Mapping maximum urban air temperature on hot summer days

Remote Sensing of Environment

Volumn 154, Issue , 2014, Pages 38-45

  Ho, Hung Chak ^a   Knudby, Anders ^a   Sirovyak, Paul ^a   Xu, Yongming ^b   Hodul, Matus ^a   Henderson, Sarah B ^c,d  

^a SIMON FRASER UNIVERSITY   (Canada)

^b NANJING UNIVERSITY OF INFORMATION SCIENCE AND TECHNOLOGY   (China)

^c UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^d BRITISH COLUMBIA CENTRE FOR DISEASE CONTROL   (Canada)

Author keywords

Air temperature; Landsat; Random forest; Remote sensing application; Spatial modeling; Statistical model; Urban; Urban heat island

Indexed keywords

DECISION TREES; ERRORS; MAPPING; REGRESSION ANALYSIS;

AIR TEMPERATURE; LANDSAT; RANDOM FORESTS; REMOTE SENSING APPLICATIONS; SPATIAL MODELING; STATISTICAL MODELING; URBAN; URBAN HEAT ISLAND;

ATMOSPHERIC TEMPERATURE;

AIR TEMPERATURE; LANDSAT; MAPPING; MICROCLIMATE; REGRESSION ANALYSIS; SUMMER; TEMPERATURE PROFILE; URBAN REGION; ERROR ANALYSIS; HEAT ISLAND; REMOTE SENSING; TEMPERATURE GRADIENT; URBAN ATMOSPHERE;

BRITISH COLUMBIA; CANADA; VANCOUVER [BRITISH COLUMBIA];

EID: 84906835900     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.08.012     Document Type: Article

References (83)

1. Anderson G., Bell M. Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities. Environmental Health Perspectives 2011, 119(2):210-218.
2. Anderson A., Chapman M., Drobot S., Tadesse A., Lambi B., Wiener G. Quality of mobile air temperature and atmospheric pressure observations from the 2010 development test environment experiment. Journal of Applied Meteorology and Climatology 2012, 51(4):691-701.
3. Barsi J.A., Barker J.L., Schott J.R. An Atmospheric Correction Parameter Calculator for a single thermal band earth-sensing instrument. Toulouse, France: IGARSS IEEE International Geoscience and Remote Sensing Symposium 2003.
4. Benali A., Carvalho A., Nunes J., Carvalhais N., Santos A. Estimating air surface temperature in Portugal using MODIS LST data. Remote Sensing of Environment 2012, 124(2012):108-121.
5. Breiman L. Random forests. Machine Learning 2001, 45(1):5-32.
6. Bristow K., Campbell G. On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agricultural and Forest Meteorology 1984, 31:159-166.
7. Bruzzone L., Melgani F. Robust multiple estimator systems for the analysis of biophysical parameters from remotely sensed data. IEEE Transactions on Geoscience and Remote Sensing 2005, 43(1):159-174.
8. Buscail C., Upegui E., Viel J.-F. Mapping heatwave health risk at the community level for public health action. International Journal of Health Geographics 2012, 11:38.
9. Camps-Valls G., Bruzzone L., Rojo-Alvarez J.L., Melgani F. Robust support vector regression for biophysical variable estimation from remotely sensed images. IEEE Geoscience and Remote Sensing Letters 2006, 3(3):339-343.
10. Camps-Valls G., Gómez-Chova L., Muñoz-Marí J., Vila-Francés J., Amorós-López J., Calpe-Maravilla J. Retrieval of oceanic chlorophyll concentration with relevance vector machines. Remote Sensing of Environment 2006, 105(1):23-33.
11. Chen L., Ng E., An X., Ren C., Lee M., Wang U., et al. Sky view factor analysis of street canyons and its implications for daytime intra-urban air temperature differentials in high-rise, high-density urban areas of Hong Kong: A GIS-based simulation approach. International Journal of Climatology 2012, 32:121-136.
12. Cortes C., Vapnik V. Support-vector networks. Machine Learning 1995, 20(3):273-297.
13. Czajkowski K.P., Goward S.N., Stadler S., Walz A. Thermal remote sensing of near surface environmental variables: Application over the Oklahoma Mesonet. The Professional Geographer 2000, 52(2):345-357.
14. Das S., Samui P., Sabat A., Sitharam T. Prediction of swelling pressure of soil using artificial intelligence techniques. Environmental Earth Sciences 2010, 61:393-403.
15. Durbha S., King R., Younan N. Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer. Remote Sensing of Environment 2007, 107(1-2):348-361.
16. Emamifar S., Rahimikhoob A., Noroozi A. Daily mean temperature estimation from MODIS land surface temperature. International Journal of Climatology 2013, 10.1002/joc.3655.
17. Fu P., Rich P. A geometric solar radiation model with applications in agriculture and forestry. Computers and Electronics in Agriculture 2002, 37:25-35.
18. Gao B.-C. NDWI-a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment 1996, 58:257-266.
19. Garske T., Ferguson N., Ghani A. Estimating air temperature and its influence on malaria transmission across Africa. PLoS One 2013, 8(2):e56487.
20. Genuer R., Poggi J.-M., Tuleau-Malot C. Variable selection using random forests. Pattern Recognition Letters 2010, 31(14):2225-2236.
21. Gislason P., Benediktsson J., Sveinsson J. Random forests for land cover classification. Pattern Recognition Letters 2006, 27:294-300.
22. Goodchild M.F. Citizens as sensors: The world of volunteered geography. GeoJournal 2007, 69(4):211-221.
23. Harvell C., Mitchell C., Ward J., Altizer S., Dobson A., Ostfeld R., et al. Climate warming and disease risks for terrestrial and marine biota. Science 2002, 296(5576):2158-2162.
24. Hijmans R.J., van Etten J. Raster. Geographic analysis and modeling with raster data: R package version 0.9.8-40/r681 See, (essay, and, social science essay). http://www.R-Forge.R-project.org/projects/raster/.fic.
25. Hondula D., Davis R., Leisten M., Saha M., Veazey L., Wegner C. Fine-scale spatial variability of heat-related mortality in Philadelphia County, USA, from 1983-2008: A case-series analysis. Environmental Health 2012, 11:16.
26. Huang C., Davis L., Townshend J. An assessment of support vector machines for land cover classification. International Journal of Remote Sensing 2002, 23(4):725-749.
27. Hulley G.C., Hook S.J. The North American ASTER Land Surface Emissivity Database (NAALSED) version 2.0. Remote Sensing of Environment 2009, 113(9):1967-1975.
28. Jang J., Viau A., Anctil F. Neural network estimation of air temperatures from AVHRR data. International Journal of Remote Sensing 2004, 25(21):4541-4554.
29. Katsouyanni K., Pantazopoulou A., Touloumi G., Tselepidaki I., Moustris K., Asimakopoulos D., et al. Evidence for interaction between air pollution and high temperature in the causation of excess mortality. Archives of Environmental Health: An International Journal 1993, 48(4):235-242.
30. Knudby A., Brenning A., LeDrew E. New approaches to modelling fish-habitat relationships. Ecological Modelling 2010, 221:503-511.
31. Knudby A., LeDrew E., Brenning A. Predictive mapping of reef fish species richness, diversity and biomass in Zanzibar using IKONOS imagery and machine-learning techniques. Remote Sensing of Environment 2010, 114(6):1230-1241.
32. Koken P., Piver W., Ye F., Elixhauser A., Olsen L., Portier C. Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver. Environmental Health Perspectives 2003, 111(10):1312-1317.
33. Kolokotroni M., Giridharan R. Urban heat island intensity in London: An investigation of the impact of physical characteristics on changes in outdoor air temperature during summer. Solar Energy 2008, 82(11):986-998.
34. Kuhn K., Campbell-Lendrum D., Davies C. A continental risk map for malaria mosquito (Diptera: Culicidae) vectors in Europe. Journal of Medical Entomology 2002, 39(4):621-630.
35. Kunst A., Looman C., Mackenback J. Outdoor air temperature and mortality in the Netherlands: A time-series analysis. American Journal of Epidemiology 1993, 137(3):331-341.
36. Kutner M., Nachtsheim C., Neter J. Applied linear regression models 2004, McGraw Hill. 4th ed.
37. Laaidi K., Zeghnoun A., Dousset B., Bretin P., Vandentorren S., Giraudet E., et al. The impact of heat islands on mortality in Paris during the August 2003 heat wave. Environmental Health Perspectives 2012, 120(2):254-259.
38. Liaw A., Wiener M. Breiman and Cutler's random forests for classification and regression, R package 2012.
39. Liu J.G., Moore J.M. Pixel block intensity modulation: Adding spatial detail to TM band 6 thermal imagery. International Journal of Remote Sensing 1998, 19:2477-2491.
40. Maria K., Renganathan G. Urban heat island intensity in London: An investigation of the impact of physical characteristics on changes in outdoor air temperature during summer. Solar Energy 2008, 82(11):986-998.
41. Medina-Ramon M., Zanobetti A., Cavanagh D., Schwartz J. Extreme temperatures and mortality: Assessing effect modification by personal characteristics and specific cause of death in a multi-city case-only analysis. Environmental Health Perspectives 2006, 114(9):1131-1136.
42. Melgani F., Bruzzone L. Classification of hyperspectral remote sensing images with support vector machines. IEEE Transactions on Geoscience and Remote Sensing 2004, 42(8):1778-1790.
43. Meteotest Meteonorm handbook, Part III: Theory part 2 Accessed online in February 9 (2011). http://www.meteonorm.com/media/pdf/mn6_software.pdf.
44. Meyer D., Dimitriadou E., Hornik K., Weingessel A., Leisch F. Misc functions of the department of statistics (e1071), TU Wien, R package 2012.
45. Mostovoy G.V., King R.L., Reddy K.R., Kakani V.G., Filippova M.G. Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi. GIScience and Remote Sensing 2006, 43(1):78-110.
46. Mountrakis G., Im J., Ogole C. Support vector machines in remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing 2011, 66(2011):247-259.
47. Murray K., Conner M.M. Methods to quantify variable importance: Implications for the analysis of noisy ecological data. Ecology 2009, 90:348-355.
48. Nichol J.E., Fung W.Y., Lam K.-S., Wong M.S. Urban heat island diagnosis using ASTER satellite images and 'in situ' air temperature. Atmospheric Research 2009, 276-284.
49. Nichol J.E., To P.H. Temporal characteristics of thermal satellite images for urban heat stress and heat island mapping. ISPRS Journal of Photogrammetry and Remote Sensing 2012, 74:153-162.
50. Ocak I., Seker S. Calculation of surface settlements caused by EPBM tunneling using artificial neural network, SVM, and Gaussian processes. Environmental Earth Sciences 2013, 10.1007/s12665-012-2214-x.
51. Oke T. The distinction between canopy and boundary-layer urban heat islands. Atmosphere 1976, 14(4):268-277.
52. Oke T. The urban energy balance. Progress in Physical Geography 1988, 12:471-508.
53. Oke T., Hay J. The climate of Vancouver. B.C. Geographical Series 1994, 50. Tantalus Press, Vancouver, British Columbia. 2nd ed.
54. Oke T.R., Maxwell G.B. Urban heat island dynamics in Montreal and Vancouver. Atmospheric Environment 1975, 9(2):191-200.
55. Oommen T., Misra D., Twarakavi N., Prakash A., Sahoo B., Bandopadhyay S. An objective analysis of support vector machine based classification for remote sensing. Mathematical Geosciences 2008, 40(4):409-424.
56. Pal M., Mather P.M. Support vector machines for classification in remote sensing. International Journal of Remote Sensing 2005, 26(5):1007-1011.
57. Prihodko L., Goward S.N. Estimation of air temperature from remotely sensed surface observations. Remote Sensing of Environment 1997, 60(3):335-346.
58. R Core Development Team R: A language and environment for statistical computing http://www.R-project.org/.
59. Runnalls K., Oke T. Dynamics and controls of the near-surface heat island of Vancouver, British Columbia. Physical Geography 2000, 21(4):283-304.
60. Saaroni H., Baruch Z. Estimating the urban heat island contribution to urban and rural air temperature differences over complex terrain: Application to an arid city. Journal of Applied Meteorology and Climatology 2010, 49:2159-2166.
61. Sandholt I., Rasmussen K., Andersen J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment 2002, 79(2-3):213-224.
62. Sieber R. Public participation geographic information systems: A literature review and framework. Annals of the Association of American Geographers 2006, 96(3):491-507.
63. Singh R., Joshi P., Kishtawal C. A new method to determine near surface air temperature from satellite observations. International Journal of Remote Sensing 2006, 27(14):2831-2846.
64. Statistics Canada Greater Vancouver, British Columbia (Code5915) (table). 2006 Community Profiles. 2006 Census. Statistics Canada Catalogue no. 92-591-XWE 2007, (Ottawa. Released March 13, 2007).
65. Stisen S., Sandholt I., Norgaard A., Fensholt R., Eklundh L. Estimation of diurnal air temperature using MSG SEVIRI data in West Africa. Remote Sensing of Environment 2007, 110(2):262-274.
66. Strobl C., Malley J., Tutz G. An introduction to recursive partitioning: Rational, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods 2009, 14(4):323-348.
67. Stumpf A., Kerle N. Object-oriented mapping of landslides using random forests. Remote Sensing of Environment 2011, 115:2564-2577.
68. Su J., Brauer M., Buzzelli M. Estimating urban morphometry at the neighborhood scale for improvement in modeling long-term average air pollution concentrations. Atmospheric Environment 2008, 42:7884-7893.
69. Sun D., Li Y., Wang Q. A unified model for remotely estimating chlorophyll a in Lake Taihu, China, based on SVM and in situ hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing 2009, 47(8):2957-2965.
70. Sun Y.J., Wang J.F., Zhang R.H., Gillies R.R., Xue Y., Bo Y.C. Air temperature retrieval from remote sensing data based on thermodynamics. Theoretical and Applied Climatology 2005, 80(1):37-48.
71. Timm B., McGraigal K. Fine-scale remotely-sensed cover mapping of coastal dune and salt marsh ecosystems at Cape Cod National Seashore using Random Forests. Remote Sensing of Environment 2012, 127:106-117.
72. Tomlinson C., Chapman L., Thornes J., Baker C. Including the urban heat island in spatial heat health risk assessment strategies: A case study for Birmingham, UK. International Journal of Health Geographics 2011, 10:42.
73. Unger J., Sümeghya Z., Zobokib J. Temperature cross-section features in an urban area. Atmospheric Research 2001, 58(2):117-127.
74. Vancutsem C., Ceccato P., Dinku T., Connor S.J. Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sensing of Environment 2010, 114(2):449-465.
75. Vogt J., Viau A.A., Paquet F. Mapping regional air temperature fields using satellite derived surface skin temperatures. International Journal of Climatology 1997, 17:1559-1579.
76. Weng Q., Lu D., Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment 2004, 89:467-483.
77. Willmott C.J., Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate Research 2005, 30:79-82.
78. Wong M., Nichol J., Ng E. A study of the "wall effect" caused by proliferation of high-rise buildings using GIS techniques. Landscape and Urban Planning 2011, 102:245-253.
79. World Meteorological Organization Guide to meteorological instruments and methods of observation. WMO-No. 8 1996, (Geneva). 6th ed.
80. Xu Y., Qin Z., Shen Y. Study on the estimation of nearsurface air temperature from MODIS data by statistical methods. International Journal of Remote Sensing 2012, 33(24):7629-7643.
81. Zakšek K., Oštir K. Downscaling land surface temperature for urban heat island diurnal cycle analysis. Remote Sensing of Environment 2012, 117:114-124.
82. Zakšek K., Schroedter-Homscheidt M. Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments. ISPRS Journal of Photogrammetry and Remote Sensing 2009, 64(4):414-421.
83. Zhu W., Lu A., Jia S. Estimation of daily maximum and minimum air temperature using MODIS land surface temperature products. Remote Sensing of Environment 2013, 130(2013):62-73.