Scholarly record
DYNAMICS ASSESSMENT OF CHANGES IN FOREST COVER AREA ON THE UKRAINE TERRITORY IN THE 21TH CENTURY BASED ON SATELLITE DATA
Abstract
In Ukraine, as well as all regions of the world, deforestation processes are taking place. Monitoring forests in real-time is one of the key ways to solve the problem of deforestation. Satellite technologies make it possible to do this promptly and in time and space. In this research, the online platform Google Earth Engine was used, which provides access to remote sensing data and geospatial data sets with analysis capabilities. The research was conducted for the period 2001-2023 at the regional level and each administrative oblast. Noting that the war started on the territory of Ukraine in 2022, the research was also conducted separately for the years 2022-2023. Comparison of the obtained data with the pre-war period made it possible to assess the impact of hostilities on the forest cover within each administrative oblast, and they were ranked by the total area of forest cover loss. The analysis of the obtained data shows that a significant increase in deforestation, compared to 2001-2021, occurs in those areas where hostilities are taking place: Luhansk, Kharkiv, Kherson, Donetsk oblasts, or occurred in 2022 and where the strengthening of the northern border is currently taking place, by creating defensive structures in forest areas (Kyiv and Zhytomyr oblasts).
Publication Impact Profile
- Captures
- Mendeley - Readers: 2
Publication details
References14
Bodo, T., Gimah, B.G., & Seomoni, K.J. (2021). Deforestation and Habitat Loss: Human Causes, Consequences and Possible Solutions. Journal of Geographical Research. 4(2), 22�30. DOI: 10.30564/jgr.v4i2.3059
Ievsiukov T. O., Martyn A., Elistratova L., Apostolov A., Kostyuchenko Yu. V. and Yuschenko M. (2018) An Investigation of the Impact of the Military Crisis in Ukraine on Agricultural Production and Land Resources in Crisis Territories: Approaches, Algorithms, and Methods. in: Agricultural Production: Management, Opportunities and Challenges, ed. by Sarah Waechter, Nova Science Publishers, USA, pp. 21-86, ISBN: 978-1-53613-719-4
Lesia Yelistratova, Alexander �postolov, Vadim Lyalko, Olha Tomchenko, Anna Khyzhniak, Artur Hodorovsky (2022). The results of socio-ecological monitoring during military operations in Ukraine using satellite information. Rev. Roum. Geogr./Rom. Journ. Geogr., 66, (2), p. 117�1361
Oral, H.V. (2020). Deforestation. In: Romaniuk, S., Thapa, M., Marton, P. (eds) The Palgrave Encyclopedia of Global Security Studies. Palgrave Macmillan, Cham. DOI: 10.1007/978-3-319-74336-3_390-1
Berenguer, Erika., Armenteras, Dolors., Lees, Alexander., Smith, Charlotte., Fearnside, Philip., Nascimento, Nathalia., G, Ane., Almeida, Claudio., Aragao, Luiz., Barlow, Jos., Bilbao, Bibiana., Brando, Paulo., Bynoe, Paulette., Finer, Matt., Flo-Res, Bernardo., Jenkins, Clinton., Silva-Junior, Celso., Souza Jr, Carlos., Garcia-Villacorta, Roosevelt. (2021). Chapter 19: Drivers and ecological impacts of deforestation and forest degradation. Amazon Assessment Report 2021. DOI: 10.55161/AIZJ1133
Blanc, Lilian, Gond, Valery, Ho Tong Minh, Dinh. (2016). Remote Sensing and Measuring Deforestation. Land Surface Remote Sensing. Environment and Risks. 27-53. DOI: 10.1016/B978-1-78548-105-5.50002-5
Wang, J.; He, Z.; Wang, C.; Feng, M.; Pang, Y.; Yu, T.; Li, X. Investigation of Long-Term Forest Dynamics in Protected Areas of Northeast China Using Landsat Data. Remote Sens. 2022. V. 14. 2988. [Electronic resource]. - Mode access: DOI: 10.3390/rs14132988
Braun, A.C. (2022). Deforestation by Afforestation: Land Use Change in the Coastal Range of Chile. Remote Sens. 14, 1686. DOI: 10.3390/rs14071686
Matosak, B.M.; Fonseca, L.M.G.; Taquary, E.C.; Maretto, R.V.; Bendini, H.d.N.; Adami, M. (2022). Mapping Deforestation in Cerrado Based on Hybrid Deep Learning Architecture and Medium Spatial Resolution Satellite Time Series. Remote Sens. 14, 209. DOI: 10.3390/rs14010209
Torres, D.L.; Turnes, J.N.; Soto Vega, P.J.; Feitosa, R.Q.; Silva, D.E.; Marcato Junior, J.; Almeida, C. (2021). Deforestation Detection with Fully Convolutional Networks in the Amazon Forest from Landsat-8 and Sentinel-2 Images. Remote Sens. 13(24), 5084. DOI: 10.3390/rs13245084
Naing Tun, Z., Dargusch, P., McMoran, D., McAlpine, C., Hill, G. (2021). Patterns and Drivers of Deforestation and Forest Degradation in Myanmar. Sustainability. 13(14), 7539. DOI: 10.3390/su13147539
Mitchell, A.L., Rosenqvist, A. & Mora, B. (2017). Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+. Carbon Balance Manage 12, 9. DOI: 10.1186/s13021-017-0078-9
Lee, S.-H.; Han, K.-J.; Lee, K.; Lee, K.-J.; Oh, K.-Y.; Lee, M.-J. (2020). Classification of Landscape Affected by Deforestation Using High-Resolution Remote Sensing Data and Deep-Learning Techniques. Remote Sens. 12(20), 3372. DOI: 10.3390/rs12203372
Gonzalez-Gonzalez, A., Villegas, J. C., Clerici, N., & Salazar, J. F. (2021). Spatial-temporal dynamics of deforestation and its drivers indicate need for locally-adapted environmental governance in Colombia. Ecological Indicators, 126, 107695. DOI: 10.1016/j.ecolind.2021.107695
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.