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Thermal Infrared Images to Identify the Contribution of Surface Materials to the Canopy Layer Heat Island in Hot-Humid Urban Areas Cover

Thermal Infrared Images to Identify the Contribution of Surface Materials to the Canopy Layer Heat Island in Hot-Humid Urban Areas

Open Access
|Oct 2020

References

  1. [1] Berger M. A review of measures on reducing heat in tropical and subtropical cities. Sustainable future energy 2012 and 10th SEE Forum: Green, Sustainable, Renewable, Efficient 2012:445–451, November 21–23, Bandar Seri Begawan, Brunei Darussalam.
  2. [2] Tan J., Zheng Y., Tang X., Guo C., Li L., Song G., Zhen X., Yuan D., Kalkstein A. J., Li F., Chen H. The urban heat island and its impact on heat waves and human health in Shanghai. International Journal of Biometeorology 2010:54:75–84. https://doi.org/10.1007/s00484-009-0256-x">https://doi.org/10.1007/s00484-009-0256-x10.1007/s00484-009-0256-x19727842
  3. [3] Hunt A., Watkiss P. Climate change impacts and adaptation in cities: a review of the literature. Climate Change 2011:104:13–49. https://doi.org/10.1007/s10584-010-9975-6">https://doi.org/10.1007/s10584-010-9975-610.1007/s10584-010-9975-6
  4. [4] Cui Y., Yan D., Hong T., Ma J. Temporal and spatial characteristics of the urban heat island in Beijing and the impact on building design and energy performance. Energy 2017:130:286–297. https://doi.org/10.1016/j.energy.2017.04.053">https://doi.org/10.1016/j.energy.2017.04.05310.1016/j.energy.2017.04.053
  5. [5] Oke T., Mills G., Christen A., Voogt J. Urban Climates.1st ed., Cambridge: Cambridge University Press, 2017.10.1017/9781139016476
  6. [6] Shafaghat A., Manteghi G., Keyvanfar A., Bin Lamit H., Saito K., Ossen D. R. Street Geometry Factors Influence Urban Microclimate in Tropical Coastal Cities: A Review. Environmental and Climate Technologies 2016:17(1):61–75. https://doi.org/10.1515/rtuect-2016-0006">https://doi.org/10.1515/rtuect-2016-000610.1515/rtuect-2016-0006
  7. [7] Arnfield A. J. Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology 2003:23:1–26. https://doi.org/10.1002/joc.859">https://doi.org/10.1002/joc.85910.1002/joc.859
  8. [8] Azevedo J. A., Chapman L. Muller C. L. Quantifying the Daytime and Night-Time Urban Heat Island in Birmingham, UK: A Comparison of Satellite Derived Land Surface Temperature and High Resolution Air Temperature Observations. Remote Sensing 2016:8:153. https://doi.org/10.3390/rs8020153">https://doi.org/10.3390/rs802015310.3390/rs8020153
  9. [9] Oke T. R. The Heat Island of the Urban Boundary Layer: Characteristics, Causes and Effects. Dordrecht: Springer Netherlands, 1995.10.1007/978-94-017-3686-2_5
  10. [10] Al-Hafiz B. Contribution to the Study of the Impact of Building Materials on the Urban Heat Island and the Energy Demand of Buildings. Environmental Engineering. Ensa Nantes. 2017.
  11. [11] Wong E., Akbari H., Bell R., Cole D. Urban Heat Island Basics. Heat Island Compendium. San Francisco: United States Environmental Protection Agency (EPA), 2008.
  12. [12] Oke T. R. The energetic basis of the urban heat island. In Quarterly Journal of the Royal Meteorological Society 1982:108:455:1–24. https://doi.org/10.1002/qj.49710845502">https://doi.org/10.1002/qj.4971084550210.1002/qj.49710845502
  13. [13] Roth M. Urban Heat Islands. In Handbook of Environmental Fluid Dynamics Volume Two: Systems, Pollution, Modeling, and Measurements. CRC Press. 2012:162–181. https://doi.org/10.1201/b13691-15">https://doi.org/10.1201/b13691-1510.1201/b13691-15
  14. [14] Georgakis C., Santamouris M. Determination of the Surface and Canopy Urban Heat Islands in Athens Central Zone Using Advance Monitoring. Climate 2017:5(4):97. https://doi.org/10.3390/cli5040097">https://doi.org/10.3390/cli504009710.3390/cli5040097
  15. [15] Olgyay V., Lyndon D., Reynolds J., Yeang K. Design with Climate: Bioclimatic Approach to Architectural Regionalism. New Jersey: Princeton University Press, 1963.
  16. [16] Sen S. Impact of Pavement on the Urban Heat Island. Unpublished thesis, University of Illinois at Urbana Campaign, Illinois, US, 2015.
  17. [17] Pisselo A. L. State of the art on the development of cool coatings for buildings and cities. Solar Energy 2017:144:660–680. https://doi.org/10.1016/j.solener.2017.01.068">https://doi.org/10.1016/j.solener.2017.01.06810.1016/j.solener.2017.01.068
  18. [18] Synnefa A., Santamoris M., Apostolakis K. On the development, optical properties and thermal performance of cool colored coatings for the urban environment. Solar Energy 2007:81(4):488–497. https://doi.org/10.1016/j.solener.2006.08.005">https://doi.org/10.1016/j.solener.2006.08.00510.1016/j.solener.2006.08.005
  19. [19] Fox J., Osmond P., Peters A. The Effect of Building Facade on Outdoor Microclimate–Reflectance Recovery from Terrestrial Multispectral Images Using a Robust Empirical Line Method. Climate 2018:6(3):56. https://doi.org/10.3390/cli6030056">https://doi.org/10.3390/cli603005610.3390/cli6030056
  20. [20] Oke T. R., Mills G., Christen A., Voogt J. A. Urban Climates. Cambridge University Press, 2017.10.1017/9781139016476
  21. [21] Kakoniti A., Georgiou G., Marakkos K., Kumar P., Neophytou M.K.-A. The role of material selection in the urban heat island effect in dry-mid latitude climates. Environmental Fluid Mechanics 2015:16:347–371. 10.1007/s10652-015-9426-z">http://doi.org/10.1007/s10652-015-9426-z10.1007/s10652-015-9426-z
  22. [22] Yavuzturk C., Ksaibati K., Chiasson A. D. Assessment of Temperature Fluctuations in Asphalt Pavements Due to Thermal Environmental Conditions Using a Two-Dimensional, Transient Finite-Difference Approach. Journal of Material in Civil Engineering 2005:17(4):465–475. 10.1061/(ASCE)0899-1561(2005)17:4(465)">http://doi.org/10.1061/(ASCE)0899-1561(2005)17:4(465)10.1061/(ASCE)0899-1561(2005)17:4(465)
  23. [23] Mohajerani A., Bakaric J., Jeffrey-Bailey T. The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete. Journal of Environmental Management 2017:197:522–538. 10.1016/j.jenvman.2017.03.095">http://doi.org/10.1016/j.jenvman.2017.03.09510.1016/j.jenvman.2017.03.09528412623
  24. [24] Golden J. S., Brazel A. J., Salmond J., Laws D. Energy and water sustainability – the role of urban climate change from metropolitan infrastructure. Journal of Engineering and Sustainable Development 2006:1(1):55–70. https://doi.org/10.3992/2166-2517-1.1.55">https://doi.org/10.3992/2166-2517-1.1.5510.3992/2166-2517-1.1.55
  25. [25] Jeanjean A., Olives R., Py X. Selection criteria of thermal mass materials for low-energy building construction applied to conventional and alternative materials. Energy and Buildings 2013:63:36–48. 10.1016/j.enbuild.2013.03.047">http://doi.org/10.1016/j.enbuild.2013.03.04710.1016/j.enbuild.2013.03.047
  26. [26] Lin D. J., Hsu Y. C., Citraningrum A., Adhitana P. The Impact of Different Types of Permeable Pavement Utilization on Air Temperature above the Pavement. Advanced Materials Research 2013:723:678–685. https://doi.org/10.4028/www.scientific.net/AMR.723.678">https://doi.org/10.4028/www.scientific.net/AMR.723.67810.4028/www.scientific.net/AMR.723.678
  27. [27] Voogt J. A., Oke T. R. Thermal remote sensing of urban climates. Remote Sensing Environment 2003:86(3):370–384. https://doi.org/10.1016/S0034-4257(03)00079-8">https://doi.org/10.1016/S0034-4257(03)00079-810.1016/S0034-4257(03)00079-8
  28. [28] Yang Z. Y., Cai W. H., Yang J. Evaluation of MODIS Land Surface Temperature Data to Estimate Near-Surface Air Temperature in Northeast China. Remote Sensing 2017:9(5):410. https://doi.org/10.3390/rs9050410">https://doi.org/10.3390/rs905041010.3390/rs9050410
  29. [29] Tomlinson C. J., Chapman L., Thornes J. E., Baker C. Remote sensing land surface temperature for meteorology and climatology: a review. Meteorological Applications 2011:18:3. https://doi.org/10.1002/met.287">https://doi.org/10.1002/met.28710.1002/met.287
  30. [30] Jeevalaskhmi D., Reddy N., Manikiam B. Land Surface Temperature Retrieval from LANDSAT Data Using Emissivity Estimation. International Journal of Applied Engineering Research 2017:12(20):9679–9687.
  31. [31] Li S., Jiang G.-M. Land Surface Temperature Retrieval From Landsat-8 Data With the Generalized Split-Window Algorithm. Access IEEE 2018:99:18149–18162. https://doi.org/10.1109/access.2018.2818741">https://doi.org/10.1109/access.2018.281874110.1109/ACCESS.2018.2818741
  32. [32] Meng X., Cheng J., Zhao S., Liu S., Yao Y. Estimating Land Surface Temperature from Landsat-8 Data using the NOAA JPSS Enterprise Algorithm. Remote Sensing 2018:11(2):155. https://doi.org/10.3390/rs11020155">https://doi.org/10.3390/rs1102015510.3390/rs11020155
  33. [33] Solanky V., Singh S., Katiyar S. K. Land Surface Temperature Estimation Using Remote Sensing Data. Proceedings of ICWEES-2016. Springer 2018:343–351. https://doi.org/10.1007/978-981-10-5801-1_24">https://doi.org/10.1007/978-981-10-5801-1_2410.1007/978-981-10-5801-1_24
  34. [34] Wang S., He L., Hu W. A Temperature and Emissivity Separation Algorithm for Landsat-8 Thermal Infrared Sensor Data. Remote Sensing 2015:7:8:9904–9927. https://doi.org/10.3390/rs70809904">https://doi.org/10.3390/rs7080990410.3390/rs70809904
  35. [35] Ryu Y.-H., Baik J.-J. Quantitative Analysis of Factors Contributing to Urban Heat Island Intensity. Journal of Applied Meteorology and Climatology 2012:51(5):842–854. https://doi.org/10.1175/jamc-d-11-098.1">https://doi.org/10.1175/jamc-d-11-098.110.1175/JAMC-D-11-098.1
  36. [36] Marwasta D. The Influence of Yogyakarta Urban Physical Development to Residential Comfort. The 1st International Conference on South East Asia Study (ICSEAS), 13–14 October 2016, 2018:175–188. https://doi.org/10.18502/kss.v3i5.2332">https://doi.org/10.18502/kss.v3i5.233210.18502/kss.v3i5.2332
  37. [37] Wicahyani S., Sasongko S. B., Izzati M. Pulau Bahang Kota (Urban Heat Island) di Kota Yogyakarta dan Daerah Sekitarnya Hasil Interpretasi Citra Landsat OLITIRS Tahun 2013. Jurnal Geografi 2014:11(2). https://doi.org/10.15294/jg.v11i2.8027">https://doi.org/10.15294/jg.v11i2.8027
  38. [38] Guntoro I. Analisis Urban Heat Island untuk Pengendalian Pemanasan Global di Kota Yogyakarta Menggunakan Citra Penginderaan jauh. Unpublished thesis, Universitas Sebelas Maret, Indonesia, 2012.
  39. [39] Google Earth. [Online]. [Accessed 09.09.2019]. Available: https://www.google.com/earth/
  40. [40] Dirksen M., Ronda R. J., Theeuwes N. E., Pagani G. A. Sky view factor calculations and its application in urban heat island studies. Urban Climate 2019:30:100498. https://doi.org/10.1016/j.uclim.2019.100498">https://doi.org/10.1016/j.uclim.2019.10049810.1016/j.uclim.2019.100498
  41. [41] Lin P., Gou Z., Lau S. S.-Y., Qin H. The Impact of Urban Design Descriptors on Outdoor Thermal Environment: A Literature Review. Energies 2017:10(12):2151. https://doi.org/10.3390/en10122151">https://doi.org/10.3390/en1012215110.3390/en10122151
  42. [42] De B., Mukherjee M. Optimizing Street Canyon Orientation for Rajarhat, Newtown, Kolkata, India. Environmental and Climate Technologies 2017:21(1):5–17. https://doi.org/10.1515/rtuect-2017-0012">https://doi.org/10.1515/rtuect-2017-001210.1515/rtuect-2017-0012
  43. [43] Lindberg F., Grimmond C. S. Continuous sky view factor maps for high resolution urban digital elevation model. Climate Research 2010:42:177–183. https://doi.org/10.3354/cr00882">https://doi.org/10.3354/cr0088210.3354/cr00882
  44. [44] Shea C., Jamieson B. Some fundamentals of handheld snow surface thermography. The Cryosphere 2011:5:55–66. https://doi.org/10.5194/tc-5-55-2011">https://doi.org/10.5194/tc-5-55-201110.5194/tc-5-55-2011
  45. [45] Usamentiaga R., Venegas P., Guerediaga J., Vega L., Molleda J., Bulnes F. G. Infrared Thermography for Temperature Measurement and Non-Destructive Testing. Sensors 2014:14:12305–12348. https://doi.org/10.3390/s140712305">https://doi.org/10.3390/s14071230510.3390/s140712305416842225014096
  46. [46] Boue C., Fournier D. Infrared thermography measurement of the thermal parameters (effusivity, diffusivity and conductivity) of materials. Quantitative InfraRed Thermography Journal 2009:16(3–4):175–188. https://doi.org/10.3166/qirt.6.175-188">https://doi.org/10.3166/qirt.6.175-18810.3166/qirt.6.175-188
  47. [47] User’s manual FLIR Ex series [Online]. [Accessed 09.09.2019]. Available: https://www.flir.com/globalassets/imported-assets/document/flir-ex-series-user-manual.pdf
  48. [48] U.S. Geological Survey (USGS). Landsat 8 (L8) Data Users Handbook. Sioux Falls: EROS, 2016.
  49. [49] EarthExplorer. [Online]. [Accessed 09.09.2019]. Available: http://earthexplorer.usgs.gov
  50. [50] Rees W. G. Physical Principles of Remote Sensing. Cambridge University Press. Cambridge, England, 1990.
  51. [51] Xu R., Liu J., Xu J. Extraction of High-Precision Urban Impervious Surfaces from Sentinel-2 Multispectral Imagery via Modified Linier Spectral Mixture Analysis. Sensors 2018:18(9):2873. https://doi.org/10.3390/s18092873">https://doi.org/10.3390/s1809287310.3390/s18092873616522230200304
  52. [52] Ahmed B., Kamruzzaman Md., Zhu X., Rahman Md. S., Choi K. Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh. Remote Sensing 2013:5:11:5969–5998. https://doi.org/10.3390/rs5115969">https://doi.org/10.3390/rs511596910.3390/rs5115969
  53. [53] Chen X., Zhao H., Li P., Yong Z. Remote sensing image based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment 2006:104(2):133–146. https://doi.org/10.1016/j.rse.2005.11.016">https://doi.org/10.1016/j.rse.2005.11.01610.1016/j.rse.2005.11.016
  54. [54] Dash P., Göttsche F.-M., Olesen F.-S., Fischer H. Land surface temperature and emissivity estimation from passive sensor data: theory and practice; current trends. International Journal of Remote Sensing 2002:23(13):2563–2594. https://doi.org/10.1080/01431160110115041">https://doi.org/10.1080/0143116011011504110.1080/01431160110115041
  55. [55] Van de Griend A. A., Owe M. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. International Journal of Remote Sensing 1993:6:1119–1131. https://doi.org/10.1080/01431169308904400">https://doi.org/10.1080/0143116930890440010.1080/01431169308904400
  56. [56] Bonafoni S., Baldineli G., Verducci P., Pescuitti A. Remote Sensing Techniques for Urban Heating Analysis: A Case Study of Sustainable Construction at District Level. Sustainability 2017:9(8):1308. https://doi.org/10.3390/su9081308">https://doi.org/10.3390/su908130810.3390/su9081308
  57. [57] Liang S., Fang H., Chen M. Atmospheric Correction of Landsat ETM+ Land Surface Imagery Part I: Methods. IEEE Transaction on Geoscience and Remote Sensing 2001:39:11:2490–2498. 10.1109/36.964986">http://doi.org/10.1109/36.96498610.1109/36.964986
  58. [58] Mooi E., Sarstedt M. A Concise Guide to Market Research. The Process, Data, and Methods Using IBM SPSS Statistics 3rd Edition. 2011. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12541-6">https://doi.org/10.1007/978-3-642-12541-610.1007/978-3-642-12541-6
  59. [59] Janssen J. E., Torborg R. H. Thermal Radiation Properties Survey: A Review of the Literature. Honeywell Research Center, Minneapolis, 1960.
  60. [60] Hansen F. V. Albedos. U.S. Army Research Laboratory. Adelphi, Maryland, 1993.10.21236/ADA268255
  61. [61] American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). ASHRAE Handbook: Fundamentals. Atlanta, GA, U.S., 2001.
  62. [62] Moreira A., Bremm C., Fontana D. C., Kuplich T. M. Seasonal dynamic of vegetation indices as a criterion for grouping grassland typologies. Scientia Agricola 2019:76(1):24–72. https://doi.org/10.1590/1678-992x-2017-0173">https://doi.org/10.1590/1678-992x-2017-017310.1590/1678-992x-2017-0173
  63. [63] Schmidt H., Karnieli A. Remote sensing of the seasonal variability of vegetation in a semi-arid environment. Journal of Arid Environments 2000:45(1):43–59. https://doi.org/10.1006/jare.1999.0607">https://doi.org/10.1006/jare.1999.060710.1006/jare.1999.0607
  64. [64] Yuan F., Bauer M. E. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment 2007:106(3):375–386. https://doi.org/10.1016/j.rse.2006.09.003">https://doi.org/10.1016/j.rse.2006.09.00310.1016/j.rse.2006.09.003
  65. [65] Alavi Panah S. K., Rezael A. A., Azadi Ghatar S., Jeddi Azgandi H. R. Investigation on impervious surface (ISA) and normalized difference vegetation index (NDVI) as representative parameters of the urban heat island by using satellite imageries. Journal of Geography and Planning 2016:20(55):183–207.
DOI: https://doi.org/10.2478/rtuect-2020-0037 | Journal eISSN: 2255-8837 | Journal ISSN: 1691-5208
Language: English
Page range: 604 - 623
Published on: Oct 15, 2020
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year

© 2020 Floriberta Binarti, Pranowo Pranowo, Soesilo Boedi Leksono, published by Riga Technical University
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