Abstract
Under the demand of urban expansion and the constraints of China’s ‘National Main Functional Area Planning’ policy, urban agglomerations are facing with a huge contradiction between land utilization and ecological protection, especially for Harbin-Changchun urban agglomeration who owns a large number of land used for the protection of agricultural production and ecological function. To alleviate this contradiction and provide insight into future land use patterns under different ecological constraints’ scenarios, we introduced the patch-based land use simulation (PLUS) model and simulated urban expansion of the Harbin-Changchun urban agglomeration. After verifying the accuracy of the simulation result in 2018, we predicted future urban expansion under the constraints of three different ecological scenarios in 2026. The morphological spatial pattern analysis (MSPA) method and minimum cumulative resistance (MCR) model were also introduced to identify different levels of ecological security pattern (ESP) as ecological constraints. The predicted result of the optimal protection (OP) scenario showed less proportion of water and forest than those of natural expansion (NE) and basic protection (BP) scenarios in 2026. The conclusions are that the PLUS model can improve the simulation accuracy at urban agglomeration scale compared with other cellular automata (CA) models, and the future urban expansion under OP scenario has the least threat to the ecosystem, while the expansion under the natural expansion (NE) scenario poses the greatest threat to the ecosystem. Combined with the MSPA and MCR methods, PLUS model can also be used in other spatial simulations of urban agglomerations under ecological constraints.
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References
Beatriz A, Daunt P, Sanna T et al., 2021. Urban expansion and forest reserves: drivers of change and persistence on the coast of São Paulo State (Brazil). Land Use Policy, 101: 105189. doi: https://doi.org/10.1016/j.landusepol.2020.105189
Bennett M M, Smith L C, 2017. Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics. Remote Sensing of Environment, 192: 176–197. doi: https://doi.org/10.1016/j.rse.2017.01.005
Cengiz S, Görmüş S, Oğuz D, 2022. Analysis of the urban growth pattern through spatial metrics; Ankara City. Land Use Policy, 112: 105812. doi: https://doi.org/10.1016/j.landusepol.2021.105812
Chen B, 2015. Integrated ecological modelling for sustainable urban metabolism and management. Ecological Modelling, 318: 1–4. doi: https://doi.org/10.1016/j.ecolmodel.2015.10.009
Chen Y M, Li X, Liu X P et al., 2014. Modeling urban land-use dynamics in a fast developing city using the modified logistic cellular automaton with a patch-based simulation strategy. International Journal of Geographical Information Science, 28(2): 234–255. doi: https://doi.org/10.1080/13658816.2013.831868
Chen Y M, Li X, Liu X P et al., 2019. Simulating urban growth boundaries using a patch-based cellular automaton with economic and ecological constraints. International Journal of Geographical Information Science, 33(1): 55–80. doi: https://doi.org/10.1080/13658816.2018.1514119
Chettry V, Surawar M, 2021. Delineating urban growth boundary using remote sensing, ANN-MLP and CA model: a case study of Thiruvananthapuram urban agglomeration, India. Journal of the Indian Society of Remote Sensing, 49(10): 2437–2450. doi: https://doi.org/10.1007/s12524-021-01401-x
Deng X Z, Huang J K, Rozelle S et al., 2008. Growth, population and industrialization, and urban land expansion of China. Journal of Urban Economics, 63(1): 96–115. doi: https://doi.org/10.1016/j.jue.2006.12.006
Fan F L, Wang Y P, Qiu M H et al., 2009. Evaluating the temporal and spatial urban expansion patterns of Guangzhou from 1979 to 2003 by remote sensing and GIS methods. International Journal of Geographical Information Science, 23(11): 1371–1388. doi: https://doi.org/10.1080/13658810802443432
Fang Chuanglin, Song Jitao, Zhang Qiang et al., 2005. The formation, development and spatial heterogeneity patterns for the structures system of urban agglomerations in China. Acta Geographica Sinica, 60(5): 827–840. (in Chinese)
Geshkov M V, DeSalvo J S, 2012. The effect of land-use controls on the spatial size of U. S. urbanized areas. Journal of Regional Science, 52(4): 648–675. doi: https://doi.org/10.1111/j.1467-9787.2012.00763.x
Gong J Z, Liu Y S, Xia B C et al., 2009. Urban ecological security assessment and forecasting, based on a cellular automata model: a case study of Guangzhou, China. Ecological Modelling, 220(24): 3612–3620. doi: https://doi.org/10.1016/j.ecolmodel.2009.10.018
Gu Chaolin, 2011. Study on urban agglomeration: progress and prospects. Geographical Research, 30(5): 771–784. (in Chinese)
Guo R, Bai Y J, 2019. Simulation of an urban-rural spatial structure on the basis of green infrastructure assessment: the case of Harbin, China. Land, 8(12): 196. doi: https://doi.org/10.3390/land8120196
Guo R, Wu T, Liu M R et al., 2019. The construction and optimization of ecological security pattern in the Harbin-Changchun urban agglomeration, China. International Journal of Environmental Research and Public Health, 16(7): 1190. doi: https://doi.org/10.3390/ijerph16071190
He Jianhua, Shi Xuan, Gong Jian et al., 2016. Modeling the spatial expansion of urban agglomeration considering their spatial interaction: a case study of Wuhan Metropolitan Area. Geomatics and Information Science of Wuhan University, 41(4): 462–467. (in Chinese)
He J L, Li X, Yao Y et al., 2018. Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques. International Journal of Geographical Information Science, 32(10): 2076–2097. doi: https://doi.org/10.1080/13658816.2018.1480783
Huang D Q, Huang J, Liu T, 2019. Delimiting urban growth boundaries using the CLUE-S model with village administrative boundaries. Land Use Policy, 82: 422–435. doi: https://doi.org/10.1016/j.landusepol.2018.12.028
Huang Jinchuan, Lin Haoxi, 2017. Spatial evolution analysis and multi-scenarios simulation of Beijing-Tianjin-Hebei Urban Agglomeration. Geographical Research, 36(3): 506–517. (in Chinese)
Inkoom J N, Nyarko B K, Antwi K B, 2017. Explicit modeling of spatial growth patterns in Shama, Ghana: an agent-based approach. Journal of Geovisualization and Spatial Analysis, 1(1–2): 7. doi: https://doi.org/10.1007/s41651-017-0006-2
Jawarneh R N, 2021. Modeling past, present, and future urban growth impacts on primary agricultural land in Greater Irbid Municipality, Jordan using SLEUTH (1972–2050). ISPRS International Journal of Geo-Information, 10(4): 212. doi: https://doi.org/10.3390/ijgi10040212
Li F, Ye Y P, Song B W et al., 2015. Evaluation of urban suitable ecological land based on the minimum cumulative resistance model: a case study from Changzhou, China. Ecological Modelling, 318: 194–203. doi: https://doi.org/10.1016/j.ecolmodel.2014.09.002
Li Hui, Yi Na, Yao Wenjing et al., 2011. Shangri-La county ecological land use planning based on landscape security pattern. Acta Ecologica Sinica, 31(20): 5928–5936. (in Chinese)
Li S C, Bing Z L, Jin G, 2019. Spatially explicit mapping of soil conservation service in Monetary Units due to land use/cover change for the three Gorges reservoir area, China. Remote Sensing, 11(4): 468. doi: https://doi.org/10.3390/rs11040468
Li X, Yeh A G O, 2001. Calibration of cellular automata by using neural networks for the simulation of complex urban systems. Environment and Planning A:Economy and Space, 33(8): 1445–1462. doi: https://doi.org/10.1068/a33210
Li X M, Zhou W Q, 2018. Dasymetric mapping of urban population in China based on radiance corrected DMSP-OLS nighttime light and land cover data. Science of the Total Environment, 643: 1248–1256. doi: https://doi.org/10.1016/j.scitotenv.2018.06.244
Liang X, Liu X P, Li X et al., 2018. Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method. Landscape and Urban Planning, 177: 47–63. doi: https://doi.org/10.1016/j.landurbplan.2018.04.016
Liang X, Guan Q F, Clarke K C et al., 2021. 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. doi: https://doi.org/10.1016/j.compenvurbsys.2020.101569
Lin J, Huang B, Chen M et al., 2014. Modeling urban vertical growth using cellular automata—Guangzhou as a case study. Applied Geography, 53: 172–186. doi: https://doi.org/10.1016/j.apgeog.2014.06.007
Liu Cuiling, Long Ying, 2015. Urban expansion simulation and analysis in the Beijing-Tianjin-Hebei Region. Progress in Geography, 34(2): 217–228. (in Chinese)
Liu J M, Xiao B, Li Y S et al., 2021. Simulation of dynamic urban expansion under ecological constraints using a long short term memory network model and cellular Automata. Remote Sensing, 13(8): 1499. doi: https://doi.org/10.3390/rs13081499
Liu X P, Liang X, Li X et al., 2017. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects. Landscape and Urban Planning, 168: 94–116. doi: https://doi.org/10.1016/j.landurbplan.2017.09.019
Liu Xiaoyang, Zeng Jian, Jia Mengyuan et al., 2020. Construction of ecological security pattern and simulation of urban sprawl in the urban agglomeration of Min Delta. Acta Ecologica Sinica, 40(21): 7873–7885. (in Chinese)
Lv J J, Wang Y F, Liang X et al., 2021. Simulating urban expansion by incorporating an integrated gravitational field model into a demand-driven random forest-cellular automata model. Cities, 109: 103044. doi: https://doi.org/10.1016/j.cities.2020.103044
Ouyang Xiao, Zhu Xiang, 2020. Spatio-temporal characteristics of urban land expansion in Chinese urban agglomerations. Acta Geographica Sinica, 75(3): 571–588. (in Chinese)
Pontius Jr R G, Boersma W, Castella J C et al., 2008. Comparing the input, output, and validation maps for several models of land change. The Annals of Regional Science, 42(1): 11–37. doi: https://doi.org/10.1007/s00168-007-0138-2
Qiu Yao, Chang Qing, Wang Jing, 2013. A MSPA-based planning of urban green infrastructure network—a case of Shenzhen. Chinese Landscape Architecture, 29(5): 104–108. (in Chinese)
Santé I, García A M, Miranda D et al., 2010. Cellular automata models for the simulation of real-world urban processes: a review and analysis. Landscape and Urban Planning, 96(2): 108–122. doi: https://doi.org/10.1016/j.landurbplan.2010.03.001
Saura S, Torné J, 2009. Conefor sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environmental Modelling & Software, 24(1): 135–139. doi: https://doi.org/10.1016/j.envsoft.2008.05.005
Seto K C, Fragkias M, Güneralp B et al., 2011. A meta-analysis of global urban land expansion. PLoS One, 6(8): e23777. doi: https://doi.org/10.1371/journal.pone.0023777
Soille P, Vogt P, 2009. Morphological segmentation of binary patterns. Pattern Recognition Letters, 30(4): 456–459. doi: https://doi.org/10.1016/j.patrec.2008.10.015
Su Y X, Chen X Z, Liao J S et al., 2016. Modeling the optimal ecological security pattern for guiding the urban constructed land expansions. Urban Forestry & Urban Greening, 19: 35–46. doi: https://doi.org/10.1016/j.ufug.2016.06.013
Tang Y, Yuan Y B, Zhong Q Y, 2021. Evaluation of land comprehensive carrying capacity and spatio-temporal analysis of the Harbin-Changchun urban agglomeration. International Journal of Environmental Research and Public Health, 18(2): 521. doi: https://doi.org/10.3390/ijerph18020521
Verburg P H, Overmars K P, 2009. Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model. Landscape Ecology, 24(9): 1167–1181. doi: https://doi.org/10.1007/s10980-009-9355-7
Wang Jing, Fang Chuanglin, 2011. Growth of urban construction land: progress and prospect. Progress in Geography, 30(11): 1440–1448. (in Chinese)
Wu Xinxin, Liu Xiaoping, Liang Xun et al., 2018. Multi-scenarios simulation of urban growth boundaries in Pearl River delta based on FLUS-UGB. Journal of Geo-Information Science, 20(4): 532–542. (in Chinese)
Xia C, Zhang A Q, Wang H J et al., 2019. Bidirectional urban flows in rapidly urbanizing metropolitan areas and their macro and micro impacts on urban growth: a case study of the Yangtze River middle reaches megalopolis, China. Land Use Policy, 82: 158–168. doi: https://doi.org/10.1016/j.landusepol.2018.12.007
Xu L, Huang Q H, Ding D D et al., 2018. Modelling urban expansion guided by land ecological suitability: a case study of Changzhou City, China. Habitat International, 75: 12–24. doi: https://doi.org/10.1016/j.habitatint.2018.04.002
Yang Tianrong, Kuang Wenhui, Liu Weidong et al., 2017. Optimizing the layout of eco-spatial structure in Guanzhong urban agglomeration based on the ecological security pattern. Geographical Research, 36(3): 441–452. (in Chinese)
Yao Y, Liu X P, Li X et al., 2017. Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata. International Journal of Geographical Information Science, 31(12): 2452–2479. doi: https://doi.org/10.1080/13658816.2017.1360494
Ye H, Yang Z P, Xu X L, 2020. Ecological corridors analysis based on MSPA and MCR model—a case study of the Tomur World Natural Heritage Region. Sustainability, 12(3): 959. doi: https://doi.org/10.3390/su12030959
Yu Kongjian, Wang Sisi, Li Dihua, 2012. Regional Ecological Security Patterns. Beijing: China Architecture & Building Press, 56–65. (in Chinese)
Yuan Y J, Wu S H, Yu Y N et al., 2018. Spatiotemporal interaction between ecosystem services and urbanization: case study of Nanjing City, China. Ecological Indicators, 95: 917–929. doi: https://doi.org/10.1016/j.ecolind.2018.07.056
Zhang D C, Liu X P, Wu X Y et al., 2019. Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng, China. Giscience & Remote Sensing, 56(2): 282–308. doi: https://doi.org/10.1080/15481603.2018.1507074
Zhang L Q, Peng J, Liu Y X et al., 2017. Coupling ecosystem services supply and human ecological demand to identify landscape ecological security pattern: a case study in Beijing-Tianjin-Hebei region, China. Urban Ecosystems, 20(3): 701–714. doi: https://doi.org/10.1007/s11252-016-0629-y
Zhang W T, Li B, 2021. Research on an analytical framework for urban spatial structural and functional optimisation: a case study of Beijing city, China. Land, 10(1): 86. doi: https://doi.org/10.3390/land10010086
Zhou Kan, Wu Jianxiong, Fan Jie et al., 2022. Drivers of regional environmental pollution load and zoning control: a case study of the Yangtze River economic Belt, China. Chinese Geographical Science, 32(1): 31–48. doi: https://doi.org/10.1007/s11769-022-1257-5
Zhu G Y, Tang Z S, Shangguan Z P et al., 2019. Factors affecting the spatial and temporal variations in soil erodibility of China. Journal of Geophysical Research, 124(3): 737–749. doi: https://doi.org/10.1029/2018JF00491
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Foundation item: Under the auspices of National Key R&D Program of China (No. 2018YFC0704705)
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Guo, R., Wu, T., Wu, X. et al. Simulation of Urban Land Expansion Under Ecological Constraints in Harbin-Changchun Urban Agglomeration, China. Chin. Geogr. Sci. 32, 438–455 (2022). https://doi.org/10.1007/s11769-022-1277-1
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DOI: https://doi.org/10.1007/s11769-022-1277-1