Skip to main content

Advertisement

SpringerLink
Log in

A quantifiable architecture for urban social-ecological complex landscape pattern

  • Perspective
  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

Context

For urban ecology science to facilitate urban sustainable development by improving urban residents’ material wealth and environmental suitability, it is important to quantitatively analyze urban areas using current and forthcoming data collection and analysis technologies; however, current approaches remain inadequate and are not systematic compared with the relatively mature urban ecology theory.

Objectives

Our study focuses on an improved architecture with five quantifiable layers to better explain the urban ecosystem.

Methods

The design of our quantifiable urban landscape structure roots in the urban ecosystem theory, and recent data and technology advances. Literature review support the main ideas of this work.

Results

The improved urban landscape architecture with five quantifiable layers. The top policy and management layer indicates human will on urban areas with ideal design, while the bottom layer represents the physical background of the urban ecosystem. The middle layers show intensive interactions between humans and nature, which are represented by defined patches of human activities in the social economic layer, cores of human activities in the human activity location layer, and interactions among human activities in the flow layer.

Conclusions

The potential application of this architecture has the potential to advance our knowledge on human and natural interactions and provide both long-term strategies and detailed solutions for enhancing urban sustainability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Bai L, Jiang L, Yang D, Liu Y (2019) Quantifying the spatial heterogeneity influences of natural and socioeconomic factors and their interactions on air pollution using the geographical detector method: a case study of the Yangtze River Economic Belt, China. J Clean Prod 232:692–704

    Article  CAS  Google Scholar 

  • Buyantuyev A, Wu J (2010) Urban heat island and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landsc Ecol 25:17–33

    Article  Google Scholar 

  • Cai J, Huang B, Song Y (2017) Using multi-source geospatial big data to identify the structure of polycentric cities. Remote Sens Environ 202:210–221

  • Davoudi S, Sturzaker J (2017) Urban form, policy packaging and sustainable urban metabolism. Resour Conserv Recycl 120:55–64

    Article  Google Scholar 

  • Einav L, Levin J (2014) Economics in the age of big data. Science 346:745

    Article  Google Scholar 

  • Fagerholm N, Kayhko N, Ndumbaro F, Khamis M (2012) Community stakeholders’ knowledge in landscape assessment—mapping indicators for landscape services. Ecol Indic 18:421–433

    Article  Google Scholar 

  • Flato H (2019) Socioeconomic status, air pollution and desire for local environmental protection in China: insights from national survey data. J Environ Plan Manag 63:1–18

    Google Scholar 

  • Forbe D (2013) Multi-scale analysis of the relationship between economic statistics and DMSP-OLS night light images. Gisci Remote Sens 50:483–499

    Article  Google Scholar 

  • Ghiglino C, Nishimura K, Venditti A (2020) A theory of heterogeneous city growth. I J Econ Theory 16:27–37

    Google Scholar 

  • Gong J, Liu C, Huang C (2020) Advances in urban information extraction from high-resolution remote sensing imagery. Sci China-Earth Sci 63:463–475

    Article  Google Scholar 

  • Grimm N, Foster D, Groffman P, Morgan Grove J, Hopkinson CS, Nadelhoffer KJ, Pataki DE, Peters DPC (2008) The changing landscape: ecosystem responses to urbanization and pollution across climatic and societal gradients. Front Ecol Environ 6:264–272

    Article  Google Scholar 

  • Guinee J, Heijungs R, Huppes G, Zamagni A, Masoni P, Buonamici R, Ekvall T, Rydberg T (2011) Life cycle assessment: past, present, and future. Environ Sci Technol 45:90–96

    Article  CAS  Google Scholar 

  • Han L, Zhou W, Li W, Li L (2014) Impact of urbanization level on urban air quality: a case of fine particles (PM2.5) in Chinese cities. Environ Pollut 206:183–187

    Article  Google Scholar 

  • Han L, Zhou W, Pickett S, Li W, Qian Y (2018) Multicontaminant air pollution in Chinese cities. Bull World Health Organ 96:233–242

    Article  Google Scholar 

  • Han L, Zhou W, Li W, Qian Y (2018) Urbanization strategy and environmental changes: an insight with relationship between population change and fine particulate pollution. Sci Total Environ 642:789–799

    Article  CAS  Google Scholar 

  • Han L, Li W, Zhou W, Li W, Qian Y (2020) China’s complex urban air pollution: an improved understanding with ground operational measurement. Integr Environ Assess Manag 16:306–313

    Article  CAS  Google Scholar 

  • Jiang S, Alves A, Rodrigues F, Ferreira J, Pereira FC (2015) Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput Environ Urban Syst 53:36–46

    Article  Google Scholar 

  • Lai J, Pan J (2020) China’s city network structural characteristics based on population flow during spring festival travel rush: empirical analysis of “tencent migration” big data. J Urban Plan Dev 146:04020018

    Article  Google Scholar 

  • Lowicki D (2019) Landscape pattern as an indicator of urban air pollution of particulate matter in Poland. Ecol Indic 97:17–24

    Article  CAS  Google Scholar 

  • McHale MR, Pickett STA, Barbosa O, Bunn DN, Cadenasso ML, Childers DL, Gartin M, Hess GR, Iwaniec DM, McPhearson T, Peterson MN, Poole AK, Rivers L III, Shutters ST, Zhou W (2015) The new global urban realm: complex, connected, diffuse, and diverse social-ecological systems. Sustainability 7:5211–5240

    Article  Google Scholar 

  • McPhearson T, Pickett S, Grimm N, Niemelä J, Alberti M, Elmqvist T, Weber C, Haase D, Breuste J, Qureshi S (2016) Advancing urban ecology toward a science of cities. Bioscience 66:198–212

    Article  Google Scholar 

  • Munda G (2006) Social multi-criteria evaluation for urban sustainability policies. Land Use Pol 23:86–94

    Article  Google Scholar 

  • Pickett S, Zhou W (2015) Global urbanization as a shifting context for applying ecological science toward the sustainable city. Ecosyst Health Sustain 1:5

    Article  Google Scholar 

  • Pickett S, Buckley G, Kaushal S, Williams Y (2011) Social-ecological science in the humane metropolis. Urban Ecosyst 14:319–339

    Article  Google Scholar 

  • Pickett S, Cadenasso M, Childers D, McDonnel M, Zhou W (2016) Evolution and future of urban ecological sciences: ecology in, of, and for the city. Ecosyst Health Sustain 2:e01229

    Article  Google Scholar 

  • Psyllidis A, Yang J, Bozzon A (2018) Regionalization of social interactions and points-of-interest location prediction with geosocial data. IEEE Access 6:34334–34353

    Article  Google Scholar 

  • Stern D (2004) The rise and fall of environmental Kuznets curve. World Dev 32:1419–1439

    Article  Google Scholar 

  • Tamiminia H, Salehi B, Mahdianpari M, Quackenbush L, Adeli S, Brisco B (2020) Google Earth Engine for geo-big data applications: a meta-analysis and systematic review. ISPRS-J Photogramm Remote Sens 164:152–170

    Article  Google Scholar 

  • Tan X, Han L, Zhang X, Zhou W, Li W, Qian Y (2021) A review of current air quality indexes and improvements under the multi-contaminant air pollution exposure. J Environ Manag 279:111681

    Article  CAS  Google Scholar 

  • United Nations (2018) 2018 revision of World urbanization prospects. https://population.un.org/wup/

  • Vitousek P, Mooney H, Lubchenco J, Melillo J (1997) Human domination of Earth ecosystems. Science 277:494–497

    Article  CAS  Google Scholar 

  • Wang Y, Li G (2017) Mapping urban CO2 emission using DMSP/OLS ‘city lights’ satellite data in China. Environ Plan A 49:248–251

    Article  Google Scholar 

  • Wang Y, Li M (2019) Urban impervious surface detection from remote sensing images: a review of the methods and challenges. IEEE Geosci Remote Sens Mag 7:64–93

    Article  Google Scholar 

  • Wang R, Li F, Hu D, Li B (2011) Understanding eco-complexity: social-economic-natural complex ecosystem approach. Ecol Complex 8:15–29

  • Wen Q, Yang S (2006) Urban air pollution patterns, land use, and thermal landscape: an examination of the linkage using GIS. Environ Monit Assess 117:463–489

    Article  Google Scholar 

  • Wu J (2014) Urban ecology and sustainability: the state-of-the-science and future directions. Landsc Urban Plan 125:209–221

    Article  Google Scholar 

  • Xue B, Li J, Xiao X (2019) Overview of man-land relationship research based on POI data: theory, method and application. Geogr Geo-Inf Sci 35:51–60

    Google Scholar 

  • Zhou N, Williams C (2013) An international review of eco-city theory, indicators and case studies. Lawrence Berkeley National Laboratory. https://escholarship.org/uc/item/4j59k35z

  • Zhou W, Fisher B, Pickett S (2019) Cities are hungry for actionable ecological knowledge. Front Ecol Environ 17:135

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant Nos. 32071579 and 41771201). In addition, the research received financial support from the National Key Research and Development Program (Grant No. 2016YFC0503004), Ministry of Science and Technology of the People's Republic of China, and the Frontier Science Research Project of Chinese Academy of Sciences (QYZDB-SSW-DQC034-2).

Author information

Authors and Affiliations

  1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China

    Xiaorui Tan, Lijian Han, Guodong Li, Weiqi Zhou, Weifeng Li & Yuguo Qian

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Xiaorui Tan, Lijian Han, Weiqi Zhou & Weifeng Li

  3. College of Engineering, Shantou University, Shantou, 515063, China

    Guodong Li

  4. Beijing Urban Ecosystem Research Station, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China

    Weiqi Zhou

Authors
  1. Xiaorui Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lijian Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guodong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weiqi Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weifeng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuguo Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.T. contributed to the analysis and review of the literatures, wrote and revised the manuscript; L.H. contributed to design of the research, literature review, wrote and revised the manuscript; G.L. contributed to literature review and wrote the manuscript; W.Z., W.L., and Y.G. contributed to manuscript revise.

Corresponding author

Correspondence to Lijian Han.

Ethics declarations

Conflict of interest

All authors declare no competing financial interest in this work.

Consent for publication

All author gave their consent for publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tan, X., Han, L., Li, G. et al. A quantifiable architecture for urban social-ecological complex landscape pattern. Landsc Ecol 37, 663–672 (2022). https://doi.org/10.1007/s10980-021-01381-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10980-021-01381-w

Keywords

Search

Navigation