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V. Jain et al.
study, the feature data is rasterized using the Euclidean distance rule. It computes the
Euclidean distance to the closest source for each cell, which serves as the preliminary
raster set on which further operations are performed.
2.2.1 Classification
Each raster dataset requires some stage management to convert data into a format,
whose values reflect the criteria for an optimum pipeline route analysis (PRA).
Briefly, the process for each input dataset consists of assigning values (cost) to each
pixel and converting vectors to raster for those cell values to which the weights are
assigned. For this purpose, classification of data is done to subdivide each dataset into
cells of various costs depending on their suitability for pipeline laying. In this study,
we have done classification of preliminary dataset using the ISO cluster unsupervised
classification tool
2.2.2 Cost Assignment
The classified data has some preliminary weights allocated by the system. These need
to be further modified as per the need of the problem. This is done by reclassifying
the datasets. Various factors such as the number of classes, break points and the costs
given to these classes are here adjusted. High costs are given to classes where pipe
laying will be difficult. For instance, in this study, very high costs are given to cells
with rail, water bodies or built up areas in them.
2.3 Cost Surface
Once the various cost raster is prepared, these need to be combined into a single
cost surface for further computations of least cost path. This is done by using the
weighted overlay tool in ArcGIS. Herein, the various raster is summed up into a
single raster. Every factor is given an importance value which acts as its weightage
in the combined raster. The weights are given as per experts’ opinions and references
[1–4, 6, 7]. The cost given to the various factors and their subvalue in this study are
as shown in Table 1.
2.4 Least Cost Path
Cost surface is the input to define the best pipeline route by calculating the least cost
path (LCP). ArcGIS Spatial Analyst uses the following steps (a) use the cost distance
tool to create two pre-requirements for LCP: (i) “cost distance (CD)” surface and
V. Jain et al.
study, the feature data is rasterized using the Euclidean distance rule. It computes the
Euclidean distance to the closest source for each cell, which serves as the preliminary
raster set on which further operations are performed.
2.2.1 Classification
Each raster dataset requires some stage management to convert data into a format,
whose values reflect the criteria for an optimum pipeline route analysis (PRA).
Briefly, the process for each input dataset consists of assigning values (cost) to each
pixel and converting vectors to raster for those cell values to which the weights are
assigned. For this purpose, classification of data is done to subdivide each dataset into
cells of various costs depending on their suitability for pipeline laying. In this study,
we have done classification of preliminary dataset using the ISO cluster unsupervised
classification tool
2.2.2 Cost Assignment
The classified data has some preliminary weights allocated by the system. These need
to be further modified as per the need of the problem. This is done by reclassifying
the datasets. Various factors such as the number of classes, break points and the costs
given to these classes are here adjusted. High costs are given to classes where pipe
laying will be difficult. For instance, in this study, very high costs are given to cells
with rail, water bodies or built up areas in them.
2.3 Cost Surface
Once the various cost raster is prepared, these need to be combined into a single
cost surface for further computations of least cost path. This is done by using the
weighted overlay tool in ArcGIS. Herein, the various raster is summed up into a
single raster. Every factor is given an importance value which acts as its weightage
in the combined raster. The weights are given as per experts’ opinions and references
[1–4, 6, 7]. The cost given to the various factors and their subvalue in this study are
as shown in Table 1.
2.4 Least Cost Path
Cost surface is the input to define the best pipeline route by calculating the least cost
path (LCP). ArcGIS Spatial Analyst uses the following steps (a) use the cost distance
tool to create two pre-requirements for LCP: (i) “cost distance (CD)” surface and