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      1 km land use/land cover change of China under comprehensive socioeconomic and climate scenarios for 2020–2100

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          Abstract

          In the past decades, China has undergone dramatic land use/land cover (LULC) changes. Such changes are expected to continue and profoundly affect our environment. To navigate future uncertainties toward sustainability, increasing efforts have been invested in projecting China’s future LULC following the Shared Socioeconomic Pathways (SSPs) and/or Representative Concentration Pathways (RCPs). To supplements existing datasets with a high spatial resolution, comprehensive pathway coverage, and delicate account for urban land change, here we present a 1-km gridded LULC dataset for China under 24 comprehensive SSP-RCP scenarios covering 2020–2100 at 10-year intervals. Our approach is to integrate the Global Change Analysis Model (GCAM) and Future Land Use Simulation (FLUS) model. This dataset shows good performance compared to remotely sensed CCI-LC data and is generally spatio-temporally consistent with the Land Use Harmonization version-2 dataset. This new dataset (available at 10.6084/m9.figshare.14776128.v1) provides a valuable alternative for multi-scenario-based research with high spatial resolution, such as earth system modeling, ecosystem services, and carbon neutrality.

          Abstract

          Measurement(s) Land Use and Land Cover Change
          Technology Type(s) computational modeling technique
          Factor Type(s) Shared Socioeconomic Pathways scenarios • Representative Concentration Pathways scenarios • land use and land cover change
          Sample Characteristic - Environment Land
          Sample Characteristic - Location China

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          Most cited references38

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          Global consequences of land use.

          Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.
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            The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview

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              The representative concentration pathways: an overview

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                Author and article information

                Contributors
                ghhu@geo.ecnu.edu.cn
                lixia@geo.ecnu.edu.cn
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                28 March 2022
                28 March 2022
                2022
                : 9
                : 110
                Affiliations
                [1 ]GRID grid.22069.3f, ISNI 0000 0004 0369 6365, Key Lab of Geographic Information Science (Ministry of Education), School of Geographic Sciences, , East China Normal University, ; 500 Dongchuan Road, Shanghai, 200241 China
                [2 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, Institute of Future Cities, , The Chinese University of Hong Kong, ; Shatin, NT Hong Kong SAR
                Author information
                http://orcid.org/0000-0001-8033-9378
                http://orcid.org/0000-0002-3052-1259
                http://orcid.org/0000-0003-3050-8529
                Article
                1204
                10.1038/s41597-022-01204-w
                8960815
                35347153
                05ef741d-5dd6-4dff-88c3-44b51229df43
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 August 2021
                : 14 February 2022
                Funding
                Funded by: the National Key R&D Program of China (No.2017YFA0604402)
                Categories
                Data Descriptor
                Custom metadata
                © The Author(s) 2022

                environmental impact,projection and prediction
                environmental impact, projection and prediction

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