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Spatio-temporal evolution characteristics analysis and optimization prediction of urban green infrastructure: a case study of Beijing, China

  • Birenboim, A. The influence of urban environments on our subjective momentary experiences. Environ. Plan. B-Urban Anal. CIty Sci. 45, 915–932. https://doi.org/10.1177/2399808317690149 (2018).

    Article 

    Google Scholar 

  • Flores, A., Pickett, S. T. A., Zipperer, W. C., Pouyat, R. V. & Pirani, R. Adopting a modern ecological view of the metropolitan landscape: The case of a greenspace system for the New York City region. Landsc. Urban Plan. 39, 295–308. https://doi.org/10.1016/S0169-2046(97)00084-4 (1998).

    Article 

    Google Scholar 

  • Weijs-Perrée, M., Dane, G., Berg, P. V. D. & Dorst, M. V. A multi-level path analysis of the relationships between the momentary experience characteristics, satisfaction with urban public spaces, and momentary- and long-term subjective wellbeing. Int. J. Environ. Res. Public Health. https://doi.org/10.3390/ijerph16193621 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Paulin, M. J. et al. Application of the natural capital model to assess changes in ecosystem services from changes in green infrastructure in Amsterdam. Ecosyst. Serv. 43, 101114. https://doi.org/10.1016/j.ecoser.2020.101114 (2020).

    Article 

    Google Scholar 

  • Derkzen, M. L., van Teeffelen, A. J. A., Verburg, P. H. & Diamond, S. Quantifying urban ecosystem services based on high-resolution data of urban green space: An assessment for Rotterdam, the Netherlands. J. Appl. Ecol. 52, 1020–1032. https://doi.org/10.1111/1365-2664.12469 (2015).

    Article 

    Google Scholar 

  • Leiva, M. A., Santibanez, D. A., Ibarra, S., Matus, P. & Seguel, R. A five-year study of particulate matter (PM2.5) and cerebrovascular diseases. Environ. Pollut. 181, 1–6. https://doi.org/10.1016/j.envpol.2013.05.057 (2013).

    CAS 
    Article 

    Google Scholar 

  • Venkataramanan, V. et al. Knowledge, attitudes, intentions, and behavior related to green infrastructure for flood management: A systematic literature review. Sci. Total Environ. 720, 137606. https://doi.org/10.1016/j.scitotenv.2020.137606 (2020).

    CAS 
    Article 
    PubMed 

    Google Scholar 

  • Wang, G. Z., Han, Q. & De Vries, B. The multi-objective spatial optimization of urban land use based on low-carbon city planning. Ecol. Indic. 125, 107540. https://doi.org/10.1016/j.ecolind.2021.107540 (2021).

    CAS 
    Article 

    Google Scholar 

  • Cameron, R. W. F. et al. The domestic garden—Its contribution to urban green infrastructure. Urban For. Urban Green. 11, 129–137. https://doi.org/10.1016/j.ufug.2012.01.002 (2012).

    Article 

    Google Scholar 

  • De la Sota, C., Ruffato-Ferreira, V. J., Ruiz-Garcia, L. & Alvarez, S. Urban green infrastructure as a strategy of climate change mitigation. A case study in northern Spain. Urban For. Urban Green. 40, 145–151. https://doi.org/10.1016/j.ufug.2018.09.004 (2019).

    Article 

    Google Scholar 

  • Pongsakorn, S., Jiang, X. R. & Sullivan, W. C. Green infrastructure, green stormwater infrastructure, and human health a review. Curr. Landscape. Ecol. Rep. 2, 96–110. https://doi.org/10.1007/s40823-017-0028-y (2017).

    Article 

    Google Scholar 

  • Liu, O. Y. & Russo, A. Assessing the contribution of urban green spaces in green infrastructure strategy planning for urban ecosystem conditions and services (Sust. Cities Soc., 2021). https://doi.org/10.1016/j.scs.2021.102772.

    Book 

    Google Scholar 

  • McMahon, E. T. Green infrastructure. Plan. Commission. J. (2000).

  • Mell, I. C. Green Infrastructure Concepts, Perceptions and Its Use in Spatial Planning. Doctor of Philosophy Thesis (Planning and Landscape Newcastle University, 2010).

    Google Scholar 

  • Wang, J. X. & Banzhaf, E. Towards a better understanding of green infrastructure: A critical review. Ecol. Indic. 85, 758–772. https://doi.org/10.1016/j.ecolind.2017.09.018 (2018).

    Article 

    Google Scholar 

  • Young, R., Zanders, J., Lieberknecht, K. & Fassman-Beck, E. A comprehensive typology for mainstreaming urban green infrastructure. J. Hydrol. 519, 2571–2583. https://doi.org/10.1016/j.jhydrol.2014.05.048 (2014).

    Article 

    Google Scholar 

  • Wang, J. X., Xu, C., Pauleit, S., Kindler, A. & Banzhaf, E. Spatial patterns of urban green infrastructure for equity: A novel exploration. J. Clean Prod. 238, 117858. https://doi.org/10.1016/j.jclepro.2019.117858 (2019).

    Article 

    Google Scholar 

  • Cook, E. A. Landscape structure indices for assessing urban ecological networks. Landsc. Urban Plan. 58, 269–280 (2002).

    Article 

    Google Scholar 

  • Vogt, P. & Riitters, K. GuidosToolbox: Universal digital image object analysis. Eur. J. Remote Sens. 50, 352–361. https://doi.org/10.1080/22797254.2017.1330650 (2017).

    Article 

    Google Scholar 

  • Vogt, P., Riitters, K. H., Estreguil, C., Kozak, J. & Wade, T. G. Mapping spatial patterns with morphological image processing. Landsc. Ecol. 22, 171–177. https://doi.org/10.1007/s10980-006-9013-2 (2007).

    Article 

    Google Scholar 

  • Kuttner, M., Hainz-Renetzeder, C., Hermann, A. & Wrbka, T. Borders without barriers—Structural functionality and green infrastructure in the Austrian-Hungarian transboundary region of Lake Neusiedl. Ecol. Indic. 31, 59–72. https://doi.org/10.1016/j.ecolind.2012.04.014 (2013).

    Article 

    Google Scholar 

  • Ma, Q. W., Li, Y. H. & Xu, L. H. Identification of green infrastructure networks based on ecosystem services in a rapidly urbanizing area. J. Clean Prod. 300, 126945. https://doi.org/10.1016/j.jclepro.2021.126945 (2021).

    Article 

    Google Scholar 

  • Furberg, D., Ban, Y. & Mörtberg, U. Monitoring urban green infrastructure changes and impact on habitat connectivity using high-resolution satellite data. Remote Sens. 12, 3072. https://doi.org/10.3390/rs12183072 (2020).

    Article 

    Google Scholar 

  • Barbati, A., Corona, P., Salvati, L. & Gasparella, L. Natural forest expansion into suburban countryside: Gained ground for a green infrastructure?. Urban For. Urban Green. 12, 36–43. https://doi.org/10.1016/j.ufug.2012.11 (2013).

    Article 

    Google Scholar 

  • Fluhrer, T., Chapa, F. & Hack, J. A methodology for assessing the implementation potential for retrofitted and multifunctional urban green infrastructure in public areas of the global south. Sustainability https://doi.org/10.3390/su13010384 (2021).

    Article 

    Google Scholar 

  • Carroll, C., McRae, B. H. & Brookes, A. Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America. Conserv. Biol. 26, 78–87. https://doi.org/10.1111/j.1523-1739.2011.01753.x (2012).

    Article 
    PubMed 

    Google Scholar 

  • Saura, S. & Torne, J. Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity. Environ. Modell. Softw. 24, 135–139 (2009).

    Article 

    Google Scholar 

  • Jaworek-Jakubska, J., Filipiak, M., Michalski, A. & Napierała-Filipiak, A. Spatio-temporal changes of urban forests and planning evolution in a highly dynamical urban area: The case study of Wrocław, Poland. Forests 11, 17. https://doi.org/10.3390/f11010017 (2019).

    Article 

    Google Scholar 

  • Ren, Z. B., He, X. Y., Zheng, H. F. & Wei, H. X. Spatio-temporal patterns of urban forest basal area under China’s rapid urban expansion and greening: Implications for urban green infrastructure management. Forests 9, 272. https://doi.org/10.3390/f9050272 (2018).

    Article 

    Google Scholar 

  • Elliott, R. M. et al. Identifying linkages between urban green infrastructure and ecosystem services using an expert opinion methodology. Ambio 49, 569–583. https://doi.org/10.1007/s13280-019-01223-9 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • García, A. M., Santé, I., Loureiro, X. & Miranda, D. Green infrastructure spatial planning considering ecosystem services assessment and trade-off analysis. Application at landscape scale in Galicia region (NW Spain). Ecosyst. Serv. 43, 101115. https://doi.org/10.1016/j.ecoser.2020.101115 (2020).

    Article 

    Google Scholar 

  • Tiwari, A. & Kumar, P. Integrated dispersion-deposition modelling for air pollutant reduction via green infrastructure at an urban scale. Sci. Total Environ. 723, 138078. https://doi.org/10.1016/j.scitotenv.2020.138078 (2020).

    CAS 
    Article 
    PubMed 

    Google Scholar 

  • Zhang, Y. Q. et al. Unexpected air quality impacts from implementation of green infrastructure in urban environments: A Kansas City case study. Sci. Total Environ. 744, 140960. https://doi.org/10.1016/j.scitotenv.2020.140960 (2020).

    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Alizadehtazi, B., Gurian, P. L. & Montalto, F. A. Observed variability in soil moisture in engineered urban green infrastructure systems and linkages to ecosystem services. J. Hydrol. 590, 125381. https://doi.org/10.1016/j.jhydrol.2020.125381 (2020).

    Article 

    Google Scholar 

  • Dennis, M., Cook, P. A., James, P., Wheater, C. P. & Lindley, S. J. Relationships between health outcomes in older populations and urban green infrastructure size, quality and proximity. BMC Public Health https://doi.org/10.1186/s12889-020-08762-x (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Van Oijstaeijen, W., Van Passel, S. & Cools, J. Urban green infrastructure: A review on valuation toolkits from an urban planning perspective. J. Environ. Manag. 267, 110603. https://doi.org/10.1016/j.jenvman.2020.110603 (2020).

    Article 

    Google Scholar 

  • Majekodunmi, M., Emmanuel, R. & Jafry, T. A spatial exploration of deprivation and green infrastructure ecosystem services within Glasgow city. Urban For. Urban Green. 52, 126698. https://doi.org/10.1016/j.ufug.2020.126698 (2020).

    Article 

    Google Scholar 

  • Liberalesso, T., Oliveira Cruz, C., Matos Silva, C. & Manso, M. Green infrastructure and public policies: An international review of green roofs and green walls incentives. Land Use Pol. 96, 104693. https://doi.org/10.1016/j.landusepol.2020.104693 (2020).

    Article 

    Google Scholar 

  • Lin, H. Y., Qian, J., Yan, L. J. & Huang, S. R. Analysis of spatial-temporal pattern and scenario simulation of green infrastructure in Wuyi County based on morphological spatial pattern analysis and CA-Markov model. Acta Agricult. Zhejiangensis. https://doi.org/10.3969/j.issn.1004-1524.2019.07.21 (2019).

    Article 

    Google Scholar 

  • Mitsova, D., Shuster, W. & Wang, X. H. A cellular automata model of land cover change to integrate urban growth with open space conservation. Landsc. Urban Plan. 99, 141–153. https://doi.org/10.1016/j.landurbplan.2010.10.001 (2011).

    Article 

    Google Scholar 

  • Dennis, M. et al. Mapping urban green infrastructure: A novel landscape-based approach to incorporating land use and land cover in the mapping of human-dominated systems. Land 7, 17. https://doi.org/10.3390/land7010017 (2018).

    Article 

    Google Scholar 

  • Hu, Y. J. et al. Urban expansion and farmland loss in Beijing during 1980–2015. Sustainability 10, 3927. https://doi.org/10.3390/su10113927 (2018).

    Article 

    Google Scholar 

  • Li, W. J., Wang, Y., Xie, S. Y., Sun, R. H. & Cheng, X. Impacts of landscape multifunctionality change on landscape ecological risk in a megacity, China: A case study of Beijing. Ecol. Indic. 117 (2020).

  • Song, W., Pijanowski, B. C. & Tayyebi, A. Urban expansion and its consumption of high-quality farmland in Beijing, China. Ecol. Indic. 54, 60–70. https://doi.org/10.1016/j.ecolind.2015.02.015 (2015).

    Article 

    Google Scholar 

  • Li, Z. Z., Cheng, X. Q. & Han, H. R. Future impacts of land use change on ecosystem services under different scenarios in the ecological conservation area, Beijing, China. Forests https://doi.org/10.3390/f11050584 (2020).

    Article 

    Google Scholar 

  • Liu, D. Y. et al. Interoperable scenario simulation of land-use policy for Beijing-Tianjin-Hebei region, China. Land Use Pol. 75, 155–165. https://doi.org/10.1016/j.landusepol.2018.03.040 (2018).

    Article 

    Google Scholar 

  • Mo, W. B., Wang, Y., Zhang, Y. X. & Zhuang, D. F. Impacts of road network expansion on landscape ecological risk in a megacity, China: A case study of Beijing. Sci. Total Environ. 574, 1000–1011. https://doi.org/10.1016/j.scitotenv.2016.09.048 (2017).

    CAS 
    Article 
    PubMed 

    Google Scholar 

  • Melgani, F. & Bruzzone, L. Classification of hyperspectral remote sensing images with support vector machines. IEEE Trans. Geosci. Remote Sens. 42, 1778–1790. https://doi.org/10.1109/Tgrs.2004.831865 (2004).

    Article 

    Google Scholar 

  • Zhang, C., Wang, T. J., Atkinson, P. M., Pan, X. & Li, H. P. A novel multi-parameter support vector machine for image classification. Int. J. Remote Sens. 36, 1890–1906. https://doi.org/10.1080/01431161.2015.1029096 (2015).

    CAS 
    Article 

    Google Scholar 

  • Peterson, L. K., Bergen, K. M., Brown, D. G., Vashchuk, L. & Blam, Y. Forested land-cover patterns and trends over changing forest management eras in the Siberian Baikal region. For. Ecol. Manag. 257, 911–922. https://doi.org/10.1016/j.foreco.2008.10.037 (2009).

    Article 

    Google Scholar 

  • Sang, L. L., Zhang, C., Yang, J. Y., Zhu, D. H. & Yun, W. J. Simulation of land use spatial pattern of towns and villages based on CA-Markov model. Math. Comput. Model. 54, 938–943. https://doi.org/10.1016/j.mcm.2010.11.019 (2011).

    Article 

    Google Scholar 

  • Liu, D. Y., Zheng, X. Q. & Wang, H. B. Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata. Ecol. Model. 417, 108924. https://doi.org/10.1016/j.ecolmodel.2019.108924 (2020).

    Article 

    Google Scholar 

  • Kazak, J. K. The use of a decision support system for sustainable urbanization and thermal comfort in adaptation to climate change actions-The case of the Wroclaw larger urban zone (Poland). Sustainability https://doi.org/10.3390/su10041083 (2013).

    Article 

    Google Scholar 

  • Sonnenberg, F. A. & Beck, J. R. Markov-models in medical decision-making—A practical guide. Med. Decis. Mak. 13, 322–338. https://doi.org/10.1177/0272989×9301300409 (1993).

    CAS 
    Article 

    Google Scholar 

  • Nadoushan, M. A., Soffianian, A. & Alebrahim, A. Modeling land use/cover changes by the combination of Markov chain and cellular automata Markov CA-Markov models. Int. J. Environ. Health Res. https://doi.org/10.4103/WKMP-0092.159922 (2015).

    Article 

    Google Scholar 

  • Mansour, S., Al-Belushi, M. & Al-Awadhi, T. Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques. Land Use Pol. 91, 104414. https://doi.org/10.1016/j.landusepol.2019.104414 (2020).

    Article 

    Google Scholar 

  • Karimi, H., Jafarnezhad, J., Khaledi, J. & Ahmadi, P. Monitoring and prediction of land use/land cover changes using CA-Markov model: A case study of Ravansar County in Iran. Arab. J. Geosci. https://doi.org/10.1007/s12517-018-3940-5 (2018).

    Article 

    Google Scholar 

  • Mondal, M. S., Sharma, N. C. P. K. G. & Kappas, M. Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results. Egypt. J. Remote Sens. Space Sci. https://doi.org/10.1016/j.ejrs.2016.08.001 (2016).

    Article 

    Google Scholar 

  • Liu, Q. et al. Multi-scenario simulation of land use change and its eco-environmental effect in Hainan Island based on CA-Markov model. Ecol. Environ. Sci. 30, 1522–1531. https://doi.org/10.16258/j.cnki.1674-5906.2021.07.021 (2021).

    Article 

    Google Scholar 

  • Pontius, R. G. Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogramm. Eng. Remote Sens. 68, 1041–1049 (2002).

    Google Scholar 

  • Soille, P. & Vogt, P. Morphological segmentation of binary patterns. Pattern Recognit. Lett. 30, 456–459 (2009).

    Article 

    Google Scholar 

  • Chang, Q., Liu, X. W., Wu, J. S. & He, P. MSPA-based urban green infrastructure planning and management approach for urban sustainability: Case study of Longgang in China. J. Urban Plan. Dev. https://doi.org/10.1061/(asce)up.1943-5444.0000247 (2015).

    Article 

    Google Scholar 

  • Li, K. M. et al. Spatiotemporal evolution characteristics of urban green infrastructure in central Liaoning urban agglomeration during the past 20 years based on landscape ecology and morphology. Acta Ecol. Sin. https://doi.org/10.5846/stxb202007221918 (2021).

    Article 

    Google Scholar 

  • Ning, J. et al. Spatiotemporal patterns and characteristics of land-use change in China during 2010–2015. J. Geogr. Sci. 28, 547–562. https://doi.org/10.1007/s11442-018-1490-0 (2018).

    Article 

    Google Scholar 

  • Sawyer, S. C., Epps, C. W. & Brashares, J. S. Placing linkages among fragmented habitats: Do least-cost models reflect how animals use landscapes?. J. Appl. Ecol. 48, 668–678. https://doi.org/10.1111/j.1365-2664.2011.01970.x (2011).

    Article 

    Google Scholar 

  • Yin, G. Y., Liu, L. M. & Jiang, X. L. The sustainable arable land use pattern under the tradeoff of agricultural production, economic development, and ecological protection—An analysis of Dongting Lake basin, China. Environ. Sci. Pollut. Res. 24, 25329–25345. https://doi.org/10.1007/s11356-017-0132-x (2017).

    Article 

    Google Scholar 


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