The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
A New Global Land-Use and Land-Cover Change Product at a 1-km Resolution for 2010 to 2100 Based on Human–Environment Interactions
Abstract
Global land-use and land-cover change (LUCC) data are crucial for modeling a wide range of environmental conditions. So far, access to high-resolution LUCC products at a global scale for public use is difficult because of data and technical issues. This article presents a Future Land-Use Simulation (FLUS) system to simulate global LUCC in relation to human–environment interactions, which is built and verified by using remote sensing data. IMAGE has been widely used in environmental studies despite its relatively coarse spatial resolution of 30 arc-min, which is about 55 km at the equator. Recently, an improved model has been developed to simulate global LUCC with a 5-min resolution (about 10 km at the equator). We found that even the 10-km resolution, however, still produced major distortions in land-use patterns, leading urban land areas to be underestimated by 19.77 percent at the global scale and global land change relating to urban growth to be underestimated by 60 to 97 percent, compared with the 1-km resolution model proposed through this article. These distortions occurred because a large percentage of small areas of urban land was merged into other land-use classes. During land-use change simulation, a majority of small urban clusters were also lost using the IMAGE product. Responding to these deficiencies, the 1-km FLUS product developed in this study is able to provide the spatial detail necessary to identify spatial heterogeneous land-use patterns at a global scale. We argue that this new global land-use product has strong potential in radically reducing uncertainty in global environmental modeling.
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Cites
Very high resolution interpolated climate surfaces for global land areas
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005) · International Journal of Climatology · doi:10.1002/joc.1276 · Cited by 19,825
A review of assessing the accuracy of classifications of remotely sensed data
Congalton, R. G. (1991) · Remote Sensing of Environment · doi:10.1016/0034-4257(91)90048-b · Cited by 7,724
The next generation of scenarios for climate change research and assessment
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., et al. (2010) · Nature · doi:10.1038/nature08823 · Cited by 6,467
Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools
Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211658109 · Cited by 5,086 · cited 1×
“Studies have shown that a variety of physical and economic factors can be treated as the drivers for modeling land-use dynamics (Letourneau, Verburg, and Stehfest 2012; Seto, G€uneralp, and Hutyra 2012).”
BackgroundIntergovernmental Panel on Climate Change (IPCC)
Edenhofer, O., & Seyboth, K. (2013) · Encyclopedia of Energy, Natural Resource, and Environmental Economics · doi:10.1016/b978-0-12-375067-9.00128-5 · Cited by 3,672
Atmospheric chemistry of VOCs and NOx
Atkinson, R. (2000) · Atmospheric Environment · doi:10.1016/s1352-2310(99)00460-4 · Cited by 3,500
Special report on emissions scenarios
Nakićenović, N., Alcamo, J. M., Davis, G. F., de Vries, B. J. M., Fenhann, J. V., Gaffin, S. R., Gregory, K., Griibler, A., Jung, T. Y., Kram, T., et al. (2000) · eScholarship (California Digital Library) · Cited by 3,423
World Urbanization Prospects: The 2018 Revision
United Nations Department of Economic and Social Affairs (2019) · doi:10.18356/b9e995fe-en · Cited by 2,667
Global land cover mapping at 30 m resolution: A POK-based operational approach
Chen, J., Chen, J., Liao, A., Cao, X., Chen, L., Chen, X., He, C., Han, G., Peng, S., Lu, M., et al. (2015) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2014.09.002 · Cited by 2,049
Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model
VERBURG, P. H., SOEPBOER, W., VELDKAMP, A., LIMPIADA, R., ESPALDON, V., & MASTURA, S. S. A. (2002) · Environmental Management · doi:10.1007/s00267-002-2630-x · Cited by 1,548
Cited by
Threshold responses of riverine fish communities to land use conversion across regions of the world
Chen, K., & Olden, J. D. (2020) · Global Change Biology · doi:10.1111/gcb.15251 · Cited by 106
Air pollution-induced missed abortion risk for pregnancies
Zhang, L., Liu, W., Hou, K., Lin, J., Zhou, C., Tong, X., Wang, Z., Wang, Y., Jiang, Y., Wang, Z., et al. (2019) · Nature Sustainability · doi:10.1038/s41893-019-0387-y · Cited by 92
Metadata
- Authors
- Li, X., Chen, G., Liu, X., Liang, X., Wang, S., Chen, Y., Pei, F., & Xu, X.
- Venue
- Annals of the American Association of Geographers
- Publisher
- Informa UK Limited
- Published
- 2017-04-27
- Volume
- 107
- Issue
- 5
- Pages
- 1040-1059
- ISSN
- 2469-4452 (ISSN-L)
- 2469-4460
- OpenAlex
- W2607525600
- Cited by
- 389
- References
- 47
- FWCI
- 20.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Li, X., Chen, G., Liu, X., Liang, X., Wang, S., Chen, Y., Pei, F., & Xu, X. (2017). A New Global Land-Use and Land-Cover Change Product at a 1-km Resolution for 2010 to 2100 Based on Human–Environment Interactions. Annals of the American Association of Geographers. https://doi.org/10.1080/24694452.2017.1303357
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