143

CHAPTER-5

GIS ANALYSIS

144

CHAPTER – 5

GIS ANALYSIS

5.1. Introduction and Definition

Modern surveying techniques for topographic mapping were implemented in 17th

century along with early versions of thematic mapping, e.g. for scientific or Census data.

The early 20th

century witnessed the development of “photolithography” where maps

were separated into layers. Computer hardware development leads to general purpose

computer “mapping” applications by the early 1960s. The year 1967 emerged in the

development of the world‟s first true operational Geographical Information Systems

(GIS) in Ottawa, Ontario developed by Roger Tomlinson, federal Department of Energy,

Mines and Resources. Thereafter, he has been called as father of GIS.

The art of remote sensing is an excellent tool in mapping such as lithospheric and

hydrospheric parameters and GIS is a proven tool in storing, retrieving, analyzing and

amalgamating all such parameters to select suitable sites for waste disposals (Ramasamy

Kumanan et al., 2002). Geographic Information Systems (GIS) is becoming more and

more popular among decision makers as it enables them to quickly refer the GIS outputs

which help them in solving problems and making right decisions. Visualization of

features, converting data into need-based maps (thematic maps) and capability of

providing solutions by taking into account overall scenario of an area are some of the

virtues of GIS due to which it is being implemented across a number of sectors and

departments. The generated ArcGIS maps give efficient information concerning static

and dynamic parameters of the Municipal Solid Waste Management (MSWM) problem

such as the generation rate of MSW in different wards, collection point locations,

transport means and their routes, and the number of disposal sites and their attributes

(Mufeed Sharholy et al., 2007).

145

5.2. How does GIS work?

Maps have been used for thousands of years for better administration, revenue

collection, etc. But it is only within the last few decades that the technology has

developed to a level of combining maps with computer graphics and databases to create

GIS. The themes in the graphic are only an example of the wide array of information

that can view or analyze with a GIS.

GIS is used to display and analyze spatial data which are tied to databases. This

connection is what gives GIS its power. Maps can be drawn from the database and data

can be referenced from the maps. When a database is updated, the associated map can be

updated as well. GIS databases include a wide variety of information including

geographic, social, political, environmental, and demographic. It is estimated that

approximately 80% of all information has a “spatial” or geographic component. So when

making decisions about siting new facilities, creating hiking trails, protecting wetlands,

directing emergency response vehicles, designating historic neighborhoods or redrawing

legislative districts, geography plays a significant role. In the present study, GIS

techniques have been used to identify the landfill sites for solid waste management.. For

this purpose various thematic layers are integrated in GIS by assigning weightage values

as discussed below.

5.3. Multi Criteria Decision Analysis

The selection of the appropriate landfill site can be viewed as a complex multi

criteria decision-making problem that requires an extensive evaluation process of the

potential locations and other factors as diverse as economic, technical, legal, social or

environmental issues (Geneletti, 2010).

Siting a municipal solid waste landfill is a challenging task because various

interconnected and conflicting parameters should be considered. In such a context, a

useful support is provided by a specific family of Decision Support Systems (Burstein

and Holsapple, 2008), named Multi criteria Spatial Decision Support Systems

(Malczewski, 1999), which is based on GIS and Multi criteria Decision Analysis

146

(MCDA). In reality, many decision-making problems are based on spatial (geographical)

information. These kinds of decisions are called location decisions and represent now a

major part of operations research and management science (Farahani et al., 2010).

Since the 1960s, many studies have been developed concerning the modeling of

municipal solid waste management problems. The first applications referred to land use

models and had the aim of optimizing collection routes and facilities for the selection of a

site, focusing only on financial criteria (Truitt et al., 1969). Environmental consideration

in the 1980s and 1990s draw much attention to the potential of pollution due to waste

disposal which led to more restrictive environmental regulations and to increase the

emphasis given to other criteria in the process of undesirable facilities location.

According to the sustainable development approach, a waste management system has

now to be environmentally effective, economically affordable and socially acceptable

(Bottero and Ferretti, 2011). Multi criteria Decision Analysis methods address municipal

solid waste problems.

In a preliminary screening stage, the utilization of GIS normally involves

employing a set of criteria in order to classify an area into defined classes by creating

buffer zones around geographic features to be protected (Changa et al., 2008). All map

layers are then intersected so that the resulting composite map classifies the areas into

suitable and unsuitable ones (Morrissey and Browne, 2004; Erkut et al., 2008).

The present study is focusing to identify suitable landfill sites for municipal solid

waste management in the environs of Greater Visakhapatnam Municipal Corporation.

5.4. Raw data acquisition

In this step, a thematic map has to be constructed for each identified factor and

constraint. The data such as geomorphology, land use/land cover, soil, lineament,

geology, drainage, road network and settlements are prepared for the purpose of landfill

site selection.

147

5.5. Processing

In this step, maps are computed through basic GIS operations (map overlay,

buffering, distance mapping, spatial queries, etc.).

5.6. Standardization

In this step, impact scores are made dimensionless and mutually comparable

through the identification of relevant transformation functions that convert the data

related to each criterion to a value judgment. This process identifies the partial

attractiveness of each pixel of the maps with respect to each criterion.

5.7. Aggregation

An overall suitability index for each potential site of the study area is calculated

using an adequate aggregation rule. It is necessary to highlight that the criteria considered

in the present application were selected based on the relevant international literature

(Buenrostro Delgado et al., 2008; Sumathi et al., 2008; Sharifi et al., 2009; Wang et al.,

2009; Geneletti, 2010; Nas et al., 2010) and on the requirements coming from the Waste

Management and Handling, (2000) rules which provides a list of aspects to be considered

for the location of waste facilities.

5.8. Software

In this study, ERDAS-Imagine 9.1 and ArcGIS-9.2 software were used. GIS

analysis was carried out in ArcGIS-9.2 environment.

5.9. Creation of digital coverage

In this study, ERDAS Imagine-9.1 and ArcGIS-9.2, software packages were used.

Thematic maps such as Geomorphology, geology, soil, land use/land cover, lineament,

road, drainage network and slope map of the study area have been delineated on IRS-IC,

LISS-III satellite data following standard visual interpretation techniques.

148

5.10. Drainage Pattern

In order to determine suitable landfill sites, different criteria were considered such

as distance from settlements, distance from surface waters, slope, geology, hydrogeology,

land use, distance from roads and distance from protected areas (ecologic, scientific or

historic) (Sehnaz Sener et al., 2011).The drainage pattern of the study area is extracted

from the Survey of India toposheets of 65 O/1, 65 O/2, 65 O3, 65 O/5 and 65 O/6 on

1:50,000 scale (Figure 5.1). The high drainage density is observed in hilly terrain,

whereas the low drainage density is in plains. The first to fifth order drainage is

identified in the study area. The first and second order streams are developed in hilly

areas. In addition, these streams are also developed in slopes and plains. The third and

fourth order drainage area is suitable for choosing landfill sites. The drainage order

stream lengths were measured in ArcGIS-9.2. In urban areas, the drainage pattern is

severely disturbed due to anthropogenic activities. Therefore, no prominent drainage

system has been identified in the area. There are more number of non-perennial tanks in

the upper catchment of Meghadrigedda reservoir and also Kanithi reservoir. There is a

marine creek at Naval Dockyard extended up to Visakhapatnam airport which is covered

by Mangrove forest.

The study area has medium and minor reservoirs constructed on non-perennial

rivers to cater the needs of the GVMC. Mehadrigedda reservoir with gross storage

capacity of 1162 Mcft is constructed in 1972 on Mehadrigedda River. Similarly,

Gambhiram reservoirs on Gambhiram River, Mudasarilova reservoir on

Hanumanthavaka gedda are in the study area.

The study area has dendritic, sub-dendritic drainage on the plains. Parallel and

radial drainages are seen in the hilly areas. Discontinuous and altered drainages are

observed in the urban area. Most of the streams in the urban area have been altered into

unlined sewage drains leaching pollutants into the groundwater (Jagadeeshwara Rao et

al., 2004).

Following the Municipal Solid Waste Management and Handling Rules (2000),

500 meter buffer was assigned to the higher order streams and rivers for the selection of

149

Figure 5.1: Drainage map of the study area

150

landfill sites (Figure 5.2 & 5.3). Weights are assigned to different drainage orders

following the local and pollution control board norms (Table 5.1).

Table 5.1: Drainage weights of the study area

S. No. Classes Weights Remarks Suitable/

Unsuitable

Drainage First order streams 4 Sites away from

these buffer zones

are selected

Unsuitable

Second order stream 5 Unsuitable

Third order streams 10 Suitable

Fourth order streams 10 Suitable

Fifth order streams 3 Unsuitable

Rivers 1 Unsuitable

Canals 2(Buffer in

500meters)

Suitable

151

Figure 5.2: 3rd

and 4th

order drainage buffer map

152

Figure 5.3: River buffer of 500m in the study area

153

5.11. Settlements

In this analysis, settlements of urban and rural are delineated following the

standard visual interpretation techniques. Major construction areas and road connectivity

villages are not selected in the landfill sites. Taking into consideration of municipal solid

waste Management and Handling Rules, (2000), buffering of 500 m to the settlements

was assigned in ArcGIS-9.2 environment (Figure 5.4). The villages away from the buffer

distance are considered in the analysis.

5.12. Geomorphology

In this analysis, fourteen fluvial and erosional geomorphic classes were delineated

following the standard visual interpretation techniques on IRS-P6- LISS-III January,

2011. They are structural hill, denudation hill, residual hill, inselberg, piedmont slope,

pediplain shallow-weathered, pediplain moderate-weathered, pediplain deep-weathered,

beach, intermountain valley, structural valley, marine creek, valley fill and channel fill.

Pediplain, pediments cover major area. The pediplain shallow and moderate with limited

soil cover with sparse vegetation is ideal for landfill site. Weights assigned to the

different geomorphic classes are given in Table 5.2.

Table 5.2: Weights assigned to geomorphic classes

Geomorphic

Classes Weights Remarks

Suitable/

Unsuitable

Structural hill 1 Elevated area Unsuitable

Denudational hill 2 Elevated area Unsuitable

Residual hill 3 Elevated area Unsuitable

Piedmont slope 8 Gentle elevated area Suitable

Pediplain shallow 10 Plains with low slopes Suitable

Pediplain moderate 9 Plains with moderate slopes Suitable

Pediplain deep

5

Ground water

Potential zone

Unsuitable

Intermontane valley

6

Ground water

Potential zone Unsuitable

Inselberg 4 Elevated area Unsuitable

Mudflat&sea

water/creek

0

Water logged area

Unsuitable

154

Figure 5.4: Major settlements buffer map

155

5.13. Geology

In this analysis, eight lithological units were delineated from Geological Survey

of India (GSI) map. Khondalite is the major rock type and Tirupathi sandstone covers

small area. Hence, parent rock is considered in GIS analysis. Khondalite rock is occurring

as a groundmass whereas other rock types are occurring as secondary intrusive into the

country rock. Moreover, these rock types are occurring as small hillocks with varied

extent of fractures. Hence, these rock types are unsuitable. Weights assigned to different

rock types are given in Table 5.3. Integrated map of geomorphology and geology of the

study area is shown in Figure 5.5.

Table 5.3: Weights for geological rock types

Criteria Classes Weights Remarks Suitable/

Unsuitable

Geology

Khondalite 10 Parent rock Suitable

Granite Gneiss 4 Hilly areas Unsuitable

Charnockite 3 Hilly areas Unsuitable

Leptynite/Thirupathi sandstone 2 Hilly areas Unsuitable

156

Figure 5.5: Geology and Geomorphology of the study area

157

5.14. Soil

In this analysis, ten soil types were delineated from the Visakhapatnam District

soil map following the standard visual interpretation techniques. It is observed, Red clay

soil, Red loamy soil and Red gravel clay soils covers large extent of the area. Red loamy

soils are unsuitable for landfill site selection. Loamy soils with high sand content

generally possess high porosity and permeability. Red clay soils and black clay soils are

suitable for land fill site selection. The clayey soils contain high content of impermeable

clay. Thus, clay rich soils were considered in GIS analysis and soils unsuitable were

rejected by assigning low weight values (Table 5.4).

Table 5.4: Soil weights of the study area

Criteria Classes Weights Remarks Suitable/Unsuitable

Soils

Red clay soil 10 Clayey soils are suitable

because of impermeable

nature.

Suitable

Black clay soil 9 Suitable

Red gravel clay soil 7 Suitable

Sandy soil 1 Unsuitable

5.15. Land use/land cover

In this analysis, eighteen land use/land cover classes have been identified through

standard visual interpretation techniques. They are Sandy area, Mangroves, Single crop

land, Marine creek, Double crop, Water body/tank, Fallow land, Plantation, Urban built-

up, Rural built-up, Upland with/without scrub, Gullied/Ravenous-land, Scrub/Degraded

forest, River, Deciduous dense/Reserved forest, Reservoir and Channel fill.

The wastelands and single crop (fallow) classes are considered in the GIS analysis

as they are most suitable places for selecting landfill site. The other land use/land cover

categories are not suitable for selecting landfill sites as they are already covered with

different land cover classes (Table 5.5).

158

Table 5.5: Land use/land cover weights of the study area

Criteria Classes Weights Remarks Suitable/

Unsuitable

Land use/

Land cover

Built-up-land 4 Residential area Unsuitable

Deciduous forests 1 Reserved forest Unsuitable

Degraded forest 2 Reserved forest Unsuitable

Water bodies 0 Water bodies Unsuitable

Single Crop land 8 Irrigated area Suitable

Forest plantation 5 Forest plantation Unsuitable

Wastelands-Fallow

land

10

Scrub/Wasteland

Suitable

Wastelands-Barren/

rocky lands

9

Waste land

Suitable

5.16. DEM

Digital elevation models (DEMs) are the basic components of any geographic

information system (GIS) and engineering projects. There are four major requirements on

DEMs, they must have the required accuracy, they must have the required resolution and

they should not have gaps in important areas (Buyuksalih and Jacobsen, 2004). The

terrain cannot be described by the horizontal components, the height models are required

for the generation of ortho images -one of the most often used photogrammetric product.

DEMs can be generated by laser scanning, photogrammertric methods or interferometric

synthetic aperture radar (In SAR). In any case it is time consuming and expensive. Before

2000, the best elevation models, showing a global coverage, were provided in a 1- km

raster size with varying quality. They are available as GLOBE (The Global Land 1 –km

Base Elevation Project), GTOPO30 (Global Topography in 30 sec), and DTED-0 (Digital

Terrain Elevation Data-0) products. Regionally, of course, better DEMs exist (). The

DEMs based on the US C-band are referred to mean sea level (MSL) as approximated by

the WGS84 EGM96, processed by NASA-JPL and available free of charge in the

internet (URL-1, 2008) with a spacing of 3 arcsec, corresponding to approximately 92m

at the equator. The data with a spacing of arcsec (~30m at the equator) is also in the

WEB, only for the USA. WGS84 can be ordered from the DLR Germany with a spacing

of 1 arcsec (Sefercik and Jacobsen, 2006)

159

Delineation of coastal areas vulnerable to cyclones is a difficult task as it involves

intensive fieldwork to prepare physiographic maps, height details (DEM), land use and

geomorphic maps. Preparation of such maps using conventional techniques is manpower

intensive, expensive and depends on the terrain and weather conditions. However, these

limitations can be overcome using remote sensing technique. Satellite images provide

information on coastal configuration, morphology and changes, while satellite-derived

DEM gives good details about topography of the coastal region.

DEM is a quantitative model of part of the earth‟s surface in digital form, in

particular, elevation of a region. Typically, a DEM consists of an array of uniformly

spaced elevation points in raster format. Terrain models have always appealed to military

personnel, landscape architects, civil engineers as well as earth scientists. Digital terrain

modeling is a process to obtain desirable models of the land surface. Satellite images like

aerial photographs are potential sources for generating DEM (Roth, 2001, Kocak et al.,

2005).

Digital Elevation Model (DEM) has been generated on the ASTER-30m satellite

data. The subset of the satellite imagery has been draped over the satellite image and has

generated digital elevation model of the area (Figure 5.6).

160

Figure 5.6: 3D Perspective view from LISS-III image dropped over Digital Elevation Model of the study area

161

5.17. Slope map

The contour values are assigned in ArcGIS environment; this is considered on the basis

of corresponding attributes of the slope (Figure 5.7 and Table 5.6). The areas having 0-5% slope

are the most suitable for landfill sites. The 0-5% slope is covered with plains with gentle slope.

For landfill site selection, the plain grounds are suitable. The areas under 0-5 % slope category

covered 856.8 km2. It is considered basing on surface run-off and land mass denudation. In GIS

analysis, the areas under 0-5 % slope category are considered for landfill site selection.

Table 5.6: Slope weights of the study area

Criteria Classes in percentage Weights Remarks Suitable/

Unsuitable

Slope

0-5 10 Gentle slope Suitable

5-10 9 Gentle slope Suitable

10-15 3 Strongly sloping Unsuitable

15-20 2 Moderately steep to steep sloping Unsuitable

>35 1 Very steep sloping Unsuitable

162

Figure 5.7: Slope map of the study area

163

5.18. Road network

The road network map is extracted from the Survey of India toposheets on 1:50,000 scale

(Figure 5.8). This is one of the requisites to select a landfill site. Keeping in view of this a buffer

zone analysis was carried out to the road map with the distances of 0.5 to 2 km buffer executed

in Arc tool box (Figure 5.9 and Table 5.7) so as to minimize the transportation costs. In this

analysis, only the State High-ways, district roads and major roads are considered. The minor

roads are not considered because these are important communication lines connecting to the

built-up.

Table 5.7 Weights assigned to roads in the study area

Criteria Classes Weights Remarks Suitable/

Unsuitable

Roads

National

Highway-5

Buffer of about

1500 meters Sites away from

buffer zones are

selected

Suitable

State Highway

Buffer of about

1000 meters

Major roads Buffer of about 750

meters

164

Figure 5.8: Road network of the study area

165

Figure 5.9: Road buffer map

166

5.19. Lineaments

Lineaments are seen as linear tonal discontinuities in an image. Linear features are

delineated by standard visual interpretation techniques on IRS-IC- LISS-III satellite image.

Major lineaments caused by linear streams, valleys, fractures, faults, linear vegetation growth,

etc., were covered. Further these are divided into confirmed and inferred. The confirmed

lineaments are not considered in GIS analysis, as they are structurally controlled, hence,

unsuitable for landfill sites. This is one of the requisite to select a landfill site and distance of

500m for inferred lineaments and 1000m for the confirmed lineaments have been taken into

consideration (Figure 5.10 and Table 5.8).

Table 5.8: Lineaments weights of the study area

Criteria Classes Weights Remarks Suitable/

Unsuitable

Lineaments Confirmed 2 Sites away from 500

meters buffer zones are

selected

Unsuitable

Inferred 10 Suitable

167

Figure 5.10: Lineament buffer map

168

5.20. GIS Analysis

The demand for the storage, analysis and display of complex and voluminous

environmental data has led in recent years to the use of computers for data handling and the

creation of sophisticated information systems. The Geographic Information Systems (GIS) offers

spatial data management and analysis tools that can assist users in organizing, storing, editing,

analyzing, and displaying positional and attribute information about geographical data

(Burroughs, 1986). GIS with its capability of map overlaying, reclassification, proximity analysis

and other mathematical operations can help to carry out criteria based analysis. The solid waste

can be more efficiently manage using GIS techniques. The efficiency of solid waste disposal

depends upon selection of proper site and there are several issues that have impact for site

selection (Asadi et al., 2011). An inappropriate landfill site may have negative environmental,

economic and ecological impacts. Therefore, it should be selected carefully by considering both

regulations and constraints on other sources (Sener Basak, 2004). For the design and operation of

landfills, appropriate guidelines for developing countries have to be developed by Chris

Zurbrugg and Roland Schertenleib, (1998). Keeping in view of these complex issues in mind, the

GIS analysis was carried out. The details of which is given below.

5.20.1. Map Weights

M1 = Weightage*[class (soil)]

M2 = Weightage *[class (geology)]

M3 = Weightage *[class (geomorphology)]

M4 = Weightage *[class (drainage)]

M5 = Weightage *[class (road)]

M6 = Weightage *[class (land use/land cover)]

M7 = Weightage *[class (lineaments)]

M8 = Weightage *[class (settlements)]

169

M9 = Weightage *[class (rivers)]

M10 = Weightage *[class (tanks)]

Calculate sum of weighted conditions and divided by normalization factor

New Vulnerability Map

= [*M1 + *M2 + *M3 + *M4 + *M5 + *M6 + *M7 + *M8 + *M9 + *M10]

__________________________________________________________

SUM

5.20.2. Index Overlay Analysis

Depending upon the importance for the landfill site selection in the study area these were

assigned with a particular weightage number and multiplied to obtain a map which is used for

further analysis. The values were also assigned with a particular weightage and multiplied to

obtain maps which are used for overlay analysis to obtain new vulnerability map. The class ranks

of weightages are given in Table 5.9.

Table 5.9: Thematic map Weightage

Sl. No Layers

1 M1 = 9*[class (soil)]

2 M2 = 8*[class (geology)]

3 M3 = 7*[class (geomorphology)]

4 M4 = 9*[class (drainage)]

5 M5 = 6*[class (road)]

6 M6 = 6*[class (land use/land cover)]

7 M7 = 5*[class (lineaments)]

8 M8 = 4*[class (settlements)]

9 M9 = 3*[class (rivers)]

10 M10 = 2*[class (tanks)]

Calculate sum of weighted conditions and divided by normalization factor

New Map = ([*M1 + *M2 + *M3 +*M4 + *M5 + *M6 +*M7 + *M8 + *M9 + *M10])

SUM

The different thematic maps that are prepared are overlaid after assigning non-spatial

(attribute) data to each map. Different weights are assigned to each thematic map on the basis of

170

terrain characteristics, land use/land cover type, slope and municipal solid waste handling rules

(2000). The GIS analysis is done in spatial analysis environment. The wastelands identified in

land use/land cover analysis and the areas of 0-5% slopes of the slope map are suitable for

landfill sites. Spatial analyst and expression is given using raster calculator to identify the

wastelands with zero slopes. From the results, geomorphic unit that are covered by the pediplain

shallow weathered and pediplain moderately weathered are identified by giving similar

expressions in the raster calculator, since these geomorphic units are only suitable for selecting

landfill site. For the drainage network of the area, buffer zones are generated for all the streams

giving 500 m buffer distance for higher order streams and vice-versa. For the 3rd

and 4th

order

streams a buffer of 500 m is generated. This is in view of restricting the contamination of surface

water bodies. In this, Pollution Control Board and Municipal Handling, (2000) rules were

followed. The drainage buffer map is overlaid over the other thematic maps and the features that

are away from the drainage buffer zones are selected. The finally selected sites are generated to

locate features from the generated output, which are within a distance of 0.50 to 4.00 km from

the existing road network.

5.21. Generation of suitable landfill site map

After overlaying all the themes in raster (Figure 5.11), the final map has been generated

using spatial analysis, which reflects the suitable landfill sites in the environs of Greater

Visakhapatnam municipal Corporation area (Figure 5.12). The landfill sites identified by GIS

techniques are most suitable sites for solid waste management for future requirements.

With the assigned values, 97 landfill sites have been identified in GIS Analysis. Out of

97 sites, seven sites have been identified as more suitable. The individual areas of these landfill

sites are calculated in ArcGIS-9.2 and the sites covering 1.0 km2 are considered. Priority has

been given to the sites that are in the proximity of road and boundary of Greater Vishakhapatnam

Municipal Corporation.

171

Figure 5.11: Landfill sites priority

172

Figure 5.12: Final landfill sites in the study area

173

The final output is generated after successful execution of the query. The particulars of

the finally selected landfill sites are given in Table 5.10.

Table 5.10: Suitable landfill sites identified in the analysis

S. No Name of the village Distance of

the road in

km.

Area

Km2

Latitude Longitude

1 Kotta

Talarivanipalem

1.58 1.81 17º42'38''N 83

º03'51''E

2 Pydivada Agraharam 0.71 1.03 17 º 44'41''N 83

º 06'51''E

3 Mindivanipalem 0.98 0.91 17 º 52'14''N 83

º 18'38''E

4 Ramayogi

Agraharam

0.72 0.89 17 º 52'27''N 83

º 24'36''E

5 Yeduruvanipalem 0.58 1.07 17 º 39'25''N 83

º 04'16''E

6 Denduru 1.14 1.56 17 º 51'55''N 83

º 09'20''E

7 Mantripalem 1.45 0.97 17 º 41'45''N 83

º 5'26''E

The final map has been generated using spatial analysis, they are 1). Kottatalarivanipalem

(1.81 km2), 2). Denduru (1.56 km

2), 3).Yeduruvanipalem (1.07 km

2), 4). Pydivada Agraham

(1.03 km2

), 5. Mantripalem (0.97 km2), 6. Mindivanipalem (0.91km

2) and 7. Ramayogi

Agraharam (0.89 km2). This reflects the suitable landfill sites in the environs of Greater

Visakhapatnam Municipal Corporation area.