whole study area in which way the selected environmental 
variables can have affected local surface temperature at 
different relational levels. With this endeavor it hopes to 
devote to a better understanding of urban effect on local 
surface thermal environment by taking GWR into the 
analysis process. 
Due to the complexity of urban thermal environment induced 
by the intensive variation in spatial and temporal dimension, 
a systematic investigation of the relationship between urban 
form and urban thermal landscape in a subtropical city, Hong 
Kong based on statistical regression analysis can assist in a 
holistic understanding of local surface warming. The goal of 
this research is utilizing Geographically Weighted 
Regression (GWR) to analyze the relationship between urban 
form and surface temperature variation in order to clarify the 
local effects on surface warming, moreover to reveal the 
possible dynamics in the local influences of environmental 
indicators on the variation of local surface temperature across 
space and time. 
2. METHODOLOGY 
GWR takes the advantage of the flexibility of local statistical 
technique to analyze spatially varying relationships. Among 
the attempts of taking geographical location into its analysis 
of relationships between variables, Geographically Weighted 
Regression (GWR) is quite useful which allows complex 
spatial variations in parameters to be identified, mapped and 
modeled (Huang, 2000; Brunsdon et al, 1998) GWR 
provides the utility to scrutinize the potential discrepancy of 
local relationship patterns within each parameter through 
spatially located parameter coefficient estimation of each 
parameter across the whole study area, which was impossible 
using the Ordinary Least Squares (OLS) approach. The 
inference based on the varying relationships provides more 
in-depth examination of local effects. In this research context, 
the localized exploratory data analysis of GWR enables the 
local patterns of surface warming to be revealed and 
investigated in-depth. The application of GWR in the studies 
of local effects on urban surface thermal anomalies provides 
a potential avenue for a comprehensive understanding of 
local surface warming process. 
In the literature, urban thermal environment, in particular 
UHIs is the integrated output of urban geography, regional 
climate and ecology. From the urban landscape point of view, 
"each component surface in urban landscapes (e.g., lawn, 
parking lot, road, building, cemetery, and garden) exhibits a 
unique radiative, thermal, moisture, and aerodynamic 
properties, and relates to their surrounding site environment” 
(Oke, 1982). The surface composition and configuration of 
urban fabrics which is fragmented and intensively variable in 
the spatial distribution made the heterogeneity and 
complexity of urban surface thermal landscape in spatial- 
temporal dimension. From this perspective landscape 
composition and configuration are hypothesized to influence 
urban surface thermal landscape represented by urban surface 
temperature distribution. 
The framework of the study is illustrated in Figure 1.Besides 
urban surface temperature map derived from remote sensing 
data, a host of biophysical indicators listed below can be 
generated from satellite images as well. In conjunction with 
geographic information systems (GIS) geospatial analysis, 
other measures of urban form, such as location and elevation, 
  
     
   
site openness to the sky, etc., which is listed in the box below, 
can be calculated to quantify site specific physical and spatial 
characteristics. All these measures would be employed in 
statistical models to analyze the interaction between urban 
form and urban surface temperature variation together with 
climate ancillary observation. 
  
"Vegetation Index 
*Soil index 
»ass3z223»v0»90»31222702059299 942329 
  
  
  
  
  
  
  
   
  
  
  
"Location and Elevation 
*Site Openness to the Sky 
Soar Illumination 
*Road Network Density 
a "Building Square Footage 
Dens 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
F sity Geographical Weighted 
*Other indicators Regression (GWR} 
Analysis 
Air Temperature 
Distribution Pattem 
"Wind Speed 
Wind Direction 
Relative Humidity 
"Visibility 
"TotalCioudAmount | ttm emen nnno 
  
  
  
  
  
  
  
  
  
  
  
Figure 1. Conceptual design of thermal landscape 
correlation analysis 
The study of local effect of urban environment on surface 
thermal landscape process is undertaken by statistical 
regression analysis. The first step for the statistical analysis is 
the determination of variables. In this analysis urban surface 
temperature would be the dependent variable which can be 
derived from surface temperature image of ASTER. Table 1 
cites all variables employed in the regression models. Under 
the research assumptions aforementioned, the important 
factors that have correlation with the urban surface 
temperature are listed. 
  
  
  
  
  
  
  
Ne. |Label Descrip tion Note 
1 SL eem ow surface temperature on the dayfraontl/year eene dependent variable 
1 sp road network density in year+ 
2 TP ren population density in year*e* 
3 Disttocoast distance to waterbody 
4 hshad** solar radiation at one time of day/monthiye art* ; ; 
3 footsqure-a building footsquare measurement with area Ende pendent var ka 
6 elevationavg elevation 
7 NDVI""*"** | vegetation NDVI at one tire of dayfmontl/year*** 
8 diffuR*** diffuse radiation at one time of d the arte 
  
  
Table 1. Variables list for regression analysis 
3. CASE STUDY 
The study area mainly covers the overlapped area of all of 
the remote sensing images collected for this research in Hong 
Kong illustrated in Figure 2, with all the weather stations 
located within the study area where the meteorological data 
is recorded. The related meteorological data of these stations 
was purchased from Hong Kong Observatory (HKO) for this 
study to provide simultaneous field measurements. Within 
the study area, the elevation ranges from 0 rising to 957 
meter of Tai Mo Shan in the New Territories, where the 
intensive elevation variation occurs along with the 
mountainous region extension. Most of the extensive urban 
development with high density housing located sparsely in 
Tuen Mun, Tsuen Wan, Yuen Long, Tin Shui Wai, Sha Tin, 
Tai Po, Sheung Shui, Fanling, and Kowloon, mainly focusing 
on New Territories and part of Kowloon region, which are 
detached by the mountains covering the whole study area. 
The northwest corner of the study area contains Hong Kong 
wetland park and Mai Po Ramsar Sote, with fish ponds 
surrounded. Besides housing estates, the study area includes 
   
a few indi 
Tsuen Wa 
mountains 
provides p: 
surface the 
The study | 
data used f 
of these ye 
Land Proc: 
Earth Obse 
be demons 
section. Si 
mature urt 
2003 to 2! 
developme 
recognized 
  
  
In this 1 
Temperat 
for this re 
the ecolc 
AST 08 « 
reported a 
proved to 
surface t 
Kelvin hi 
primary « 
these obs: 
some bac 
distributi 
DATE 
2005-04-17 | - 
2005-10-23 
2005-10-01 
2004-11-21 
2004-10-05 
2003-11-03 | 
2003-10-28 
Table 2. 
  
For the 
temperat 
regressio 
systemati 
the obs