140 • In terms of monthly values, rainfall is found not to have a strong influence on mean and maximum UHI intensities. Air temperature and wind speed are better predictors of monthly mean and maximum UHI intensities. • In this study area, landscape factors do not influence the nocturnal UHIraw and may only be slightly influential in terms of the daytime UHIraw . Limitations of the study and potential future work There are several limitations to this study that can be improved upon given more time, resources and expertise. These also serve as potential extensions for future work. • The lack of more site-specific meteorological information such as wind speed, solar radiation and soil moisture means that detailed analysis on the weather, moisture or antecedent factors cannot be achieved. • While this study provides a comprehensive documentation and analysis of the urban thermal environment in Singapore, it can be built upon with multidimensional statistical or numerical methods that allow for more accurate modelling of UHI where sensors may not be available. Another potential extension is the impact analysis of the variability of the thermal environment on building energy consumption and human health, creating normative value in the research. (23604 words) 141 References Adebayo, Y. R. (1990). Considerations for climate-sensitive design in tropical Africa. Energy and Buildings, 15(1-2):15–21. Aguilar, E., Auer, I., Brunet, M., Peterson, T., and Wieringa, J. (2003). 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(1998). Effects of urban surface geometry on remotelysensed surface temperature. International Journal of Remote Sensing, 19(5):895– 920. Voogt, J. A. and Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote Sensing of Environment, 86(3):370–384. Wilby, R. L. and Perry, G. L. (2006). Climate change, biodiversity and the urban environment: a critical review based on London, UK. Progress in Physical Geography, 30(1):73–98. 152 Wong, N. and Chen, Y. (2005). Study of green areas and urban heat island in a tropical city. Habitat International, 29(3):547–558. Wong, N. and Jusuf, S. K. (2010a). Air temperature distribution and the influence of sky view factor in a green singapore estate. Journal of Urban Planning and Development, 136(3):261–272. Wong, N. and Jusuf, S. K. (2010b). Study on the microclimate condition along a green pedestrian canyon in Singapore. Architectural Science Review, 53(2):196– 212. Wong, N., Kardinal Jusuf, S., Aung La Win, A., Kyaw Thu, H., Syatia Negara, T., and Xuchao, W. (2007). Environmental study of the impact of greenery in an institutional campus in the tropics. Building and Environment, 42(8):2949–2970. Yee, A., Ang, W., Teo, S., and Liew, C. (2010). The present extent of mangrove forests in Singapore. Nature in Singapore, 1(June):139–145. Yow, D. M. (2007). Urban Heat Islands: Observations, Impacts, and Adaptation. Geography Compass, 1(6):1227–1251. Zhang, X., Wu, P., and Chen, B. (2010). Relationship between vegetation greenness and urban heat island effect in Beijing City of China. Procedia Environmental Sciences, 2:1438–1450. Zhao, S., Da, L., Tang, Z., Fang, H., Song, K., and Fang, J. (2006). Ecological consequences of rapid urban expansion: Shanghai, China. Frontiers in Ecology and the Environment, 4(7):341–346. 158 S43 Mock Village 1.394 103.69 6A Not used in analysis of urban morphology S44 Waterloo Street 1.299 103.85 12 Not used in analysis of urban morphology S45 Eng Kong 1.335 103.77 3 Not used in analysis of urban morphology S46 Opp Paragon 1.304 103.84 12 Not used in analysis of urban morphology Selected metadata for observation sites. Note that LCZ = Local Climate Zone. Parent classes can be found in Appendix C and LCZs with subscript (secondary) classes are considered mixed land use or land cover (For more details, refer to Appendix C and Stewart and Oke, 2012). 159 Appendix C: LCZ classes The parent LCZ classes for built environments and land cover. Source: Stewart and Oke (2012, pp 38) 160 Appendix D: Fish-eye images for sensor localities 161 Full circular fish-eye images used to determine sky view-factor. Top row: S01, S02, S03, S04. Row 2: S05, S06, S07, S08. Row 3: S09, S10, S11, S12. Row 4: S13, S14, S15, S16. Row 5: S17, S18, S19, S20. Row 6: S21, S22, S23, S24. Row 7: S25, S28, S29, S30. Row 8: S31, S32, S34, S36. Bottom row: S37, S38, S39, S40. 162 Appendix E: Selected codes and scripts used in the study Linux shell script for cloud/rain days extraction and cropping # Extraction of cloud and rainfall overlay images (2008-2011) # from Wunderground database using nested loops for y in {2008..2011}; do for m in {01..12}; do for d in {01..31}; do wget "http://timelord.wunderground.com/timelord/satir/$y/$m/$d/01/6/50/31.png" \ -O "$y"_"$m"_"$dover".png; done; done; done # Singapore boundaries and scaling obtained from QGIS georeferencing of # image template # Perform crop using known scaling for i in *.png; do convert "$i".png -crop 21x10+107+189 "$i"_cropped.png # List of files compared with date vector to ensure no missing data find . -name "*cropped.png" -printf "%f\n" > imagelist diff imagelist datevector # Cloudless/rainless images have limited data size in terms of bytes (S) # Sample listing of days with any amount of rain. find . -name "*cropped.png" -printf "%f %s\n" | awk ’{if ($2 > $S) print}’ R code for plotting faceted plots (e.g. Figure 4.11) # To order from noon to midnight with(dataset, factor(hour,levels=c("12","13","14","15","16","17","18","19", "20","21","22","23","00","01","02","03","04","05","06", "07","08","09","10","11"))) -> dataset$hour # Faceted plot ggplot(dataset,aes(hour,value,colour=value,group=variable)) + geom_line() + facet_wrap(~ month,ncol=3) + scale_colour_gradient(low="green", high="red", name="") + scale_x_discrete(breaks=c("12","18","00","06")) + geom_hline(y=0,alpha=0.5, linetype=2) + ylab(expression(paste("UHI"[raw], Celsius))) + xlab("Hour (Local Time)") + opts(legend.position="none") 163 GRASS script for spatial interpolation (IDW) # Region and resolution declared with preset mapset g.region vect=singavect@PERMANENT g.region res=0.001 # Import CSV created in R with coords and value v.in.ascii --overwrite input=input_csv output=interpolated@PERMANENT \ fs=, x=2 y=1 # Apply masking with Singapore outline r.mask input=sg_outline@PERMANENT maskcats=* # Perform IDW and create contour lines v.surf.idw -n --overwrite --verbose input=interptest@PERMANENT output=surface column=dbl_3 r.contour --overwrite input=surface@PERMANENT output=contour step=0.2 # Set monitor for printing d.mon x0 # Displays relevant layers and outputs as PNG file d.rast surface@PERMANENT d.vect contour@PERMANENT d.vect interptest@PERMANENT d.out.file output=outputfilename format=png compression=9 --overwrite -m R function for LULC variables against UHI variables linear function fitting urbanf a; summary(lm(x ~ sqrt(y))) -> b; summary(lm(x ~ y)) -> c; try(summary(lm(x ~ log10(y))) -> d, silent=T); list(c,a,d,b) -> out; return(out) } [...]... heat island effect in Metro Manila International Journal of Remote Sensing, 29(10):2799–2818 Tso, C (1994) The impact of urban development on the thermal environment of Singapore In WMO, editor, Report of the Technical Conference on Tropical Urban Climates Dhaka Tso, C (1996) A survey of urban heat island studies in two tropical cities Atmospheric Environment, 30(3) :50 7 51 9 Unger, J (2004) Intra -urban. .. (2012) Singaporeans ”accepting of foreigners” Singapore News - ChannelNewsAsia  151 Tayan¸c, M., N¨ uzhet Dalfes, H., Karaca, M., and Yenig¨ un, O (1998) A comparative assessment of different methods for detecting inhomogeneities in Turkish temperature data set International Journal of Climatology, 18 (5) :56 1 57 8 Tiangco, M., Lagmay, A M F., and Argete, J (2008) ASTER-based study of the nighttime urban heat. .. Zones for Urban Temperature Studies Bulletin of the American Meteorological Society (pre-prints) Sundborg, A (1 950 ) Local climatological studies of the temperature conditions in an urban area Tellus, 2(3):222–232 Suomi, J and K¨ayhk¨o, J (2012) The impact of environmental factors on urban temperature variability in the coastal city of Turku, SW Finland International Journal of Climatology, 32(3): 451 –463... R (2003) Thermal remote sensing of urban climates Remote Sensing of Environment, 86(3):370–384 Wilby, R L and Perry, G L (2006) Climate change, biodiversity and the urban environment: a critical review based on London, UK Progress in Physical Geography, 30(1):73–98  152 Wong, N and Chen, Y (20 05) Study of green areas and urban heat island in a tropical city Habitat International, 29(3) :54 7 55 8 Wong,... Environmental study of the impact of greenery in an institutional campus in the tropics Building and Environment, 42(8):2949–2970 Yee, A., Ang, W., Teo, S., and Liew, C (2010) The present extent of mangrove forests in Singapore Nature in Singapore, 1(June):139–1 45 Yow, D M (2007) Urban Heat Islands: Observations, Impacts, and Adaptation Geography Compass, 1(6):1227–1 251 Zhang, X., Wu, P., and Chen, B... the influence of sky view factor in a green singapore estate Journal of Urban Planning and Development, 136(3):261–272 Wong, N and Jusuf, S K (2010b) Study on the microclimate condition along a green pedestrian canyon in Singapore Architectural Science Review, 53 (2):196– 212 Wong, N., Kardinal Jusuf, S., Aung La Win, A., Kyaw Thu, H., Syatia Negara, T., and Xuchao, W (2007) Environmental study of the. .. and urban heat island effect in Beijing City of China Procedia Environmental Sciences, 2:1438–1 450 Zhao, S., Da, L., Tang, Z., Fang, H., Song, K., and Fang, J (2006) Ecological consequences of rapid urban expansion: Shanghai, China Frontiers in Ecology and the Environment, 4(7):341–346 158 S43 Mock Village 1.394 103.69 6A Not used in analysis of urban morphology S44 Waterloo Street 1.299 103. 85 12... 150 Stewart, I D and Oke, T R (2009a) Classifying urban climate field sites by “local climate zones”: The case of Nagano, Japan International Conference on Urban Climate (ICUC7) Stewart, I D and Oke, T R (2009b) Newly developed Thermal climate zones for defining and measuring urban heat island magnitude in the canopy layer American Meteorological Society Annual Meeting, Phoenix AZ Stewart,... Swaid, H (1993) Urban climate effects of artificial heat sources and ground shadowing by buildings International Journal of Climatology, 13(7):797–812 Synnefa, A., Santamouris, M., and Livada, I (2006) A study of the thermal performance of reflective coatings for the urban environment Solar Energy, 80(8):968–981 Szymanowski, M and Kryza, M (2009) GIS-based techniques for urban heat island spatialization... urban heat island: review and new approach Climate Research, 27: 253 –264 Unger, J., S¨ umeghy, Z., Guly´as, A., Botty´an, Z., and Mucsi, L (2001) Land-use and meteorological aspects of the urban heat island Meteorological Applications, 8(2):189–194 Voogt, J A and Oke, T R (1998) Effects of urban surface geometry on remotelysensed surface temperature International Journal of Remote Sensing, 19 (5) :8 95 ... (1991) Mapping and measuring buildings in the canopy boundary layer in ten US cities Energy and Buildings, 16:10 25 1049 143 Elsayed, I S M (2011) A study on the urban heat island of the city of Kuala... (2001) On the impact of urban climate on the energy consumption of buildings Solar Energy, 70(3):201–216 Singapore Meteorological Services (1986) A study of the urban climate of Singapore In Chia,... urban heat island effect in Metro Manila International Journal of Remote Sensing, 29(10):2799–2818 Tso, C (1994) The impact of urban development on the thermal environment of Singapore In WMO,