1. INTRODUCTION 
1.1 Forward to Grading Urban Sustainability 
Sustainability is a way of thinking, a way of understanding, a 
way of acting and a way of living, for that a city planner besides 
and together with many other specialists should think, 
understand, act and live for sustainability. That’s living in a 
world where everyone takes part in protecting it, conserving its 
resources, thus sustain it. Ok, that’s one thing but who can tell 
or indicate the right way to do that, and who can measure if the 
correct method is followed, besides the closeness to this sort of 
ambiguous status of our world or part of it. 
Thus, for planners and others to do so in a spatial geographic 
world, Geoscientists provided spatial tools which if used 
effectively, the indicators of sustainability will start to flow in 
the same stream or perhaps same direction, and the closeness of 
some works or activities to satisfy an indicator can be much 
more comprehensively planned, implemented and measured. 
Giving an example of which, someone might say the emission 
level of greenhouse gases is an indicator or part of an indicator, 
or the closeness of industrial areas to dwelling is a negative 
indicator, or whatever valuable measures they can be that are set 
by specialized organizations, and herein comes the role of 
spatial analysis tools to provide an assistant for thinking about, 
understanding it, acting in accordance to, and living a life of 
such. This paper reflects role assessment using some activity 
works with practical examples of sustainability spatial analysis, 
targeting monitoring and protecting our world environment 
letting the process work flow show and prove how to use the 
different sustainability indicators particularly in urban planning. 
1.2 Analysis of some layers affecting CO2 emission 
It’s well known that CO2 is the major part of greenhouse 
gasses, these gasses off course are related to many activities 
which can be positive or negative to an indicator, but only some 
of which will be assessed herein. That is because this 
assessment shall be further continued in two parallel works 
which are going on, those works or researches have some 
factors in common, and they also differ in their goals, and the 
gap analysis they are working on, one of them is dealing with 
urban sustainability in general, while the other is only using the 
environmental spatial analysis to grab the quality measures 
associated with the process of analysis. Further using the tools 
that Geographic Information Science provides inclusive of 
remote sensing tools, or in other words *vector and Raster 
spatial analysis" the following factors were considered in the 
analysis: 
l. The energy consumption of particular buildings were 
calculated from the available sample data 
2. The suspected energy consumption of all the 
buildings in the test area were calculated 
3. Calculating the energy of a sample building that had 
implemented energy reduction strategy for one year 
4. Calculate the suspected hypothetical reduced energy 
for all the buildings if implemented a similar strategy 
for energy reduction 
5. Measure the value of equivalent Co2 reduction that is 
caused by the reduction in energy consumption 
6. Distribute the reduced values to the volumes of 
building data and calculate area wise reduced Co2 
amounts 
7. Use greenery feature classes to give a percentage of 
positive added value to Co2 reduction depending on 
the density and type of vegetation in each created 
buffer zone 
8. Use road surface feature class to give a negative 
percentage to the Co2 reduced values depending on 
the occupied sum of area within each selected 
buffered building element 
9. Calculate the resultant hypothetical reduced energy 
summation of the sub areas and for the total test area 
10. Repeat the works changing the methods of calculation 
forming scenarios to compare the results 
11. Collect actual environmental sample measurements 
from in-situ  instrumentations and verify its 
consistency with the results from the scenario 
measurements 
12. This shall be followed by starting to investigate the 
quality aspect measures in every phase of the 
operations. 
13. Then other complementary factors shall also be 
consider such as green roofs and sustainable buildings 
14. Reproduce the values of the quality model and further 
tune them, that they shall be usable generally with 
similar spatial analysis works. 
The test area comprised high rise buildings and also distributed 
villas that range of approximately on three floors, the floor 
average height was selected to be three meters initially, further 
the actual building height will be used for calculating the 
volume of a building for the sake of calculating the average unit 
energy consumption of each building hypothetically. The 
problem is the lack of actual data of energy consumption, but 
once more data is available then only the parameters will be 
verified, which off course will increase the reliability of the 
results. 
The statistics of the tables always played a role in deciding the 
values that will be used for the equations, more specifically 
histograms were generated for each resulted table values, and 
using them equations were constructed for further analysis as 
will be shown below. 
The major data sets were used for the analysis are characterized 
by table , they were selected after considering the relations of 
the different existing feature classes to those indicators touched 
by or involving the greenhouse gasses, besides them having 
relations to cultural, regional and community aspects. 
  
  
  
  
  
Feature class Major role in the analysis Specific 
Type indicator 
relation 
Buildings Represent Show the Cultural + 
consumptio | reduced CO2 community 
n units values 
Greenery Further Represent Community + 
reduce CO2 | community regional 
class level 
Road surface Increase the | Represent Cultural + 
CO2 accessibility Community 
  
  
  
  
Tablel. 
304 
Major initially used feature classes 
  
  
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Table 2 
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the sam 
sample 
the othe