CoChat
Sign Up
Cited by 119

Spatio-Temporal Modeling of the Urban Heat Island in the Phoenix Metropolitan Area: Land Use Change Implications

Wang, Chuyuan, Myint, Soe, Wang, Zhihua, Song, Jiyun·2016·Remote Sensing
DOI 10.3390/rs8030185
Open this paper in CoChat — free account

Abstract

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/rs8030185

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The combination of urban surfaces and reduced vegetation creates steep temperature gradients between densely populated urban centers and their surroundings, with urban areas containing higher temperatures.

    “The combination of urban surfaces and reduced vegetation create steep temperature gradients between densely populated urban centers and their surroundings, with urban areas containing higher temperatures (Trlica et al., 2017; Wang et al., 2016).”

    From Review of emerging contaminants in green stormwater infrastructure: antibiotic resistance genes, microplastics, tire wear particles, PFAS, and temperature (2024) · cites this paper as Wang et al., 2016

    The Discussion (section 5; page unavailable) links impervious surfaces and reduced vegetation to higher land-surface temperatures and urban heat-island effects. It does not establish steep gradients centered on densely populated urban cores; instead, it says the largest increases in urban–rural temperature difference occurred on the city outskirts, not within developed areas. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 52

  1. Hansen, J.; Ruedy, R.; Glascoe, J.; Sato, M. GISS analysis of surface temperature change. J. Geophys. Res. 1999, 104, 30997-31022. [CrossRef] · DOI
  2. Akbari, H.; Pomerantz, M.; Taha, H. Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Sol. Energy 2001, 70, 295-310. [CrossRef] · DOI
  3. Kolokotroni, M.; Ren, X.; Davies, M.; Mavrogianni, A. London's urban heat island: Impact on current and future energy consumption in office buildings. Energy Build. 2012, 47, 302-311. [CrossRef] · DOI
  4. Guhathakurta, S.; Gober, P. The impact of the Phoenix urban heat island on residential water use. J. Am. Plan. Assoc. 2007, 73, 317-329. [CrossRef] · DOI
  5. Brazel, A.; Gober, P.; Lee, S.-J.; Grossman-Clarke, S.; Zehnder, J.; Hedquist, B.; Comparri, E. Determinants of changes in the regional urban heat island in metropolitan Phoenix (Arizona, USA) between 1990 and 2004. Clim. Res. 2007, 33, 171-182. [CrossRef] · DOI
  6. Taha, H.; Kalkstein, L.S.; Sheridan, S.C.; Wong, E. The potential of urban environmental control in alleviating heat-wave health effects in five US regions. In Proceedings of the 16th Conference on Biometeorology and Aerobiology, American Meteorological Society, Vancouver, BC, Canada, 23-27 August 2004.
  7. Taha, H.; Douglas, S.; Haney, J. The UAM sensitivity analysis: The 26-28 August 1987 oxidant episode. In Analysis of Energy Efficiency and Air Quality in the South Coast Air Basin-Phase II; Taha, H., Ed.; Lawrence Berkeley Laboratory: Berkeley, CA, USA, 1994; Chapter 1.
  8. Filleul, L.; Cassadou, S.; Médina, S.; Fabres, P.; Lefranc, A.; Eilstein, D.; Le Tertre, A.; Pascal, L.; Chardon, B.; Blanchard, M.; et al. The relation between temperature, ozone, and mortality in nine French cities during the heat wave of 2003. Environ. Health Perspect. 2006, 114, 1344-1347. [CrossRef] · DOI
  9. Balling, R.C., Jr.; Brazil, S.W. Time and space characteristics of the Phoenix urban heat island. J. Ariz.-Nev. Acad. Sci. 1987, 21, 75-81.
  10. Lee, T.-W.; Lee, J.Y.; Wang, Z.-H. Scaling of the urban heat island intensity using time-dependent energy balance. Urban Clim. 2012, 2, 16-24. [CrossRef] · DOI
  11. 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 Sens. Environ. 2007, 106, 375-386. [CrossRef] · DOI
  12. Chen, X.-L.; Zhao, H.-M.; Li, P.-X.; Yin, Z.-Y. Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens. Environ. 2006, 104, 133-146. [CrossRef] · DOI
  13. Kato, S.; Yamaguchi, Y. 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 Sens. Environ. 2005, 99, 44-54. [CrossRef] · DOI
  14. Nichol, J.E.; Fung, W.Y.; Lam, K.; Wong, M.S. Urban head island diagnosis using ASTER satellite images and "in situ" air temperature. Atmos. Res. 2009, 94, 276-284. [CrossRef] · DOI
  15. Liu, L.; Zhang, Y. Urban heat island analysis using the Landsat TM data and ASTER data: A case study in Hong Kong. Remote Sens. 2011, 3, 1535-1552. [CrossRef] · DOI
  16. Myint, S.W.; Wentz, E.A.; Brazel, A.J.; Quattrochi, D.A. The impact of distinct anthropogenic and vegetation features on urban warming. Landsc. Ecol. 2013, 28, 959-978. [CrossRef] · DOI
  17. Imhoff, M.L.; Zhang, P.; Wolfe, R.E.; Bounoua, L. Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens. Environ. 2010, 114, 504-513. [CrossRef] · DOI
  18. Zheng, B.; Myint, S.W.; Fan, C. Spatial configuration of anthropogenic land cover impacts on urban warming. Landsc. Urban Plan. 2014, 130, 104-111. [CrossRef] · DOI
  19. Gober, P.; Brazil, A.; Quay, R.; Myint, S.; Grossman-Clarke, S.; Miller, A.; Rossi, S. Using watered landscape to manipulate urban heat island effects: How much water will it take to cool Phoenix? J. Am. Plan. Assoc. 2009, 76, 109-121. [CrossRef] · DOI
  20. Rossi, F.; Pisello, A.L.; Nicolini, A.; Filipponi, M.; Palombo, M. Analysis of retro-reflective surfaces for urban heat island mitigation: A new analytical model. Appl. Energy 2014, 114, 621-631. [CrossRef] · DOI
  21. Santamouris, M.; Synnefa, A.; Karlessi, T. Using advanced cool materials in the urban built environment to mitigate heat islands and improve thermal comfort conditions. Sol. Energy 2011, 85, 3085-3102. [CrossRef] · DOI · Paper page
  22. Uemoto, K.L.; Sato, N.M.N.; John, V.M. Estimating thermal performance of cool colored paints. Energy Build. 2010, 42, 17-22. [CrossRef] · DOI
  23. Jo, J.H.; Carlson, J.D.; Golden, J.S.; Bryan, H. An integrated empirical and modeling methodology for analyzing solar reflective roof technologies on commercial buildings. Build. Environ. 2010, 45, 453-460. [CrossRef] · DOI
  24. Yang, J.; Wang, Z.-H.; Kaloush, K. E. Environmental impacts on reflective materials: Is high albedo a "silver bullet" for mitigating urban heat island? Renew. Sustain. Energy Rev. 2015, 47, 830-843. [CrossRef] · DOI
  25. Schwarz, N.; Lautenbach, S.; Seppelt, R. Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures. Remote Sens. Environ. 2011, 115, 3175-3186. [CrossRef] · DOI
  26. Tomlinson, C.J.; Chapman, L.; Thornes, J.E.; Baker, C.J. Derivation of Birmingham's summer surface urban heat island from MODIS satellite images. Int. J. Climatol. 2010, 32, 214-224. [CrossRef] · DOI
  27. Rajasekar, U.; Weng, Q. Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis. ISPRS J. Photogramm. Remote Sens. 2009, 64, 86-96. [CrossRef] · DOI
  28. Cheval, S.; Dumitrescu, A. The July urban heat island of Bucharest as derived from MODIS images. Theor. Appl. Climatol. 2009, 96, 145-153. [CrossRef] · DOI
  29. Tran, H.; Uchihama, D.; Ochi, S.; Yasuoka, Y. Assessment with satellite data of the urban heat island effects in Asian mega cities. Int. J. Appl. Earth Obs. Geoinform. 2006, 8, 34-48. [CrossRef] · DOI
  30. Brazel, A.J.; Selover, N.; Vose, R.; Heisler, G. Tale of two climates-Baltimore and Phoenix urban LTER sites. Clim. Res. 2000, 15, 123-135. [CrossRef] · DOI
  31. Cermak, J.E., Davenport, A.G., Plate, E.J., Viegas, D.X., Eds.; Kluwer Academic: Dordrecht, The Netherlands, 1995; pp. 81-107.
  32. Steward, I.D.; Oke, T.R. Local climate zones for urban temperature studies. Bull. Am. Meteorol. Soc. 2012, 93, 1879-1900. [CrossRef] · DOI
  33. Wang, Z.-H.; Bou-Zeid, E.; Smith, J.A. A coupled energy transport and hydrological model for urban canopies with evaluation using a wireless sensor network. Q. J. R. Meteorol. Soc. 2013, 139, 1643-1657. [CrossRef] · DOI
  34. Schatz, J.; Kucharik, C.J. Seasonality of the urban heat island effect in Madison, Wisconsin. J. Appl. Meteorol. Clim. 2014, 53, 2371-2386. [CrossRef] · DOI
  35. Oke, T.R. The energetic basis of the urban heat island. Q. J. R. Meteorol. Soc. 1982, 108, 1-24. [CrossRef] · DOI · Paper page
  36. Weng, Q. A remote sensing GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. Int. J. Remote Sens. 2001, 22, 1999-2014.
  37. Bouyer, J.; Musy, M.; Huang, Y.; Athamena, K. Mitigating urban heat island effect by urban design: Forms and materials. In Proceedings of the Fifth Urban Research Symposium 2009, World Bank: Cities and Climate Change: Responding to an Urgent Agenda, Marseille, France, 28-29 June 2009; pp. 1-15.
  38. Lu, J.; Li, C.; Yu, C.; Jin, M.; Dong, S. Regression analysis of the relationship between urban heat island effect and urban canopy characteristics in a mountainous city, Chongqing. Indoor Built Environ. 2012, 21, 821-836. [CrossRef] · DOI
  39. Song, J.; Wang, Z.-H. Interfacing the urban land-atmosphere system through coupled urban canopy and atmospheric models. Bound. Layer Meteorol. 2015, 154, 427-448. [CrossRef] · DOI
  40. Golden, J.S. The built environment induced urban heat island effect in rapidly urbanizing arid regions-A sustainable urban engineering complexity. Environ. Sci. 2004, 1, 321-349. [CrossRef] · DOI
  41. Mills, G. Urban climatology and urban design. In Proceedings of the 15th ICB & ICUC, Sydney, Australia, 8-12 November 1999.
  42. Bohnenstengel, S.I.; Evans, S.; Clark, P.A.; Belcher, S.E. Simulations of the Landon urban heat island. Q. J. R. Meteorol. Soc. 2011, 137, 1625-1640. [CrossRef] · DOI
  43. Pal, S.; Xueref-Remy, I.; Ammoura, L.; Chazette, P.; Gibert, F.; Royer, P.; Dieudonné, E.; Dupont, J.-C.; Haeffelin, M.; Lac, C.; et al. Spatio-temporal variability of the atmospheric boundary layer depth over the Paris agglomeration: An assessment of the impact of the urban heat island intensity. Atmos. Environ. 2012, 63, 261-275. [CrossRef] · DOI
  44. Lac, C.; Donnelly, R.P.; Masson, V.; Pal, S.; Riette, S.; Donier, S.; Queguiner, S.; Tanguy, G.; Ammoura, L.; Xueref-Remy, I. CO 2 dispersion modelling over Paris region within the CO 2 -MEGAPARIS project. Atmos. Chem. Phys. 2013, 13, 4941-4961. [CrossRef] · DOI
  45. Rosenfeld, A.H.; Akbari, H.; Bretz, S.; Fishman, B.L.; Kurn, D.M.; Sailor, D.; Taha, H. Mitigation of urban heat islands: Materials, utility programs, updates. Energy Build. 1995, 22, 255-265. [CrossRef] · DOI
  46. Ca, V.T.; Asaeda, T.; Abu, E.M. Reductions in air-conditioning energy caused by a nearby park. Energy Build. 1998, 29, 83-92. [CrossRef] · DOI
  47. Ashie, Y.; Thanh, V.C.; Asaeda, T. Building canopy model for the analysis of urban climate. J. Wind Eng. Ind. Aerod. 1999, 81, 237-248. [CrossRef] · DOI
  48. Tong, H.; Walton, A.; Sang, J.; Chan, J.C.L. Numerical simulation of the urban boundary layer over the complex terrain of Hong Kong. Atmos. Environ. 2005, 39, 3549-3563. [CrossRef] · DOI
  49. Yu, C.; Hien, W.N. Thermal benefits of city parks. Energy Build. 2006, 38, 105-120. [CrossRef] · DOI
  50. Yang, J.; Wang, Z.-H. Optimizing urban irrigation schemes for the trade-off between energy and water consumption. Energy Build. 2015, 107, 335-344. [CrossRef] · DOI
  51. Taha, H. Urban climates and heat islands: Albedo, evapotranspiration, and anthropogenic heat. Energy Build. 1997, 25, 99-103. [CrossRef] · DOI
  52. Lo, C.P.; Quattrochi, D.A.; Luvall, J.C. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. Int. J. Remote Sens. 1997, 18, 287-304. [CrossRef] · DOI

Cited by

Sorted by citations

Authors
Wang, C., Myint, S., Wang, Z., & Song, J.
Affiliations
  • School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA
  • School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA
ORCID
Wang, Chuyuan
Venue
Remote Sensing
Publisher
MDPI AG
Published
2016-02-26
Volume
8
Issue
3
Pages
185
ISSN
2072-4292
DOI
10.3390/rs8030185
Cited by
119
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review