Skip to main content

Cooling Potential Simulation of Urban Green Space Using Remote Sensing and Web-Based GIS Integration in Panat Nikom Municipality, Thailand

  • Chapter
  • First Online:
Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management

Part of the book series: Water Science and Technology Library ((WSTL,volume 105))

  • 426 Accesses

Abstract

The most important local and global change driving force is urbanization because it progressively replaces natural surfaces with built surfaces. These causes enhance the urban heat island phenomenon where the temperature in the urban area is higher than the temperature in the countryside around the city. Increasing urban green space can play an important role in reducing the urban heat island effects and providing comfort to the nearby area. It can also contribute to the United Nations Sustainable Development Goals (SDGs), especially SDG 11, which aims to make cities and human settlements inclusive, safe, resilient, and sustainable. This study aimed to develop a web-based simulation platform for examining local temperature changes from the change in the proportion of green space in the city. The Worldview-3 imagery was used for green space area extraction through NDVI and land surface temperature from Landsat 8 OLI. The relationship between surface temperature and the green area was studied with NDVI using regression analysis to develop an equation for land surface temperature calculated according to the changes in the green area. The web-based GIS platform was developed using open source with Geoserver and LeafletJS using an equation developed for exploring and simulating the cooling potential of urban green spaces through a web user interface. The temperature was more related to the NDVI, which can refer to the quality of the green area rather than the size of the green space. It was concluded that the cooling potential of such green areas is determined mainly by the quantity and quality of the green space, which is essential to increasing or decreasing the local temperature and ecological environment. Setting the target for reducing the temperature to the comfort level might require tools that allow urban policymakers to know the level of temperature in the area and the temperature drop changes by increasing green area proportion to determine how much more green space the city has needs.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abutaleb K, Freddy Mudede M, Nkongolo N, Newete SW (2021) Estimating urban greenness index using remote sensing data: a case study of an affluent vs poor suburbs in the city of Johannesburg. Egypt J Remote Sensing Space Sci 24(3, Part 1):343–351. https://doi.org/10.1016/j.ejrs.2020.07.002

  • Akbar TA et al (2019) Investigative spatial distribution and modelling of existing and future urban land changes and its impact on urbanization and economy. Remote Sens 11(2)

    Google Scholar 

  • Amindin A et al (2021) Spatial and temporal analysis of urban heat island using Landsat satellite images. Environ Sci Pollut Res

    Google Scholar 

  • Amorim MCDCT, Dubreuil V (2017) Intensity of urban heat islands in tropical and temperate climates. Climate 5(4):91

    Google Scholar 

  • Aram F et al (2019) Urban green space cooling effect in cities. Heliyon 5(4):e01339

    Article  Google Scholar 

  • Arnfield AJ (2003) Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol 23(1):1–26

    Article  Google Scholar 

  • Athukorala D, Murayama Y (2021) Urban heat island formation in greater Cairo: spatio-temporal analysis of daytime and nighttime land surface temperatures along the urban-rural gradient. Remote Sens 13(7)

    Google Scholar 

  • Avdan U, Jovanovska G (2016) Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. J Sens 2016

    Google Scholar 

  • Best JW (1977) Research in education, 3rd edn., vol xii. Prentice-Hall, Englewood Cliffs, 403 p

    Google Scholar 

  • Best JW, Kahn JV (1977) Research in education. Allyn and Bacon, Boston, p 384

    Google Scholar 

  • Buo I et al (2021) Estimating the expansion of urban areas and urban heat islands (UHI) in Ghana: a case study. Nat Hazards 105(2):1299–1321

    Article  Google Scholar 

  • Busato F, Lazzarin RM, Noro M (2014) Three years of study of the urban heat island in Padua: experimental results. Sustain Cities Soc 10:251–258

    Article  Google Scholar 

  • Cao X et al (2010) Quantifying the cool island intensity of urban parks using ASTER and IKONOS data. Landsc Urban Plan 96(4):224–231

    Article  Google Scholar 

  • Chen XL et al (2006) Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens Environ 104(2):133–146

    Article  Google Scholar 

  • Collier CG (2006) The impact of urban areas on weather. Q J R Meteorol Soc 132(614):1–25

    Article  Google Scholar 

  • Dorman M (2020) Introduction to web mapping, 1st edn. CRC Press, Boca Raton

    Google Scholar 

  • Duarte L et al (2021) An open source GIS application for spatial assessment of health care quality indicators. Isprs Int J Geo-Inf 10(4)

    Google Scholar 

  • Ekwe MC et al (2021) The effect of green spaces on the urban thermal environment during a hot-dry season: a case study of Port Harcourt, Nigeria. Environ Dev Sustain 23(7):10056–10079

    Article  Google Scholar 

  • Ersoy E (2019) Landscape pattern and urban cooling islands. Fresenius Environ Bull 28(3):1943–1951

    CAS  Google Scholar 

  • Evans B, Sabel CE (2012) Open-source web-based geographical information system for health exposure assessment. Int J Health Geogr 11(1):2

    Article  Google Scholar 

  • Evans B et al (2013) Governing sustainable cities. Routledge, London

    Google Scholar 

  • Farkas G (2017) Applicability of open-source web mapping libraries for building massive web GIS clients. J Geogr Syst 19(3):273–295

    Article  Google Scholar 

  • Fernando HJS (2013) Handbook of environmental fluid dynamics. CRC Press, Taylor & Francis Group, Boca Raton, FL

    Google Scholar 

  • Fryd O (2011) The role of urban green space and trees in relation to climate change. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour 6

    Google Scholar 

  • GeoServer (2013) GeoServer-NGA-2020-12-14.jpg. www.geosolutionsgroup.com; www.geosolutionsgroup.com

  • Gonçalves A et al (2018) Urban cold and heat island in the City of Bragança (Portugal). Climate 6(3):70

    Article  Google Scholar 

  • Grilo F et al (2020) Using green to cool the grey: modelling the cooling effect of green spaces with a high spatial resolution. Sci Total Environ 724

    Google Scholar 

  • Guha S (2021) Dynamic seasonal analysis on LST-NDVI relationship and ecological health of Raipur City, India. Ecosyst Health Sustain 7(1)

    Google Scholar 

  • Hulley GC et al (2019) In: Hulley GC, Ghent D (eds) 3-land surface temperature. In: Taking the temperature of the earth. Elsevier, Amsterdam, pp 57–127

    Google Scholar 

  • Jelokhani-Niaraki M, Malczewski J (2015) Decision complexity and consensus in web-based spatial decision making: a case study of site selection problem using GIS and multicriteria analysis. Cities 45:60–70

    Article  Google Scholar 

  • Kanda M (2007) Progress in urban meteorology: a review. J Meteorol Soc Jpn 85B:363–383

    Article  Google Scholar 

  • Karnieli A et al (2010) Use of NDVI and land surface temperature for drought assessment: merits and limitations. J Clim 23(3):618–633

    Article  Google Scholar 

  • Lei LJ, Wang WC (2019) Analysis of urban landscape pattern and eco-environment benefit based on heat island effect-with Beijing, China as an example. Appl Ecol Environ Res 17(6):14577–14586

    Article  Google Scholar 

  • Li H (2016) Chapter 2—literature review on cool pavement research. In: Li H (ed) Pavement materials for heat island mitigation. Butterworth-Heinemann, Boston, pp 15–42

    Chapter  Google Scholar 

  • Liao W et al (2021) A simple and easy method to quantify the cool island intensity of urban greenspace. Urban For Urban Greening 62:127173

    Article  Google Scholar 

  • Lo CP, Quattrochi DA, Luvall JC (1997) Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. Int J Remote Sens 18(2):287–304

    Article  Google Scholar 

  • Ma Y et al (2021) Cooling effect of different land cover types: a case study in Xi’an and Xianyang, China. Sustainability 13:1099

    Article  Google Scholar 

  • Mirzaei M et al (2020) Urban heat island monitoring and impacts on citizen's general health status in Isfahan metropolis: a remote sensing and field survey approach. Remote Sens 12(8)

    Google Scholar 

  • Muenchow J, Schafer S, Kruger E (2019) Reviewing qualitative GIS research—toward a wider usage of open-source GIS and reproducible research practices. Geogr Compass 13(6)

    Google Scholar 

  • NASA (2021) Landsat 8 overview [cited 2021 16/07/2021]. Available from: https://landsat.gsfc.nasa.gov/landsat-8/landsat-8-overview

  • Nasrallah HA, Brazel AJ, Balling RC (1990) Analysis of the Kuwait-City urban heat-island. Int J Climatol 10(4):401–405

    Google Scholar 

  • Neene V, Kabemba M (2017) Development of a mobile GIS property mapping application using mobile cloud computing. Int J Adv Comput Sci Appl 8(10):57–66

    Google Scholar 

  • Ng E et al (2012) A study on the cooling effects of greening in a high-density city: an experience from Hong Kong. Build Environ 47:256–271

    Article  Google Scholar 

  • Nichol JE, Wong MS (2008) Spatial variability of air temperature and appropriate resolution for satellite-derived air temperature estimation. Int J Remote Sens 29(24):7213–7223

    Article  Google Scholar 

  • Oke TR (1981) Canyon geometry and the Nocturnal urban heat-island—comparison of scale model and field observations. J Climatol 1(3):237–0

    Google Scholar 

  • Oke TR (1982) The energetic basis of the urban heat-island. Q J R Meteorol Soc 108(455):1–24

    Google Scholar 

  • Oke TR (1987) Boundary layer climates, 2nd edn, vol xxiv. Methuen, London, 435 p

    Google Scholar 

  • Oke T (2002) Urban heat island: an overview of the research and its implications. In: Urban heat island summit 2002, City of Toronto; The clean air PARNERSHIP: urban heat island summit, Metro Hall Council Chamber, Toronto, 1st–3rd May, 2002

    Google Scholar 

  • Oke TR et al (1991) Simulation of surface urban heat islands under ideal conditions at night. 2. Diagnosis of causation. Bound Layer Meteorol 56(4):339–358

    Google Scholar 

  • Olyazadeh R et al (2017) An offline-online web-GIS Android application for fast data acquisition of landslide hazard and risk. Nat Hazard 17(4):549–561

    Article  Google Scholar 

  • Omidipoor M et al (2019) A GIS-based decision support system for facilitating participatory urban renewal process. Land Use Policy 88:104150

    Article  Google Scholar 

  • Rahaman S et al (2021) Spatio-temporal changes of green spaces and their impact on urban environment of Mumbai, India. Environ Dev Sustain 23(4):6481–6501

    Article  Google Scholar 

  • Rajkumar R, Elangovan K (2020) Impact of urbanisation on formation of urban heat island in Tirupur region using geospatial technique. Indian J Geo-Mar Sci 49(9):1593–1598

    Google Scholar 

  • Roth M (2000) Review of atmospheric turbulence over cities. Q J R Meteorol Soc 126:941–990

    Article  Google Scholar 

  • Rouse JW et al (1974) Monitoring vegetation systems in the Great Plains with ERTS. NASA special publication, vol 351, p 309

    Google Scholar 

  • Shafizadeh-Moghadam H et al (2020) Modeling the spatial variation of urban land surface temperature in relation to environmental and anthropogenic factors: a case study of Tehran, Iran. GIScience Remote Sens 57(4):483–496

    Article  Google Scholar 

  • Shahfahad et al (2021) Modelling urban heat island (UHI) and thermal field variation and their relationship with land use indices over Delhi and Mumbai metro cities. Environ Dev Sustain

    Google Scholar 

  • Shorabeh SN et al (2020) Modelling the intensity of surface urban heat island and predicting the emerging patterns: landsat multi-temporal images and Tehran as case study. Int J Remote Sens 41(19):7384–7410

    Google Scholar 

  • Siddiqui A et al (2021) Bangalore: urban heating or urban cooling? Egypt J Remote Sens Space Sci 24(2):265–272

    Google Scholar 

  • Silva AGL, Torres MCA (2021) Proposing an effective and inexpensive tool to detect urban surface temperature changes associated with urbanization processes in small cities. Build Environ 192

    Google Scholar 

  • Stisen S et al (2007) Estimation of diurnal air temperature using MSG SEVIRI data in West Africa. Remote Sens Environ 110(2):262–274

    Article  Google Scholar 

  • Sun YW et al (2021) Assessing the cooling efficiency of urban parks using data envelopment analysis and remote sensing data. Theor Appl Climatol

    Google Scholar 

  • Taha H (1997) Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energy Build 25(2):99–103

    Article  Google Scholar 

  • Tawfeek YQ, Jasim FH, Al-Jiboori MH (2020) A stud of canopy urban heat island of Baghdad, Iraq. Asian J Atmos Environ 14(3):280–288

    Google Scholar 

  • Uritescu B (2017) The influences of land use on the urban heat island in Bucharest, vol 2017, pp 259–265

    Google Scholar 

  • U.S. Environmental Protection Agency (2021) Urban heat islands. Available from: https://www.usgs.gov/media/images/urban-heat-islands

  • Vaz Monteiro M et al (2016) The impact of greenspace size on the extent of local nocturnal air temperature cooling in London. Urban For Urban Greening 16:160–169

    Article  Google Scholar 

  • Weng QH (2009) Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS J Photogramm Remote Sens 64(4):335–344

    Article  Google Scholar 

  • Weng Q (2019) Land surface temperature data generation. In: Techniques and methods in urban remote sensing, pp 91–127

    Google Scholar 

  • World Health Organization (2013) Urban population growth. Global Health Observatory. Available from: http://www.who.int/gho/urban_health/situation_trends/urban_population_growth_text/en/

  • Wu H et al (2011) Monitoring and evaluating the quality of web map service resources for optimizing map composition over the internet to support decision making. Comput Geosci 37(4):485–494

    Article  Google Scholar 

  • Wu C et al (2021) Estimating the cooling effect of pocket green space in high density urban areas in Shanghai, China. http://doi.org/10.3389/fenvs.2021.657969

  • Wuebbles DJ et al (2017) Climate science special report: fourth national climate assessment (NCA4), vol I

    Google Scholar 

  • Yang CB et al (2017) The cooling effect of urban parks and its monthly variations in a snow climate city. Remote Sens 9(10)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chanida Suwanprasit .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Suwanprasit, C., Homhuan, S., Charoentrakulpeeti, W. (2022). Cooling Potential Simulation of Urban Green Space Using Remote Sensing and Web-Based GIS Integration in Panat Nikom Municipality, Thailand. In: Singh, V.P., Yadav, S., Yadav, K.K., Corzo Perez, G.A., Muñoz-Arriola, F., Yadava, R.N. (eds) Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management. Water Science and Technology Library, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-031-14096-9_16

Download citation

Publish with us

Policies and ethics