GIS-based land-use/land cover change analysis: a case study of Zhytomyr region, Ukraine
DOI:
https://doi.org/10.15407/knit2023.04.024Keywords:
GIS technologies, land cover change, land-use, rural area, urban areaAbstract
Today, the deep and wide implementation of geoinformation technologies in the many fields of human activity is due to the powerful development of three scientific and technical components: statistical, software, technical, and space technologies. In this article, based on GIS technologies, an analysis of the state of land use and its changes in the territory of the Zhytomyr region, as well as the impact of Russian aggression against Ukraine on these processes, was carried out. The structure and the dynamics of the main classes of the land cover of the region for the past 7 years were analyzed, the main causes and consequences of such trends were determined, and the analysis of changes in the land cover was carried out. According to the results of this study, in 2022, 52 % of the territory of the Zhytomyr Region was under forested areas, which consist of two categories: forests and other forested areas. The first category remained unchanged during the studied period since the government system of protection and reproduction of forest resources functions effectively. While the second category significantly decreased due to the fact that firewood is the most available fuel resource for heating buildings, so the population began to harvest wood in the form of felling and clearing old gardens, forested bushes and rivers (irrigation canals), and forest strips. Agriculture of the Zhytomyr Region develops due to extensification. According to Google Dynamic World data, in 2022, 34 % of the territory of the Zhytomyr Region is systematically used for growing agricultural crops. Over the past seven years, there has been a significant increase in cultivated land by 27 %. In the structure of the land cover of the Zhytomyr region, the grass cover is 4.9 %, but it is gradually decreasing. A decrease was observed for all types of territorial communities until 2021 (10 % annually on average), while, in 2022, the decline slowed down significantly in rural and village territorial communities and stopped in urban ones. This dynamic is connected with two factors: 1) part of the gardens of rural households were sown with grass due to the fact that men were mobilized to the Armed Forces of Ukraine as a result of Russian aggression, and growing grass requires less human costs; 2) Russian aggression caused a shortage of certain food products, and their significant increase in price while keeping cattle provides food for the rural household, so, in 2022, most of the offspring from cattle were not sold and left for further maintenance. In turn, the increase in cattle requires more feed, an important component of which is grass.References
Abdelouhed F., Algouti A., Algouti A., Mohammed I., Mourabit Z. (2021). Contribution of GIS and remote sensing in
geological mapping, lineament extractions and hydrothermal alteration minerals mapping using aster satellite images: case
study of central Jebilets-Morocco. Disaster Adv., 14, 15-25.
Abou t local self-government in Ukraine: Law of Ukraine dated May 21, 1997 No. 280/97-VR. (1997) Inform. Verkhovna
Rada of Ukraine, 24 (170).
Adulaimi A. A. A., Pradhan B., Chakraborty S., Alamri A. (2021). Traffic noise modelling using land use regression model
based on machine learning, statistical regression and GIS. Energies, 14 (16), 5095.
https://doi.org/10.3390/en14165095
Bolstad P. (2019). GIS Fundamentals: A first text on Geographic Information Systems. 6th Ed. Ann Arbor: XanEdu. 764.
Brow n C. F., Brumby S. P., Guzder-Williams B., Birch T., Hyde S. B., Mazzariello J., et al. (2022). Dynamic world, near
real-time global 10 m land use land cover mapping. Sci. Data, 9 (1), 1-17.
Buch horn M., Lesiv M., Tsendbazar N.-E., Herold M., Bertels L., Smets B. (2020). Copernicus global land cover layers - collection 2. Remote Sens, 12, 1044.
https://doi.org/10.3390/rs12061044
Cegi elska K., Noszczyk T., Kukulska A., Szylar M., Hernik J., Dixon-Gough R., et al. (2018). Land use and land cover
changes in post-socialist countries: Some observations from Hungary and Poland. Land Use Policy, 78, 1-18.
https://doi.org/10.1016/j.landusepol.2018.06.017
Chen J., Chen J., Liao A., Cao X., Chen L., Chen X., He C., et al. (2015). Global land cover mapping at 30 m resolution: APOK-based operational approach. ISPRS J. Photogramm. Remote Sens., 103, 7-27.
Chen Z., Wang L., Wei A., Gao J., Lu Y., Zhou J. (2019). Land-use change from arable lands to orchards reduced soil erosion and increased nutrient loss in a small catchment. Sci. Total Environment, 648, 1097-1104.
https://doi.org/10.1016/j.scitotenv.2018.08.141
Cons titution of Ukraine (1996, June). URL: https://zakon.rada.gov.ua/laws/show/ ~ 93 ~ 254 %D0 %BA/96- %D0 %B2
%D1 %80#n4603/ (Last accessed: 23.12.2022).
https://doi.org/10.4314/vulnew.v80i1.2
da C unha E. R., Santos C. A. G., da Silva R. M., Bacani V. M., Pott A. (2021). Future scenarios based on a CA-Markov land
use and land cover simulation model for a tropical humid basin in the Cerrado / Atlantic forest ecotone of Brazil. Land Use Policy, 101, 105141.
DeMers M. (2009). Fundamentals of Geographic Information Systems. 4th Ed. NY, Wiley.
Envi ronmental passport of the Zhytomyr region. (2022). Zhytomyr. Regional State Administration, 187. URL: https://cutt.
ly/RVnNFOV (Last accessed: 23.12.2022).
https://doi.org/10.1016/S0262-4079(22)00433-X
Fedo niuk T., Bog M., Orlov O., Appenroth K. J. (2022). Lemna aequinoctialis migrates further into temperate continental
Europe - A new alien aquatic plant for Ukraine. Feddes Repertorium, 133, 305-312. doi:10.1002/fedr.202200001.
https://doi.org/10.1002/fedr.202200001
Fedoniuk T., Borsuk O., Melnychuk T., Zymaroieva A., Pazych V. (2021). Assessment of the consequences of forest fires in
on the territory of the Chornobyl radiation and ecological biosphere reserve. Sci. Horizons, 24 (8), 26-36.
doi:10.48077/scihor.
https://doi.org/10.48077/scihor.24(8).2021.26-36
Fu P., Sun J. (2010). Web GIS: Principles and Applications. Redlands, CA, ESRI Press.
Gash aw T., Tulu T., Argaw M., Worqlul A. W. (2017). Evaluation and prediction of land use/land cover changes in the Andassa watershed, Blue Nile basin, Ethiopia. Environ. Syst. Res., 6, 1-15.
https://doi.org/10.1186/s40068-017-0094-5
Gore lick N., Hancher M., Dixon M., Ilyushchenko S., Thau D., Moore R. (2017). Google Earth engine: Planetary-scale
geospatial analysis for everyone. Remote Sens. Environ., 202, 18-27.
Hera symchuk R., Valerko L., Marteniuk G. (2018). Climate change tendencies on the territory of the city of NovohradVolynskyi in Zhytomyr region. Sci. Horizons, 65 (2), 42-50. https://doi.org/10.33249/2663-2144-2018-65-2-42-50.
https://doi.org/10.33249/2663-2144-2018-65-2-42-50
Hoque M. Z., Islam I., Ahmed M., Hasan S. S., Prodhan F. A. (2022). Spatio-temporal changes of land use land cover and
ecosystem service values in coastal Bangladesh. Egyptian J. Remote Sensing and Space Sci., 25 (1), 173-180.
Horo bets O. V., Yevpak I. I. (2017). Climate change trends in Zhytomyr region. Climatic changes and their consequences
on the territory of Zhytomyr region. Sci. Young. Ecology - 2017: coll. materials of the 13th All-Ukrainian science and practice conf. students, graduate students and young scientists, 153-157 [in Ukrainian].
Javed A., Khan I. (2012). Land use/land cover change due to mining activities in Singrauli industrial belt, Madhya Pradesh
using remote sensing and GIS. J. Environmental Res. and Development, 6 (3A).
Karr a K., Kontgis C., Statman-Weil Z., Mazzariello J. C., Mathis M., Brumby S. P. (2021). Global land use/land cover with
Sentinel 2 and deep learning. NY, USA, IEEE, Manhattan, 4704-4707.
Kuss ul N. M., Shelestov A. Yu., Skakun S. V., Basarab R. M., Yaylimov B. Ya., et al. (2015). Retrospective regional map of
the Earth's cover for Ukraine: Methodology of construction and analysis of results. Space Science and Technology, 21 (3),31-39.
Lenn ert J., Farkas J. Z., Kovács A. D., Molnár A., Módos R., Baka D., Kovács Z. (2020). Measuring and predicting longterm land cover changes in the functional urban area of Budapest. Sustainability, 12, 3331.
https://doi.org/10.3390/su12083331
Maguire D. J., Goodchild M. F., Rhind D. W. (1997). Geographic Information Systems: principles, and applications. Longman
Scientific and Technical, Harlow.
Mark M., Kudakwashe M. (2010). Rate of land-use/land-cover changes in Shurugwi district, Zimbabwe: drivers for change.
J. Sustainable Development in Africa, 12 (3), 107-121.
Mishra V . N., Rai P. K. (2016). A remote sensing aided multi-layer perceptron-Markov chain analysis for land use and land cover change prediction in Patna district (Bihar), India. Arab. J. Geosci., 9, 1-18.
https://doi.org/10.1007/s12517-015-2138-3
Mohanta N. (2021). How many satellites are orbiting the Earth in 2021? Geospatial World, No. 05 (28).
Orlov O. O., Fedoniuk T. P., Iakushenko D. M., Danylyk I. M., Kish R. Y., Zymaroieva A. А., Khant G. А. (2021). Distribution and ecological growth conditions of Utricularia australis R. Br. in Ukraine. J. Water and Land Development, 48 (1-3),
-47.
doi:10.24425/jwld.2021.136144.
Oromia Forest and Wildlife Enterprise (OFWE). Farm Africa and SOS Sahel Ethiopia. Bale mountains eco-region reduction of emission from deforestation and forest degradation (REDD+) Project-Ethiopia. URL: https://s3. amazonaws. com/
CCBA/Projects/Bale_Mountains_Eco-region_Reductions_of_Emissions_from_Deforestation_and_Forest_Degradation_Project/Bale+Mtns+REDD %2B+VCS %2BCCB+Project+Description+version+3. 0 (Last accessed: 23.12.2022).
Otterman J. (1974). Baring high-albedo soils by overgrazing: a hypothesized desertification mechanism. Science, 186 (4163), 531-533.
https://doi.org/10.1126/science.186.4163.531
Parveen S., Basheer J., Praveen B. (2018). A literature review on land use land cover changes. Int. J. Adv. Res., 6 (7), 1-6.
https://doi.org/10.21474/IJAR01/7327
Phiri D., Si mwanda M., Salekin S., Nyirenda V. R., Murayama Y., Ranagalage M. (2020). Sentinel-2 data for land cover/ use mapping: a review. Remote Sens., 12, 2291.
Plugar E., P lugar D., Stakhno N. (2021). Space technologies in achieving the aims of sustainable development. IOP Conference Ser.: Earth and Environmental Sci., 385 (1), 012039.
https://doi.org/10.1088/1755-1315/853/1/012039
Prakasam C. (2010). Land use and land cover change detection through remote sensing approach: A case study of Kodaikanal Taluk, Tamil Nadu. Int. J. Geomatics and Geosci., 1 (2), 150.
Praveen B., Gupta D. (2019). Multispectral-TIR data analysis by split window algorithm for coal fire detection and monitoring. Int. J. Human. and Soc. Sci. Invention, 6, 33-37.
Pyvovar P., Chmil A., Bogonos M., et al. (2021). Agricultural markets in Ukraine: current situation and market outlook until
Publications Office: website. URL: https://data.europa.eu/doi/10.2760/669345 (Last accessed: 23.12.2022).
Pyvovar P., Skydan O., Topolnytskyi P., Prysiazhna T. (2022). Analysis of rural areas of Ukraine on the basis of ESA WorldCover 2020. Sci. Horizons, 25(5), 74-85. https://doi.org/10.48077/scihor.
https://doi.org/10.48077/scihor
Regions of U kraine: Art. collection for 2020: [in 2 parts]. State. Statistics Service of Ukraine, Kyiv (2020).
URL: http://www.ukrstat.gov.ua/ (Last accessed: 23.12.2022) [in Ukrainian].
Sahani N., Ghosh T. (2021). GIS-based spatial prediction of recreational trail susceptibility in protected area of Sikkim Himalaya using logistic regression, decision tree and random forest model. Ecological Informatics, 64, 101352.
https://doi.org/10.1016/j.ecoinf.2021.101352
Sala O. E., Chapin F. S., Armesto J. J., Berlow E., Bloomfield J., Dirzo R., et al. (2000). Global biodiversity scenarios for
the year 2100. Science, 287 (5459), 1770-1774.
Schirpke U., Tasser E. (2021). Trends in ecosystem services across Europe due to land-use/cover changes. Sustainability, 13 (13), 7095.
https://doi.org/10.3390/su13137095
Schramm M., Pebesma E., Milenković M., Foresta L., Dries J., Jacob A., et al. (2021). The OpenEO API-harmonising the
use of Earth observation cloud services using virtual data Cube functionalities. Remote Sensing, 13, 1125.
https://doi.org/10.3390/rs13061125
Siebritz L. A., Desai A., Cooper, A. K., Coetzee S. (2022). The South African spatial data infrastructure - Where are the
Municipalities? Int. J. Spatial Data Infrastructures Res., 15, 143-170.
Skakun S., Ku ssul N., Shelestov A., Lavreniuk M., Kussul O. (2016). Efficiency assessment of multitemporal C-band Radarsat-2 intensity and Landsat-8 surface reflectance satellite imagery for crop classification in Ukraine. IEEE J. Selected
Topics in Applied Earth Observations and Remote Sensing. 9 (8), 3712-3719.
https://doi.org/10.1109/JSTARS.2015.2454297
Skydan O. V., Fedoniuk T. P., Pyvovar P. V., Dankevych V. Y., Dankevych Y. M. (2021). Landscape fire safety management:
the experience of Ukraine and the EU. News Nat. Acad. Sci. Republic of Kazakhstan. Ser. Geology and Techn. Sci., 6 (450),
-132.
doi:10.32014/2021.2518-170X. 128.
Stehman S. V. , Pengra B. W., Horton J. A., Wellington D. F. (2021). Validation of the US geological survey's land change
monitoring, assessment and projection (LCMAP) collection 1.0 annual land cover products 1985-2017. Remote Sens. Environment, 265, 112646.
https://doi.org/10.1016/j.rse.2021.112646
Sulla-Menashe D., Gray J. M., Abercrombie S. P., Friedl M. A. (2019). Hierarchical mapping of annual global land cover
to present: The MODIS collection 6 land cover product. Remote Sens. Environ., 222, 183-194.
Talukdar S., Singha P., Mahato S., Praveen B., Rahman A. (2020). Dynamics of ecosystem services (ESs) in response to
land use land cover (LU/LC) changes in the lower Gangetic plain of India. Ecological Indicators, 112, 106-121.
Trimble S. W. , Crosson P. (2000). US soil erosion rates - myth and reality. Science, 289 (5477), 248-250.
https://doi.org/10.1126/science.289.5477.248
Venkatesan A., Lowenthal J., Prem P., Vidaurri M. (2020). The impact of satellite constellations on space as an ancestral global commons. Nature Astron., 4, 1043-1048.
https://doi.org/10.1038/s41550-020-01238-3
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 Sensing, 14 (16), 4101.
https://doi.org/10.3390/rs14164101
Viana C. M., Girão I., Rocha J. (2019). Long-term satellite image time-series for land use/land cover change detection using refined open-source data in a rural region. Remote Sensing, 11 (9), 1104.
https://doi.org/10.3390/rs11091104
Vitousek P. M., Mooney H. A., Lubchenco J., Melillo J. M. (1997). Human domination of Earth's ecosystems. Science, 277
https://doi.org/10.1126/science.277.5325.494
(5325), 494-499.
Worboys M., Duckham M. (2004). GIS: a computing perspective. Boca Raton, CRC Press.
https://doi.org/10.4324/9780203481554
Wubie M. A., Assen M., Nicolau M. D. (2016). Patterns, causes and consequences of land use / cover dynamics in the Gumara watershed of lake Tana basin, Northwestern Ethiopia. Environ. Syst. Res., 5, 1-12.
https://doi.org/10.1186/s40068-016-0058-1
Yailymov B. Ya. (2016). Avtomatyzovana informatsiina tekhnolohiia kartohrafuvannia zemnoho pokryvu na osnovi metodiv
ta modelei zlyttia suputnykovykh danykh: avtoref. dys. … kand. tekhn. nauk. Kyiv, 22 s.
Zanaga D., Van De Kerchove R., De Keersmaecker W., Souverijns N., Brockmann C., et al. (2021). ESA WorldCover 10 m
V100. OpenAIRE: website. URL: https://worldcover2020.esa.int/downloader (Last accessed: 23.12.2022).
