Analysis of Land Use in the Seaside Regions of Ukraine in 2017—2022 Based on Satellite Information
DOI:
https://doi.org/10.15407/scine21.01.050Keywords:
land use, land cover, natural assets, land resource management, remote sensing of the Earth, satellite data, deep learning, convolutional neural networksAbstract
Introduction. Land is recognized as a primary national asset under the special protection of the state, as mandated by Ukrainian law. It serves as the foremost natural resource, a vital foundation for human life and activity, and underpins the establishment and development of all sectors of the national economy. Therefore, an eff ectively organized, sustainable economy is unattainable without the rational utilization and protection of land resources.
Problem Statement. Research on land use in Ukraine’s coastal regions has become especially relevant. Since parts of these areas have been under occupation since 2014, understanding the spatial-temporal variability of land use in these regions presents significant challenges for Ukraine.
Purpose. To analyze land use in the coastal regions of Ukraine using satellite data to assess spatio-temporal changes.
Materials and Methods. This research utilized land use/land cover (LULC) mapping based on satellite data from Sentinel-2, analyzed through deep learning models using artificial neural networks.
Results. The spatial distribution of land use in Ukraine’s coastal regions in 2022 was thoroughly analyzed. Additionally, the spatio-temporal variability of land use from 2017 to 2022 was assessed, revealing distinctive patterns in the spatial distribution of various land cover classes. The findings show that the innovative approaches to LULC mapping and the resulting data can be effectively applied to land resource management in Ukraine.
Conclusions. The LULC mapping approach demonstrates significant potential for interdisciplinary research and applied work in natural resource management and territorial planning at both the national and regional levels. Moreover, these innovative LULC mapping methods present a robust tool for identifying and understanding the scale of natural, anthropogenic, and military-induced emergencies.
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References
Constitution of Ukraine: The Official Bulletin of the Verkhovna Rada of Ukraine. 1996. No. 30. URL: https://zakon.rada. gov.ua/laws/show/254к/96-вр#Text (Last accessed: 29.08.2023) [in Ukrainian]
Garnaga, O. (2011). Theoretical Principles Of Rational Land Use. Ukrainian Journal Ekonomist, 12, 41—44 [in Ukrainian].
Tretiak, A. M. (2006). Land management design: theoretical foundations and territorial land management. Kyiv [in Ukrainian].
Shchuryk, M. V., Danyliuk, H. V. (2014). Ontological and spiritual principles of recreation of prirodoresursnoy of sphere: regional cut. Scientific and information bulletin of the Ivano-Frankivsk University of Law named after King Danylo Halytskyi, 10, 251—258 [in Ukrainian].
Hutorov, O. I. (2010). Economic-ecological assessment of agricultural lands and problems of their sustainable use. Ag ro incom, 1—2—3, 35—40 [in Ukrainian].
Tretiak, A. M., Tretiak, N. A. (2011). Economics and efficiency of land use management in Ukraine. Economics of nature use and environmental protection, 14—24 [in Ukrainian].
Hetman, O., Iermakova, O., Laiko, O., Nikishyna, O. (2019). Ecologization of innovative development of regions on the opinciples of gloсalization. Management Theory and Studies for Rural Business and Infrastructure Development, 41(3), 369—380. https://doi.org/10.15544/mts.2019.30
Petrushenko, М., She vchenko, H., Burkynskyi, B., Khumarova, N. (2019). A game-theoretical model for investment in inclusive recreation and wellness in Ukraine: the regional context. Investment Management and Financial Innovations, 16(4), 382—394. https://dx.doi.org/10.21511/imfi.16(4).2019.32
Burkynskyi, B., Laiko, O., Horiachuk, V., Shlafman, N., Krivtsova, O. (2021). Assessment of the socio-economic and environmental development of a region: A result-oriented approach. Problems and Perspectives in Management, 19(2), 40—56. https://dx.doi.org/10.21511/ppm.19(2).2021.04
Midlen, A. (2021). What is the blue economy? A spatialised governmentality perspective. Maritime Studies, 20, 423—448. https://doi.org/10.1007/s40152-021-00240-3
Germond-Duret, C. (2022). Framing the blue economy: Placelessness, development and sustainability. Development and Change, 53, 308—334. https://doi.org/10.1111/dech.12703.
Hadley, D. (2009). Land use and the coastal zone. Land Use Policy, 26(1), 198—203. https://doi.org/10.1016/j.landusepol.2009.09.014
Wu, T., Barrett, J. (2022). Coastal land use management methodologies under pressure from climate change and population growth. Environmental Management, 70, 827—839. https://doi.org/10.1007/s00267-022-01705-9
Lafortezza, R., Chen, J., Cecil, K. B., Randrup, T. B. (2018). Nature-based solutions for resilient landscapes and cities. Environmental Research, 165, 431—441. https://doi.org/10.1016/j.envres.2017.11.038
Zavar, E., Hagelman, R. R. (2018). Resilient landscapes: The reconstruction of southeastern Connecticut following the 1938 hurricane. Professional Geographer, 70(3), 443—452. https://doi.org/10.1080/00330124.2017.1417138
Kimhi, S., Eshel, Y., Marciano, H., Adini, B. (2023). Impact of the war in Ukraine on resilience, protective, and vulnerability factors. Frontiers in Public Health, 11, 1053940. https://doi.org/10.3389/fpubh.2023.1053940
Kaliraj, S., Chandrasekar, N., Ramachandran, K. K., Srinivas, Y., Saravanan, S. (2017). Coastal landuse and land cover change and transformations of Kanyakumari coast, India using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science, 20(2), 169—185. https://doi.org/10.1016/j.ejrs.2017.04.003
Boucquey, N., St Martin, K., Fairbanks, L., Campbell, L. M., Wise, S. (2019). Ocean data portals: Performing a new infrastructure for ocean governance. Environment and Planning D: Society and Space, 37(3), 484—503. https://doi. org/10.1177/0263775818822829
Vitousek, S., Buscombe, D., Vos, K., Barnard, P., Ritchie, A., Warrick, J. (2023). The future of coastal monitoring through satellite remote sensing. Cambridge Prisms: Coastal Futures, 1, E10. https://doi.org/10.1017/cft.2022.4
Stepanova, Yu. V. (2023). Preservation of the ecological state of the marine coastal zone of Ukraine as a strategic goal of blue growth. Economic Innovations, 25(3(88)), 230—242. https://doi.org/10.31520/ei.2023.25.3(88).230-242
On the approval of the Concept of the State-wide target program for land use and protection: order of the Cabinet of Ministers of Ukraine dated January 19, 2022 No. 70-p. URL: https://zakon.rada.gov.ua/laws/show/70-2022-р#Text (Last accessed: 04.09.2023) [in Ukrainian].
Sryberko, А., Petrushenko, М., Stepanova, Yu. (2023, May). Conceptual principles of natural asset management modeling within blue growth. A collection of theses of reports based on the materials of the International Scientific and Practical Conference: “Theory and Practice of Management” (24—26 May 2023, Lutsk, Ukraine). Lutsk, 239—243 [in Ukrainian].
Sryberko, A. (2019). Calculation of the vertical distribution of water temperature in the Black Sea by satellite data. Ge ographia Technica, 14(2), 97—111. https://doi.org/10.21163/GT_2019.142.09
Venter, Z. S., Barton, D. N., Chakraborty, T., Simensen, T., Singh, G. (2022). Global 10 m Land Use Land Cover Datasets: A Comparison of Dynamic World, World Cover and Esri Land Cover. Remote Sens, 14, 4101. https://doi.org/10.3390/rs14164101
Benhammou, Y., Alcaraz-Segura, D., Guirado, E., Khaldi, R., Achchab, B., Herrera, F., Tabik, S. (2022). Sentinel2GlobalLULC: A Sentinel-2 RGB image tile dataset for global land use/cover mapping with deep learning. Sci. Data, 9, 681. https://doi.org/10.1038/s41597-022-01775-8
ArcGIS Living Atlas of the World. URL: https://livingatlas.arcgis.com/en/home/ (Last accessed: 04.09.2023).
Sentinel-2 10 m Land Use/Land Cover Time Series. URL: https://www.arcgis.com/home/item.html?id=cfcb7609de5f4 78eb7666240902d4d3d (Last accessed: 04.09.2023).
Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., Brumby, S. P. (2021). Global land use / land co ver with Sentinel 2 and deep learning. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (16—11 July, 2021, Brussels, Belgium). Brussel, 4704—4707. https://doi.org/10.1109/IGARSS47720.2021.9553499
ArcGIS Living Atlas of the World. Esri Sentinel-2 Land Cover Explorer. URL: https://www.esri.com/arcgis-blog/ products/product/uncategorized/global-land-cover-updates/ (Last accessed: 08.09.202 3).
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