High-resolution global land use projections can be modeled using socioeconomic and climate scenarios
Is it true that high-resolution global land use projections can be modeled using socioeconomic and climate scenarios?
Yes. Multiple studies demonstrate that high-resolution land use projections can be successfully modeled by integrating socioeconomic pathways and climate scenarios.
Verdict: SUPPORTED · 8 sources for, 0 against · Last checked
The retrieved literature consistently shows that researchers use Shared Socioeconomic Pathways (SSPs) and climate scenarios (such as RCPs) combined with high-resolution remote sensing and machine learning techniques to model future land use and land cover changes. All relevant papers support the claim, and none refute it.
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Gomes, L., Bianchi, F., Cardoso, I., Schulte, R., Arts, B., & Filho, E. F. (2020). Land use and land cover scenarios: An interdisciplinary approach integrating local conditions and the global shared socioeconomic pathways. doi.org. https://doi.org/10.1016/j.landusepol.2020.104723
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Subbarayan, S., Youssef, Y. M., Singh, L., Dąbrowska, D., Alarifi, N., Ramsankaran, R., Visweshwaran, R., & Saqr, A. M. (2025). Soil and Water Assessment Tool-Based Prediction of Runoff Under Scenarios of Land Use/Land Cover and Climate Change Across Indian Agro-Climatic Zones: Implications for Sustainable Development Goals. doi.org. https://doi.org/10.3390/w17030458
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Bukovsky, M., Gao, J., Mearns, L., & O’Neill, B. (2020). SSP‐Based Land‐Use Change Scenarios: A Critical Uncertainty in Future Regional Climate Change Projections. doi.org. https://doi.org/10.1029/2020EF001782
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Ji, P., Su, R., Wu, G., Xue, L., Zhang, Z., Fang, H., Gao, R., Zhang, W., & Zhang, D. (2025). Projecting Future Wetland Dynamics Under Climate Change and Land Use Pressure: A Machine Learning Approach Using Remote Sensing and Markov Chain Modeling. doi.org. https://doi.org/10.3390/rs17061089
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Hasnaoui, Y., Tachi, S., Bouguerra, H., Yaseen, Z., Gilja, G., Szczepanek, R., & Navarro-Pedreño, J. (2025). Integrated Remote Sensing and Deep Learning Models for Flash Flood Detection Based on Spatio-temporal Land Use and Cover Changes in the Mediterranean Region. doi.org. https://doi.org/10.1007/s10666-025-10035-z
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Kabo-bah, A., Cobbina, N. A., Siabi, E. K., Siabi, S. E., & Ahiada, W. B. (2025). Flood projections over the White Volta Basin under the shared socioeconomic pathways: an analytical hierarchical approach. doi.org. https://doi.org/10.3389/fclim.2025.1564665
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Qin, B., Zhao, J., Chen, G., Wang, R., & Lin, Y. (2025). An Integrated Framework for Assessing Dynamics of Ecological Spatial Network Resilience Under Climate Change Scenarios: A Case Study of the Yunnan Central Urban Agglomeration. doi.org. https://doi.org/10.3390/land14101988
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Rehman, A., Sajjad, M., Lu, H., Lu, S., Cao, L., Han, Z., Feng, W., Qi, S., Zhang, Y., Wang, J., Riaz, M. T., & Abbas, S. (2025). Exacerbating landslide risks under future climate change and land use scenarios: evidence from the Western Himalayas in Pakistan. doi.org. https://doi.org/10.1080/19475705.2025.2577170
What does the evidence say?
The retrieved literature consistently shows that researchers use Shared Socioeconomic Pathways (SSPs) and climate scenarios (such as RCPs) combined with high-resolution remote sensing and machine learning techniques to model future land use and land cover changes. All relevant papers support the claim, and none refute it.
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