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InfraRed Investigation in Singapore (IRIS) Observatory: Urban heat island contributors and mitigators analysis using neighborhood-scale thermal imaging (2210.11663v2)

Published 21 Oct 2022 in physics.ao-ph, cs.CV, and cs.CY

Abstract: This paper studies heat fluxes from contributors and mitigators of urban heat islands using thermal images and weather data. Thermal images were collected from an observatory operating on the rooftop of a building between November 2021 and April 2022. Over the same period, an automatic weather station network was used to measure weather conditions at several locations on a university campus in Singapore. From data collected by the observatory and the automatic weather station network, a method was developed to estimate the heat emitted by building facades, vegetation, and traffic. Before performing the analysis of urban heat fluxes, it was observed that the surface temperature collected from the observatory is sensitive to some variables. After the sensitivity analysis, thermal images were calibrated against measurements of the surface temperature in an outdoor environment. Finally, several contributors and mitigators of urban heat islands were analyzed from heat fluxes assessed with thermal images and weather data. According to thermal images collected by the rooftop observatory, concrete walls are an important contributor to urban heat islands due to the longwave radiation they emit at night. Vegetation, on the other hand, seems to be an effective mitigator because of latent heat fluxes generated by evapotranspiration. Traffic looks to be a negligible source of heat if considered over a small portion of a road. In the future, more efforts can be made to estimate the magnitude of the heat released by an air-conditioning system from thermal images.

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References (79)
  1. H. Ritchie and M. Roser. Urbanization. Our world in data, 2018.
  2. Heatwave and health impact research: A global review. Health & place, 53:210–218, 2018.
  3. Review of methods for retrieving urban heat islands. Materials Today: Proceedings, 27:3004–3009, 2020.
  4. Assessment of urban heat island using satellite remotely sensed imagery: a review. South African Geographical Journal= Suid-Afrikaanse Geografiese Tydskrif, 96(2):198–214, 2014.
  5. Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures. International journal of applied earth observation and geoinformation, 67:30–42, 2018.
  6. Infrared thermography in the built environment: A multi-scale review. Renewable and sustainable energy reviews, 165:112540, 2022.
  7. The urban heat island and its impact on heat waves and human health in Shanghai. International journal of biometeorology, 54(1):75–84, 2010.
  8. D. Wolters and T. Brandsma. Estimating the urban heat island in residential areas in the Netherlands using observations by weather amateurs. Journal of Applied Meteorology and Climatology, 51(4):711–721, 2012.
  9. The Birmingham Urban Climate Laboratory—A high density, urban meteorological dataset, from 2012–2014. Scientific data, 3(1):1–8, 2016.
  10. Crowdsourcing air temperature from citizen weather stations for urban climate research. Urban Climate, 19:170–191, 2017.
  11. A high density urban temperature network deployed in several cities of Eurasian Arctic. Environmental Research Letters, 13(7):075007, 2018.
  12. Is the urban heat island exacerbated during heatwaves in southern Australian cities? Theoretical and Applied Climatology, 137(1):441–457, 2019.
  13. Impact of urban heat island on the variation of heating loads in residential and office buildings in Tianjin. Energy and Buildings, 226:110357, 2020.
  14. M. Szymanowski and M. Kryza. Local regression models for spatial interpolation of urban heat island—an example from Wrocław, SW poland. Theoretical and applied climatology, 108(1):53–71, 2012.
  15. Spatial and temporal characteristics of Beijing urban heat island intensity. Journal of applied meteorology and climatology, 52(8):1803–1816, 2013.
  16. Observations of urban heat island advection from a high-density monitoring network. Quarterly Journal of the Royal Meteorological Society, 142(699):2434–2441, 2016.
  17. Can the crowdsourcing data paradigm take atmospheric science to a new level? a case study of the urban heat island of London quantified using Netatmo weather stations. International Journal of Climatology, 37(9):3597–3605, 2017.
  18. Analysis of local-scale urban heat island characteristics using an integrated method of mobile measurement and GIS-based spatial interpolation. Building and Environment, 117:191–207, 2017.
  19. N. Yadav and C. Sharma. Spatial variations of intra-city urban heat island in megacity Delhi. Sustainable cities and society, 37:298–306, 2018.
  20. Investigating urban heat island through spatial analysis of New York City streetscapes. Journal of cleaner production, 233:972–992, 2019.
  21. The urban climate of Ghent, Belgium: A case study combining a high-accuracy monitoring network with numerical simulations. Urban Climate, 31:100565, 2020.
  22. Improvement of community monitoring network data for urban heat island investigation in Hong Kong. Urban Climate, 37:100852, 2021.
  23. A review on the CFD analysis of urban microclimate. Renewable and Sustainable Energy Reviews, 80:1613–1640, 2017.
  24. P. A. Mirzaei. Cfd modeling of micro and urban climates: Problems to be solved in the new decade. Sustainable Cities and Society, 69:102839, 2021.
  25. J. K. S. Ching. A perspective on urban canopy layer modeling for weather, climate and air quality applications. Urban Climate, 3:13–39, 2013.
  26. G. F. Garuma. Review of urban surface parameterizations for numerical climate models. Urban Climate, 24:830–851, 2018.
  27. Z. Jandaghian and U. Berardi. Comparing urban canopy models for microclimate simulations in Weather Research and Forecasting Models. Sustainable Cities and Society, 55:102025, 2020.
  28. Determination of regional land surface heat flux densities over heterogeneous landscape of heife integrating satellite remote sensing with field observations. Journal of the Meteorological Society of Japan. Ser. II, 80(3):485–501, 2002.
  29. N. Chrysoulakis. Estimation of the all-wave Net Radiation Balance in Urban Environment with the combined use of Terra/ASTER multispectral imagery and in-situ spatial data. J. Geophys. Res, 108(D18):4582, 2003.
  30. Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days. Remote sensing of environment, 97(1):52–67, 2005.
  31. Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature/emissivity products. Journal of Geophysical Research: Atmospheres, 110(D11), 2005.
  32. B. Tang and Z.-L. Li. Estimation of instantaneous net surface longwave radiation from MODIS cloud-free data. Remote Sensing of Environment, 112(9):3482–3492, 2008.
  33. G. Bisht and Rafael L. Bras. Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study. Remote Sensing of Environment, 114(7):1522–1534, 2010.
  34. Estimation of clear-sky land surface longwave radiation from modis data products by merging multiple models. Journal of Geophysical Research: Atmospheres, 117(D22), 2012.
  35. Evaluation of six high-spatial resolution clear-sky surface upward longwave radiation estimation methods with MODIS. Remote Sensing, 12(11):1834, 2020.
  36. Surface flux estimation using radiometric temperature: A dual-temperature-difference method to minimize measurement errors. Water Resources Research, 36(8):2263–2274, 2000.
  37. Surface energy fluxes over El Reno, Oklahoma, using high-resolution remotely sensed data. Water resources research, 39(6), 2003.
  38. Urban surface heat fluxes infrared remote sensing inversion and their relationship with land use types. Journal of Geographical Sciences, 22(4):699–715, 2012.
  39. G. Rios and P. Ramamurthy. A novel model to estimate sensible heat fluxes in urban areas using satellite-derived data. Remote Sensing of Environment, 270:112880, 2022.
  40. S. Kato and Y. Yamaguchi. Analysis of urban heat-island effect using ASTER and ETM+ Data: Separation of anthropogenic heat discharge and natural heat radiation from sensible heat flux. Remote Sensing of Environment, 99(1-2):44–54, 2005.
  41. S. Kato and Y. Yamaguchi. Estimation of storage heat flux in an urban area using ASTER data. Remote Sensing of Environment, 110(1):1–17, 2007.
  42. Modelling of urban sensible heat flux at multiple spatial scales: A demonstration using airborne hyperspectral imagery of Shanghai and a temperature–emissivity separation approach. Remote Sensing of Environment, 112(9):3493–3510, 2008.
  43. Assessing intra-urban surface energy fluxes using remotely sensed ASTER imagery and routine meteorological data: A case study in indianapolis, USA. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(10):4046–4057, 2013.
  44. Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data. Journal of environmental management, 148:143–152, 2015.
  45. S. Chen and D. Hu. Parameterizing anthropogenic heat flux with an energy-consumption inventory and multi-source remote sensing data. Remote Sensing, 9(11):1165, 2017.
  46. Analysis of long-wave radiation from urban facets derived from time-sequential thermography (TST) and 3D city model. In 7th International Conference on Urban Climate, volume 29, 2009.
  47. Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling. Remote Sensing of Environment, 237:111524, 2020.
  48. Urban surface temperature observations from ground-based thermography: intra-and inter-facet variability. Urban Climate, 35:100748, 2021.
  49. Verification and application of continuous surface temperature monitoring technique for investigation of nocturnal sensible heat release characteristics by building fabrics. Energy and Buildings, 53:108–116, 2012.
  50. Analysis of the sensible heat flux from the exterior surface of buildings using time sequential thermography. Atmospheric Environment, 33(24-25):3941–3951, 1999.
  51. The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems. Remote Sensing, 13(8):1426, 2021.
  52. A vegetated urban canopy model for meteorological and environmental modelling. Boundary-Layer Meteorology, 126(1):73–102, 2008.
  53. C. S. B. Grimmond. The suburban energy balance: Methodological considerations and results for a mid-latitude west coast city under winter and spring conditions. International Journal of Climatology, 12(5):481–497, 1992.
  54. Dependence between urban morphology and outdoor air temperature: A tropical campus study using random forests algorithm. Sustainable Cities and Society, 61:102200, 2020.
  55. I. M. Sobol. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and computers in simulation, 55(1-3):271–280, 2001.
  56. P. E. Osborne and T. Alvares-Sanches. Quantifying how landscape composition and configuration affect urban land surface temperatures using machine learning and neutral landscapes. Computers, Environment and Urban Systems, 76:80–90, 2019.
  57. A physically-based model of interactions between a building and its outdoor conditions at the urban microscale. Energy and Buildings, 237:110788, 2021.
  58. MSS. Historical Daily Records, 2022.
  59. Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index. Computer physics communications, 181(2):259–270, 2010.
  60. A synthesis of the push-pull fatigue behaviour of plain and notched stainless steel specimens by using the specific heat loss. Fatigue & Fracture of Engineering Materials & Structures, 36(12):1306–1322, 2013.
  61. R. Raman and A. Thakur. Thermal emissivity of materials. Applied Energy, 12(3):205–220, 1982.
  62. H. N. Ritland. Density phenomena in the transformation range of a borosilicate crown glass. Journal of the American Ceramic Society, 37(8):370–377, 1954.
  63. Effect of composition and temperature on the specific heat of glass. Journal of the American Ceramic Society, 34(9):260–271, 1951.
  64. Optically transparent bamboo with high strength and low thermal conductivity. ACS Applied Materials & Interfaces, 13(1):1662–1669, 2020.
  65. S. Iffat. Relation between density and compressive strength of hardened concrete. Concrete Research Letters, 6(4):182–189, 2015.
  66. G. De Schutter and L. Taerwe. Specific heat and thermal diffusivity of hardening concrete. Magazine of Concrete research, 47(172):203–208, 1995.
  67. An experimental study on thermal conductivity of concrete. Cement and concrete research, 33(3):363–371, 2003.
  68. A. Olioso. Simulating the relationship between thermal emissivity and the normalized difference vegetation index. International Journal of Remote Sensing, 16(16):3211–3216, 1995.
  69. Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation, analysis and validation. Remote Sensing of Environment, 112(12):4318–4332, 2008.
  70. Temperature-land cover interactions: The inversion of urban heat island phenomenon in desert city areas. Remote Sensing of Environment, 130:136–152, 2013.
  71. M Santamouris. Analyzing the heat island magnitude and characteristics in one hundred Asian and Australian cities and regions. Science of the Total Environment, 512:582–598, 2015.
  72. T. R. Oke. Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of climatology, 1(3):237–254, 1981.
  73. Mechanisms of thermoregulation in plants. Plant signaling & behavior, 3(8):595–597, 2008.
  74. Estimation of broadband land surface emissivity from multi-spectral thermal infrared remote sensing. Agronomie, 22(6):695–696, 2002.
  75. Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0–14.0 μ𝜇\muitalic_μm). Remote sensing of environment, 109(4):393–405, 2007.
  76. Estimating broadband emissivity of arid regions and its seasonal variations using thermal infrared remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 46(2):334–343, 2008.
  77. V. Masson. A physically-based scheme for the urban energy budget in atmospheric models. Boundary-layer meteorology, 94(3):357–397, 2000.
  78. Urban energy exchanges monitoring from space. Scientific reports, 8(1):1–8, 2018.
  79. M. Waldemar and D. Klecha. Modeling of atmospheric transmission coefficient in infrared for thermovision measurements. In Proceedings of the Sensor, pages 903–907, 2015.
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