IDEAS home Printed from https://ideas.repec.org/p/wiw/wus045/45680654.html
   My bibliography  Save this paper

Investigating social inequality of urban green spacedistribution using Sentinel-2: the case of Vienna

Author

Listed:
  • Wimmer, Lorenz
  • Maus, Victor
  • Luckeneder, Sebastian

Abstract

Urban green space (UGS) is known to provide several benefits for the local population, including regulating local climate and improving human health. The inequality hypothesis claims that these environmental amenities are unequally distributed across space and among different social groups. We propose using a continuous vegetation index derived from satellite imagery to investigate environmental inequality (EI) in UGS distribution. We used spatial autoregressive models to describe the relationship between the normalized difference vegetation index (NDVI) and socioeconomic variables in a case study on the city of Vienna at an unprecedented level of detail (250 m resolution). We show statistically significant evidence for the existence of EI in Vienna. Neighborhoods with a higher share of foreigners have significantly less UGS. Results are robust across spatial aggregation levels and alternative spatial and non-spatial model specifications. We find that our model outperforms alternative ground measure for UGS, as NDVI does not cluster around extreme values. We demonstrate the potential of satellite imagery to investigate complex social problems related to EI in urban areas.

Suggested Citation

  • Wimmer, Lorenz & Maus, Victor & Luckeneder, Sebastian, 2023. "Investigating social inequality of urban green spacedistribution using Sentinel-2: the case of Vienna," Ecological Economic Papers 46/2023, WU Vienna University of Economics and Business.
  • Handle: RePEc:wiw:wus045:45680654
    as

    Download full text from publisher

    File URL: https://research.wu.ac.at/en/publications/d7d6e6d9-2e14-4448-999a-2963c725e6f7
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Auspurg, Katrin & Hinz, Thomas & Schmid, Laura, 2017. "Contexts and conditions of ethnic discrimination: Evidence from a field experiment in a German housing market," Journal of Housing Economics, Elsevier, vol. 35(C), pages 26-36.
    2. Roger S. Bivand & David W. S. Wong, 2018. "Comparing implementations of global and local indicators of spatial association," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 716-748, September.
    3. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    4. Kirsten Schwarz & Michail Fragkias & Christopher G Boone & Weiqi Zhou & Melissa McHale & J Morgan Grove & Jarlath O’Neil-Dunne & Joseph P McFadden & Geoffrey L Buckley & Dan Childers & Laura Ogden & S, 2015. "Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-17, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tibor Sipos & Anteneh Afework Mekonnen & Zsombor Szabó, 2021. "Spatial Econometric Analysis of Road Traffic Crashes," Sustainability, MDPI, vol. 13(5), pages 1-16, February.
    2. Adjin, K. Christophe & Henning, Christian H. C. A., 2019. "Farmers organizations and food availability in Senegal: An impact analysis using a spatial econometrics approach," Working Papers of Agricultural Policy WP2019-07, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    3. Zhao, Nan & Liu, Xiaojie & Pan, Changfeng & Wang, Chenyang, 2021. "The performance of green innovation: From an efficiency perspective," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    4. María Ayuda & Fernando Collantes & Vicente Pinilla, 2010. "From locational fundamentals to increasing returns: the spatial concentration of population in Spain, 1787–2000," Journal of Geographical Systems, Springer, vol. 12(1), pages 25-50, March.
    5. Ruaa Al Juboori & Divya S. Subramaniam & Leslie Hinyard & J. S. Onésimo Sandoval, 2023. "Unveiling Spatial Associations between COVID-19 Severe Health Index, Racial/Ethnic Composition, and Community Factors in the United States," IJERPH, MDPI, vol. 20(17), pages 1-17, August.
    6. Junming Li & Meijun Jin & Honglin Li, 2019. "Exploring Spatial Influence of Remotely Sensed PM 2.5 Concentration Using a Developed Deep Convolutional Neural Network Model," IJERPH, MDPI, vol. 16(3), pages 1-11, February.
    7. Wen-Yong Guo & Josep M. Serra-Diaz & Wolf L. Eiserhardt & Brian S. Maitner & Cory Merow & Cyrille Violle & Matthew J. Pound & Miao Sun & Ferry Slik & Anne Blach-Overgaard & Brian J. Enquist & Jens-Chr, 2023. "Climate change and land use threaten global hotspots of phylogenetic endemism for trees," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    8. Kristien Werck & Bruno Heyndels & Benny Geys, 2008. "The impact of ‘central places’ on spatial spending patterns: evidence from Flemish local government cultural expenditures," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 32(1), pages 35-58, March.
    9. Pede, Valerien O. & Florax, Raymond J.G.M. & Holt, Matthew T., 2009. "A Spatial Econometric Star Model With An Application To U.S. County Economic Growth, 1969–2003," Working papers 48117, Purdue University, Department of Agricultural Economics.
    10. Juergen Deppner & Marcelo Cajias, 2024. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 68(2), pages 235-273, February.
    11. Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach," China Economic Review, Elsevier, vol. 27(C), pages 264-276.
    12. Yuping Deng & Helian Xu, 2015. "International Direct Investment and Transboundary Pollution: An Empirical Analysis of Complex Networks," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    13. Simonetta Longhi & Peter Nijkamp & Jacques Poot, 2006. "Spatial Heterogeneity And The Wage Curve Revisited," Journal of Regional Science, Wiley Blackwell, vol. 46(4), pages 707-731, October.
    14. Eveline Van Leeuwen & Sandy Dall'erba, 2000. "Does Agricultural Employment Benefit From EU Support?," Regional and Urban Modeling 283600099, EcoMod.
    15. Tapsuwan, Sorada & Polyakov, Maksym & Bark, Rosalind & Nolan, Martin, 2015. "Valuing the Barmah–Millewa Forest and in stream river flows: A spatial heteroskedasticity and autocorrelation consistent (SHAC) approach," Ecological Economics, Elsevier, vol. 110(C), pages 98-105.
    16. Cassette, Aurélie & Paty, Sonia, 2006. "La concurrence fiscale entre communes est-elle plus intense en milieu urbain qu’en milieu rural ?," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 78.
    17. Vassilis Tselios, 2008. "Income and educational inequalities in the regions of the European Union: Geographical spillovers under welfare state restrictions," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 403-430, August.
    18. Mur, Jesús & Angulo, Ana, 2009. "Model selection strategies in a spatial setting: Some additional results," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 200-213, March.
    19. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    20. Ingrid Gould Ellen & Stephen L. Ross, 2018. "Race and the City," Working Papers 2018-022, Human Capital and Economic Opportunity Working Group.

    More about this item

    Keywords

    Remote Sensing; Foreigners; NDVI; Environmental Inequality; Spatial Regression; Socioeconomics;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wus045:45680654. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: WU Library (email available below). General contact details of provider: https://research.wu.ac.at/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.