NHST-Surat 2011, RS, GIS, Solid waste management, buffer zone

1. 1
APPLICATION OF RS AND GIS IN SOLID WASTE MANAGEMENT
IN URBAN AREA
S. P. Parmar
Asst. Professor, Dept. of Civil Engg,
Faculty of Technology, D.D. University, Nadiad, Gujarat
E-Mail.ID: samirddu@gmail.com Contact No. 9427619628
ABSTRACT
As in most developing countries, today solid waste management is one of the key parameters for evaluating
the human development index of a nation. The role of municipalities in the development of the cities and
towns is thus very crucial in the modern context when urbanization is expanding rapidly. Remote sensing and
Geographical information system is an advanced tool to simplify the management procedure. Geographic
Information System (GIS) has proved to be an ideal tool for urban planning and management owing to its
versatility in handling a large set of data, providing an efficient environment for analysis and powerful set of
tools for collecting, storing, retrieving, transforming and displaying spatial data. The present paper explores
modern GIS in the estimation of solid waste in cities and comparison of effectiveness of present waste
collectors with new suggested solid waste collectors by buffer zoning in relevant area. It is expected that
such assessment of the existing infrastructure will help the local government bodies in formulating the
necessary principles for better utilization of their existing resources.
Key words: RS, GIS, Solid waste management, buffer zone.
1. Introduction
The present case study discusses the applications of GIS in solid waste management with Ward
Vijay Colony of Dehradun. The objective is simply to deliver the services efficiently by taking
appropriate planning and management arrangements. The concept of systematic urban planning is
becoming very popular nowadays in the areas related to urban management and development. GIS
is commonly used as a tool to simplify this process. City planning is a classic application of GIS, in
which common data is used to co-ordinate activities and reduce duplication of effort. However, it
has been argued in various studies that in addition to being a planning tool, GIS can also be used as
a means for stakeholder involvement. Since public actions are an aspect of the reality planned, and
plans often implicitly influence public behavior, it is all the more important that PPA approach
should be adopted along with this.
1.1: Objectives
1. To analyses and estimate the generation of solid waste;
2. To Generation of digital database of study area;
3. To propose the sites for locating solid waste dustbins; and
4. To propose methodology and design for the management of solid waste
1.2: Data Used
Satellite remote sensing has demonstrated a large potential to obtain urban information especially
for high resolution sensors. The remote sensing devices are being constantly improved to acquire
high resolution remotely sensed data. However the spatial and spectral bands in which sensors
collect the remotely sensed data are too important parameters in urban utility mapping and
development of urban resource information system. In the case study IRS-1D LISS-II (26th
March
2002) and PAN data (26th
March 2002) has been used.

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1.3: Characteristics of PAN camera
Geometric resolution from altitude of 817 km 5.8 m
Effective focal length for optics swath 980 mm
Field-of-view for optics ±2.5º [across track]
Spectral band 0.5-0.75 μm
1.4: Characteristics of LISS- III Sensor
Table-2: Sensor characteristics
Band 2 0.52 - 0.59 μm
Band 3 0.62 - 0.68 μm
Band 4 0.77 - 0.86 μm
Band 5 1.55 – 1.70 μm
Geometric resolution 23.5m for bands 2, 3, 4.
70.5 m for band 5.
Equivalent focal length
(bands 2, 3, 4/ band 5)
347.5mm/301.2mm
Swath 141 km for bands 2, 3, 4.
Radiometric resolution 7 bits
Band-to-band registration ±0.25 pixel
1.5: Topographical Maps
Survey of India (SOI) topographic maps on 1:50,000 scales cover entire project area. These maps
have been used for preparing base map, drainage etc, for the study area. The SOI guide map at
1:20,000 scales has been used for aid in visual interpretation, extraction of roads and at the time of
field verification.
1.6: Table -3: Details of SOI Maps.
SOI Map No Scale Year Of Survey Year Of Publication
53 F/ 15- 16 1: 50,000 1966-67 1972 (1st
ed.)
Guide Map 1: 20,000 1973-74 1975 (1st
ed.)
Hardware and Software Used
Hardware- Microsoft Windows operating system (P-IV), Global Positioning System Garmin with
12-channel facility.
Software- ERDAS Imagine Version 8.4; Arc View 3.2a; Microsoft Office 2000.
2. Profile of the Study Area
The whole city of dehradun is divided in to 45 wards to facilitate the governing body. For our study
areas we have considered ward no 44. Ward no 44 is situated on north of the Dehradun centre and
its major boundary is connected with cantonment area. The ward is connected with the main city by
Cantonment Road as Main Road. The whole ward is having major portion is of Institutional
Buildings like SOI, IIRS, School of Management, Archeological Survey of India, College of
Advance Sciences and two schools. The residential area is divided into the three classes like Higher
Income Group (HIG), Middle Income Group (MIG) and Lower Income Group (LIG). Very small
amount of area is acquired by Slums in low lying areas along with drains. The population of the
Vijaynagar ward is 8097, in which males are 4103 and female are 3994. The total number of

3. 3
household is 1569 is there in the ward No 44. All the houses are not more then two stories and
major portion of residential area is covered by MIG and HIG peoples.
Figure-1: Vijay Colony Ward
Figure-2: Satellite Imagery of Vijay Colony (ward no.44)
3. Waste management
3.1: Quantity and Characteristics of Solid Waste
Quantity and characteristics of the waste are the major factors, which decide magnitude of waste
management problem. It is necessary to carry out weight estimation exercise regularly to assess the
quantity of waste. Future per capita quantity can be estimated with the help of projected population
and annual increase of per capita quantity. On the basis of the waste quantity, infrastructure
requirement can be estimated. This data will also serve as a basis for selection of disposal/treatment
option.

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3.2: Role of RS & GIS in SWM
Solid waste systems are quite complex in nature due to large number of variables and parameters
such as varying quantities of solid waste with different composition, manpower, vehicles and
equipment, processing and disposal options. It is directly related to the geography of area and the
quality of life of the population. Remote Sensing and Geographical Information System provides
the best platform for computerized analysis for decision making in planning and operation of the
system. It links spatial data with the geographical information about a particular feature on a map.
It has the capability to dynamically analyze the changing nature of the urban ecosystem. It enables
the local planners to estimate in advance, the scale of environmental change on population
parameters.
3.3: Quantification of solid waste
The quantity and general composition of the waste material that is generated is of critical
importance in the design and operations of solid waste management system. Unfortunately, reliable
quantity and composition data are difficult to obtain.
3.4: Traditional methods of waste estimation
1.Load count analysis: In this method the quantity and composition of solid waste are determined
by recording the estimated volume and general composition of each load of waste delivered to a
landfill or transfer station during a specific period of time. The total mass and mass distribution is
determined using average density data for each waste category.
2. Mass Volume analysis: This method is similar to the above method with the added feature that
the mass of each load is also recorded.
3.5: Factors that affect generation rate
ÿ Geographic location.
ÿ Season of the year.
ÿ Collection frequency.
ÿ Public attitudes.
ÿ Characteristics of population (Social Status).
ÿ Legislative laws.
ÿ Recycling.
ÿ Design criteria for refuse generation.
Quantum of refuses α population of city or symbolically Q = m x p.
Where, Q is the quantum of refuse, p is the population and m is constant. The value of mass m as
discussed above depends on the geographical location, economic function of the city and
behavioral pattern of city dwellers, commonly called as Solid waste multiplier generally expressed
as Kg/Capita/day.
4. OBSERVATION AND ANALYSIS
4.1: Database Preparation & Generation
The prerequisite to geographic analysis is that the data is in proper format for the software used to
perform analysis. It is very important that the data is free of all types of errors and the data is well
structured. It should be insured that a functional geographic database containing the number of
associated coverage’s is available, where each coverage contains clean topology, accuracy of all
features and attributes are verified and a system of tics or ground control points exists. The digital
format offers flexible input as well as output. Hence, it should be used to its maximum capability.

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The success of any Geographic analysis is using GIS, which largely depends upon completion of
database used to perform analysis.
4.2: Analysis
The ward Vijay Colony has more then 70 per cent area under the Survey of India and Indian
Institute of Remote Sensing. Author did not consider Survey of India, IIRS, and Archeological
Survey of India in the study as they have their own system of solid waste management. So for the
convenience author consider them under the Institutional area.
The roads are classified into four categories- Main road, Colony road, and Lane and Mud lane on
the basis of the width. Main road, New Cantonment road and Kalidas road have width 14 m and 8
m respectively. Lane and mud lane have width 4m and 2 m respectively. Mud lane is in the LIG
area where conditions are of slum type. The resident of LIG areas are not properly attended by the
municipality workers as the way is very narrow. As a result they disposing their garbage in the near
by drain, which is along with the mud lane. This area is not properly accessible from all sides. The
space along the roads is not adequate for putting the solid waste dustbins. This is one of the main
reasons that people use to throw their waste in the open. Roads have their influence zone, which is
shown in the fig.4. Author considers the buffer zone of the road is up to 60 meters. This buffer
zone covers most of the ward area, i.e. the road network is good in the area but the width is not
appropriate. In the study area the built-up area is 21.572 ha (16%) whereas non built-up is 18.415
ha (14%). In the above map the institutional area having 70 percent i.e., 94.146 ha.
Fig.3: Digitization of Road Network in Vijay colony

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Figure-4: Buffer Zone of Road Network
Fig-5: Built / Non built area classification

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Landuse in Vijay Colony
17%
24%
16%
3%
39%
1%
HIG
MIG
LIG
Commercial
Green Space
Resi/ Commercial
Landuse Classification in Vijay Colony,
Dehradun
16%
14%
70%
Built up Area
Non Built Up Area
Institrutional
Fig-6: Land use Classification in Vijay Colony ward
Distribution of land use of the Vijay colony is shown as the following fig-6, shows residential area
as HIG (5.526 ha.), MIG (7.731 ha.) and LIG (5.364 ha.); commercial, green space and the
residential/ Commercial area. Chart 2 shows the study area as built-up and non built-up area along
with the institutional area. Institute and Residential area is also shown in the map (Fig.7).
Residential/ Commercial and Institutional areas are shown in the map (Fig.8). Institutional area is
about 94.146 ha, Commercial having 0.867 ha. And the residential/ commercial is having 0.463 ha.
Green space in the study area is having a significant percentage. It has the area of about 12.676 ha.
Fig-7: Income based classification of house holds.

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Fig-8: Classification based on zoning
4.3: Waste estimation
Population of ward No. 44; Vijay colony is 8097 according to census2001 data. The number of
house hold is 1569. The population density of the ward is 52.56 %.Assumed rate of solid waste
generation is 0.4 kg/person/day.
Avg. No of persons per household = Total population of ward ÷ Total no. of Household
= 8097 ÷ 1569
= 5.16 no
The waste generated per one
household
= No of persons /Household x 0.4
= 5.16 x 0.4
= 2.064 kg/day.
Total waste generated within a
ward
= Total no of Household x Waste generated per
household
= 1569 x 2.064
= 3238.416 kg/day
In the study area the residential area is divided into HIG (30%), MIG (41%) and LIG (29%).
Author assumed the generation of waste for HIG is 0.5 kg/ day; MIG- 0.35 kg/ day and LIG- 0.25
kg/day. As a result HIG generates 1230.68 kg/ day whereas MIG generates 1177.51 kg/ day and
LIG creates 593.4 kg/ day. It shows that HIG group generates max. Most amount of solid waste
which mainly consists of the plastics.
One solid waste bin can handle about 2.5 tonnes of solid waste, which is the total amount of solid
waste collected for two days. In the study area, the resident used to throw their garbage in the open

9. 9
land. On the basis of these open dumping the author find out the location through GPS in the study
area. There are eleven prominent sites where people usually dump their waste. These eleven sites
approximately cover the whole area as shown in the map (Fig-9).
Fig-9: Buffer zone for the existing waste collection centers
In our study area, practically author proposes two new sites for solid waste collection bin and one
already exists near SOI. The proposed one site for locating solid waste bin near the bridge on New
Cantonment Road, and the second one is on the Bridge on the end of Kalidas Road. These two sites
are chosen because of the easily accessible and directly approachable for the municipal vehicle.
The municipal workers collect the waste from the colony by a small hand pulling vehicle and put it
within the Solid waste bin. On the basis of these three sites buffer zones has been created which
covers most of the ward. (Dia. 525 meter by a single Solid Waste Bin).
Fig-10: Buffer zone for new proposed solid waste collection sites.

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5. Conclusions
Geographic Information System (GIS) has proved to be an ideal tool for urban planning and
management owing to its versatility in handling a large set of data, providing an efficient
environment for analysis and powerful set of tools for collecting, storing, retrieving, transforming
and displaying spatial data. The present paper explores modern GIS in the location planning of
waste collection bins and its effectiveness with distance of every house hold. It is expected that
such assessment of the existing infrastructure will help the local government bodies in formulating
the necessary principles for better utilization of their existing resources. The following conclusion
can be drawn:
ß Remote sensing is an upcoming and valuable tool to generate information about Solid
Waste management.
ß The GPS is helpful in locating those points such as dustbins, which are not visible in
satellite data.
ß As for the solid waste management , GIS is a significant tool-
- For computing the quantity of waste from different urban areas.
- For planning the collection and transportation facilities.
- For assessment of temporary storage units i.e. dustbins.
ß By using remote sensing and GIS techniques, suitable dumping site is easy to find out.
ß Remote Sensing, GIS and GPS, together form a very efficient tool for solid Waste
management.
References
∑ UNGASS (1997) (United National General Assembly Special Session) Special session of
the General Assembly to review and appraise the implementation of Agenda 21 "Earth
Summit II" Declaration, June, paragraph 23.
∑ Von Rimscha, S. (1997). "Building the New” GIS-Europe, Vol. 6(9):pp. 28-30.
∑ NEERI Report ‘Strategy Paper on Solid Waste Management in India’, pp.1-7, 1996.
∑ Agrawl, Deepti (2003), “Solid waste management in Haridwar district –A Geospatial
approach”, M.Sc. Dissertation.
∑ Minakshi Kumar (2000),” Site Suitability analysis for solid waste disposal – A RS and
GIS approach”.
∑ Balkoteswarababu. T, (2000), “Environmental Impact assessment with Special emphasis
on Solid Waste management and ground water potential analysis”.
∑ Kumar, Sunil (2005) “Municipal Solid waste management in India; Present practices
and future challenges”.
∑ Oberoi S.V, Singh, L, Gaurav, Ohri, “A Solid waste management (SWM) in Varanasi City
using GIS”.
∑ www.dehradun.nic.in
∑ www.surveyofindia.gov.in
∑ www.iirs-nrsa.gov.in
∑ http://www.epa.gov/epaoswer/non-hw/reduce/catbook/iwm.htm