Full text: Proceedings, XXth congress (Part 4)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
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&. Walking Path -HEPU 
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source A: Polygon 244 
pestination B: Polygon 112 
walking Path 
FROM bolygon 244 
TO polygon 231 
CROSS link 2 
: TO polygon 88 
= CROSS link 1 
tas 1 ETS potygon 143 
  
  
  
  
  
  
Links 
EE | Street Blocks 
Selected Links 
Selected Street Blocks 
Figure 5: path between point A and point B 
To know if there is any connectivity between any two polvgons, 
say polygon 88 and polygon 231, just simply by making a 
query of “polyl=88 and poly2=231" or “polyl=231 and 
poly2=88". In this case, the record of link 2 is retricved. 
Similarly, with the previous selected polygons, the result is 
obtained. Figure 5 shows the result of using base map features 
to find a walking path between two points. The pedestrian is 
suggested fo start at polygon 244, polygon 231 and then cross 
the link 2 to reach polygon 88, cross the link 1 to reach polygon 
143 followed by crossing the link 5 to arrive polygon 112, the 
destination. However, it is important to realize that land feature 
configuration in most cases is not that ‘simple’ as illustrated in 
the above example, but with a lot more complexities. 
In Figure 6, there is a barrier between polygon 161 and 86 and 
there are two links connecting polygon 231 and polygon 203. In 
this application, barriers or traffic islands are not considered as 
parts of the solution because they are inaccessible for 
pedestrians. Therefore, these kinds of non-passable features are 
checked and removed from the polygon list (Figure 3) during 
the implementation of the algorithm. Furthermore, there are the 
possibilities of more than one existing link connecting two 
polygons (e.g. the two links between polygons 231 and 203). 
With all these in mind, computation of the optimal walking path 
follows the algorithm as summarized below: 
Step I: Construct a line between the source and destination 
points 
Step 2: Get all intersection points on the line 
Step 3: Overlay the start and end point of each line segment 
with the street and construct a list with polygon ID 
Check inadequate polygons: to see if any physical 
dividers and traffic islands included in the above list. If 
yes, remove them. 
Step 5: Check 1f there are more than one links connecting two 
polygons, if yes, compare the distance of each line 
with the constructed line. Choose the closest onc. 
Step 4: 
60 
Step 6: Query the link with provided polygon ID in the list to 
obtain the connectivity relationships between polygons 
Step 7: Display the result 
  
ource A: Polygon 161 
& Walking Path - HKPU 
  
FROM poly 
  
  
  
  
  
  
  
  
  
rt = yon 161 
rs" \CRoss link 12 
#2 UNKs {TO polygon 36 
{TO BeTygun 88 
F^ ROADF. CROSS link 2 
Lj TO polygon 231 
r""jcRoss link 19 
^| jTO polygon 203 
E 
Moser. | TT TE 
mee emm Links 
Street Blocks 
Barriers 
Selected Links 
Selected Street Blocks 
Figure 6: Computation with the existence of barrier and more 
than one link between polygons 
4. DISCUSSION AND CONCLUSION 
The study indicates that there is a potential to compute walking 
path without the use of road centerline. Although the work 
presented here lacks evaluation or examination, the results 
should be considered as encouraging. It is understandable that 
the accuracy required for walking path is relatively lower, when 
compared with accuracv required for driving path. But one of 
the important components of the future work should be included 
the evaluation. part of the proposed algorithm to test the 
reliability of the model. Besides, the algorithm should be 
further developed and investigated with more walking path 
features such as building blocks, stairs, subways, bridges. As 
can be seen in Figure 5, pedestrians are allowed to move from 
one polygon to another polygon (from polygon 244 to polygon 
23] in this case) without crossing any links in between. 
Therefore, some sophisticated assumptions or considerations 
are needed to take into account in the algorithm. For this 
particular case, the algorithm should consider the road width 
and the existence of barriers etc. in order to determine if it is 
suitable for pedestrians to cross. As a result, further analytical 
and theoretical works and studies are required to explore the 
feasibility of the proposed algorithm. 
This paper introduces a new idea of using an independent of 
any arc-node data model to find path for pedestrians. In fact, the 
objective of transportation system is to improve individual 
accessibility. However, most GIS-T focus on vehicle navigation, 
individual accessibility is less common. This research could be 
important and useful for those people who interested in this area. 
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