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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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