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eISSN: 2083-5906
ISSN: 1230-1485
ISSN: 1230-1485
ORIGINAL RESEARCH
Multi Scenario Simulation of Land Use
in Chaohu Lake Basin Based on PLUS Model
1
School of Geomatics, Anhui University of Science & Technology, NO. 168 Taifeng Road, Huainan 232001, China
Submission date: 2024-02-23
Final revision date: 2024-03-20
Acceptance date: 2024-04-13
Online publication date: 2024-06-13
Publication date: 2025-01-09
Corresponding author
WeiLing Guo
School of Geomatics, Anhui University of Science & Technology, NO. 168 Taifeng Road, Huainan 232001, China
School of Geomatics, Anhui University of Science & Technology, NO. 168 Taifeng Road, Huainan 232001, China
Pol. J. Environ. Stud. 2025;34(2):1207-1219
KEYWORDS
TOPICS
ABSTRACT
Land is the fundamental resource upon which human survival depends. Research on land use
change coverage (LUCC) is crucial for predicting the future development of human society. This study
focuses on the Chaohu Lake Basin as the research area and selects three-time nodes to analyze the
spatiotemporal characteristics and driving forces of LUCC in the Chaohu Lake Basin from 2000 to 2020.
Three scenarios were established: natural development (ND), ecological protection (EP), and cultivated
land protection (CP). The LUCC of Chaohu Lake Basin in 2030 was simulated by the PLUS model
CARS module. Conclusion: (1) More than 95% of the land types are woodland, urban land, cultivated
land, and water bodies. From 2000 to 2020, 562.1634 km2 of cultivated land decayed and 544.9752 km2
of urban land expanded, with land transfers primarily occurring between farmland and urban land.
(2) The accuracy validation results of the PLUS model show an overall accuracy as high as 95.27%
and a kappa coefficient of 0.9182, meeting the requirements for land use simulation and prediction.
(3) Annual precipitation and population are the main drivers of changes in urban land and arable land.
(4) A comprehensive comparison of LUCC simulation results under three scenarios shows that the
expansion of urban land is restricted under the CP scenario while also ensuring the total amount of
farmland. This research provides a scientific basis and a decision-making reference for local government
land resource development and optimization.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
REFERENCES (44)
1.
YANG S., ZHAO W., LIU Y., WANG S., WANG J., ZHAI R. Influence of land use change on the ecosystem service trade‑offs in the ecological restoration area: Dynamics and scenarios in the Yanhe watershed, China. *Science of The Total Environment*, 644, 556, 2018. <https://doi.org/10.1016/j.scit...> PMid:29990905.
2.
JIANG S., MENG J., ZHU L., CHENG H. Spatial‑temporal pattern of land use conflict in China and its multilevel driving mechanisms. *Science of The Total Environment*, 801, 149697, 2021. <https://doi.org/10.1016/j.scit...> PMid:34467921.
3.
LIANG J., LI S., LI X., LI X., LIU Q., MENG Q., LIN A., LI J. Trade‑off analyses and optimization of water‑related ecosystem services (WRESs) based on land use change in a typical agricultural watershed, southern China. *Journal of Cleaner Production*, 279, 123851, 2021. <https://doi.org/10.1016/j.jcle...>.
4.
SHIBABAW T., RAPPE GEORGE M.O., GÄRDENÄS A.I. The combined impacts of land use change and climate change on soil organic carbon stocks in the Ethiopian highlands. *Geoderma Regional*, 32, e00613, 2023. <https://doi.org/10.1016/j.geod...>.
5.
ZHANG J., ZHANG Y. Remote sensing research issues of the National Land Use Change Program of China. *ISPRS Journal of Photogrammetry and Remote Sensing*, 62 (6), 461, 2007. <https://doi.org/10.1016/j.ispr...>.
6.
JUSTICE C., GUTMAN G., VADREVU K.P. NASA Land Cover and Land Use Change (LCLUC): An interdisciplinary research program. *Journal of Environmental Management*, 148, 4, 2015. <https://doi.org/10.1016/j.jenv...> PMid:25500156.
7.
PIELKE R.A. Land Use and Climate Change. *Science*, 310 (5754), 1625, 2005. <https://doi.org/10.1126/scienc...> PMid:16339435.
8.
LEACH N.P. Hydrologic response of land use and land cover changes. *The University of Iowa*, United States – Iowa, 2015.
9.
HOUGHTON R.A., HOUSE J.I., PONGRATZ J., VAN DER WERF G.R., DEFRIES R.S., HANSEN M.C., LE QUÉRÉ C., RAMANKUTTY N. Carbon emissions from land use and land‑cover change. *Biogeosciences*, 9 (12), 5125, 2012. <https://doi.org/10.5194/bg-9-5...>.
10.
STONE B., JR. Land Use as Climate Change Mitigation. *Environmental Science & Technology*, 43 (24), 9052, 2009. <https://doi.org/10.1021/es9021...> PMid:20000494.
11.
LETOURNEAU A., VERBURG P.H., STEHFEST E. A land‑use systems approach to represent land‑use dynamics at continental and global scales. *Environmental Modelling & Software*, 33, 61, 2012. <https://doi.org/10.1016/j.envs...>.
12.
CALDERÓN‑LOOR M., HADJIKAKOU M., HEWITT R., MARCOS‑MARTINEZ R., BRYAN B.A. Integrated high‑resolution, continental‑scale land change forecasting. *Environmental Modelling & Software*, 166, 105749, 2023. <https://doi.org/10.1016/j.envs...>.
13.
KUMAR M., DENIS D.M., KUNDU A., JOSHI N., SURYAVANSHI S. Understanding land use/land cover and climate change impacts on hydrological components of Usri watershed, India. *Applied Water Science*, 12 (3), 39, 2022. <https://doi.org/10.1007/s13201...>.
14.
JANIZADEH S., CHANDRA PAL S., SAHA A., CHOWDHURI I., AHMADI K., MIRZAEI S., MOSAVI A.H., TIEFENBACHER J.P. Mapping the spatial and temporal variability of flood hazard affected by climate and land‑use changes in the future. *Journal of Environmental Management*, 298, 113551, 2021. <https://doi.org/10.1016/j.jenv...> PMid:34435571.
15.
WU H., LIN A., XING X., SONG D., LI Y. Identifying core driving factors of urban land use change from global land cover products and POI data using the random forest method. *International Journal of Applied Earth Observation and Geoinformation*, 103, 102475, 2021. <https://doi.org/10.1016/j.jag....>.
16.
FAN X., ZHAO L., HE D. Land Use Changes and its Driving Factors in a Coastal Zone. *Polish Journal of Environmental Studies*, 29 (2), 1143, 2020. <https://doi.org/10.15244/pjoes...>.
17.
WANG Z., CAO J. Assessing and Predicting the Impact of Multi‑Scenario Land Use Changes on the Ecosystem Service Value: A Case Study in the Upstream of Xiong'an New Area, China. *Sustainability*, 13 (2), 2021. <https://doi.org/10.3390/su1302...>.
18.
LI W., XIANG M., DUAN L., LIU Y., YANG X., MEI H., WEI Y., ZHANG J., DENG L. Simulation of land utilization change and ecosystem service value evolution in Tibetan area of Sichuan Province. *Alexandria Engineering Journal*, 70, 13, 2023. <https://doi.org/10.1016/j.aej....>.
19.
SHEN G., YANG X., JIN Y., LUO S., XU B., ZHOU Q. Land Use Changes in the Zoige Plateau Based on the Object‑Oriented Method and Their Effects on Landscape Patterns. *Remote Sensing*, 12 (1), 14, 2020. <https://doi.org/10.3390/rs1201...>.
20.
SUN S., MU L., FENG R., WANG L., HE J. GAN‑Based LUCC Prediction via the Combination of Prior City Planning Information and Land‑Use Probability. *IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing*, 14, 10189, 2021. <https://doi.org/10.1109/JSTARS...>.
21.
ZESHAN M.T., MUSTAFA M.R., BAIG M.F. Monitoring Land Use Changes and Their Future Prospects Using GIS and ANN‑CA for Perak River Basin, Malaysia. *Water*, 13 (16), 2286, 2021. <https://doi.org/10.3390/w13162...>.
22.
BESHIR S., MOGES A., DANANTO M. Trend analysis, past dynamics and future prediction of land use and land cover change in upper Wabe‑Shebele river basin. *Heliyon*, 9 (9), e19128, 2023. <https://doi.org/10.1016/j.heli...> PMid:37662774 PMCid:PMC10472002.
23.
LIU X., LIANG X., LI X., XU X., OU J., CHEN Y., LI S., WANG S., PEI F. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects. *Landscape and Urban Planning*, 168, 94, 2017. <https://doi.org/10.1016/j.land...>.
24.
LIANG X., GUAN Q., CLARKE K.C., CHEN G., GUO S., YAO Y. Mixed‑cell cellular automata: A new approach for simulating the spatio‑temporal dynamics of mixed land use structures. *Landscape and Urban Planning*, 205, 103960, 2021. <https://doi.org/10.1016/j.land...>.
25.
LIANG X., LIU X., LI X., CHEN Y., TIAN H., YAO Y. Delineating multi‑scenario urban growth boundaries with a CA‑based FLUS model and morphological method. *Landscape and Urban Planning*, 177, 47, 2018. <https://doi.org/10.1016/j.land...>.
26.
LIU X., WEI M., LI Z., ZENG J. Multi‑scenario simulation of urban growth boundaries with an ESP‑FLUS model: A case study of the Min Delta region, China. *Ecological Indicators*, 135, 108538, 2022. <https://doi.org/10.1016/j.ecol...>.
27.
LIN J., HE P., YANG L., HE X., LU S., LIU D. Predicting future urban waterlogging‑prone areas by coupling the maximum entropy and FLUS model. *Sustainable Cities and Society*, 80, 103812, 2022. <https://doi.org/10.1016/j.scs....>.
28.
ASIF M., KAZMI J.H., TARIQ A., ZHAO N., GULUZADE R., SOUFAN W., ALMUTAIRI K.F., SABAGH A.E., ASLAM M. Modelling of land use and land cover changes and prediction using CA‑Markov and Random Forest. *Geocarto International*, 38 (1), 2210532, 2023. <https://doi.org/10.1080/101060...>.
29.
SUN C., BAO Y., VANDANSAMBUU B., BAO Y. Simulation and Prediction of Land Use/Cover Changes Based on CLUE‑S and CA‑Markov Models: A Case Study of a Typical Pastoral Area in Mongolia. *Sustainability*, 14 (23), 15707, 2022. <https://doi.org/10.3390/su1423...>.
30.
NOURI J., GHARAGOZLOU A., ARJMANDI R., FARYADI S., ADL M. Predicting Urban Land Use Changes Using a CA‑Markov Model. *Arabian Journal for Science and Engineering*, 39 (7), 5565, 2014. <https://doi.org/10.1007/s13369...>.
31.
LIU P., HU Y., JIA W. Land use optimization research based on FLUS model and ecosystem services – setting Jinan City as an example. *Urban Climate*, 40, 100984, 2021. <https://doi.org/10.1016/j.ucli...>.
32.
LIANG X., LIU X., LI D., ZHAO H., CHEN G. Urban growth simulation by incorporating planning policies into a CA‑based future land‑use simulation model. *International Journal of Geographical Information Science*, 32 (11), 2294, 2018. <https://doi.org/10.1080/136588...>.
33.
LIANG X., GUAN Q., CLARKE K.C., LIU S., WANG B., YAO Y. Understanding the drivers of sustainable land expansion using a patch‑generating land use simulation (PLUS) model: A case study in Wuhan, China. *Computers, Environment and Urban Systems*, 85, 101569, 2021. <https://doi.org/10.1016/j.comp...>.
34.
WANG J., ZHANG J., XIONG N., LIANG B., WANG Z., CRESSEY E.L. Spatial and Temporal Variation, Simulation and Prediction of Land Use in Ecological Conservation Area of Western Beijing. *Sustainability*, 14 (6), 1452, 2022. <https://doi.org/10.3390/rs1406...>.
35.
ZHU L., HUANG Y. Multi‑Scenario Simulation of Ecosystem Service Value in Wuhan Metropolitan Area Based on PLUS‑GMOP Model. *Sustainability*, 14 (20), 13604, 2022. <https://doi.org/10.3390/su1420...>.
36.
YU Z., ZHAO M., GAO Y., WANG T., ZHAO Z., WANG S. Multiscenario Simulation and Prediction of Land Use in Huaibei City Based on CLUE‑S and PLUS Model. *Sustainability*, 13 (12), 7142, 2023. <https://doi.org/10.3390/app131...>.
37.
CAO X., LIU Z., LI S., GAO Z. Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province. *Sustainability*, 19 (11), 6640, 2022. <https://doi.org/10.3390/ijerph...> PMid:35682224 PMCid:PMC9180353.
38.
LIN X., FU H. Multi‑scenario simulation analysis of cultivated land based on PLUS model – A case study of Haikou, China. *Frontiers in Ecology and Evolution*, 11, 2023. <https://doi.org/10.3389/fevo.2...>.
39.
ZHANG S., ZHONG Q., CHENG D., XU C., CHANG Y., LIN Y., LI B. Landscape ecological risk projection based on the PLUS model under the localized shared socioeconomic pathways in the Fujian Delta region. *Ecological Indicators*, 136, 108642, 2022. <https://doi.org/10.1016/j.ecol...>.
40.
LIN Z., PENG S. Comparison of multimodel simulations of land use and land cover change considering integrated constraints – A case study of the Fuxian Lake basin. *Ecological Indicators*, 142, 109254, 2022. <https://doi.org/10.1016/j.ecol...>.
41.
WANG Q., GUAN Q., SUN Y., DU Q., XIAO X., LUO H., ZHANG J., MI J. Simulation of future land use/cover change (LUCC) in typical watersheds of arid regions under multiple scenarios. *Journal of Environmental Management*, 335, 117543, 2023. <https://doi.org/10.1016/j.jenv...> PMid:36848808.
42.
LI X., LIU Z., LI S., LI Y. Multi‑Scenario Simulation Analysis of Land Use Impacts on Habitat Quality in Tianjin Based on the PLUS Model Coupled with the InVEST Model. *Sustainability*, 14 (11), 6923, 2022. <https://doi.org/10.3390/su1411...>.
43.
CHEN Y., WANG Y., DING T., WANG K., WU H. Water footprint and virtual water trade analysis in water‑rich basins: Case of the Chaohu Lake Basin in China. *Science of The Total Environment*, 843, 156906, 2022. <https://doi.org/10.1016/j.scit...> PMid:35753485.
44.
GAO L., TAO F., LIU R., WANG Z., LENG H., ZHOU T. Multi‑scenario simulation and ecological risk analysis of land use based on the PLUS model: A case study of Nanjing. *Sustainable Cities and Society*, 85, 104055, 2022. <https://doi.org/10.1016/j.scs....>.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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