GIS Based Temporal Sheltering Optimization
K.Naghdi1 , M.J.Valadanzoej 2 , A.Mansourian 3 , M.Saadatseresht 4
1: Faculty of Geodesy & Geomatics Eng.
K.N.Toosi University of Technology, Tehran, Iran
2: Faculty of Geodesy & Geomatics Eng.
K.N.Toosi University of Technology, Tehran, Iran
3: Faculty of Geodesy & Geomatics Eng.
K.N.Toosi University of Technology, Tehran, Iran
4:Center of Excellence for Geomatics Engineering and Disaster Management
Tehran University , Iran
Temporal sheltering is a very important issue in disaster management, since optimum temporal
settlement of people in predefined safe areas may decreases the number of victims who would
faces with post earthquake disasters.
For an optimum sheltering, several factors should be considered including minimal movement of
people and homogeneous distribution of victims in safe areas with respect to their.
In the context of research project, RS and GIS techniques were utilized for optimization of
temporal settlement in three steps. First, determination of safe areas, second, determination of
optimum path between building blocks and safe areas, and finally grouping of building blocks
relating to each safe area. This paper outlines the results of the research.
Disasters have always been with people during the history and the human generations have
always had to tolerate disaster and its caused damages. According to  disaster is defined as:
“Serious disruption of the functioning of a community or a society causing widespread
human, material, economic or environmental losses which exceed the ability of the
affected community or society to cope using its own resources.”
Due to negative impacts of disaster on society and sustainable making an appropriate
management of disaster is a necessity.
With this in mind, disaster management is defined as a cycle of activities including mitigation,
preparedness, response and recovery. Mitigation efforts refer to those activities which reduce the
vulnerability of society to the impacts of disasters. Preparedness efforts refer to those activities
which make the government and disaster responders prepare for responding to a disaster, if it
occurs. Response refers to the activities necessary to address the immediate and short-term
effects of a disaster, which focus primarily on the actions necessary to save lives, to protect
property and to meet basic human needs. Relief, rescue, search, firefighting, medical service,
permit control, sheltering, evacuation, law enforcement and many others are samples of disaster
response activities. Recovery efforts refer to those activities that bring communities back to
normal (such as reconstruction) and they should be toward meeting mitigation and preparedness
needs (Figure 1) .
Depending on whether the event is predictable or unpredictable, the place of temporal
sheltering in the cycle of disaster management will be different. If the disaster is predictable like
the earthquake, sheltering the injureds is the major part after the disaster, which is a part of the
response phase. In this situation for temporal sheltering of the injured people, the safe areas
around the city or the countryside should be recognized as well as the rescue operations. In the
next process, the injured people should be transferred to these safe areas by the optimum path.
When the disaster is predictable like flood, sheltering the people will be explained in the
preparation phase. In other word, people should be carried to safe areas by optimum path before
the disaster occurrences. In figure (2) the process of improving temporal sheltering in general in
GIS environment can be seen with the usage of remote sensing images. In next part of the article
the process will be explained in details .
2. The process of temporal sheltering optimization
Based on the figure (2) the process of optimizing temporal sheltering is done in three steps.
First, determination of safe areas, second, determination of optimum path between building
blocks and safe areas, and finally grouping of building blocks relating to each safe area. Each of
these processes will be explained next.
2.1. Determination of safe areas
Safe area must be safe for people transferred there from danger and should be available .
On the other hand, the capacity and distribution of these places should be in a way that not only it
should support surrounding all building blocks but also the distance between building blocks and
the safe area should not be more than a defined threshold (e.g. 1 km). For determining safe areas
some parameters such as availability of facilities, area size, slope, the distance from danger, etc.
should be brought into consideration.
Safe areas maybe open (e.g. parks) or closed (e.g. schools). Closed areas can’t be extracted
from satellite imageries and should be extracted from available maps. However, open areas can
be extracted from satellite imageries. Open areas classified open areas with smooth texture and
In this research, for extracting open areas with smooth texture, texture analysis is used. At
first the texture analysis is conducted by applying a window with suitable size to the image. Then
by thresholding on the image variance areas are extracted. Some post processing in GIS and
image processing systems are also applied for extracting safe areas based on the mentioned
parameters. That defines a safe area.
For extracting areas with coarse texture, the NDVI index is also used since this index has
higher sensitivity to chlorophyll from plants (figure 4). The other steps for extracting coarse
texture are similar to smooth ones, as mentioned above.
2.2. Determination of optimum path
After determination of safe areas for temporal sheltering, determination of optimum path
between the building blocks and safe areas is the second phase. In fact, for reducing the
displacement time/distance of population in danger, the optimum path between each building
blocks and the safe area located in a suitable distance, should be searched and determined by
For determination of optimum path between the building blocks and safe areas, we can
consider three simple to complicated standard: (A): The shortest straight path between them. (B):
The shortest path between them in roads network. (C): The shortest safe optimum path in roads
network (by considering traffic data, safety of the road, etc.). In this research the first case is
consider to continue procedure.
2.3. Temporal sheltering mapping
The last step in the process of optimizing temporal sheltering is to prepare a map presenting
safe areas and optimum path for reaching them. This map is given to the people at the preparation
phase. Using this map everybody knows where and how to go in the case of a disaster for
temporal settlement and receiving relief services.
Optimization temporal sheltering means grouping building blocks for each safe area in such
away: 1) Distribution of the population in the safe areas to be corresponding with its capacity.
2) The population movement from building blocks to the safe areas should be minimized so that
people can be sheltered rapidly. In order to have the least movement of people, the
highly-populated building blocks should get closer to safe areas nearby. In other words, the
multiplication of the population in danger means the number of people who are remained alive in
the building blocks with high dangerousness.
Thus, the multiplication of the length of the optimum path in the population in danger equals
to the cost of replacing the population of each block. The aim of optimization is to minimize the
total of these costs for all building blocks (V objective function), In addition the population
should also distribute to the safe areas with respect to their capacities (U objective function).
Based on the equation (1), these two objective functions namely U and V should be
simultaneously minimized .
for solving the optimization problem
In this equation dij is the length of path and pij is the population in danger relating the ith
building blocks that are assigned to the jth safe area with the Cj capacity.
For having an optimized grouping the above objective function should be optimized
simultaneously. For minimized objective function of U and V simultaneously, multi-objective
optimization problem should be used . There are three general ways for solving
multi-objective optimization problems: (A): Weighted Averaging. (B): Making Constrains. (C):
In this research the second method has been used. V objective function is considered as the
optimizing function and the U objective function is considered as additional constrain. The
concluded answer from the first objective function is refined in order to bring the second
condition. For this work, safe areas that have overflow of population as a result of doing the first
objective function are being solved by the optimized replacement of population to empty safe
areas (Figure 5).
In the figure (5), the color of safe areas explains the amount of population overflow and the
color of the line explains the amount of V costs. Figure (6) explain the amount of changes for
objective functions within the optimization.
Figure 6: objective Function (U & V)
Step 3. V cost
Step 4. V & U
Step 1. The test area Step 2. The point model of the test area
The table(1) shows the amount of optimizing objective functions for each safe area and in its
last line the total overflow of population (sum of positive amounts of U cost) and the total V cost.
In this research, temporal sheltering optimization in disaster management was modeled and
explained. In this regard the details of three steps of determining safe areas, determining optimum
path and groupings of building blocks were explained and the result of the model was given.
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