Articles | Volume 25, issue 7
https://doi.org/10.5194/acp-25-4251-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-4251-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Apr 2025
Research article |
| 15 Apr 2025
| 15 Apr 2025
Highly resolved satellite-remote-sensing-based land-use-change inventory yields weaker surface-albedo-induced global cooling
Xiaohu Jian
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Xiaodong Zhang
CORRESPONDING AUTHOR
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Xinrui Liu
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Kaijie Chen
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Tao Huang
Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
Shu Tao
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Junfeng Liu
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Hong Gao
Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
Yuan Zhao
Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
Ruiyu Zhugu
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
Jianmin Ma
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, People's Republic of China
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Cited articles
Achard, F., Eva, H. D., Stibig, H. J., Mayaux, P., Gallego, J., Richards, T., and Malingreau, J. P.: Determination of Deforestation Rates of the World's Humid Tropical Forests, Science, 297, 999–1002, https://doi.org/10.1126/science.1070656, 2002.
Andela, N., Morton, D. C., Chen, L. G. Y., Werf, G. R. V. D., Kasibhatla, P. S., Defries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., and Randerson, J. T.: A human-driven decline in global burned area, Science, 356, 1356–1362, https://doi.org/10.1126/science.aal4108, 2017.
Andrade, B. O., Koch, C., Boldrini, I. I., Martin, E. V., Hasenack, H., Hermann, J. M., Kollmann, J., Pillar, V. D., and Overbeck, G. E.: Grassland degradation and restoration: a conceptual framework of stages and thresholds illustrated by southern Brazilian grasslands, Nat. Conservacao, 13, 95–104, https://doi.org/10.1016/J.NCON.2015.08.002, 2015.
Andrews, D.: An Introduction to Atmospheric Physics (2nd edn.), Cambridge University Press, ISBN 9780511800788, https://doi.org/10.1017/CBO9780511800788, 2012.
Andrews, T. and Forster, P. M.: Energy budget constraints on historical radiative forcing, Nat. Clim. Change, 10, 313–316, https://doi.org/10.1038/s41558-020-0696-1, 2020.
Andrews, T., Betts, R. A., Booth, B. B. B., Jones, C. D., and Jones, G. S.: Effective radiative forcing from historical land use change, Clim. Dynam., 48, 3489–3505, https://doi.org/10.1007/s00382-016-3280-7, 2017.
Aragão, L. E. O. C. and Shimabukuro, Y. E.: The Incidence of Fire in Amazonian Forests with Implications for REDD, Science, 328, 1275–1278, https://doi.org/10.1126/science.1186925, 2010.
Armenteras, D., Schneider, L., and Dávalos, L. M.: Fires in protected areas reveal unforeseen costs of Colombian peace, Nat. Ecol. Evol., 3, 20–23, https://doi.org/10.1038/s41559-018-0727-8, 2019.
Armenteras, D., Dávalos, L. M., Barreto, J. S., Miranda, A., Hernández-moreno, A., Zamorano-Elgueta, C., González-Delgado, T. M., Meza-Elizalde, M. C., and Retana, J.: Fire-induced loss of the world's most biodiverse forests in Latin America, Sci. Adv., 7, eabd3357, https://doi.org/10.1126/sciadv.abd3357, 2021.
Atsri, H. K., Konko, Y., Cuni-Sanchez, A., Abotsi, K. E., and Kokou, K.: Changes in the West African forest-savanna mosaic, insights from central Togo, PLoS One, 13, e0203999, https://doi.org/10.1371/journal.pone.0203999, 2018.
Aune, S., Bryn, A., and Hovstad, K. A.: Loss of semi-natural grassland in a boreal landscape: impacts of agricultural intensification and abandonment, J. Land Use Sci., 13, 375–390, https://doi.org/10.1080/1747423X.2018.1539779, 2018.
Bardgett, R. D., Bullock, J. M., Lavorel, S., Manning, P., Schaffner, U., Ostle, N., Chomel, M., Durigan, G., Fry, E. L., Johnson, D., Lavallee, J. M., Provost, G. L., Luo, S., Png, K., Sankaran, M., Hou, X. Y., Zhou, H. K., Ma, L., Ren, W. B., Li, X. L., Ding, Y., Li, Y. H., and Shi, H. X.: Combatting global grassland degradation, Nat. Rev. Earth Environ., 2, 720–735, https://doi.org/10.1038/s43017-021-00207-2, 2021.
Betts, R. A.: Offset of the potential carbon sink from boreal forestation by decreases in surface albedo, Nature, 408, 187–190, https://doi.org/10.1038/35041545, 2000.
Betts, R. A., Falloon, P. D., Goldewijk, K. K., and Ramankutty, N.: Biogeophysical effects of land use on climate: Model simulations of radiative forcing and large-scale temperature change, Agr. Forest Meteorol., 142, 216–233, https://doi.org/10.1016/j.agrformet.2006.08.021, 2007.
Bodart, C., Brink, A. B., Donnay, F., Lupi, A., Mayaux, P., and Achard, F.: Continental estimates of forest cover and forest cover changes in the dry ecosystems of Africa between 1990 and 2000, J. Biogeogr., 40, 1036–1047, https://doi.org/10.1111/jbi.12084, 2013.
Bonan, G. B.: Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008.
Bond, W. J.: Ancient grasslands at risk, Science, 351, 120–122, https://doi.org/10.1126/science.aad5132, 2016.
Bullock, E. L., Woodcock, C. E., Souza Jr, C., and Olofsson, P.: Satellite-based estimates reveal widespread forest degradation in the Amazon, Glob. Change Biol., 26, 2956–2969, https://doi.org/10.1111/gcb.15029, 2020.
Cai, M. and Kalnay, E.: Impact of land-use change on climate, Nature, 427, 214, https://doi.org/10.1038/427214a, 2004.
Chang, J., Cias, P., Gasser, T., Smith, P., Herrero, M., Havlik, P., Obersteiner, M., Guenet, B., Goll, D. S., Li, W., Naipal, V., Peng, S. S., Qiu, C. J., Tian, H. Q., Viovy, N., Yue, C., and Zhu, D.: Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands, Nat. Commun., 12, 118, https://doi.org/10.1038/s41467-020-20406-7, 2021.
Da Ponte, E., Fleckenstein, M., Leinenkugel, P., Parker, A., Oppelt, N., and Kuenzer, C.: Tropical forest cover dynamics for Latin America using Earth observation data: a review covering the continental, regional, and local scale, Int. J. Remote Sens., 36, 3196–3342, https://doi.org/10.1080/01431161.2015.1058539, 2015.
Davidson, E. A., de Araujo, A. C., Artaxo, P., Balch, J. K., Brown, I. F., C.,Bustamante, M. M., Coe, M. T., DeFries, R. S., Keller, M., Longo, M., Munger, J. W., Schroeder, W., Soares-Filho, B. S., Souza, C. M., and Wofsy, S. C.: The Amazon basin in transition, Nature, 481, 321–328, https://doi.org/10.1038/nature10717, 2012.
Escobar, H.: Bolsonaro's first moves have Brazilian scientists worried, Science, 363, 330, https://doi.org/10.1126/science.363.6425.330, 2019.
Estoque, R. C., Ooba, M., Avitabile, V., Hijioka, Y., DasGupta, R., Togawa, T., and Murayama, Y.: The future of Southeast Asia's forests, Nat. Commun., 10, 1829, https://doi.org/10.1038/s41467-019-09646-4, 2019.
FAO: Global Forest Resources Assessment 2010, https://www.fao.org/forest-resources-assessment/past-assessments/fra-2010/en/ (last access: 11 April 2025), 2010.
FAO: Global Forest Resources Assessment 2020, https://www.fao.org/interactive/forest-resources-assessment/2020/en/ (last access: 11 April 2025), 2020.
FAO, Food and Agricultural data: FAOSTAT, https://www.fao.org/faostat/en/ (last access: 28 March 2025), 2017.
Feddema, J. J., Oleson, K. W., Bonan, G. B., Mearns, L. O., Buja, L. E., Meehl, G. A., and Washington, W. M.: The Importance of Land-Cover Change in Simulating Future Climates, Science, 310, 1674–1678, https://doi.org/10.1126/science.1118160, 2005.
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, C. J., Monfreda, C., Patz, J. A., Prentice, I. C., Ramankutty, N., and Snyder, P. K.: Global Consequences of Land Use, Science, 309, 570–574, https://doi.org/10.1126/science.1111772, 2005.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D. W., Haywood, J., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., and Dorland, R. V.: Changes in Atmospheric Constituents and in Radiative Forcing, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge and New York, https://www.ipcc.ch/report/ar4/wg1/changesin-atmospheric-constituents-and-radiative-forcing/ (last access: 21 March 2025), 2007.
Gaillard, C., Langan, L., Pfeiffer, M., Kumar, D., Martens, C., Higgins, S. I., and Scheiter, S.: African shrub distribution emerges via a trade-off between height and sapwood conductivity, J. Biogeogr., 45, 2815–2826, https://doi.org/10.1111/jbi.13447, 2018.
Gasser, T. and Fu, B.: Compact earth system model, Github [code], https://github.com/tgasser/OSCAR (last access: 22 January 2024), 2019.
Gasser, T., Ciais, P., Boucher, O., Quilcaille, Y., Tortora, M., Bopp, L., and Hauglustaine, D.: The compact Earth system model OSCAR v2.2: description and first results, Geosci. Model Dev., 10, 271–319, https://doi.org/10.5194/gmd-10-271-2017, 2017.
Gong, P., Wang, J., Yu, L., Zhao, Y. C., Zhao, Y. Y., Liang, L., Niu, Z., Huang, X. M., Fu, H. H., Liu, S., Li, C. C., Li, X. Y., Fu, W., Liu, C. X., Xu, Y., Wang, X. Y., Cheng, Q., Hu, L. Y., Yao, W. B., Zhang, H., Zhu, P., Zhao, Z. Y., Zhang, H. Y., Zheng, Y. M., Ji, L. Y., Zhang, Y. W., Chen, H., Yan, A., Guo, J. H., Yu, L., Wang, L., Liu, X. J., Shi, T. T., Zhu, M. H., Chen, Y. L., Yang, G. W., Tang, P., Xu, B., Giri, C., Clinton, N., Zhu, Z. L., Chen, J., and Chen, J.: Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data, Int. J. Remote Sens., 34, 2607–2654, https://doi.org/10.1080/01431161.2012.748992, 2013.
Gries, T., Redlin, M., and Ugarte, J. E.: Human-induced climate change: the impact of land-use change, Theor. Appl. Climatol., 135, 1031–1044, https://doi.org/10.1007/s00704-018-2422-8, 2019.
Hansen, J. and Nazarenko, L.: Soot climate forcing via snow and ice albedos, P. Natl. Acad. Sci. USA, 101, 423–428, https://doi.org/10.1073/pnas.2237157100, 2003.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townshend, J. R. G.: High-Resolution Global Maps of 21st-Century Forest Cover Change, Science, 342, 850–853, https://doi.org/10.1126/science.1244693, 2013.
Hinz, R., Sulser, T. B., Huefner, R., Croz, D. M. D., Dunston, S., Nautiyal, S., Ringler, C., Schuengel, J., Tikhile, P., Wimmer, F., and Schaldach, R.: Agricultural Development and Land Use Change in India: A Scenario Analysis of Trade-Offs Between UN Sustainable Development Goals (SDGs), Earths Future, 8, e2019EF001287, https://doi.org/10.1029/2019EF001287, 2020.
Houghton, R. A., House, J. I., Pongratz, J., van der Werf, G. R., DeFries, R. S., Hansen, M. C., Le Quéré, C., and Ramankutty, N.: Carbon emissions from land use and land-cover change, Biogeosciences, 9, 5125–5142, https://doi.org/10.5194/bg-9-5125-2012, 2012.
Huang, T., Ma, J. M., Song, S. J., Ling, Z. L., Macdonald, R. W., Gao, H., Tao, S., Shen, H. Z., Zhao, Y., Liu, X. R., Tian, C. G., Li, Y. F., Jia, H. L., Lian, L. L., and Mao, X. X.: Health and environmental consequences of crop residue burning correlated with increasing crop yields midst India's Green Revolution, Npj. Clim. Atmos. Sci., 5, 81, https://doi.org/10.1038/s41612-022-00306-x, 2022.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer, G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones, C. D., Kindermann, G., Kinoshita, T., Goldwijk, K. K., Riahi, K., Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., Vuuren, D. P. V., and Wang, Y. P.: Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands, Clim. Chang., 109, 117–161, https://doi.org/10.1007/s10584-011-0153-2, 2011.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., and Zhang, X.: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6, Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, 2020.
Igusky, K.: Quantifying Albedo and Surface Temperature over Different Land Covers: Implications for Carbon Offsets, Duke University Press, https://hdl.handle.net/10161/497 (last access: 11 April 2025), 2008.
Imai, N., Furukawa, T., Tsujino, R., Kitamura, S., and Yumoto, T.: Factors affecting forest area change in Southeast Asia during 1980–2010, PLoS One, 13, e0197391, https://doi.org/10.1371/journal.pone.0197391, 2018.
Intergovernmental Panel on Climate Change (IPCC), Climate Change 2001: The Scientific Basis is the most comprehensive and up-to-date scientific assessment of past, present and future climate change, Cambridge University Press, Cambridge and New York, https://www.ipcc.ch/report/ar3/wg1/ (last access: 21 March 2025), 2001.
Intergovernmental Panel on Climate Change (IPCC), Climate change 2021: The physical science basis, the working Group I contribution to the sixth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge and New York, https://www.ipcc.ch/report/ar6/wg1/ (last access: 21 March 2025), 2021.
Jackson, R. B., Randerson, J. T., Canadell, J. G., Amderson, R. G., Avissar, R., Baldocchi, D. D., Bonan, G. B., Caldeira, K., Diffenbaugh, N. S., Field, C. B., Hungate, B. A., Jobbágy, E. G., Kueppers, L. M., Nosetto, M. D., and Pataki, D. E.: Protecting climate with forests, Environ. Res. Lett., 3, 044006, https://doi.org/10.1088/1748-9326/3/4/044006, 2008.
Jian, X. H., Zhang, X. D., Liu, Y. J., Liu, X. R., Chen, K. J., Wang, L. F., Li, J. X., Zhao, Y., Luo, J. M., Zhugu, R. Y., and Ma, J. M.: The Response of Radiative Forcing to High Spatiotemporally Resolved Land-Use Change and Transition From 1982 to 2010 in China, Geophys. Res. Lett., 49, e2022GL099003, https://doi.org/10.1029/2022GL099003, 2022.
Jiao, T., Williams, C. A., Ghimire, B., Masek, J., Gao, F., and Schaaf, C.: Global climate forcing from albedo change caused by large-scale deforestation and reforestation: quantification and attribution of geographic variation, Clim. Chang., 142, 463–476, https://doi.org/10.1007/s10584-017-1962-8, 2017.
Keenan, R. J., Reams, G. A., Achard, F., Freitas, J. V. D., Grainger, A., and Lindquist, E.: Dynamics of global forest area: Results from the FAO Global Forest Resources Assessment 2015, Forest Ecol. Manag., 353, 9–20, https://doi.org/10.1016/j.foreco.2015.06.014, 2015.
Lark, T. J., Spawn, S. A., Bougie, M., and Gibbs, H. K.: Cropland expansion in the United States produces marginal yields at high costs to wildlife, Nat. Commun., 11, 4295, https://doi.org/10.1038/s41467-020-18045-z, 2020.
Leys, B. A., Marlon, J. R., Umbanhowar, C., and Vannière, B.: Global fire history of grassland biomes, Ecol. Evol., 8, 8831–8852, https://doi.org/10.1002/ece3.4394, 2018.
Li, B. G., Gasser, T., Ciais, P., Piao, S. L., Tao, S., Balkanski, Y., Hauglustaine, D., Boisier, J. P., Chen, Z., Huang, M. T., Li, L. Z. X., Li, Y., Liu, H. Y., Liu, H. F., Peng, S. S., Shen, Z. H., Sun, Z. Z., Wang, R., Wang, T., Yin, G. D., Yin, Y., Zeng, H., Zeng, Z. Z., and Zhou, F.: The contribution of China's emissions to global climate forcing, Nature, 531, 357–361, https://doi.org/10.1038/nature17165, 2016.
Liu, H., Gong, P., Wang, J., Clinton, N., Bai, Y., and Liang, S.: Annual dynamics of global land cover and its long-term changes from 1982 to 2015, Earth Syst. Sci. Data, 12, 1217–1243, https://doi.org/10.5194/essd-12-1217-2020, 2020.
Liu, H., Gong, P., Wang, J., Clinton, N., Bai, Y., and Liang, S.: Annual dynamics of global land cover and its long-term changes from 1982 to 2015, link to GeoTIFF files, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.913496, 2020b.
Liu, X. R., Zhang, X. D., Huang, Y. F., Chen, K, J., Wang, L. F., Ma, J. M., Huang, T., Zhao, Y., Gao, H., Tao, S., Liu, J. F., Jian, X. H., and Luo, J. M.: The Direct Radiative Forcing Impact of Agriculture-Emitted Black Carbon Associated With India's Green Revolution, Earths Future, 9, e2021EF001975, https://doi.org/10.1029/2021EF001975, 2021.
Liu, X. Y. and Xin, L. J.: China's deserts greening and response to climate variability and human activities, PLoS One, 16, e0256462, https://doi.org/10.1371/journal.pone.0256462, 2021.
Mograbi, P. J., Erasmus, B. F. N., Witkowski, E. T. F., Asner, G. P., Wessels, K. J., Mathieu, R., Knapp, D. E., Martin, R. E., and Main, R.: Biomass Increases Go under Cover: Woody Vegetation Dynamics in South African Rangelands, PLoS One, 10, e0127093, https://doi.org/10.1371/journal.pone.0127093, 2015.
Myhre, G. and Myhre, A.: Uncertainties in Radiative Forcing due to Surface Albedo Changes Caused by Land-Use Changes, J. Climate, 16, 1511–1524, https://doi.org/10.1175/1520-0442(2003)016<1511:UIRFDT>2.0.CO;2, 2003.
Nogueira, D. S., Marimon, B. S., Marimon-Junior, B. H., Oliveira, E. A., Morandi, P., Reis, S. M., Elias, F., Neves, E. C., Feldpausch, T. R., Lloyd, J., and Phillips, O. L.: Impacts of Fire on Forest Biomass Dynamics at the Southern Amazon Edge, Environ. Conserv., 46, 285–292, https://doi.org/10.1017/S0376892919000110, 2019.
Ouyang, Z. T., Sciusco, P., Jiao, T., Feron, S., Lei, C., Li, F., John, R., Fan, P., Li, X., Williams, C. A., Chen, G. Z., Wang, C. H., and Chen, J. Q.: Albedo changes caused by future urbanization contribute to global warming, Nat. Commun., 13, 3800, https://doi.org/10.1038/s41467-022-31558-z, 2022.
Parr, C. L., Lehmann, C. E. R., Bond, W. J., Hoffmann, W. A., and Andersen, A. N.: Tropical grassy biomes: misunderstood, neglected, and under threat, Trends Ecol. Evol., 29, 205–213, https://doi.org/10.1016/j.tree.2014.02.004, 2014.
Peking University: Dataset for ACP-egusphere-2024-1497, Zenodo [data set], https://doi.org/10.5281/zenodo.14586249, 2025.
Pendrill, F., Persson, U. M., Godar, J., Kastner, T., Moran, D., Schmidt, S., and Wood, R.: Agricultural and forestry trade drives large share of tropical deforestation emissions, Global Environ. Chang., 56, 1–10, https://doi.org/10.1016/j.gloenvcha.2019.03.002, 2019.
Peng, S. S., Piao, S. L., Zeng, Z. Z., Ciais, P., Zhou, L. M., Li, L. Z. X., Myneni, R. B., Yin, Y., and Zeng, H.: Afforestation in China cools local land surface temperature, P. Natl. Acad. Sci. USA, 111, 2915–2919, https://doi.org/10.1073/pnas.1315126111, 2014.
Pingali, P. L.: Green, Revolution: Impacts, limits, and the path ahead, P. Natl. Acad. Sci. USA, 109, 12302–12308, https://doi.org/10.1073/pnas.0912953109, 2012.
Pongratz, J., Raddatz, T., Reick, C. H., Esch, M., and Claussen, M.: Radiative forcing from anthropogenic land cover change since AD 800, Geophys. Res. Lett., 36, L02709, https://doi.org/10.1029/2008GL036394, 2009.
Ramanathan, V.: Greenhouse Effect Due to Chlorofluorocarbons: Climatic Implications, Science, 190, 50–52, https://doi.org/10.1126/science.190.4209.50, 1975.
National Forestry and Grassland Administration of China: Seventh National Forest Resource Inventory Report, https://www.forestry.gov.cn/c/www/lczy/8432.jhtml (last access: 11 April 2025), 2009.
Sherwood, S. C., Bony, S., Boucher, O., Bretherton, C., Forster, P. M., Gregory, J. M., and Stevens, B.: Adjustments in the Forcing-Feedback Framework for Understanding Climate Change, B. Am. Meteorol. Soc., 96, 217–228, https://doi.org/10.1175/BAMS-D-13-00167.1, 2015.
Spawn, S. A., Lark, T. J., and Gibbs, H. K.: Carbon emissions from cropland expansion in the United States, Environ. Res. Lett., 14, 045009, https://doi.org/10.1088/1748-9326/ab0399, 2019.
Stibig, H.-J., Achard, F., Carboni, S., Raši, R., and Miettinen, J.: Change in tropical forest cover of Southeast Asia from 1990 to 2010, Biogeosciences, 11, 247–258, https://doi.org/10.5194/bg-11-247-2014, 2014.
Sun, W., Ding, X., Su, J., Mu, X., Zhang, Y., Gao, P., and Zhao, G.: Land use and cover changes on the Loess Plateau: A comparison of six global or national land use and cover datasets, Land Use Policy, 119, 106165, https://doi.org/10.1016/j.landusepol.2022.106165, 2022.
Teluguntla, P. G., Thenkabail, P. S., Xiong, J., Gumma, M. K., Giri, C., Milesi, C., Ozdogan, M., Congalton, R., Tilton, J., Sankey, T. T., Massey, R., Phalke, A., and Yadav, K.: Global Cropland Area Database (GCAD) derived from remote sensing in support of food security in the twenty-fifirst century: Current achievements and future possibilities, in: Remote sensing handbook, Volume II, Land resources monitoring, modeling, and mapping with remote sensing, edited by: Thenkabail, P. S., Chap. 7, p. 849, Boca Raton: CRC Press, http://oar.icrisat.org/id/eprint/9224 (last access: 5 January 2016), 2015.
Vose, R. S., Kari, T. R., Easterling, D. R., Williams, C. N., and Menne, M. J.: Impact of land-use change on climate, Nature, 427, 213–214, https://doi.org/10.1038/427213b, 2004.
Wang, X. M., Ge, Q. S., Geng, X., Wang, Z. S., Gao, L., Bryan, B. A., Chen, S. Q., Su, Y. N., Cai, D. W., Ye, J. S., Sun, J. M., Lu, H. Y., Liu, B. L., Dong, Z. B., Cao, S. X., Hua, T., Chen, S. Y., Sun, F. B., Luo, G. P., Wang, Z. T., Hu, S., Xu, D. Y., Chen, M. X., Li, D. F., Liu, F., Xu, X. L., Han, D. M., Zheng, Y., Xiao, F. Y., Li, X. B., Wang, P., and Chen, F. H.: Unintended consequences of combating desertification in China, Nat. Commun., 14, 1139, https://doi.org/10.1038/s41467-023-36835-z, 2023.
Ward, D. S., Mahowald, N. M., and Kloster, S.: Potential climate forcing of land use and land cover change, Atmos. Chem. Phys., 14, 12701–12724, https://doi.org/10.5194/acp-14-12701-2014, 2014.
Winkler, K., Fuchs, R., Rounsevell, M., and Herold, M.: Global land use changes are four times greater than previously estimated, Nat. Commun., 12, 2501, https://doi.org/10.1038/s41467-021-22702-2, 2021.
Yang, J. X.: China's Rapid Urbanization, Science, 342, 310–310, https://doi.org/10.1126/science.342.6156.310-a, 2013.
Zablon, A. A., Nasta, P., Zlotnik, V., and Wedin, D.: Impact of grassland conversion to forest on groundwater recharge in the Nebraska Sand Hills, J. Hydrol. Reg. Stud., 15, 171–183, https://doi.org/10.1016/j.ejrh.2018.01.001, 2018.
Zhang, X., Huang, T., Zhang, L., Shen, Y., Zhao, Y., Gao, H., Mao, X., Jia, C., and Ma, J.: Three-North Shelter Forest Program contribution to long-term increasing trends of biogenic isoprene emissions in northern China, Atmos. Chem. Phys., 16, 6949–6960, https://doi.org/10.5194/acp-16-6949-2016, 2016.
Zhang, X. D., Huang, T., Zhang, L. M., Gao, H., Shen, Y. J., and Ma, J. M.: Trends of deposition fluxes and loadings of sulfur dioxide and nitrogen oxides in the artificial Three Northern Regions Shelter Forest across northern China, Environ. Pollut., 207, 238–247, https://doi.org/10.1016/j.envpol.2015.09.022, 2015.
Zhu, F., Emile-Geay, J., Mckay, N. P., Hakim, G. J., Khider, D., Ault, T. R., Steig, E. J., Dee, S., and Kirchner, J. W.: Cliamte models can correctly simulate the continuum of global-average temperature variability, P. Natl. Acad. Sci. USA, 116, 8728–8733, https://doi.org/10.1073/pnas.1809959116, 2019.
Short summary
We implemented a new global land-use-change (LUC) dataset from 1982 to 2010 into a compact earth system model and carried out extensive multiple model scenario simulations. Our result reveals that the global radiative forcing (RF) induced by LUC driving surface albedo change is −0.12 W m−2, 20 % lower than the Intergovernmental Panel on Climate Change (IPCC), and vegetation changes play a key role in RF evolution, which provides an important reference for the assessment of earth energy balance.
We implemented a new global land-use-change (LUC) dataset from 1982 to 2010 into a compact earth...
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