LULC Dynamics and Carbon Sequestration in Major Iron Ore Regions of Russia and China
DOI:
https://doi.org/10.52575/2712-7443-2024-48-4-542-564Keywords:
Land use/land cover (LULC) dynamics, Carbon sequestration, Iron ore mining regions, Sustainable land managementAbstract
This study examines the dynamics of land use/land cover (LULC) and carbon sequestration in Lebedinsky and Stoylensky mining and processing plants (LGOK and SGOK) located in iron ore regions of Russia and the Anshan-Benxi iron ore region of China from 1985 to 2020. Through spatial analysis and estimation of carbon sequestration by vegetation and its deposition by soils, the impact of mining activities, urban expansion, and ecological restoration efforts on regional land use patterns and carbon sequestration capacities were assessed. The results reveal significant LULC transformations in both regions, primarily driven by mining development and urbanization. In Russia, cropland area decreased by approximately 8 % (640.78 km²), largely replaced by construction land and forest, with forest cover rising from 12.69 % to 16.69 %, indicating effective ecological management. Conversely, in China, stronger development pressures led to a decrease in forest cover from 40.44 % to 36.73 % and an increase in construction land from 5.62 % to 12.51 %. Carbon sequestration analysis revealed contrasting trends: while the total carbon sequestration in the Russian mining regions remained stable, with a slight increase of 3.69 megatons (Mt), the total carbon sequestration in the Chinese mining regions declined significantly by 31.41 Mt, primarily due to reductions in forest and grassland carbon sequestration. These findings underscore the need for sustainable development that balances economic growth and ecological stability in mining regions. Implementing effective strategies such as afforestation, wetland restoration, and adaptive land-use policies is essential to mitigate the environmental impacts of mining and to sustain carbon sequestration. Future policies should prioritize harmonizing industrial growth with environmental conservation to promote sustainable land use in heavily industrialized areas.
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Список литературы
Беленко В.В., Ассех К.Ф. 2022. Проблемные вопросы обнаружения изменений состава земель методами дистанционного зондирования Земли из космоса для целей рационального использования на примере Республики Кот-д'Ивуар. Известия высших учебных заведений. Геодезия и аэрофотосъемка, 66(4): 86–100. https://doi.org/10.30533/0536-101X-2022-66-4-86-100.
Гзогян С.Р., Гзогян Т.Н. 2018. Особенности вещественного состава богатых железных руд месторождений КМА. Научные ведомости Белгородского государственного университета. Серия: Естественные науки, 42(2): 131–141. https://doi.org/10.18413/2075-4671-2018-42-2-131-141.
Кирсанов А.К. 2023. Обзор современного состояния горнодобывающей промышленности Китая. Горные науки и технологии, 8(2): 115–127. https://doi.org/10.17073/2500-0632-2022-11-35.
Корнилов А.Г., Кичигин Е.В., Колмыков С.Н., Новых Л.Л., Дроздова Е.А., Петин А.Н., Присный А.В., Лазарев А.В., Колчанов А.Ф. 2015. Экологическая ситуация в районах размещения горнодобывающих предприятий региона Курской магнитной аномалии. Белгород, Изд. Белгородского государственного университета, 157 с.
Полетаев А.О., Лисецкий Ф.Н. 2023. Использование мониторинговых данных и ГИС-технологий для корректировки границ санитарно-защитных зон в связи с развитием Старооскольско-Губкинского промышленного района. Геополитика и экогеодинамика регионов, 9(3): 338–347.
Савин И.Ю., Березуцкая Э.Р. 2024. Концепция наземного покрова (Land Cover) как основа дистанционного мониторинга земель. Региональные геосистемы, 48(1): 77–90. https://doi.org/10.52575/2712-7443-2024-48-1-77-90.
Хуан Л., Полетаев А.О. 2024. Использование возможностей космического мониторинга для выявления особенностей трансформации земель в зоне влияния ведущих железорудных предприятий России и Китая. В кн.: Геоэкология и рациональное недропользование: от науки к практике. Материалы IV Всероссийской научной конференции молодых ученых, Белгород, 10 октября 2024. Белгород, Белгородский государственный национальный исследовательский университет: 117–125.
Abbas Z., Yang G., Zhong Y., Zhao Y. 2021. Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China. Land, 10(6): 584. https://doi.org/10.3390/land10060584.
Alshari E.A., Gawali B.W. 2021. Development of a Classification System for LULC Using Remote Sensing and GIS. Global Transitions Proceedings, 2(1): 8–17. https://doi.org/10.1016/j.gltp.2021.01.002.
Anderson J.R. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data. US Government Printing Office, 28 p.
Basheer S., Wang X., Farooque A.A., Nawaz R.A., Liu K., Adekanmbi T., Liu S. 2022. Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques. Remote Sensing, 14(19): 4978. https://doi.org/10.3390/rs14194978.
Chazdon R.L. 2008. Beyond Deforestation: Restoring Forests and Ecosystem Services on Degraded Lands. Science, 320(5882): 1458–1460. https://doi.org/10.1126/science.1155365.
Di Gregorio A. 2005. Land Cover Classification System: Classification Concepts and User Manual. Rome, Food and Agriculture Organization of the United Nations, 208 p.
Digra M., Dhir R., Sharma N. 2022. Land Use Land Cover Classification of Remote Sensing Images Based on the Deep Learning Approaches: A Statistical Analysis and Review. Arabian Journal of Geosciences, 15: 1003. https://doi.org/10.1007/s12517-022-10246-8.
Foley J.A., Defries R., Asner G.P., Barford C., Bonan G., Carpenter S.R., Chapin F.S., Coe M.T., Daily G.C., Gibbs H.K., Helkowski J.H., Holloway T., Howard E.A., Kucharik Ch.J., Monfreda Ch., Patz J.A., Prentice I.C., Ramankutty N., Snyder P.K. 2005. Global Consequences of Land Use. Science, 309(5734): 570–574. https://doi.org/10.1126/science.1111772.
Galperin A. 2015. Using of Man-Made Massives in Russian Mining (Engineering: Geological Aspects). Engineering Geology for Society and Territory, 6: 1057–1062. https://doi.org/10.1007/978-3-319-09060-3_192.
Grimm N.B., Faeth S.H., Golubiewski N.E., Redman C.L., Wu J., Bai X., Briggs J.M. 2008. Global Change and the Ecology of Cities. Science, 319(5864): 756–760. https://doi.org/10.1126/science.1150195.
Han H., Li X. 2022. Sustainable Land Use Management in Mining Areas: Challenges and Strategies. Resources Policy, 76: 102616. https://doi.org/10.1016/j.resourpol.2022.102616.
Hu X., Liao W., Wei Y., Wei Z., Huang Sh. 2024. Analysis of Land Use Change and Its Economic and Ecological Value under the Optimal Scenario and Green Development Advancement Policy: A Case Study of Hechi, China. Sustainability, 16(12): 5039. https://doi.org/10.3390/su16125039.
Kou X., Zhao J., Sang W. 2024. Impact of Typical Land Use Expansion Induced by Ecological Restoration and Protection Projects on Landscape Patterns. Land, 13(9): 1513. https://doi.org/10.3390/land13091513.
Lal R. 2004. Soil Carbon Sequestration Impacts on Global Climate Change and Food Security. Science, 304(5677): 1623–1627. https://doi.org/10.1126/science.1097396.
Lambin E.F., Geist H.J. 2008. Land-Use and Land-Cover Change: Local Processes and Global Impacts. Springer Science & Business Media, 222 p.
Lambin E.F., Geist H.J., Lepers E. 2003. Dynamics of Land-Use and Land-Cover Change in Tropical Regions. Annual Review of Environment and Resources, 28(1): 205–241. https://doi.org/10.1146/annurev.energy.28.050302.105459.
Liu H., Wang Q., Liu N., Zhang H., Tan Y., Zhang Z. 2023. The Impact of Land Use/Cover Change on Ecological Environment Quality and Its Spatial Spillover Effect under the Coupling Effect of Urban Expansion and Open-Pit Mining Activities. Sustainability, 15(20): 14900. https://doi.org/10.3390/su152014900.
Liu Y., Li J., Yang Y. 2023. Urbanization and Its Effects on Land Use and Land Cover Change in the Anshan-Benxi Region, China. Journal of Geographical Sciences, 33(2): 245–260. https://doi.org/10.1007/s11442-023-2035-6.
Liu Y., Zhan J., Deng X. 2005. Spatio-Temporal Patterns and Driving Forces of Urban Land Expansion in China During the Economic Reform Era. Ambio: A Journal of the Human Environment, 34(6): 450–455. https://doi.org/10.1579/0044-7447-34.6.450.
Ni J. 2013. Carbon Storage in Chinese Terrestrial Ecosystems: Approaching a More Accurate Estimate. Climatic Change, 119(3): 905–917. https://doi.org/10.1007/s10584-013-0767-7.
Pan Y., Birdsey R.A., Fang J., Houghton R., Kauppi P.E., Kurz W.A., Phillips O.L., Shvidenko A., Lewis S.L., Canadell J.G., Ciais P., Jackson R.B., Pacala S.W., McGuire A.D., Piao S., Rautiainen A., Sitch S., Hayes D. 2011. A Large and Persistent Carbon Sink in the World's Forests. Science, 333(6045): 988–993. https://doi.org/10.1126/science.1201609.
Pang Z., Bu J., Yuan Y., Zheng J., Xue Q., Wang J., Guo H., Zuo H. 2023. The Low‐Carbon Production of Iron and Steel Industry Transition Process in China. Steel Research International, 95(3): 2300500. https://doi.org/10.1002/srin.202300500.
Pirnazar M., Haghighi N., Azhand D., Ostad-Ali-Askari K., Eslamian S., Dalezios N.R., Singh V.P. 2021. Land Use Change Detection and Prediction Using Markov-CA and Publishing on the Web with Platform Map Server: Case Study Qom Metropolis, Iran. Journal of Geography and Cartography, 4(1): 7–20. https://doi.org/10.24294/jgc.v4i1.453.
Pontius G.R., Malanson J. 2005. Comparison of the Structure and Accuracy of Two Land Change Models. International Journal of Geographical Information Science, 19(2): 243–265. https://doi.org/10.1080/13658810410001713434.
Post W.M., Kwon K.C. 2000. Soil Carbon Sequestration and Land-Use Change: Processes and Potential. Global Change Biology, 6(3): 317–327. https://doi.org/10.1046/j.1365-2486.2000.00308.x.
Seto K.C., Güneralp B., Hutyra L.R. 2012. Global Forecasts of Urban Expansion to 2030 and Direct Impacts on Biodiversity and Carbon Pools. Proceedings of the National Academy of Sciences, 109(40): 16083–16088. https://doi.org/10.1073/pnas.1211658109.
Turner B.L., Lambin E.F., Reenberg A. 2007. The Emergence of Land Change Science for Global Environmental Change and Sustainability. Proceedings of the National Academy of Sciences, 104(52): 20666–20671. https://doi.org/10.1073/pnas.0704119104.
Turner B.L., Skole D., Sanderson S., Fischer G., Fresco L., Leemans R. 1995. Land-Use and Land-Cover Change: Science/Research Plan. IGBP Report, 35: 132.
Verburg P.H., Schot P.P., Dijst M.J., Veldkamp A. 2004. Land Use Change Modelling: Current Practice and Research Priorities. GeoJournal, 61(4): 309–324. https://doi.org/10.1007/s10708-004-4946-y.
Wohlfart C., Mack B., Liu G., Kuenzer C. 2017. Multi-Faceted Land Cover and Land Use Change Analyses in the Yellow River Basin Based on Dense Landsat Time Series: Exemplary Analysis in Mining, Agriculture, Forest, and Urban Areas. Applied Geography, 85: 73–88. https://doi.org/10.1016/j.apgeog.2017.06.004.
Worlanyo A.S., Jiangfeng L. 2021. Evaluating the Environmental and Economic Impact of Mining for Post-Mined Land Restoration and Land-Use: A Review. Journal of Environmental Management, 279: 111623. https://doi.org/10.1016/j.jenvman.2020.111623.
Wu J., Yang J., Ma L., Li Z., Shen X. 2016. A System Analysis of the Development Strategy of Iron Ore in China. Resources Policy, 48: 32–40. https://doi.org/10.1016/j.resourpol.2016.01.010.
Wu Q., Wang L., Wang T., Chen H., Du P. 2024. Global Versus Local? A Study on the Synergistic Relationship of Ecosystem Service Trade-Offs from Multiple Perspectives Based on Ecological Restoration Zoning of National Land Space – A Case Study of Liaoning Province. Applied Sciences, 14(22): 10421. https://doi.org/10.3390/app142210421.
Xu Y., Li J., Zhang C., Raval S., Guo L., Yang F. 2024. Dynamics of Carbon Sequestration in Vegetation Affected by Large-Scale Surface Coal Mining and Subsequent Restoration. Scientific Reports, 14: 13479. https://doi.org/10.1038/s41598-024-64381-1.
Yifter T., Razoumny Yu., Lobanov V. 2022. Deep Transfer Learning of Satellite Imagery for Land Use and Land Cover Classification. Informatics and Automation, 21(5): 963–982. https://doi.org/10.15622/ia.21.5.5.
Zhang X., Liu L., Chen X., Gao Y., Xie S., Mi J. 2021. GLC_FCS30: Global Land Cover Product with Fine Classification System at 30 m Using Time-Series Landsat Imagery. Earth System Science Data, 13(6): 2753–2776. https://doi.org/10.5194/essd-13-2753-2021.
Zhang Z., Bai Z., He Z., Bao N. 2012. Dynamic Changes of Land Use Type and Carbon Sinks Based RS and GIS in Pingshuo Opencast Coal Mine. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 28(3): 230–236. https://doi.org/10.3969/j.issn.1002-6819.2012.03.040.
Zheng L., Li Y., Chen Y., Wang R., Yan S., Xia C., Zhang B., Shao J. 2024. Driving Model of Land Use Change on the Evolution of Carbon Stock: A Case Study of Chongqing, China. Environmental Science and Pollution Research International, 31(3): 4238–4255. https://doi.org/10.1007/s11356-023-31335-5.
Kong T., Zhang K., Huang L., Di J., Wang Y., Zhang J. 2023. Effects of mixed application of microbial agents on growth and substrate properties of alfalfa in coal gangue matrix with different particle sizes. Journal of China Coal Society, 48(S1): 241–251. https://doi.org/10.13225/j.cnki.jccs.2022.0615 (in Chinese).
Shvidenko A., Nilsson S. 2003. A Synthesis of the Impact of Russian Forests on the Global Carbon Budget for 1961–1998. Tellus B: Chemical and Physical Meteorology, 55(2): 391–415. https://doi.org/10.3402/tellusb.v55i2.16722.
Di Gregorio A., Jansen L.J.M. 2006. Land Cover Classification System (LCCS): Classification Concepts and User Manual. Rome, FAO, 179 p.
Shelestov A., Lavreniuk M., Kussul N., Novikov A., Skakun S. 2017. Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping. Frontiers in Earth Science, 5: 1–10. https://doi.org/10.3389/FEART.2017.00017.
Rasskazov I.Y., Arkhipova Y.A., Kryukov V.G., Volkov A.F. 2023. Mining Industry in the Russian Far East: Balancing the Interests of Subsoil Use and the State. Journal of Mining Science, 59(3): 481–489.
Rengma N.S., Yadav M. 2024. Generation and Classification of Patch-Based Land Use and Land Cover Dataset in Diverse Indian Landscapes: A Comparative Study of Machine Learning and Deep Learning Models. Environmental Monitoring and Assessment, 196(6): 568. https://doi.org/10.1007/s10661-024-12719-7.
Ahialey E.K., Kabo-Bah A.T., Gyamfi S. 2024. LULC Changes in the Region of the Proposed Pwalugu Hydropower Project Using GIS and Remote Sensing Technique. Journal of Geography and Cartography, 7(2): 8282. https://doi.org/10.24294/jgc.v7i2.8282.
References
Belenko V.V., Assekh K.F. 2022. Problematic Issues of Detecting Changes in Land Composition Using Remote Sensing Methods for Rational Land Use: The Case of Côte d'Ivoire. Annals of Higher Educational Institutions. Geodesy and Aerial Photography, 66(4): 86–100 (in Russian). https://doi.org/10.30533/0536-101X-2022-66-4-86-100.
Gzogyan S.R., Gzogyan T.N. 2018. Material Composition of Rich Iron Ore Deposits of KMA. Scientific Bulletin of Belgorod State University. Series: Natural Sciences, 42(2): 131–141 (in Russian). https://doi.org/10.18413/2075-4671-2018-42-2-131-141.
Kirsanov A.K. 2023. Chinese Mining Industry: State of the Art Review. Mining Science and Technology, 8(2): 115–127 (in Russian). https://doi.org/10.17073/2500-0632-2022-11-35.
Kornilov A.G., Kichigin E.V., Kolmykov S.N., Novykh L.L., Drozdova E.A., Petin A.N., Prisny A.V., Lazarev A.V., Kolchanov A.F. 2015. Environmental Situation in the Areas where Mining Enterprises on the Region of Kursk Magnetic Anomaly. Belgorod, Publ. Belgorod State University, 157 p. (in Russian).
Poletaev A.O., Lisetskiy F.N. 2023. The Use of Monitoring Data and GIS Technologies to Adjust the Boundaries of Sanitary Protection Zones in Connection with the Development of the Stary Oskol and Gubkin Industrial Area. Geopolitics and Ecogeodynamics of Regions, 9(3): 338–347 (in Russian).
Savin I.Yu., Berezutskaya E.R. 2024. The Concept of Land Cover as a Basis for Remote Sensing Monitoring of Land. Regional Geosystems, 48(1): 77–90 (in Russian). https://doi.org/10.52575/2712-7443-2024-48-1-77-90.
Huang L., Poletaev A.O. 2024. Using Space Monitoring Capabilities to Identify Land Transformation Features in the Influence Zones of Major Iron Ore Enterprises in Russia and China. In: Geoecology and Rational Subsoil Use: From Science to Practice. Proceedings of the 4th All-Russian Scientific Conference of Young Scientists, Belgorod, 10 October 2024. Belgorod, Pabl. Belgorod State National Research University: 117–125 (in Russian).
Abbas Z., Yang G., Zhong Y., Zhao Y. 2021. Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China. Land, 10(6): 584. https://doi.org/10.3390/land10060584.
Ahialey E.K., Kabo-Bah A.T., Gyamfi S. 2024. LULC Changes in the Region of the Proposed Pwalugu Hydropower Project Using GIS and Remote Sensing Technique. Journal of Geography and Cartography, 7(2): 8282. https://doi.org/10.24294/jgc.v7i2.8282.
Alshari E.A., Gawali B.W. 2021. Development of a Classification System for LULC Using Remote Sensing and GIS. Global Transitions Proceedings, 2(1): 8–17. https://doi.org/10.1016/j.gltp.2021.01.002.
Anderson J.R. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data. US Government Printing Office, 28 p.
Basheer S., Wang X., Farooque A.A., Nawaz R.A., Liu K., Adekanmbi T., Liu S. 2022. Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques. Remote Sensing, 14(19): 4978. https://doi.org/10.3390/rs14194978.
Chazdon R.L. 2008. Beyond Deforestation: Restoring Forests and Ecosystem Services on Degraded Lands. Science, 320(5882): 1458–1460. https://doi.org/10.1126/science.1155365.
Di Gregorio A. 2005. Land Cover Classification System: Classification Concepts and User Manual. Rome, Food and Agriculture Organization of the United Nations, 208 p.
Di Gregorio A., Jansen L.J.M. 2006. Land Cover Classification System (LCCS): Classification Concepts and User Manual. Rome, FAO, 179 p.
Digra M., Dhir R., Sharma N. 2022. Land Use Land Cover Classification of Remote Sensing Images Based on the Deep Learning Approaches: A Statistical Analysis and Review. Arabian Journal of Geosciences, 15: 1003. https://doi.org/10.1007/s12517-022-10246-8.
Foley J.A., Defries R., Asner G.P., Barford C., Bonan G., Carpenter S.R., Chapin F.S., Coe M.T., Daily G.C., Gibbs H.K., Helkowski J.H., Holloway T., Howard E.A., Kucharik Ch.J., Monfreda Ch., Patz J.A., Prentice I.C., Ramankutty N., Snyder P.K. 2005. Global Consequences of Land Use. Science, 309(5734): 570–574. https://doi.org/10.1126/science.1111772.
Galperin A. 2015. Using of Man-Made Massives in Russian Mining (Engineering: Geological Aspects). Engineering Geology for Society and Territory, 6: 1057–1062. https://doi.org/10.1007/978-3-319-09060-3_192.
Grimm N.B., Faeth S.H., Golubiewski N.E., Redman C.L., Wu J., Bai X., Briggs J.M. 2008. Global Change and the Ecology of Cities. Science, 319(5864): 756–760. https://doi.org/10.1126/science.1150195.
Han H., Li X. 2022. Sustainable Land Use Management in Mining Areas: Challenges and Strategies. Resources Policy, 76: 102616. https://doi.org/10.1016/j.resourpol.2022.102616.
Hu X., Liao W., Wei Y., Wei Z., Huang Sh. 2024. Analysis of Land Use Change and Its Economic and Ecological Value under the Optimal Scenario and Green Development Advancement Policy: A Case Study of Hechi, China. Sustainability, 16(12): 5039. https://doi.org/10.3390/su16125039.
Kong T., Zhang K., Huang L., Di J., Wang Y., Zhang J. 2023. Effects of mixed application of microbial agents on growth and substrate properties of alfalfa in coal gangue matrix with different particle sizes. Journal of China Coal Society, 48(S1): 241–251. https://doi.org/10.13225/j.cnki.jccs.2022.0615 (in Chinese) .
Kou X., Zhao J., Sang W. 2024. Impact of Typical Land Use Expansion Induced by Ecological Restoration and Protection Projects on Landscape Patterns. Land, 13(9): 1513.https://doi.org/10.3390/land13091513.
Lal R. 2004. Soil Carbon Sequestration Impacts on Global Climate Change and Food Security. Science, 304(5677): 1623–1627. https://doi.org/10.1126/science.1097396.
Lambin E.F., Geist H.J. 2008. Land-Use and Land-Cover Change: Local Processes and Global Impacts. Springer Science & Business Media, 222 p.
Lambin E.F., Geist H.J., Lepers E. 2003. Dynamics of Land-Use and Land-Cover Change in Tropical Regions. Annual Review of Environment and Resources, 28(1): 205–241. https://doi.org/10.1146/annurev.energy.28.050302.105459.
Liu H., Wang Q., Liu N., Zhang H., Tan Y., Zhang Z. 2023. The Impact of Land Use/Cover Change on Ecological Environment Quality and Its Spatial Spillover Effect under the Coupling Effect of Urban Expansion and Open-Pit Mining Activities. Sustainability, 15(20): 14900. https://doi.org/10.3390/su152014900.
Liu Y., Li J., Yang Y. 2023. Urbanization and Its Effects on Land Use and Land Cover Change in the Anshan-Benxi Region, China. Journal of Geographical Sciences, 33(2): 245–260. https://doi.org/10.1007/s11442-023-2035-6.
Liu Y., Zhan J., Deng X. 2005. Spatio-Temporal Patterns and Driving Forces of Urban Land Expansion in China During the Economic Reform Era. Ambio: A Journal of the Human Environment, 34(6): 450–455. https://doi.org/10.1579/0044-7447-34.6.450.
Ni J. 2013. Carbon Storage in Chinese Terrestrial Ecosystems: Approaching a More Accurate Estimate. Climatic Change, 119(3): 905–917. https://doi.org/10.1007/s10584-013-0767-7.
Pan Y., Birdsey R.A., Fang J., Houghton R., Kauppi P.E., Kurz W.A., Phillips O.L., Shvidenko A., Lewis S.L., Canadell J.G., Ciais P., Jackson R.B., Pacala S.W., McGuire A.D., Piao S., Rautiainen A., Sitch S., Hayes D. 2011. A Large and Persistent Carbon Sink in the World's Forests. Science, 333(6045): 988–993. https://doi.org/10.1126/science.1201609.
Pang Z., Bu J., Yuan Y., Zheng J., Xue Q., Wang J., Guo H., Zuo H. 2023. The Low‐Carbon Production of Iron and Steel Industry Transition Process in China. Steel Research International, 95(3): 2300500. https://doi.org/10.1002/srin.202300500.
Pirnazar M., Haghighi N., Azhand D., Ostad-Ali-Askari K., Eslamian S., Dalezios N.R., Singh V.P. 2021. Land Use Change Detection and Prediction Using Markov-CA and Publishing on the Web with Platform Map Server: Case Study Qom Metropolis, Iran. Journal of Geography and Cartography, 4(1): 7–20. https://doi.org/10.24294/jgc.v4i1.453.
Pontius G.R., Malanson J. 2005. Comparison of the Structure and Accuracy of Two Land Change Models. International Journal of Geographical Information Science, 19(2): 243–265. https://doi.org/10.1080/13658810410001713434.
Post W.M., Kwon K.C. 2000. Soil Carbon Sequestration and Land-Use Change: Processes and Potential. Global Change Biology, 6(3): 317–327. https://doi.org/10.1046/j.1365-2486.2000.00308.x.
Rasskazov I.Y., Arkhipova Y.A., Kryukov V.G., Volkov A.F. 2023. Mining Industry in the Russian Far East: Balancing the Interests of Subsoil Use and the State. Journal of Mining Science, 59(3): 481–489.
Rengma N.S., Yadav M. 2024. Generation and Classification of Patch-Based Land Use and Land Cover Dataset in Diverse Indian Landscapes: A Comparative Study of Machine Learning and Deep Learning Models. Environmental Monitoring and Assessment, 196(6): 568. https://doi.org/10.1007/s10661-024-12719-7.
Seto K.C., Güneralp B., Hutyra L.R. 2012. Global Forecasts of Urban Expansion to 2030 and Direct Impacts on Biodiversity and Carbon Pools. Proceedings of the National Academy of Sciences, 109(40): 16083–16088. https://doi.org/10.1073/pnas.1211658109.
Shelestov A., Lavreniuk M., Kussul N., Novikov A., Skakun S. 2017. Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping. Frontiers in Earth Science, 5: 1–10. https://doi.org/10.3389/FEART.2017.00017.
Shvidenko A., Nilsson S. 2003. A Synthesis of the Impact of Russian Forests on the Global Carbon Budget for 1961–1998. Tellus B: Chemical and Physical Meteorology, 55(2): 391–415. https://doi.org/10.3402/tellusb.v55i2.16722.
Turner B.L., Lambin E.F., Reenberg A. 2007. The Emergence of Land Change Science for Global Environmental Change and Sustainability. Proceedings of the National Academy of Sciences, 104(52): 20666–20671. https://doi.org/10.1073/pnas.0704119104.
Turner B.L., Skole D., Sanderson S., Fischer G., Fresco L., Leemans R. 1995. Land-Use and Land-Cover Change: Science/Research Plan. IGBP Report, 35: 132.
Verburg P.H., Schot P.P., Dijst M.J., Veldkamp A. 2004. Land Use Change Modelling: Current Practice and Research Priorities. GeoJournal, 61(4): 309–324. https://doi.org/10.1007/s10708-004-4946-y.
Wohlfart C., Mack B., Liu G., Kuenzer C. 2017. Multi-Faceted Land Cover and Land Use Change Analyses in the Yellow River Basin Based on Dense Landsat Time Series: Exemplary Analysis in Mining, Agriculture, Forest, and Urban Areas. Applied Geography, 85: 73–88. https://doi.org/10.1016/j.apgeog.2017.06.004.
Worlanyo A.S., Jiangfeng L. 2021. Evaluating the Environmental and Economic Impact of Mining for Post-Mined Land Restoration and Land-Use: A Review. Journal of Environmental Management, 279: 111623. https://doi.org/10.1016/j.jenvman.2020.111623.
Wu J., Yang J., Ma L., Li Z., Shen X. 2016. A System Analysis of the Development Strategy of Iron Ore in China. Resources Policy, 48: 32–40. https://doi.org/10.1016/j.resourpol.2016.01.010.
Wu Q., Wang L., Wang T., Chen H., Du P. 2024. Global Versus Local? A Study on the Synergistic Relationship of Ecosystem Service Trade-Offs from Multiple Perspectives Based on Ecological Restoration Zoning of National Land Space – A Case Study of Liaoning Province. Applied Sciences, 14(22): 10421. https://doi.org/10.3390/app142210421.
Xu Y., Li J., Zhang C., Raval S., Guo L., Yang F. 2024. Dynamics of Carbon Sequestration in Vegetation Affected by Large-Scale Surface Coal Mining and Subsequent Restoration. Scientific Reports, 14: 13479. https://doi.org/10.1038/s41598-024-64381-1.
Yifter T., Razoumny Yu., Lobanov V. 2022. Deep Transfer Learning of Satellite Imagery for Land Use and Land Cover Classification. Informatics and Automation, 21(5): 963–982. https://doi.org/10.15622/ia.21.5.5.
Zhang X., Liu L., Chen X., Gao Y., Xie S., Mi J. 2021. GLC_FCS30: Global Land Cover Product with Fine Classification System at 30 m Using Time-Series Landsat Imagery. Earth System Science Data, 13(6): 2753–2776. https://doi.org/10.5194/essd-13-2753-2021.
Zhang Z., Bai Z., He Z., Bao N. 2012. Dynamic Changes of Land Use Type and Carbon Sinks Based RS and GIS in Pingshuo Opencast Coal Mine. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 28(3): 230–236. https://doi.org/10.3969/j.issn.1002-6819.2012.03.040.
Zheng L., Li Y., Chen Y., Wang R., Yan S., Xia C., Zhang B., Shao J. 2024. Driving Model of Land Use Change on the Evolution of Carbon Stock: A Case Study of Chongqing, China. Environmental Science and Pollution Research International, 31(3): 4238–4255. https://doi.org/10.1007/s11356-023-31335-5.
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