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International Journal of Engineering & Technology IJET-IJENS Vol: 10 No: 02 97
Locating Bins using GIS
I.A.K.S.Illeperuma1, Dr. Lal Samarakoon
2.
1Senior Lecturer dept. of CPRSG, Faculty of Geomatics2Director GIC Asian Institute of Technology, Thailand
AbstractIn todays world solid waste management is
a global environmental issue which creates
significant health and environmental risk.
This is a crucial problem in Sri Lanka too
due to the lack of a proper solid waste
management system.
This study was conducted to improve the
present solid waste management system of
Maharagama Urban Council, Sri Lanka
using GIS.
Sample survey was done to collect the data
about amount of waste generated from ahouse, number of people and income of a
family and the households attitude towards
the waste from randomly selected houses.
GPS survey was carried out to find out thesensitive locations.
Model was created to estimate the amount of
waste generated from each house. GIS was
used to identify the locations for bins and
estimate the required capacity of them. It
could be found that 1006 bins with 100m
service area are required to cover entire area.
Key Words: Urban Solid Waste
Management (USWM), Bin location,
Geographical Information System (GIS),
Service area, Global Positioning System(GPS).
Introduction
Solid Waste Management (SWM) is a
function of combination of various activities
such as collection, transportation and disposal
of solid waste. It also includes processing and
treatment of the solid waste before disposing.
(Robinson, 1986). The purpose of SWM is to
create uncontaminated environment for people
without disturbing natural resources (Worldresource Foundation, 1996; McDougall et al.,
2001) and a proper SWM helps safe disposal,
reduction of final waste and increase re-use and
recycling. On the other hand a poor
management system, on the contrary, leads to a
filthy environment affecting the well-being of
the people residing therein.
At the present all over the world, due to the
industrialization, urbanization and uncontrolled
urban sprawl and improvement of living
conditions and population growth, SWM
become a monumental problem. Wastecollection, transportation and disposal methods
may vary from place to place over the world.
SWM system has improved with the help of
new technology in developed countries.
In Australia urban households have been
given a bin to put their waste and those bins are
emptied weekly by the local council. (ISWA,
UNEP, 2002).
Basic measures taken in recent years to
control waste management in Japan include:
pollution prevention, reuse and recycling,
and waste incineration with air pollution
control. (Sakai et al., 1996).
Netherland government has
implemented high land filling tax to make it
less interest by the people and incinerationof waste is the favored method of waste
treatment to reduce environmental risk
(Bartelings, 2003).
The most popular method of waste
disposal in Canadian urban centers is
curbside collection. But in rural areas people
have to carry their waste to the transfer
stations. Then waste from this transfer
station is transported to landfill site (ISWA,
UNEP, 2002).Studied carried out by Visvanathan et al.,
2001 shows that in Asia waste disposal is aserious problem due to uncontrolled and
unmonitored urbanization, and lack of
financial and human resources trained in
SWM system. According to this study the percapita generation of waste in Asian cities rang
from 0.2kg/day to 1.7kg/day. Also ithighlighted that in Sri Lanka waste generation
per capita rang from 0.4 to 0.85kg/day/person
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due to increased consumption patterns as well
as the movement of the people from the rural
areas to urban centers.
In Thailand people are encouraged to waste
segregation at the source of waste generation.
Therefore wastes are sorted into 3 types:
recyclable, food and toxic and dispose them
into 3 different dustbins. (Bui Van Ga, 2004).
Similarly in many Indian cities and towns,
solid waste is normally disposed in an open
dump. (Mufeed, 2006).
Although collection and disposal of the
municipal waste have been improved in
Vietnam, there is no safely disposed method.
Recycling and reuse in Vietnam is an actively
implemented by informal waste pickers
(Vietnam Environment Monitor, 2004).
Bangladesh is also experiencing the
problems of solid waste management. Lessthan fifty percent of whole waste generated in
Dhaka City was collected by Dhaka City
Corporation and bins are not located
sufficiently along the road. So it can be seen
that waste are scattered over the area (Syed,
2006).
Similar to most of developing nations, in
Sri Lanka, solid waste, especially Urban Solid
Waste (USW), is a critical problem and it
becomes severe due to absence of proper solid
waste management systems in the country. At
present recyclable, reusable and organic wasteare collected together and being dumped in
environmentally very sensitive places like road
sides, marshy lands, low lying areas, public
places, forest and wild life areas, water courses
etc. causing numerous negative environmental
impacts (Hazardous Waste Management Unit,
2004).
There are no sufficient infrastructure and
resources for the SWM in many Urban
Councils of the country, and there are no
enough and suitable services to dispose most of
the solid waste from households and industries.(Levien et al. 2000).
With the introduction of new policies for
rapid economic changes during the last two
decades it can be seen that rapid urbanization
and also it is more difficult to find lands for
disposal or waste treatment facilities in
urban areas than in rural areas. Therefore
people in those areas compelled to dispose
their waste in improper manner creating
environmental and health hazards. In
contrast western province is highly
urbanized and densely populated compared
with the other provinces in the country. So
the waste management problem is more
severe in the western province (42 Sri
Lanka, 2001). Thereby Colombo is the most
severely affected area with the disposal
generation of around 1500 tons per day
(Perera, 2003). This problem is quite
significant in Maharagama Urban Council
(UC) which is in Colombo district. To
minimize environmental and health hazards
it is necessary to locate bins along the roads
so that people can find a bin to dispose theirwaste easily. Therefore this
study aims to identify the proper locations
for bins along the roads using GIS in the
Maharagama UC area.
2. Study Area
Maharagama UC is one of the largest
Urban Council in Sri Lanka lies in the
Colombo district in Western province. It is
situated at 6.8460
North latitude and 79.9280
East longitude and is subdivided into 41 GN
divisions for administrative purpose (Fig 1).It covers an area of 3775 hectares. Principal
towns of the area are Maharagama, Mirihana
and Kottawa and it has a population of just
over 177000 people. There are about 28000
households in the area. The UC officers
were estimating per capita waste generation
is around 2.5kg in the area. Rukmale West,
Makumbura South and Kottawa East GN
divisions and the Wijerama, and
Pragathipura GN divisions are the lowest
and highest populated GN divisions
respectively. Most of the commercial landsand industries are found along main roads.
There are more residential lands and
relatively less agricultural lands in the area.
(Table 1)
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Table 1. Landuse data of Maharagama UC area
From personal communication made with
Officials in UC regarding urban solid waste
management in Maharagama UC area, it could
be known that UC provide polythene bags to
householders to collect disposal materials and
to deliver these bags to the vehicle at the time
of collection or place them by the side of the
road closer to their house or put them into the
bin located along the road for the cleaners to
collect these bags when they come to collect
waste. From the UC officers, it was found
that four compactors and two tippers are
used in collecting waste along the main
streets and ten tractors are used in lanes and
small streets where trucks can not approach.Due to the unjustifiable command area of
the existing dustbins located along the road,
those bins are not used by most of the
householders to dispose their waste and
instead they use drains, roadside, water
bodies or any other improper things. This
creates poor sanitary conditions in the area
due to animals: goats, dogs, cows, cats,
crows etc. foraging for food. Further, this
waste may causes to block the drainage
system and creates flood during raining
seasons making significant inconvenience topeople and also stagnant and harmful water
pools may form making a better
environment for sources of many diseases
such as flies, cockroaches, mosquitoes and
rodents. When these wastes are rotten and
decomposed neighborhood make dirty, bad
smelling. Lighter waste materials are
observed to have been scattered by animals,
Landuse Area (m2)
Barren 197016.88
Cemetry 17706.30
Commercial 820892.91
Industry 393868.83
Marshy land 1013882.06
Other agricultural land 1316884.96
Paddy 4958619.18Playground 38522.72
Public 867372.81
Religious land 223419.15
Residential land 26514910.94
Scrub 345844.38
Water bodies 327383.73
Fig 1. Map of Maharagama UC Area
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wind and vehicles adding unpleasant outlook to
the area.
All the wastes collected from households
and other places by UC were transferred to
open dump site located at Navinna GN division
of the Maharagama UC area. Maharagama UC
officials said that then these wastes are sold tothe private company. Company people sort
them out at the site and bring to their place.
In some of the areas wastes are collected by
UC very frequently while in some other areas
wastes are not collected at all by the UC. If the
UC vehicle comes to collect the waste almost
all householders are prepared to put their waste
into the vehicle. Only the householders of those
areas where the UC does not collect waste
adopt alternative methods to solve their
problem of waste disposal. Followings are the
disposal methods used by those people todispose their waste.
1) Collect and Burn.
In this method all types of wastes together
collect and burn.
2) Dispose waste into a hole in the garden.
People who have enough space to dispose
their waste, prepare a hole in their garden and
dispose their all waste into this hole.
3) Collect all types of waste under the tree.
4) Plastic / paper/ polythene burn and other
waste dispose into a hole in the garden.
In this method plastic, paper and polythene
waste were separate from household waste
and they were burned. Then rest of the waste
was disposed into a hole in the garden.
5) Put all waste into the UC vehicle when it
comes to collect waste.
Inquiries made from officials of the Central
Environmental Authority and Maharagama UC,
it revealed that government offices and schools
have their own procedures to collect waste and
they do not use bins located along the roadsideto dispose their waste. Everyday UC vehicles
go to those places and collect those wastes.
Further they stressed that commercial waste too
is separately collect by the UC. Therefore in
this study consideration was limited only to the
residential buildings.
3. Methodology
Methodology followed in this study is
included conducting questionnaire survey to
collect data and GIS based analysis to find
proper location for bins along the roads.
Procedure of the study can be summarized
as in Fig. 2.
3.2 Data collection
For this study, data from different
sources were collected and were integrated
to create database for the study area. Digital
maps of Land use/Land cover, road networkof the area, streams, water bodies,
population density map and foot print of
buildings over the area were collected from
Road Development Authority of the
country. Digital map of building foot print
with height attribute was collected from
Survey Department of the country. Few
questions were prepared to collect the data
about amount of waste generated from a
house, number of people in a house, income
of a family and to have an idea about the
peoples attitudes towards the waste. Then
using this questionnaire, householders from
randomly selected ten houses in each GN
division of the Maharagama UC were
interviewed. Altogether four hundred and
ten households were used for this
questionnaire survey. Same time GPS
survey was conducted to find the location of
GPS Survey Questionnaire Survey
Identify the
sensitive
areas
Models to
estimate amount
of waste
generate from a
house
Road
Network
Identify the
locations for
bins & calculate
service area
Determine
capacity of bin
Fig. 2. Procedure of the study
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these houses. Two sample bags which can be
filled with one kilogram and half kilogram of
waste were used to estimate the weight of
waste generated from these households.
Showing these bags, householders were asked
how many bags of waste are generated from
their house. Further to get the location ofsensitive areas such as school, religious places
etc. where bin should not be located at the close
proximity of them, GPS was used. Locations of
bus stops over the area were surveyed too.
3.3 Allocation of bins along the road
Procedures conducted in this process
mainly divided into two. Firstly analysis of
sample survey data was done to create models
to estimate the number of people in a house and
amount of waste generate from a house per dayand income of a family. Allocation of bins
along the road is the second and main part of
this process. Fig. 3 summarized the work flow.
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Centroids are within
sensitive area
Sample Survey data
Model formation
Approximate
number of people in
each household
Approximate income
of each household
Landuse
data
Building
Layer
Identify households
in residential area
Rasterization
Waste density
map
Estimation of waste generate
from each household
Polygonization
Identify centroids in
high density area
yes
Exclude points
Centroids are on the
roadNo Yes
No
Shift the points to
the closest point on
closest road
Considercentroids as bin
location
Calculate service
area of initial
bins
Network data
set (Road)
Locate otherbins
Calculate servicearea of bins
Determine number of
houses in each servicearea
Calculate
capacity of bins
Fig. 3. Work flow for allocation bin along the roads
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Generally it could be said that amount of
waste generated from a house mainly depend
on the number of people in that house,
education level and income of the family. But
household wise information was unavailable to
collect. Also it is out of scope to conduct a field
survey to gather information from eachhousehold in the area as time consuming.
Therefore regression analysis was done using
sample data to estimate number of inhabitant in
a house, income of a family and amount of
waste generated from a house per day and
Minitab statistical software was used for the
analysis.
Generally it can be assumed that number of
people in a house depends on the education
level of the family, size of the house and
number of storey in a building. During field
survey it was noticed that there were nohousing complex in the area and no multi
storied houses. Although there are two storied
houses, one family with three or four members
are living in most of those houses. Therefore a
number of storeys in a building were not
considered when estimating the number of
people in those houses. Since education levels
of each and every household of the study area
was not available only the size of the house
was considered to estimate the number of
inhabitant of the family. Regression analysis
was done to find out the relationship between
Number of people and area of the house.
Following equation obtained with P value zero.
Then this equation was used to estimate the
number of people in the house when analysis
the whole dataset.
With the available data, income of the
family is estimated by using the area of the
house. Regression analysis was done to find outthe relationship between income and the area of
the house. Following equation was got with the
P value zero and it was used to approximate the
income of a family when considered whole
dataset.
Finally to create the equation to estimate
the amount of waste generated from a house,
regression analysis was done following
relationship was created.
In this calculation it is assumed that all
people in the house generate equal amount
of waste though it depend on various
factors.
Normally people use a road to go to the
bin to dump their waste. Hence the service
area of a bin which is a region including thehouseholds that dispose waste to the bin in
consideration can not be a circular area. In
GIS software Network Analyst function
facilitate to find service area of a particular
distance around any location on a network.
A network service area is an area that covers
all accessible roads which are passing
through that location and have specified
length. As an example, in Fig. 4-B brown
colored area is a 100m service area of a bin
calculated using network analyst function of
ARC GIS software without using trim
length. This area covers all road sections
which are passing through the bin location
with 100 meter length from the bin and
service area polygon is created by joining
end point of these roads. Therefore this
service area polygon may exclude some
householders who can reach to this bin by
walking maximum distance of 100 meters or
less than 100 meters. In Fig. 4-A service
area of a bin was calculated same as in Fig.
4-B but using trim length. Therefore thispolygon covers more householders who can
reach to this bin by walking 100 meters or
less than 100 meters. Therefore this method
was used to calculate the service area of a
bin in this study.
Number of people = 0.0315 * Area of the house
Income = 208 * Area
Amount of Waste = 0.174*Number of people
in a house + 0.000021*Income
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As a first step of determining service area
polygons of bins, Network data set which is
made of network elements: edges, junction
and turn has to be created. Then service area
analysis layer has to be created to determine
the service area polygon of each bin. Fig. 5shows input and outputs of service area
analysis layer.
Fig. 5. Input and outputs of service area
analysis layer
Impedance which is cost attribute of
traversing along road, polygon break which is
extent of the service area to be calculated and
trim polygon length is a length that trims the
edges of the polygon to a specified distance
are input of the service area analysis layer.
From questionnaire survey data it could be
found that 98%of the householders
maximum preferable walking distance to thebin to dispose their waste is 100m. Therefore
bins were located at the maximum preferable
walking distance of 100 meters by computing
service area of the each bin, considering road
network data. 20m buffer zones were created
around schools and religious places and 30
meters buffer zones were created around
water features to avoid locating bin at the
close proximity of them. Though people
requested to keep a bin near to the bus stop,
four meter buffer was created around bus stop
to avoid locating bin very closer to them.As a guide to locate initial bins, waste
density map is prepared to identify the high
density waste generation area and first bins
were located at the centroids of the high
density area. First step of doing this, waste
generation point map is converted to raster
map with cell size 100m and cell value of this
raster map calculate as bellow.
Cell Value = Sum of the attribute of all the
points within the cell
Where attribute is amount of waste generate
from the point.
Then waste density map was prepared
using the following equation.
Waste Density = Cell Value / Area of the cell
Network data
set
Network location
(Bin locations)
Service area
polygons
Roads within each
service area
polygon
Input
Outputs
100m
Fig. 4. 100m service area polygon
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To identify the centroids of the high
density areas this density map was
polygonized and polygons with their
centroids at the high density areas were
shown in the Fig. 6. Then centroid of this
high density area was considered as location
of the bins and check whether they are within
the buffer zones of sensitive area or not.
Centroids which are in buffer zones were
excluded. However bin should be located
along the roadside. Therefore to check
whether the other centroid points are on the
road, they were overlay with the road
network.
If a road crosses over the centroid points
then centroid location is considered as a bin
location. If not firstly locate the point at
centroid then it is shifted to the closest point
on the closest road of that point. It was done
by drawing a perpendicular line from the
centroid to the closest road. Then the
intersection point of that line and road was
consider as the location of the bin since it is
the most closest point on the road to that
particular centroid.
Thereby service areas of these bins were
calculated by using network analysis. To
locate the next bins trial and error method is
used with the aim of avoiding much
overlapping of the service areas, cover more
areas and all the sections of the road network
by service area. If these points produce
satisfactory results, then proceed to find the
location of the next bin. Self judgment will
be applied to select a location for the bin.
This way all the points will be located (Fig.
7.).
Fig. 6. Polygons with their centroid over the high waste density area.
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Fig. 7. Location of bins along the roads
After locating bins, amount of waste
generated within service areas of each bin
which is the capacity of bins to collect the
waste within a day can be easily determined
with ARC GIS software. This is the capacity
of bins to collect the waste within a day.
There by considering present waste collection
frequency by UC, capacity of bins were
determined.
4. Results and discussionFrom questionnaire survey data analysis it
could be found that mainly three methods are
used to dispose the household waste in this
area (Fig. 8).
65.4%
21.7%
12.9%
Category
Burn
Open dumping
Put into the UC vehicle
Disposal methods practice i n the Area
Fig. 8. Disposal methods
All these methods create environmental and
air pollution and create an inviting
environment for such pests as flies,
mosquitoes, cockroaches, rats etc. Therefore
the danger of spreading diseases like Dengue,
Malaria, Brain fever, Pylaria etc. is there too.
People in this area adapted to these disposal
methods since there is no proper waste
collection procedure by the UC. Hence it is
necessary to locate bins along the road so that
people can find the bin easily to dispose their
waste. Using Network Analysis function in
ARC GIS software 1006 bins were located tocover entire area (Fig. 9). Thereby amount of
waste generated within service areas of each
bin were determined. Fig. 10 bellow shows
the amount of waste generated within each of
the service area per day. According to the Fig.
10, amount of waste gathered into a bin per
day range from three kilograms to hundred
kilograms in the UC area. Bins with same
capacity can be located along the roadside.
Then there might be some bins which get
filled within a day or even in a less time while
some bins get filled in two days or take evenmore time. So capacity of the bin determines
the waste removal frequency of the bin too.
Then when deciding the capacity of the bins it
is better to consider the frequency of waste
removal from bin and optimum path of the
UC vehicles to transport the waste from bin to
landfill site too.
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Fig. 9 Location of bins along the road
Fig. 10. Amount of waste generated within service area polygon per day
From the questionnaire survey it could be
seen that in some of the areas wastes are
collected by UC very frequently while in
some other areas wastes are not collected at
all by the UC. Table 2 given bellow shows
that the percentage of households of different
frequencies of waste collection by the UC.
Fig.11 shows the frequencies of household
waste collection by the UC in different GN
divisions.
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Table 2 Frequent of waste is collected by the UC and percentage of households
Fig. 11 Frequency of households waste collection by the UC
(Households shown in the figure are houses used for questionnaire survey)
It is necessary to make an arrangement to
extend the present waste collection procedure
to cover entire area. Further waste cannot
keep in the bin for long time it better to
collect waste from bin twice a week. With this
waste collection frequency required capacity
of each bin to accommodate waste dispose by
the people within the service area polygon
each bin is shown in the Fig. 12.
Frequent of waste
collect
% of
Households
Every other day 4.88
Once a week 53.17
Twice a week 7.32
Not collected by UC 34.63
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Fig. 12. Capacity of bin
5 Conclusion
Service area of a bin can be calculated
accurately using Network Analysis function
in GIS software instead of creating circular
buffer around it. Therefore it can be conclude
that GIS can be used to locate bins along
roads accurately based on road network.
Further in this study amount of waste generate
within the service area of a bin was
determined with the help of GIS. Also it can
be conclude that GIS based computation for
waste generation estimation can ensure
accurate design of capacity of bins.
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