He, Z., Wang, X., Liang, X., Wu, L. and Yao, J. (2024) Integrating spatiotemporal co-evolution patterns of land types with cellular automata to enhance the reliability of land use projections. International Journal of Geographical Information Science, (doi: 10.1080/13658816.2024.2314575) (Early Online Publication)
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Abstract
Land use and land cover change (LUCC) simulation aids the interpretation of the causes and consequences of future landscape dynamics under various scenarios, which in turn supports policy decisions. The essence of LUCC simulation lies in representing complex spatiotemporal associations among land types, including competitions and interactions. Currently, analyses of complex spatiotemporal LUCC associations mainly focus on the spatial configuration of land use while ignoring the intricate spatiotemporal co-evolution patterns of land types. Therefore, by integrating spatiotemporal co-evolution pattern mining (STC) in a future land use simulation (FLUS) model, a land use change simulation model named STC-FLUS was developed in this study. The proposed model is innovative because it can accurately quantify the spatiotemporal co-evolution patterns of land types, which can be effectively incorporated into LUCC simulations. A set of simulations indicate that the STC-FLUS model is more accurate than the classical FLUS model, with a figure of merit score of 0.135 compared with 0.114. Simulation results under five localized shared socioeconomic pathway scenarios from 2020 to 2040 demonstrate that the proposed model is effective for future LUCC simulation under a set of development scenarios. We conclude that spatiotemporal co-evolution patterns of land types can enhance the reliability of land use projections. Moreover, the STC-FLUS model can serve as a useful tool to understand future land use dynamics.
| Item Type: | Articles |
|---|---|
| Additional Information: | The work was supported by the National Natural Science Foundation of China (No. 42171408, No. 42271437). It is also supported by the “CUG Scholar” Scientific Research Funds at China University of Geosciences (Wuhan) (Project No. 2022127) and the State Key Laboratory of Geo-Information Engineering (No. SKLGIE2020-Z-4-1) |
| Keywords: | LUCC, FLUS model, spatiotemporal co-evolution pattern mining, localized shared socioeconomic pathways. |
| Status: | Early Online Publication |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Yao, Dr Jing |
| Authors: | He, Z., Wang, X., Liang, X., Wu, L., and Yao, J. |
| College/School: | College of Social Sciences > School of Social and Political Sciences > Urban Studies |
| Journal Name: | International Journal of Geographical Information Science |
| Publisher: | Taylor & Francis |
| ISSN: | 1365-8816 |
| ISSN (Online): | 1365-8824 |
| Published Online: | 06 February 2024 |
| Copyright Holders: | Copyright © 2024 Informa UK Limited, trading as Taylor & Francis Group |
| First Published: | First published in International Journal of Geographical Information Science 2024 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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