Abstract
Rapid urbanization contributes to the development of phenomena such as climate variability, especially in tropical countries, which negatively impact ecosystems and humans, factors that influence urban sustainability. Additionally, the increase of building construction prevents the flow of wind streams contributing to the retention of pollutants and hot air masses, causing events such as urban heat islands (UHI). This study aimed to analyze from the micro-territorial level, the influence of urban growth on the UHI phenomenon over the last two decades (2000–2020) in the locality of Kennedy, in Bogotá, Colombia. For this purpose, environmental and socio-economic factors were evaluated. For the former, Landsat satellite images and spectral indices were used to evaluate the spatial–temporal variation in the quantity and quality of vegetation, bodies of water, urbanized areas, impervious surfaces, as well as to calculate the land surface temperature and its distribution in the study area. With regard to the socio-economic factors, the variables considered for analysis were population density and energy consumption. Lastly, a principal component analysis was carried out to identify possible associations between the variables and to identify the contribution of each micro-territory to the UHI phenomenon in the study area. The spatio-temporal variations reveal a growing trend over time, especially in impermeable areas where several economic activities, vehicular traffic, and population density converge, which require certain actions to be prioritized in territorial planning and the addition of public green spaces in urban zones.
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References
Aguilar H, Mora R, Vargas C (2014) Atmospheric Correction Methodology for Aster, Rapideye, Spot 2 and Landsat 8 Images With Envi Flaash Module Software. Revista Geográfica de América Central 2(53):39–59. https://doi.org/10.15359/rgac.2-53.2
Alcaldía Mayor de Bogotá (2017) Consumos energéticos urbanos por usos y actividades económicas por UPZ en Bogotá DC 2009–2012–2015. Bogotá.
Amanollahi J, Tzanis C, Ramli MF, Abdullah AM (2016) Urban heat evolution in a tropical area utilizing Landsat imagery. Atmos Res 167:175–182. https://doi.org/10.1016/j.atmosres.2015.07.019
Barreto-Martin C, Ronal, SP, Calderon-Rivera D, Angela JL, Mesa-Fernández D (2021) Spatio-temporal analysis of the hydrological response to land cover changes in the sub-basin of the Chicú river, Colombia. Heliyon, 7. https://doi.org/10.1016/j.heliyon.2021.e07358
Bokaie M, Zarkesh MK, Arasteh PD, Hosseini A (2016) Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use/ Land Cover in Tehran. Sustain Cities Soc 23:94–104. https://doi.org/10.1016/j.scs.2016.03.009
Carpio M, González Á, González M, Verichev K (2020) Influence of pavements on the urban heat island phenomenon: A scientific evolution analysis. Energy and Buildings 226:110379. https://doi.org/10.1016/j.enbuild.2020.110379
Chen XL, Zhao HM, Li PX, Yin ZY (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. https://doi.org/10.1016/j.rse.2005.11.016
Chen X, Zhang Y (2017) Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China. Sustain Cities Soc 32:87–99. https://doi.org/10.1016/j.scs.2017.03.013
de Smith MJ, Goodchild MF, Longley PA, Associates (2021) Geospatial Analysis A Comprehensive Guide to Principles Techniques and Software Tools (6th ed.). Retrieved from https://www.spatialanalysisonline.com/HTML/index.html
Veeduría Distrital (2018) Kennedy: Ficha Local. Retrieved from https://www.veeduriadistrital.gov.co/sites/default/files/files/Ficha%20Localidad%20Kennedy.pdf
Dobbs C, Hernández-Moreno Á, Reyes-Paecke S, Miranda MD (2018) Exploring temporal dynamics of urban ecosystem services in Latin America: The case of Bogota (Colombia) and Santiago (Chile). Ecol Indic 85:1068–1080. https://doi.org/10.1016/j.ecolind.2017.11.062
Escobar Franco LF (2012) Plan Ambiental Local Kennedy 2013–2016. Alcaldía Local de Kennedy, 1–68. Retrieved from http://ambientebogota.gov.co/documents/10157/2883162/PAL+Kennedy+2013-2016.pdf
Estoque RC, Murayama Y (2017) Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015). ISPRS J Photogramm Remote Sens 133:18–29. https://doi.org/10.1016/j.isprsjprs.2017.09.008
Ezimand K, Kakroodi AA, Kiavarz M (2018) The development of spectral indices for detecting built-up land areas and their relationship with land-surface temperature. Int J Remote Sens 39(23):8428–8449. https://doi.org/10.1080/01431161.2018.1488282
Ezimand K, Chahardoli M, Azadbakht M, Matkan AA (2021) Spatiotemporal analysis of land surface temperature using multi-temporal and multi-sensor image fusion techniques. Sustain Cities Soc 64(2020) 102508. https://doi.org/10.1016/j.scs.2020.102508
Gaudencio, Ramos Niembro Fiscal Escalante R, Maqueda Zamora M, Sada Gámiz J, Horacio BS(1999) Variables que influyen en el consumo de energía eléctrica. Retrieved from https://www.ineel.mx/publica/boletin-ef99/aplief99.htm
Grigoraș G, Urițescu B (2019) Land Use/Land Cover changes dynamics and their effects on Surface Urban Heat Island in Bucharest, Romania. Int J Appl Earth Obs Geoinf 80:115–126. https://doi.org/10.1016/j.jag.2019.03.009
Grover A, Singh RB (2015) Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (ndvi): A comparative study of Delhi and Mumbai. Environments - MDPI 2(2):125–138. https://doi.org/10.3390/environments2020125
Gunawardena K, Kershaw T, Steemers K (2019) Simulation pathway for estimating heat island influence on urban/suburban building space-conditioning loads and response to facade material changes. Build Environ 150(January):195–205. https://doi.org/10.1016/j.buildenv.2019.01.006
Guzman LA, Gomez AM, Rivera C (2017) A Strategic Tour Generation Modeling within a Dynamic Land-Use and Transport Framework: A Case Study of Bogota, Colombia. Trans Res Procedia 25:2536–2551. https://doi.org/10.1016/j.trpro.2017.05.292
Ihlen V, USGS (2019a) Landsat 7 (L7) Data Users Handbook p. 151. Retrieved from https://landsat.usgs.gov/sites/default/files/documents/LSDS-1927_L7_Data_Users_Handbook.pdf
Ihlen V, USGS (2019b) Landsat 8 (L8) Data Users Handbook p. 114. Retrieved from https://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf
Kao JY, Kelley GE (1996) Factors affecting the energy consumption of two refrigerator-freezers. Ashraetransaction 102(2):525–545
Kaur R, Pandey P (2022) A review on spectral indices for built - up area extraction using remote sensing technology. Arab J Geosci. https://doi.org/10.1007/s12517-022-09688-x
Kikon N, Singh P, Singh SK, Vyas A (2016) Assessment of urban heat islands (UHI) of Noida City, India using multi-temporal satellite data. Sustain Cities Soc 22:19–28. https://doi.org/10.1016/j.scs.2016.01.005
Litardo J, Palme M, Borbor-Cordova M, Caiza R, Macias J, Hidalgo-Leon R, Soriano G (2020) Urban Heat Island intensity and buildings’ energy needs in Duran, Ecuador: Simulation studies and proposal of mitigation strategies. Sustain Cities Soc 62(July):102387. https://doi.org/10.1016/j.scs.2020.102387
Liu X, Zhou Y, Yue W, Li X, Liu Y, Lu D (2020) Spatiotemporal patterns of summer urban heat island in Beijing, China using an improved land surface temperature. J Clean Prod 257:120529. https://doi.org/10.1016/j.jclepro.2020.120529
Madanian M, Soffianian AR, Soltani Koupai S, Pourmanafi S, Momeni M (2018) The study of thermal pattern changes using Landsat-derived land surface temperature in the central part of Isfahan province. Sustain Cities Soc 39:650–661. https://doi.org/10.1016/j.scs.2018.03.018
Min M, Lin C, Duan X, Jin Z, Zhang L (2019) Spatial distribution and driving force analysis of urban heat island effect based on raster data: A case study of the Nanjing metropolitan area, China. Sustain Cities Soc 50:101637. https://doi.org/10.1016/j.scs.2019.101637
Molina Jaramillo AN (2018) Território, espaços e saúde: Redimensionar o espaço em saúde pública. Cad Saude Publica 34(1):1–12. https://doi.org/10.1590/0102-311x00075117
Musse MA, Barona DA, Santana Rodriguez LM (2018) Urban environmental quality assessment using remote sensing and census data. Int J Appl Earth Obs Geoinf 71:95–108. https://doi.org/10.1016/j.jag.2018.05.010
Ngarambe J, Joen SJ, Han CH, Yun GY (2021) Exploring the relationship between particulate matter, CO, SO2, NO2, O3 and urban heat island in Seoul. Korea Journal of Hazardous Materials 403(2):123615. https://doi.org/10.1016/j.jhazmat.2020.123615
Oke TR (1982) The energetic basis of the urban heat island (Symons Memorial Lecture, 20 May 1980). Q J R Meteorol Soc 108(455):1–24
Oke TR (1988) The urban energy balance. Prog Phys Geogr 12(4):471–508. https://doi.org/10.1177/030913338801200401
Papparelli A, Kurbán A, Cúnsulo M (2011) Isla de calor y ocupación espacial urbana en San Juan, Argentina: análisis evolutivo. Cuadernos De Vivienda y Urbanismo 4(7):110–120
Parvez MI, Aina YA (2019) Exploring the Influence of Land Use Type and Population Density on Urban Heat Island Intensity. Advances in Remote Sensing and Geo Informatics Applications. CAJG 2018. Adv Sci Technol Innov (IEREK Interdisciplinary Series for Sustainable Development) 113–115. https://doi.org/10.1007/978-3-030-01440-7_27
de Faria Peres L, de Lucena AJ, Rotunno Filho OC, de Almeida Franca JR (2018) The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data. Int J Appl Earth Observ Geoinform 64:104–116. https://doi.org/10.1016/j.jag.2017.08.012
Portela CI, Massi KG, Rodrigues T, Alcântara E (2020) Impact of urban and industrial features on land surface temperature: Evidences from satellite thermal indices. Sustain Cities Soc 56(February):102100. https://doi.org/10.1016/j.scs.2020.102100
Ramírez-Aguilar EA, Lucas Souza LC (2019) Urban form and population density: Influences on Urban Heat Island intensities in Bogotá. Colombia Urban Climate 29(May):100497. https://doi.org/10.1016/j.uclim.2019.100497
Rizwan AM, Dennis LYC, Liu C (2008) A review on the generation, determination and mitigation of Urban Heat Island. J Environ Sci 20(1):120–128. https://doi.org/10.1016/S1001-0742(08)60019-4
SDA (2020) Informe Anual de Calidad del aire de Bogotá - 2019. 1–201. Retrieved from http://rmcab.ambientebogota.gov.co/Pagesfiles/IA200531InformeAnualdeCalidaddelAireAño2019.pdf
SDP (2020) Proyecciones de población. Retrieved from http://www.sdp.gov.co/sites/default/files/visor_proyecciones_sdp_v1.1_0.xlsm
Senanayake IP, Welivitiya WDDP, Nadeeka PM (2013) Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data. Urban Climate 5:19–35. https://doi.org/10.1016/j.uclim.2013.07.004
Shen L, Kyllo J, Guo X (2013) An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability. Sustainability 5(2):524–559. https://doi.org/10.3390/su5020524
Singh P, Kikon N, Verma P (2017) Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustain Cities Soc 32:100–114. https://doi.org/10.1016/j.scs.2017.02.018
Soltani A, Sharifi E (2017) Daily variation of urban heat island effect and its correlations to urban greenery: A case study of Adelaide. Frontiers of Architectural Research 6(4):529–538. https://doi.org/10.1016/j.foar.2017.08.001
Ulpiani G (2021) On the linkage between urban heat island and urban pollution island: Three-decade literature review towards a conceptual framework. Sci Total Environ 751:141727. https://doi.org/10.1016/j.scitotenv.2020.141727
UN-Habitat (2019) Implementación de la Agenda 2030 y la Nueva Agenda Urbana. Retrieved from https://www.aciamericas.coop/xxiconferencia/wp-content/uploads/2019/12/05_Quintana-ONU-Habitat.pdf
UNDP (2020) Goal 11: Sustainable cities and communities. Retrieved November 11, 2020, from https://www.undp.org/content/undp/en/home/sustainable-development-goals/goal-11-sustainable-cities-and-communities.html#targets
United Nations (2007) Indicators of Sustainable Development: Guidelines and Methodologies (3th ed.). https://doi.org/10.1016/j.cirpj.2010.03.002
United Nations (2019) World urbanization prospects The 2018 Revision. https://doi.org/10.18356/b9e995fe-en
Wang S, Ma Q, Ding H, Liang H (2018) Detection of urban expansion and land surface temperature change using multi-temporal landsat images. Resour Conserv Recycl 128:526–534. https://doi.org/10.1016/j.resconrec.2016.05.011
WHO (2006) WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide. Global update 2005. Retrieved from https://apps.who.int/iris/bitstream/handle/10665/69477/WHO_SDE_PHE_OEH_06.02_eng.pdf;jsessionid=54263785E93420048269696C80477B40?sequence=1
Wu X, Wang G, Yao R, Wang L, Yu D, Gui X (2019) Investigating surface urban heat islands in South America based on MODIS data from 2003–2016. Remote Sensing 11:1212. https://doi.org/10.3390/rs11101212
Xu H (2006) Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033. https://doi.org/10.1080/01431160600589179
Yao L, Sun S, Song C, Li J, Xu W, Xu Y (2021) Understanding the spatiotemporal pattern of the urban heat island footprint in the context of urbanization, a case study in Beijing. China Applied Geography 133
Yuan F, Bauer ME (2007) Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sens Environ 106(3):375–386. https://doi.org/10.1016/j.rse.2006.09.003
Yue W, Liu Y, Fan P (2012) Assessing spatial pattern of urban thermal environment in Shanghai, China 899–911. https://doi.org/10.1007/s00477-012-0638-1
Yunda JG, Sletto B (2020) Densification, private sector-led development, and social polarization in the global south: Lessons from a century of zoning in Bogotá. Cities 97:102550. https://doi.org/10.1016/j.cities.2019.102550
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sens 24(3):583–594. https://doi.org/10.1080/01431160304987
Zhang X, Estoque RC, Murayama Y (2017) An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables. Sustain Cities Soc 32:557–568. https://doi.org/10.1016/j.scs.2017.05.005
Zhou D, Xiao J, Bonafoni S, Berger C, Deilami K, Zhou Y, Sobrino JA (2019) Satellite remote sensing of surface urban heat islands: Progress, challenges, and perspectives. Remote Sens 11(1):1–36. https://doi.org/10.3390/rs11010048
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All authors contributed to the conception and design of the study. Data collection, analysis and interpretation were performed by Nidia Isabel Molina-Gómez, Laura Marcela Varon-Bravo and Ronal Sierra-Parada. Nidia Isabel Molina-Gómez and Laura Marcela Varon-Bravo wrote the original draft; Nidia Isabel Molina-Gómez, Laura Marcela Varon-Bravo, Ronal Sierra-Parada and P. Amparo López-Jiménez wrote, reviewed and edited the final manuscript; and P. Amparo López-Jiménez was involved in supervision. All authors have read and approved the final manuscript.
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Molina-Gómez, N.I., Varon-Bravo, L.M., Sierra-Parada, R. et al. Urban growth and heat islands: A case study in micro-territories for urban sustainability. Urban Ecosyst 25, 1379–1397 (2022). https://doi.org/10.1007/s11252-022-01232-9
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DOI: https://doi.org/10.1007/s11252-022-01232-9