Skip to main content

Advertisement

SpringerLink
Log in

Urban Ecosystems Research in India: Advances and Opportunities

  • REVIEW
  • Published:
Current Landscape Ecology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

This article provides an overview of major research themes that address urban issues from a landscape perspective in India in the last 5 years. Landscape ecology research on urban ecosystems in India is largely focused on four themes—(i) landscape characterization, (ii) urban dynamics, (iii) urban heat island, and (iv) urban green spaces.

Recent Findings

Urban ecosystem research in India is dominated by studies utilizing remote sensing and GIS tools. Moderate resolution satellite data is most preferred to analyze changes within the city and its surroundings. Most of the studies from India are concentrated on urban dynamics and its characterization. In terms of size, studies are skewed, and focus more on larger cities. Also, studies are focused on analyzing changes in one city as compared to multiple cities. Urban growth modelling holds the potential to steer future urban growth policies of governing bodies and develop sustainable cities in the future. However, this is not well explored in Indian context and is still in its nascent stage. Research on thermal environment is concentrated on the nonlinear spatial relationships between multiple factors, and less on their interactions. In terms of green spaces, landscape connectivity and multifunctionality are largely missing. Much of the research addresses the availability of green spaces while accessibility is poorly understood.

Summary

Urban ecosystems in India are still in early developmental stages and research on mending urban issues from landscape perspective is one of the most promising choices. Learnings from past developmental trends, patterns, and policies can have a large impact on how future policies are drawn. For this, it is important to steer research into most pressing urban issues and advance them with new methodologies and actionable inferences. Research on urban problems in India is diversifying over time but needs cautious redirecting to address the needs of fast-paced unplanned urbanization. Studies in the past 5 years show a general trend towards individual case studies which provide quantitative measures of various themes. However, these studies fall short of analyzing government policies and their impacts on urban development and their consequences. Studies should also explore the integration of landscape planning and findings from urban heat island (UHI)– and urban green space (UGS)–related research to improve the living conditions in urban ecosystems. This would also require research on coupling of natural and socio-economic factors. The full potential of landscape research can only be realized by combining different themes of research as urban ecosystem is highly interdependent.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. Wu J. Urban ecology and sustainability: the state-of-the-science and future directions. Landsc Urban Plan [Internet]. Elsevier B.V. 2014;125:209–21. Available from: https://doi.org/10.1016/j.landurbplan.2014.01.018

  2. Grineski SE. Toward an integrative urban ecology: voices from the IGERTs. Bull Ecol Soc Am. 2003;84:200–5.

    Article  Google Scholar 

  3. Pickett STA, Cadenasso ML, Childers DL, Mcdonnell MJ, Zhou W. Evolution and future of urban ecological science: ecology in, of, and for the city. Ecosystem Health and Sustainability [Internet]. 2016;2:e01229. Available from: https://doi.org/10.1002/ehs2.1229

  4. Wu J. Making the case for landscape ecology. Landsc J [Internet]. 2008;27:41–50. Available from: https://www.jstor.org/stable/43323803

  5. United Nations, Department of Economic and Social Affairs PD. World Urbanization Prospects. World urbanization prospects: the 2018 revision (ST/ESA/SER.A/420). New York; 2019.

  6. Grubler A, Fisk D. Energizing sustainable cities: assessing urban energy. Routledge; 2013.

  7. Luo H, Li L, Lei Y, Wu S, Yan D, Fu X, et al. Decoupling analysis between economic growth and resources environment in Central Plains Urban Agglomeration. Science of the Total Environment. Elsevier B.V.; 2021;752.

  8. Singh RB, Srinagesh B, Anand S. Advances in geographical and environmental sciences urban health risk and resilience in Asian cities [Internet]. Available from: http://www.springer.com/series/13113

  9. Agarwal S, Nagendra H. Classification of Indian cities using Google Earth Engine. J Land Use Sci. Taylor and Francis Ltd. 2019;14:425–39.

  10. Mahadevia D, Bhatia N. Towards new urban agenda: a radical reorientation of urban planning education in India. Environment and Urbanization ASIA. Sage Publications India Pvt. Ltd. 2021;12:187–201.

  11. Das A, Das M, Barman H. Access to basic amenities and services to urban households in West Bengal: does its location and size of settlements matter? GeoJournal. Springer Science and Business Media Deutschland GmbH. 2021;86:885–913.

    Google Scholar 

  12. Avashia V, Garg A. Implications of land use transitions and climate change on local flooding in urban areas: an assessment of 42 Indian cities. Land use policy. Elsevier Ltd; 2020;95.

  13. Luck M, Wu J. A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA. Landsc Ecol. 2002;17:327–39.

    Article  Google Scholar 

  14. Grafius DR, Corstanje R, Harris JA. Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis. Landsc Ecol [Internet]. Springer Netherlands; 2018;33:557–73. Available from: https://doi.org/10.1007/s10980-018-0618-z

  15. Wang H, He Q, Liu X, Zhuang Y, Hong S. Global urbanization research from 1991 to 2009 : a systematic research review. Landsc Urban Plan [Internet]. Elsevier B.V. 2012;104:299–309. Available from: https://doi.org/10.1016/j.landurbplan.2011.11.006

  16. Dadashpoor H, Azizi P, Moghadasi M. Land use change, urbanization, and change in landscape pattern in a metropolitan area. Sci Total Environ.[Internet]. Elsevier B.V. 2019;655:707–19. Available from: https://doi.org/10.1016/j.scitotenv.2018.11.267

  17. Shannon CE, Weaver W. The mathematical theory of communication. Bell Syst Tech J. [Internet]. 1948;14:306–17. Available from: https://pubmed.ncbi.nlm.nih.gov/9230594/

  18. BenoitB M. The fractal geometry of nature. New York: W.H. Freeman and Company; 1983.

    Google Scholar 

  19. Herold M, Scepan J, Clarke KC. The use of remote sensing and landscape metrics to describe structures and changes in urban land uses. Environ Plan A. 2002;34:1443–58.

    Article  Google Scholar 

  20. Gustafson EJ. Quantifying landscape spatial pattern: what is the state of the art? Ecosystems. 1998;1:143–56.

    Article  Google Scholar 

  21. • McGarigal K. FRAGSTATS [Internet]. FRAGSTATS HELP,University of Massachusetts, Amherst. 2015. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23917890. This help book provides a detailed account of all the commonly used landscape metrics. This also provides a conceptual understanding of various ecological concepts that are studied using landscape metrics.

  22. Reba M, Seto KC. A systematic review and assessment of algorithms to detect, characterize, and monitor urban land change. Remote Sens Environ [Internet]. Elsevier; 2020;242:111739. Available from: https://doi.org/10.1016/j.rse.2020.111739

  23. Vaz E, Taubenböck H, Kotha M, Arsanjani JJ. Urban change in Goa. India Habitat Int Elsevier Ltd. 2017;68:24–9.

    Article  Google Scholar 

  24. Dutta I, Das A. Exploring the dynamics of urban sprawl using geo-spatial indices: a study of English Bazar Urban Agglomeration. West Bengal Applied Geomatics Springer Verlag. 2019;11:259–76.

    Google Scholar 

  25. Anees MM, Sajjad S, Joshi PK. Characterizing urban area dynamics in historic city of Kurukshetra, India, using remote sensing and spatial metric tools. Geocarto Int Taylor and Francis Ltd. 2019;34:1584–607.

    Article  Google Scholar 

  26. Chatterjee N das, Chatterjee S, Khan A. Spatial modeling of urban sprawl around Greater Bhubaneswar city, India. Model Earth Syst Environ. Springer Science and Business Media Deutschland GmbH. 2016;2.

  27. Lal K, Kumar D, Kumar A. Spatio-temporal landscape modeling of urban growth patterns in Dhanbad Urban Agglomeration, India using geoinformatics techniques. Egypt J Remote Sens Space Sci. Elsevier B.V. 2017;20:91–102.

  28. Aithal BH, Ramachandra TV. Visualization of urban growth pattern in Chennai using geoinformatics and spatial metrics. J Indian Soc Remote Sens. Springer India. 2016;44:617–33.

  29. Anees MM, Mann D, Sharma M, Banzhaf E, Joshi PK. Assessment of urban dynamics to understand spatiotemporal differentiation at various scales using remote sensing and geospatial tools. Remote Sens (Basel). 2020;12.

  30. • Chakraborti S, Das DN, Mondal B, Shafizadeh-Moghadam H, Feng Y. A neural network and landscape metrics to propose a flexible urban growth boundary: a case study. Ecol Indic. Elsevier B.V. 2018;93:952–65. This paper provides a unique methodology to delineate the urban boundary which is usually problematic in urban studies.

  31. Arora A, Pandey M, Mishra VN, Kumar R, Rai PK, Costache R, et al. Comparative evaluation of geospatial scenario-based land change simulation models using landscape metrics. Ecol Indic. Elsevier B.V. 2021;128.

  32. Sathyakumar V, Ramsankaran RAAJ, Bardhan R. Linking remotely sensed Urban Green Space (UGS) distribution patterns and Socio-Economic Status (SES) - a multi-scale probabilistic analysis based in Mumbai, India. GIsci Remote Sens. Taylor and Francis Inc. 2019;56:645–69.

  33. Pramanik S, Punia M. Assessment of green space cooling effects in dense urban landscape: a case study of Delhi, India. Model Earth Syst Environ. Springer Science and Business Media Deutschland GmbH. 2019;5:867–84.

  34. Dutta I, Das A. Exploring the Spatio-temporal pattern of regional heat island (RHI) in an urban agglomeration of secondary cities in Eastern India. Urban Clim. Elsevier B.V. 2020;34.

  35. Pramanik S, Punia M, Yu H, Chakraborty S. Is dense or sprawl growth more prone to heat-related health risks? Spatial regression-based study in Delhi, India. Sustain Cities Soc [Internet]. 2022;81:103808. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2210670722001378

  36. Das A, Basu T. Assessment of peri-urban wetland ecological degradation through importance-performance analysis (IPA): a study on Chatra Wetland, India. Ecol Indic. Elsevier B.V. 2020;114.

  37. Shi W, Goodchild MF, Batty M, Kwan M-P, Zhang A. Urban informatics [Internet]. 2021. Available from: http://www.springer.com/series/14773

  38. Liu X, Huang Y, Xu X, Li X, Li X, Ciais P, et al. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nat Sustain Nature Research. 2020;3:564–70.

    Article  Google Scholar 

  39. Bhat PA, Mir AA, Ahmed P. Urban sprawl and its impact on landuse / land cover dynamics of Dehradun City, India. Int J Sustain Built Environ. [Internet]. The Gulf Organisation for Research and Development; 2017;6:513–21. Available from: https://doi.org/10.1016/j.ijsbe.2017.10.003

  40. Sahana M, Hong H, Sajjad H. Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: a study on Kolkata urban agglomeration, India. Sci Total Environ. Elsevier B.V. 2018;628–629:1557–66.

  41. Mandal J, Ghosh N, Mukhopadhyay A. Urban growth dynamics and changing land-use land-cover of megacity Kolkata and its environs. J Indian Soc Remote Sens. Springer. 2019;47:1707–25.

  42. Dinda S, das Chatterjee N, Ghosh S. An integrated simulation approach to the assessment of urban growth pattern and loss in urban green space in Kolkata, India: a GIS-based analysis. Ecol Indic. Elsevier B.V. 2021;121.

  43. Dhanaraj K, Angadi DP. Urban expansion quantification from remote sensing data for sustainable land-use planning in Mangaluru, India. Remote Sens Appl. Elsevier B.V. 2021;23.

  44. Roy B, Kasemi N. Monitoring urban growth dynamics using remote sensing and GIS techniques of Raiganj Urban Agglomeration, India. Egypt J Remote Sens Space Sci. Elsevier B.V. 2021;24:221–30.

  45. • Kantakumar LN, Kumar S, Schneider K. Spatiotemporal urban expansion in Pune metropolis, India using remote sensing. Habitat Int [Internet]. Elsevier Ltd. 2016;51:11–22. Available from: https://doi.org/10.1016/j.habitatint.2015.10.007. This study identifies different growth phases a city undergoes and showcases the capability of GIS tools in assisting urban planning.

  46. Jokar Arsanjani J, Helbich M, de Noronha VE. Spatiotemporal simulation of urban growth patterns using agent-based modeling: the case of Tehran. Cities Elsevier Ltd. 2013;32:33–42.

    Article  Google Scholar 

  47. Baker WL. A review of models of landscape change. Landsc Ecol: SPB Academic Publishing; 1989.

    Book  Google Scholar 

  48. Sillero N. What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods. Ecol Modell. 2011;222:1343–6.

    Article  Google Scholar 

  49. Mozaffaree Pour N, Oja T. Urban expansion simulated by integrated cellular automata and agent-based models; an example of Tallinn, Estonia. Urban Science. MDPI AG. 2021;5:85.

  50. Lin W, Sun Y, Nijhuis S, Wang Z. Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou Metropolitan Area as a case study. Sci Total Environ. Elsevier B.V. 2020;739.

  51. Irwin EG. New directions for urban economic models of land use change: incorporating spatial dynamics and heterogeneity. J Reg Sci. 2010;50:65–91.

  52. Coppola P, Papa E. Accessibility planning tools for sustainable and integrated land use/transport (LUT) development: an application to Rome. Procedia Soc Behav Sci Elsevier BV. 2013;87:133–46.

    Article  Google Scholar 

  53. Bharath HA, Chandan MC, Vinay S, Ramachandra T v. Modelling urban dynamics in rapidly urbanising Indian cities. Egypt J Remote Sens Space Sci. Elsevier B.V. 2018;21:201–10.

  54. Ramachandra T v., Sellers JM, Bharath HA, Vinay S. Modeling urban dynamics along two major industrial corridors in India. Spat Inf Res. Springer Science and Business Media B.V. 2019;27:37–48.

  55. Siddiqui A, Siddiqui A, Maithani S, Jha AK, Kumar P, Srivastav SK. Urban growth dynamics of an Indian metropolitan using CA Markov and Logistic Regression. Egypt J Remote Sens Space Sci. Elsevier B.V. 2018;21:229–36.

  56. Aarthi AD, Gnanappazham L. Urban growth prediction using neural network coupled agents-based Cellular Automata model for Sriperumbudur Taluk, Tamil Nadu, India. Egypt J Remote Sens Space Sci. Elsevier B.V. 2018;21:353–62.

  57. Kantakumar LN, Kumar S, Schneider K. Spatiotemporal urban expansion in Pune metropolis, India using remote sensing. Habitat Int [Internet]. Elsevier Ltd. 2016;51:11–22. Available from: https://doi.org/10.1016/j.habitatint.2015.10.007

  58. Foley JA, DeFries R, Asner GP, Barford C, Bonan G, Carpenter SR, et al. Global consequences of land use [Internet]. Available from: https://www.science.org

  59. Oke TR. Towards better scientific communication in urban climate. Theor Appl Climatol Springer Wien. 2006;84:179–90.

    Article  Google Scholar 

  60. Deng Q, Zhao J, Liu W, Li Y. Heatstroke at home: prediction by thermoregulation modeling. Build Environ Elsevier Ltd. 2018;137:147–56.

    Article  Google Scholar 

  61. Peng J, Xie P, Liu Y, Ma J. Urban thermal environment dynamics and associated landscape pattern factors: a case study in the Beijing metropolitan region. Remote Sens Environ. Elsevier Inc. 2016;173:145–55.

  62. Voogt JA, Oke TR. Thermal remote sensing of urban climates. Remote Sens Environ. Elsevier Inc. 2003;86:370–84.

  63. Branea A-M, Gaman MS, Badescu S, Ana-Maria B, Mihai-Ionut D, Stelian GM, et al. Challanges regarding the study of urban heat islands. Ruleset for researchers [Internet]. 2016. Available from: https://www.researchgate.net/publication/309740257

  64. Ghosh S, Das A. Modelling urban cooling island impact of green space and water bodies on surface urban heat island in a continuously developing urban area. Model Earth Syst Environ. Springer Science and Business Media Deutschland GmbH. 2018;4:501–15.

  65. Kotharkar R, Bagade A. Evaluating urban heat island in the critical local climate zones of an Indian city. Landsc Urban Plan. Elsevier B.V. 2018;169:92–104.

  66. Aslam MY, Krishna KR, Beig G, Tinmaker MIR, Chate DM. Seasonal variation of urban heat island and its impact on air-quality using SAFAR observations at Delhi, India. Am J Clim Change. Scientific Research Publishing, Inc. 2017;06:294–305.

  67. Kumar R, Mishra V, Buzan J, Kumar R, Shindell D, Huber M. Dominant control of agriculture and irrigation on urban heat island in India. Sci Rep. Nature Publishing Group. 2017;7.

  68. Kumar R, Mishra V. Decline in surface urban heat island intensity in India during heatwaves. Environ Res Commun. Institute of Physics. 2019.

  69. Rajan EHS, Amirtham LR. Urban heat island intensity and evaluation of outdoor thermal comfort in Chennai, India. Environ Dev Sustain. Springer Science and Business Media B.V. 2021;23:16304–24.

  70. Veena K, Parammasivam KM, Venkatesh TN. Urban Heat Island studies: current status in India and a comparison with the International studies. J Earth Syst Sci. Springer. 2020;129.

  71. Sultana S, Satyanarayana ANV. Assessment of urbanisation and urban heat island intensities using landsat imageries during 2000 – 2018 over a sub-tropical Indian City. Sustain Cities Soc. Elsevier Ltd. 2020;52.

  72. Dutta K, Basu D, Agrawal S. Nocturnal and diurnal trends of surface urban heat island intensity: a seasonal variability analysis for smart urban planning. ISPRS Annals of the Photogrammetry. Remote Sensing and Spatial Information Sciences. Copernicus GmbH. 2019;25–33.

  73. Yadav N, Sharma C, Peshin SK, Masiwal R. Study of intra-city urban heat island intensity and its influence on atmospheric chemistry and energy consumption in Delhi. Sustain Cities Soc Elsevier Ltd. 2017;32:202–11.

    Article  Google Scholar 

  74. Saha S, Saha A, Das M, Saha A, Sarkar R, Das A. Analyzing spatial relationship between land use/land cover (LULC) and land surface temperature (LST) of three urban agglomerations (UAs) of Eastern India. Remote Sens Appl. Elsevier B.V. 2021;22.

  75. Singh P, Kikon N, Verma P. Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustain Cities Soc. Elsevier Ltd. 2017;32:100–14.

  76. Mohammad P, Goswami A, Bonafoni S. The impact of the land cover dynamics on surface urban heat island variations in semi-arid cities: a case study in Ahmedabad City, India, using multi-sensor/source data. Sensors (Switzerland). MDPI AG. 2019;19.

  77. • Mohammad P, Goswami A. Quantifying diurnal and seasonal variation of surface urban heat island intensity and its associated determinants across different climatic zones over Indian cities. GIsci Remote Sens. Taylor and Francis Ltd. 2021;58:955–81. This study provides an example of intensive research that has captured the variation in multiple cities around India (n=150). Such studies are necessary to understand how different cities have regional differences and how strategies can be tailored according to them.

  78. Chatterjee S, Khan A, Dinda A, Mithun S, Khatun R, Akbari H, et al. Simulating micro-scale thermal interactions in different building environments for mitigating urban heat islands. Sci Total Environ. Elsevier B.V. 2019;663:610–31.

  79. Turaga RMR, Jha-Thakur U, Chakrabarti S, Hossain D. Exploring the role of Urban Green Spaces in “smartening” cities in India. Impact Assess. Proj. Apprais. Taylor and Francis Ltd. 2020;38:479–90.

  80. Shahtahmassebi AR, Li C, Fan Y, Wu Y, lin Y, Gan M, et al. Remote sensing of urban green spaces: a review. Urban For Urban Green [Internet]. Elsevier GmbH. 2021;57:126946. Available from: https://doi.org/10.1016/j.ufug.2020.126946

  81. Singh KK. Urban green space availability in Bathinda City, India. Environ Monit Assess. Springer International Publishing. 2018;190.

  82. Anguluri R, Narayanan P. Role of green space in urban planning: outlook towards smart cities. Urban For Urban Green Elsevier GmbH. 2017;25:58–65.

    Article  Google Scholar 

  83. Badiu DL, IojǍ CI, PǍtroescu M, Breuste J, Artmann M, NiţǍ MR, et al. Is urban green space per capita a valuable target to achieve cities’ sustainability goals? Romania as a case study. Ecol Indic. Elsevier B.V. 2016;70:53–66.

  84. Lahoti S, Kefi M, Lahoti A, Saito O. Mapping methodology of public urban green spaces using GIS: an example of Nagpur City, India. Sustainability. MDPI AG. 2019;11:2166.

  85. Ghosh P, Singh KK. Spatiotemporal dynamics of urban green and blue spaces using geospatial techniques in Chandannagar city, India Geo J. Springer Science and Business Media Deutschland GmbH. 2021;

  86. Dutta D, Rahman A, Paul SK, Kundu A. Spatial and temporal trends of urban green spaces: an assessment using hyper-temporal NDVI datasets. Geocarto Int. Taylor and Francis Ltd. 2021;

  87. Bardhan R, Debnath R, Bandopadhyay S. A conceptual model for identifying the risk susceptibility of urban green spaces using geo-spatial techniques. Model Earth Syst Environ. Springer Science and Business Media Deutschland GmbH. 2016;2.

  88. Ramaiah M, Avtar R. Urban green spaces and their need in cities of rapidly urbanizing India: a review. Urban Sci. MDPI AG. 2019;3:94.

  89. Gupta K, Roy A, Luthra K, Maithani S, Mahavir. GIS based analysis for assessing the accessibility at hierarchical levels of urban green spaces. Urban For Urban Green. Elsevier GmbH. 2016;18:198–211.

  90. Lindley S, Pauleit S, Yeshitela K, Cilliers S, Shackleton C. Rethinking urban green infrastructure and ecosystem services from the perspective of sub-Saharan African cities. Landsc Urban Plan [Internet]. Elsevier. 2018;180:328–38. Available from: https://doi.org/10.1016/j.landurbplan.2018.08.016

  91. • Wang J. Urban green infrastructure planning: multifunctional networks for sustainable urban development. Technical University of Munich. 2020. This study provides a comprehensive understanding of UGI concepts and their application in growing cities. It especially, focuses on assessing multifunctional green infrastructure and spatial patterns in relation to equitable access for citizens to urban green spaces.

  92. Diksha, Kumar A. Analysing urban sprawl and land consumption patterns in major capital cities in the Himalayan region using geoinformatics. Appl Geogr [Internet]. Elsevier Ltd. 2017;89:112–23. Available from: https://doi.org/10.1016/j.apgeog.2017.10.010

  93. Xu X, Min X. Quantifying spatiotemporal patterns of urban expansion in China using remote sensing data. Cities [Internet]. Elsevier Ltd. 2013;35:104–13. Available from: https://doi.org/10.1016/j.cities.2013.05.002

  94. Zhao S, Zhou D, Zhu C, Qu W, Zhao J, Sun Y. Rates and patterns of urban expansion in China ’ s 32 major cities over the past three decades. Landsc Ecol. Springer Netherlands. 2015;30:1541–59.

  95. Bounoua L, Nigro J, Zhang P, Thome K, Lachir A. Mapping urbanization in the United States from 2001 to 2011. Appl Geogr [Internet]. Elsevier Ltd. 2018;90:123–33. Available from: https://doi.org/10.1016/j.apgeog.2017.12.002

  96. Meerow S, Newell JP. Spatial planning for multifunctional green infrastructure: growing resilience in Detroit. Landsc Urban Plan [Internet]. Elsevier B.V. 2017;159:62–75. Available from: https://doi.org/10.1016/j.landurbplan.2016.10.005

  97. Zhou W, Wang J, Cadenasso ML. Effects of the spatial configuration of trees on urban heat mitigation: a comparative study. Remote Sens Environ [Internet]. Elsevier Inc. 2017;195:1–12. Available from: https://doi.org/10.1016/j.rse.2017.03.043

  98. Wesley EJ, Brunsell NA. Greenspace pattern and the surface urban heat island: a biophysically-based approach to investigating the effects of urban landscape configuration. Remote Sens (Basel). 2019;11.

  99. Masoudi M, Tan PY. Multi-year comparison of the effects of spatial pattern of urban green spaces on urban land surface temperature. Landsc Urban Plan Elsevier. 2019;184:44–58.

    Article  Google Scholar 

  100. Estoque RC, Murayama Y, Myint SW. Effects of landscape composition and pattern on land surface temperature: an urban heat island study in the megacities of Southeast Asia. Sci Total Environ. [Internet]. Elsevier B.V. 2017;577:349–59. Available from: https://doi.org/10.1016/j.scitotenv.2016.10.195

  101. Wang J, Xu C, Pauleit S, Kindler A, Banzhaf E. Spatial patterns of urban green infrastructure for equity: a novel exploration. J Clean Prod. 2019;238.

  102. Sundara Rajoo K, Singh Karam D, Abdu A, Rosli Z, James Gerusu G. Addressing psychosocial issues caused by the COVID-19 lockdown: can urban greeneries help? Urban For Urban Green [Internet]. Elsevier GmbH. 2021;65:127340. Available from: https://doi.org/10.1016/j.ufug.2021.127340

  103. Wortzel JD, Wiebe DJ, DiDomenico GE, Visoki E, South E, Tam V, et al. Association between urban greenspace and mental wellbeing during the COVID-19 pandemic in a U.S. cohort. Front sustain cities. 2021;3:1–11.

  104. Jabbar M, Yusoff MM, Shafie A. Assessing the role of urban green spaces for human well-being: a systematic review. Geo J [Internet]. Springer Netherlands. 2021;7. Available from: https://doi.org/10.1007/s10708-021-10474-7

  105. Berdejo-Espinola V, Suárez-Castro AF, Amano T, Fielding KS, Oh RRY, Fuller RA. Urban green space use during a time of stress: a case study during the COVID-19 pandemic in Brisbane. Australia People and Nature. 2021;3:597–609.

    Article  PubMed  Google Scholar 

  106. Korpilo S, Kajosaari A, Rinne T, Hasanzadeh K, Raymond CM, Kyttä M. Coping with crisis: green space use in Helsinki before and during the COVID-19 pandemic. Frontiers in Sustainable Cities. 2021;3:1–13.

    Article  Google Scholar 

  107. Labib SM, Lindley S, Huck JJ. Spatial dimensions of the influence of urban green-blue spaces on human health: a systematic review. Environ Res [Internet]. Elsevier Inc. 2020;180:108869. Available from: https://doi.org/10.1016/j.envres.2019.108869

Download references

Author information

Authors and Affiliations

  1. School of the Environment, Yale University, New Haven, CN, 06511, USA

    Mangalasseril Mohammad Anees

  2. Centre for Econics and Ecosystem Management, Eberswalde University for Sustainable Development, 16225, Eberswalde, Germany

    Deepika Mann

  3. Special Centre for Disaster Research, Jawaharlal Nehru University, New Delhi, India, 110066

    Susanta Mahato

Authors
  1. Mangalasseril Mohammad Anees
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deepika Mann
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Susanta Mahato
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mangalasseril Mohammad Anees.

Ethics declarations

Conflict of Interest 

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Anees, M.M., Mann, D. & Mahato, S. Urban Ecosystems Research in India: Advances and Opportunities. Curr Landscape Ecol Rep 8, 34–48 (2023). https://doi.org/10.1007/s40823-022-00083-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40823-022-00083-6

Keywords

Search

Navigation