A remote sensing approach. The Egyptian
dc.relation.referencesenJournal of Remote Sensing and Space Science, 16(1), 119-123. DOI: 10.1016/j.ejrs.2013.04.004
dc.relation.referencesenKagalo, O. O. et al. (2016). Regional scheme of ecological
dc.relation.referencesennetwork formation of Khmelnytsky region. Institute
dc.relation.referencesenof Ecology of the Carpathians NASU. Lviv–
dc.relation.referencesenKhmelnytskyi. 71. (in Ukrainian).
dc.relation.referencesenKhilchevskyi V. K., Hrebin, V. V. (2014). Water Fund
dc.relation.referencesenof Ukraine: artificial reservoirs – reservoirs and
dc.relation.referencesenponds: a guide. Kyiv: Interperes LTD. 164 p. ISBN 978-965-098-2
dc.relation.referencesenKhmelnytskyi Regional State Administration Department
dc.relation.referencesenof Ecology and Natural Resources. (2017).
dc.relation.referencesenEnvironmental condition of Khmelnytskyi
dc.relation.referencesenregion in 2016. Khmelnytskyi. (in Ukrainian).
dc.relation.referencesenRetrieved from https://menr.gov.ua/files/docs/Reg.report/Natsionalna%20dopovid%20Khmelnytska%202016%20rik.pdf. (Accessed: 14.10.2019).
dc.relation.referencesenKozlova, M. V., Tursunova, G. Sh., Gorelic, O. V., &
dc.relation.referencesenZemlyanov, I. V. (2018). The use of remote sensing
dc.relation.referencesendata for studying tundra phytocenoses the example
dc.relation.referencesenof the rivers’ water-protection zones of the Nenets
dc.relation.referencesenAutonomous District. Ecosystems: ecology and
dc.relation.referencesendynamics, 2(1). P. 92–110. DOI: 10.24411/2542-2006-2017-10005 (in Russian).
dc.relation.referencesenLacaux, J. P., Tourre, Y. M., Vignolles, C., Ndione, J. A., &
dc.relation.referencesenLafaye, M. (2007). Classification of ponds from
dc.relation.referencesenhigh-spatial resolution remote sensing: Application
dc.relation.referencesento Rift Valley Fever epidemics in Senegal. Remote
dc.relation.referencesenSensing of Environment, 106(1), 66–74. DOI: 10.1016/j.rse.2006.07.012
dc.relation.referencesenMcFeeters, S. K. (1996). The use of the Normalized
dc.relation.referencesenDifference Water Index (NDWI) in the
dc.relation.referencesendelineation of open water features. International
dc.relation.referencesenjournal of remote sensing, 17(7), 1425–1432.
dc.relation.referencesenDOI: 10.1080/01431169608948714.
dc.relation.referencesenMustafa, Y. M., Amin, M. S. M., Lee, T. S., & Shariff,
dc.relation.referencesenA. R. M. (2012). Evaluation of land development
dc.relation.referencesenimpact on a tropical watershed hydrology using
dc.relation.referencesenremote sensing and GIS. Journal of spatial
dc.relation.referencesenhydrology, 5(2).
dc.relation.referencesenShevchuk, S. A., Vyshnevskyi, V. I., & Babii, P. O. (2014). Specification of hydrographic characteristics
dc.relation.referencesenof rivers using remote sensing techniques. Bulletin
dc.relation.referencesenof geodesy and cartography, 5(92), 29-32. UDK 556.5.08 + 556.51. (in Ukrainian).
dc.relation.referencesenSingh, K. V., Setia, R., Sahoo, S., Prasad, A., & Pateriya, B. (2015). Evaluation of NDWI and MNDWI for
dc.relation.referencesenassessment of waterlogging by integrating
dc.relation.referencesendigital elevation model and groundwater level.
dc.relation.referencesenGeocarto International, 30(6), 650–661. DOI: 10.1080/10106049.2014.965757
dc.relation.referencesenXu, H. (2006). Modification of normalized difference
dc.relation.referencesenwater index (NDWI) to enhance open water
dc.relation.referencesenfeatures in remotely sensed imagery. International
dc.relation.referencesenjournal of remote sensing, 27(14), 3025–3033. DOI: 10.1080/014311606005891
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111878/
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S2352938519301272
dc.relation.urihttp://meteo.ru/data/162-temperature-precipitation#описание-массиваданных
dc.relation.urihttps://pubs.er.usgs.gov/publication/ofr20151042
dc.relation.urihttps://ieeexplore.ieee.org/document/4157507
dc.relation.urihttps://www.kmu.gov.ua/npas/249573705
dc.relation.urihttps://menr.gov.ua/files/docs/Reg.report/Національна%20доповідь%20Хмельницька%202016%20рік.pdf
dc.rights.holder© Національний університет “Львівська політехніка”, 2020
dc.subjectдистанційне зондування землі
dc.subjectсупутниковий знімок
dc.subjectіндекс
dc.subjectкартосхема
dc.subjectlandsat
dc.subjectплоща водойм
dc.subjectEarth remote sensing
dc.subjectsatellite image
dc.subjectindex
dc.subjectmap
dc.subjectLandsat
dc.subjectopen water area
dc.subject.udc528.8
dc.titleUsage of the earth remote sensing data for the assessment of surface water area dynamics on the basis of Iziaslav district of Khmelnytsky region, Ukraine
dc.title.alternativeВикористання даних дистанційного зондування Землі для оцінки динаміки площ поверхневих вод на прикладі Ізяславського району Хмельницької області
dc.typeArticle

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