from the histogram below in figure 9 
Road Factor. 
  
  
Rt ORRSTI KUCFN IN 
ROS ase 
  
Figure 9 Road surface factor histogram 
Combining the road factor map with the original CO2 reduced 
map, the resultant map will be as illustrated in fig 10 a map of 
CO2 reduced values but aggregated using the factor from road 
surface. 
  
    
> Reduced Col values by = |; 
^ p, Contolfiag Energy Consumption & Road Effects Á 
  
  
  
Figure 10 Reduced CO2 (energy reduction and Road factors) 
3.4 CO2 and Combined effects from Greenery and Roads 
When combing the resultant maps we a get a better 
understanding of the CO2 reduction that considers not only 
energy reduction but also factors from greenery and factors 
from road surfaces., and this off course can be done for several 
more factors that has a regional, climate, or cultural effect to 
assess sustainability measures, the resultant map is illustrated 
below in figure 11. 
These maps are to be combined in more scenarios where the 
pixel level is different; this measure will involve interpolations 
which will result considering neighbour pixel values. 
Again as this practice was performed for CO2 reduction it can 
be repeated for other gasses, provided that those layers shall be 
used that has most effect on it, then also combinations of 
different gasses maps perhaps weighted to their level of harming 
to the environment and sustainability and finally the results 
should be used to assist the indicators and to improve the works 
of urban design, redesign and urban management towards 
sustainability. 
The factor map above calculated is used with the taken value 
    
    
  
  
Reduced Co values hy Controlling 
4 Enecgy Consusiption & (Grecoery Favorite, & Road Effects) 
  
  
  
  
Figure 11 Reduced CO2 Map 
(Energy reduction + Green factor - Road factors) 
4. CONCLUSION 
GIS role to assist ranking urban sustainability is shown 
using the practical examples above, where tangible results 
could be measured, and clear understanding is provided, 
conducting the scenarios thus provide urban planners the 
tools to manage sustainability and use the indicators more 
effectively relating them to GIS layers. 
The results on the other hand showed that condensing 
greenery areas and decreasing some categories of road 
surfaces help sustain urban planning by providing more 
accurate results of CO2 reduction, further assessments 
should take place to replace the assumptions with actual 
values and consequently verify the scenarios results. 
References: 
ADM, ADM Energy Management Report 2011 
Wilson, J., Tyedmers, P, Pelot, R 2007. Contrasting and 
Comparing sustainable development indicator metrics. 
Reza Banai, Land Resources Sustainability for Urban 
Development 
Abdulmuttalib h, Quality Aspects of Monitoring Environmental 
Variations Using Combined GIS & Remote Sensing Techniques 
with Emphases on Data Modelling, FIG 2006 
Abdulmuttalib h, Total Quality Measures for Environmental 
Coastal Monitoring Using Remote Sensing, Lidar Bathymetry, 
Radar Altimetry and GIS Techniques, FIG Congress 2006 
Abdulmuttalib H, Aspects of Data modelling of Fused Surfaces 
with Planimetric Data In a Topographic Geodatabase, 
ISPRS Congress Istanbul 
Abdulmuttalib H., (1998), *GIS Modeled Surfaces And Total 
Quality Management”, 2nd Int. Ph.D. Symposium in Civil 
Engineering 1998 Budapest. 
4.1 Acknowledgements 
We thank those whom participated in the support activities of 
conducting the analysis or in providing some data, and 
particularly Albert Agasthyan and Khalid Khamis. 
  
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