Intraurban Analysis of Surface Urban Heat Island From Disagregated Thermal Radiance Images

Autores

  • Vanessa da Silva Brum Bastos vdsbb@st-andrews.ac.uk
    Research and Teaching Fellow na School of Geography and Sustainble Development - University of St. Andrews (United Kingdom https://orcid.org/0000-0002-5865-0204
  • Leila Maria Garcia Fonseca Fonseca leila@dpi.inpe.br
    Pesquisadora do Instituto Nacional de Pesquisas Espaciais – INPE https://orcid.org/0000-0001-6057-7387
  • Carolina Moutinho Duque de Pinho carolina.pinho@ufabc.edu.br
    Professora do curso de Bacharelado em Planejamento Territorial da Universidade Federal do ABC (UFABC). https://orcid.org/0000-0002-7054-4463

Palavras-chave:

land surface temperature, thermal, disaggregation, surface urban heat island

Resumo

Ilhas de calor de superfície (ICS)são áreas com temperature de superfície maior do que as áreas ao redor. Vários estudos tem usado imagens termais de satélite para investigar a influência da urbanização nos padrões de temperatura de superfície; entretanto a baixa resolução espacial dos atuais sensores termais limita a análise dos padrões de variação intraurbana de temperatura de superfície. Com o objetivo de surpassar essa limitação, nós utilizamos o the Enhanced Physical Model (EPM) para gerar dados de temperatura de superfície com maior nível de detalhamento para a cidade de São Paulo- Brasil. Esse método utiliza um modelo de regressão linear e a lei de Planck para combinar NDVI, NDWI e UI para estimar a temperatura de superfície com maior nível de detalhes espaciais.  Primeiro, para calibrar o modelo, nós reamostramos uma banda termal ASTER para 1000 m e utilizamos o método EPM para estimar a banda original de 100 m. A banda termal estimatada de 100 m atingiu um R2= 0.66 em relação a banda termal original. A seguir,  nós aplicamos o método EPM para estimar a temperatura de superfície à 15 m. A imagem de temperatura de superfície de 15 m facilitou a identificação de potenciais ilhas de calor de superfície. O modelo EPM fornece um produto com alto grau de detalhamento espacial, o que permite que pesquisadores identifiquem as mudanças de temperatura de superfície que não seriam evidentes na imagem  termal ASTER original (90 m de resolução espacial). Em suma, o modelo nos permitiu quantificar e mapear a influência de diferentes padrões de urbanização na distribuição dos padrões de temperatura de superfície.

Referências

ADLER-GOLDEN, S. M. et al. Atmospheric Correction for Short-wave Spectral Imagery Based on MODTRAN 4, in: Imaging Spectrometry V, 1999, vol. 3753, no. July, pp. 61–69.

ANIELLO C.; MORGAN, K.; NEWLAND, L. Micro-urban heat island landsat TM and a GIS using, Comput. Geosci., vol. 21, no. 8, p. 4, 1995.

AZEVEDO, T. S. et al Ilhas de calor e aedes aegypti : um estudo preliminar para a cidade de Santa Bárbara d ’ Oeste , sp – Bra , utilizando sensoriamento remoto, in: I Congreso Latinoamericano de Ecología Urbana “ Desafíos y escenarios de desarrollo para las ciudades latino-americanas” , 2012, pp. 174–185.

BECHTEL, B.; BÖHNER, J.; WIESNER, S. Downscaling of diurnal land surface temperature cycles for urban heat island monitoring, pp. 91–94, 2013.

BOGGIONE, G. A. et al, Simulation of a Panchromatic Band by Spectral Combination of Multispectral ETM + Bands, in: International Symposium on Remote Sensing of Environment (ISRSE), 2003, pp. 4–6.

CLIMATE PROTECTION PARTNERSHIP, Reducing Urban Heat Islands : Compendium of Strategies Urban Heat Island Basics, USA, 2010.

CROW, W. T.; WOOD, E. F., The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using Ensemble Kalman filtering : a case study based on ESTAR measurements during SGP97. vol. 26, no. 2003, pp. 137–149, 2005.

DENNISON, P. et al. Wildfire temperature and land cover modeling using hyperspectral data, Remote Sens. Environ., vol. 100, no. 2, pp. 212–222, Jan. 2006.

DOMINGUEZ, A. et al. High-resolution urban thermal sharpener (HUTS), Remote Sens. Environ., vol. 115, no. 7, pp. 1772–1780, Jul. 2011.

ECKMANN, T.; ROBERTS, D.; STILL, C. Using multiple endmember spectral mixture analysis to retrieve subpixel fire properties from MODIS Remote Sens. Environ., vol. 112, no. 10, pp. 3773–3783, Oct. 2008.

EFRAIN, A., B. et al. Urban Heat Island development during the last two decades in Porto Alegre, Brazil and its monitoring, pp. 61–64, 2013.

FUCKNER, M. A., Aplicação de imagens ASTER no estudo do ambiente urbano de São Paulo e Rio de Janeiro, São José dos Campos: INPE, 2008.

GALLO, K. P. et al. Assessment of urban heat islands: a satellite perspective, Atmos. Res., vol. 37, no. 1–3, pp. 37–43, Jul. 1995.

GAO, B. NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sens. Environ., vol. 58, no. 3, pp. 257–266, Dec. 1996.

GARTLAND, L. Heat Island: Understanding and mitigating heat in urban areas. London: EarthScan, 2008, p. 215.

HAJAT, S.; KOSATKY, T. Heat-related mortality: a review and exploration of heterogeneity, J. Epidemiol. Community Health, vol. 64, no. 9, pp. 753–60, Sep. 2010.

HOWARD, L., The climate of London deduced from meteorological observations, made at different places in the neighbourhood of the metropolis. Londres: W.Philips&G.Yards, 1820, p. 410.

IBGE, Síntese dos indicadores sociais: Uma análise das condições de vida da população brasileira 2010, Rio de Janeiro: IBGE, 2010.

JAYAMANNA S., Relation Between Social and Environmental Conditions in Colombo. Sri Lanka and the Urban Index Estimated by Satellite Remote Sensing Data, Int. Arch. Photogramm. Remote Sens., vol. XXXI, no. B7, pp. 321–326, 1996.

JENSEN, J. R., Remote Sensing of the Environment: An Earth Resource Perspective, 2a ed. Englewood Cliffs: Prentice Hall, 2006, p. 592.

KAWASHIMA, S. Relation between Vegetation, Surface Temperature, and Surface Composition in the Tokyo Region during Winter, Remote Sens. Environ., vol. 60, no. April, pp. 52–60, 1994.

KEALY, P. S.; HOOK, S. J. Separating Temperature and Emissivity in Thermal Infrared Multispectral Scanner Data: Implications, IEEE Trans. Geosci. Remote Sens., vol. 31, no. 6, pp. 1155–1164, 1993.

KUSTAS W.; ANDERSON M. Advances in thermal infrared remote sensing for land surface modelling Agric. For. Meteorol., vol. 149, no. 12, pp. 2071–2081, Dec. 2009.

LIU, D.; PU, R., Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval, pp. 2695–2706, 2008.

LIU, D.; ZHU, X., An Enhanced Physical Method for Downscaling Thermal Infrared Radiance, IEEE Geosci. Remote Sens. Lett., vol. 9, no. 4, pp. 690–694, Jul. 2012.

LOMBARDO, M. A. Ilha de Calor nas Metrópoles, vol. 16, no. 1. São Paulo: Hucitec, 1985, p. 244.

MCLAUGHLIN, D., An integrated approach to hydrologic data assimilation: interpolation, smoothing, and filtering, Adv. Water Resour., vol. 25, no. 8–12, pp. 1275–1286, Aug. 2002.

MCMICHAEL A. J. et al. International study of temperature, heat and urban mortality: the ‘ISOTHURM’ project., Int. J. Epidemiol., vol. 37, no. 5, pp. 1121–31, Oct. 2008.

MENDONÇA, F.; DANNI-OLIVEIRA, I. M. Climatologia: Noções básicas de climas do Brasil. São Paulo: Oficina de Textos, 2007, p. 206.

MERLIN O. et al. Multidimensional Disaggregation of Land Surface and Microwave-L Bands vol. 50, no. 5, pp. 1864–1880, 2012.

MEMON, R. A.; LEUNG, D. Y. C.; CHUNHO, L., A review on the generation, determination and mitigation of urban heat island. J. Environ. Sci. (China), vol. 20, no. 1, pp. 120–8, Jan. 2008.

MONTEIRO, C. A. F. Teoria e Clima Urbano. São Paulo: USP, 1976.

NICHOL, J.; WONG, M. S. Mapping urban environmental quality using satellite data and multiple parameters, Environ. Plan. B Plan. Des., vol. 36, no. 1, pp. 170–185, 2009.

NOVO, E. M. L. de M., Sensoriamento remoto: princípios e aplicações, 4a ed. São Paulo: Blucher, 2010, p. 387.

OGASHAWARA, I.; BASTOS V. B., A Quantitative Approach for Analyzing the Relationship between Urban Heat Islands and Land Cover, Remote Sens., vol. 4, no. 12, pp. 3596–3618, Nov. 2012.

OKE, T. R. Boundary Layer Climates, 2nd ed. London: Methuen, 1987, p. 435.

REES, W. G. Physical Principles of Remote Sensing, 2a ed. Cambridge: Cambrydge University Press, 2001, p. 369.

ROTH, M.; OKE, T. R. Satellite-derived urban heat island from three coastal cities and and the utilization of such data in urban climatology, Int. J. Remote Sens., vol. 10, no. 11, pp. 1699–1720, 1989.

ROUSE, J. W. et al., Monitoring vegetation systems in the Great Plains with ERTS, in: Third ERTS Symposium, 1973, vol. 1, pp. 309–317.

SZYMANSKI, J. J. et al. Subpixel temperature retrieval with multispectral sensors, vol. 3717, no. 1981, 1999.

TAN, J. et al. The urban heat island and its impact on heat waves and human health in Shanghai, Int. J. Biometeorol., vol. 54, no. 1, pp. 75–84, Jan. 2010.

VOOGT, J.; OKE, T. Thermal remote sensing of urban climates, Remote Sens. Environ., vol. 86, no. 3, pp. 370–384, Aug. 2003.

WANG, G.; HE, G.; LIU, J. A New Classification Method for High Spatial Resolution Remote, pp. 186–190, 2012.

YANG G. et al. A Novel Method to Estimate Subpixel Temperature by Fusing Solar-Reflective and Thermal-Infrared Remote-Sensing Data with an Artificial Neural Network, IEEE Trans. Geosci. Remote Sens., vol. 48, no. 4, pp. 2170–2178, Apr. 2010.

ZAKŠEK, K.; OŠTIR, K. Downscaling land surface temperature for urban heat island diurnal cycle analysis, Remote Sens. Environ., vol. 117, pp. 114–124, Feb. 2012.

ZHAN, W. Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats, Remote Sens. Environ., vol. 131, no. 19, pp. 119–139, Apr. 2013

ZHOU J. et al. Maximum Nighttime Urban Heat Island (UHI) Intensity Simulation by Integrating Remotely Sensed Data and Meteorological Observations, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 4, no. 1, pp. 138–146, Mar. 2011.

Downloads

Publicado

2021-08-31

Como Citar

da Silva Brum Bastos, V., Fonseca, L. M. G. F., & Moutinho Duque de Pinho, C. (2021). Intraurban Analysis of Surface Urban Heat Island From Disagregated Thermal Radiance Images. Revista Geoaraguaia, 11(Especial), 07–33. Recuperado de https://periodicoscientificos.ufmt.br/ojs/index.php/geo/article/view/12043