[IJET-V1I5P1] Authors :Ahmed Mohamed Abushnafa, R. K. Pandeyb, Deepak Lalc

International Journal of Engineering and Techniques - Volume 1 Issue 5, Sep-Oct 2015
ISSN: 2395-1303 http://www.ijetjournal.org Page 1
Identification and Evaluation of New Industrial Zones in Giridih
District using Remote Sensing & GIS Techniques
Ahmed Mohamed Abushnafa1
, R. K. Pandeyb2
, Deepak Lalc3
1
(Department of Civil Engineering, Sam Higginbotom Institute of Agriculture Technology & Sciences, )
2
(Department of Civil Engineering, Sam Higginbotom Institute of Agriculture Technology & Sciences)
3
(Department of Soil Water, Land Engineering and Management, Sam Higginbotom Institute of Agriculture Technology &
Science)
I. INTRODUCTION
One of the key factors is to start-up a process and
expands or reallocate of all kinds of business is
identifying a best suitable site for that business,
the success or failure of the establishment of an
industrial system depends on the site selection
acts, the main objective in industrial site selection
is to find the most suitable site with all the
desired conditions satisfied defined by the
selection criteria. Geographical data is used in
industrial site selection by decision makers and
managers which concludes that industrial site
selection process is spatial decision problem and
GIS has been identified as a decision making
tool. Geographic information systems (GIS) has
been identified as a powerful tool for performing
spatial analysis to store, capture, display, query,
analyze and output geographic information,GIS
has been used for the site suitability analysis for
an Industrial development in Giridhi District in
Jharkhand.
Abstract:
This study was carried out to identify suitable sites for Industrial development at Giridih District in Jharkhand state
using GIS-based multi-criteria evaluation (MCE) such as landuse/landcover, groundwater, geomorphology, slope, road
proximity, rail proximity, river proximity factors. High resolution spatial data (Landsat7 ETM+) and seven thematic
information layers were analyzed using ArcGIS 9.3 and ERDAS Imagine 9.2 softwares to identify suitable areas for
establishing an industry in Giridhi District. The entire study focuses on GIS based Overlay Weight Ages. In this study
landuse/landcover, groundwater, geomorphology, slope, road proximity, rail proximity, river proximity are the factors that
were identified for the multi-criteria evaluation. Various thematic maps were generated using visual interpretation of
Landsat7 ETM+ satellite data for every variable showing site suitability measured on a size of 1-10. Weights for every
criterion are created by contrasting with one another based on their significance. The final suitability map was obtained using
weighted overlay techniques and Spatial Analyst Tool. Outcome generated through the GIS analysis shows that 160.85 km2
areas is very highly suitable, 407.85 km2 area is moderately suitable; 4398.30 km2 area is less suitable, for industrial
development.
Keywords — Industrial, suitable site, Remote Sensing, GIS.
RESEARCH ARTICLE OPEN ACCESS

This paper presents a powerful solution for
spatial decision support, the current study focuses
suitable site offering of industrial development
depending on multi-criteria decision analysis and
geographic information system based (GIS)
overlay analysis the most suitable site for
industrial development in study area. Thematic
maps on the selected criteria were developed
from the paradigm of typical GIS software,
thereafter; weightings were assigned to each
criterion dependant on their ratings and relative
importance in accordance with the relative
magnitude of impact. A GIS-based overlay
examination was performed to identify the
suitable site for the industrial development. [1]
Major developments are now taking place in the
integration of remote sensing data and GIS due to
the increased demand for the spatial information.
There are three main ways in which remote
sensing and GIS technologies are complementary
to each other a) Remote sensing can be used as a
tool to gather data sets for use in GIS; b) GIS
datasets can be used as ancillary information to
improve products derived from remote sensing
and c) RS data and GIS data can be used together
in resource analysis and modeling. The
integration of RS and GIS known as Geo-spatial
analysis is crucial tool for the resources manager
to challenges face in twenty first century. It
allows us as resource managers to develop,
analyze, and display spatially explicit to deal
with larger spatial scales such as regional
landscapes.[2]
1.1 Objectives
1. Generate various thematic maps
(geomorphology, ground water, slope,
road, rail, and river) for assessing the land
use and availability of other resources
necessary for setting up an industry in
Giridih District.
2. To identify and locate a suitable site using
multi criteria approach for setting up an
industry in Giridih District.
II. MATERIALS AND METHODS
2.1 Study Area
Giridih is located at 24.18°N 86.3°E. with an
Average elevation of 289 meters (948 ft) it is
bounded by Jamui in the north ,Bokaro and
Dhanbad in the south Deghar and Jamtara in the
east and Kodarma and Hazaribag in the west.
Giridih District is geographically divided into
two natural divisions, which are the central
plateau and lower plateau. The central plateau
touches the western portion of the district near
Bagodar block. The lower plateaus have an
undulating surface and an average height of 1300
feet. In the north and north-west, the lower
plateaus form fairly level tablelands until they
reach the ghats when they drop to about 700 feet.
Giridih district is divided into two main water

heads – Barakar and Usri rivers. Giridih is rich in
mineral resources and has several large coal
fields with one of the best qualities of metallurgical coal
in India. Mica is found in abundance near the blocks Tisri
and Gawan. Mica is of importance not only to Jharkhand
but to India and other countries as well. [2].
Fig 1: study area
2.1.1 Economy
This town used to bustle with economic activity
in the period from 60s to 80's when the mineral
mica processing and export community reaped
tremendous gains through exports to the USSR.
Since the decline of the USSR however and its
split into twelve CIS countries, the industry has
slowly declined and is currently ailing. On the
southern side of Giridih, in Beniadih, are the coal
mines of Central Coalfields Limited, a subsidiary
of Coal India Limited (a Navratna and the
world's largest coal miner). It is the largest
industry in the Giridih district and major
contributor to the economy of the town. Central
Coalfields Limited itself is a Miniratna. The Data
Processing Center of Data Processing Division
(DPD) of National Sample Survey Organization
(NSSO) provides complete IT solution from
sample selection, software development to
processing and tabulation of data canvassed
through various socio-economic surveys of
National Sample Survey Organization. [4]
2.1.2 Availability of Minerals:
The main mineral of the district is Coal. However
Building Stone, Sand Stone, Quartz & Red
Bricks are also minerals and mining of this
district. [5] Minerals present in the Giridih
district is shown in
Table 1
Table 1 production of mineral 2010-11 source: district mining office,
giridih
2.1.4 Software's Used
1. ArcGIS Desktop 9.3
2. ERDAS Imagine 9.2
Name of mineral Production (in tons)
Coal 5,81,361MT
Building Stone 1,94,823MT
Sand Stone 25,000M3
Quartz 12,477MT
Chemney Bricks 30,00,000
Mica Not available
Sand Not available
Red Bricks Not available

2.1.5 Data used
Table 2:SatelliteData
Table3. Toposheet Data
2.1.3 Potential for new mineral based industry
Purpose , Fly Ash Bricks , Mica Paper, Stone Chip Mineral
Grinding ,Quartz Grinding & Calcinations, Chimney
Bricks , Mica Powder, De-Hydrated Lime, Refractory
Bricks Mineral Based:- Hard Coke , Soft Coke for
Cooking.
2.2 Methodology
The methodology for locating the best Industrial
site in Giridhi District, for each and use activity
is guided by the intent to minimize the possible
adverse effects of development on the
environment and on existing communities, and to
emphasize the positive impacts of such
development, by locating them in a most suitable
location The best Industrial site in Giridhi
District is achieved by examining a number of
Criterion, assigning them a scale of 1-10 as per
the order of importance to identify the most
suitable location. By adopting this site suitability
method, One can identify the considered criteria
systematically and analyze the net outcome as the
best suitable site using a Geographic Information
System.By revising the relative importance to
identified criteria based upon the particular land
use under consideration, it is possible to generate
“suitability maps” for each individual land use,
and then generate a final composite land use that
is based on a best possible collective suitability
of multiple land uses To achieve this, all the
criteria are assigned a “rank” denoting their
relative levels of importance within the suitability
study. These ranks are assigned as numeric
values ranging from 1 to 10, with 1 reflecting a
low level of importance and 10 reflecting a high
level of importance. Using Weighted Overlay
techniques in ArcGIS Software, We have
overlayed all the prepared thematic layers like
landuse/landcover, groundwater, geomorphology,
slope, road proximity, rail proximity, river
proximity with all weightages, We have
identified the best suitable site for industrial
development in Giridhi District.[6]
2.2.1 Weighted Overlay
The Weighted Overlay tool applies one of the
most used approaches for overlay analysis to
solve multi-criteria problems such as site
selection and suitability models. In a weighted
overlay analysis, each of the general overlay
analysis steps are followed. “Since the input
criteria layers will be in different
numberingsystems with different ranges, to
combine them in a single analysis, each cell for
each criterion
Remote sensing data Landsat satellite data
Sensor Enhanced thematic mapper plus (ETM)
Temporal resolution 16 days
Spatial resolution 30m* 30m
Spectral range 0.45 – 12.5µm
Image size 183 km * 170 km
Sensor type Opto-mechanical
No. of bands 8
Swath 183 km
SOI Map No. Scale Purpose
72H, 72L, 72E,73I 1:250,000
Geo-referencing
of satellite data,
Study area
boundary
extraction
72H/12, 72H/13,
72H/14,72L/1,
72L/2,L72/3,
72E/13,
73I/1,73I/5
1:50,000
Ground truth &
mapping

must be reclassified into a common preference scale such as 1 to 10, with 10 being the most favorable.
Each of the criteria in the weighted overlay analysis may not be equal in importance. You can weigh the
important criteria more than the other criteria” [7]. The input criteria are multiplied by the weights and
then added together
Fig 2: methodology of research
Image processing
Georeferencing
Georeferencing
Mosaicing
Signature development
SOI Toposheet
Supervised classification
Satellite Data landsat7
ETM+
Road Network
mapping
Land use and land
cover mapping
Geomorphology
Mapping
Industrial Site Suitability mapping
Rail Network
mapping
River Network
mapping
Slope Map
Groundwater
mapping
DEM
Projectio
n
Over-Lay of All Layers

III. RESULT AND DISCUISON
3.1 Land use / land cover Map
Table 3.1 weightage for land use and land cover map
Land use land cover classes Area (km2
) Area (%) Suitability score
Agriculture Land Crop Land –Kharif crop 1981.99 39.89 4
Agriculture Land Crop Land More than two crop 0.0529 0.001 4
Agriculture land crop land Rabi crop 98.52 1.98 4
Agriculture Land Crop Land Two crop area 127.07 2.56 4
Agriculture Land- Fallow- Current Fallow 555.97 11.19 4
Build- up land (Rural) 242.01 4.87 5
Buildup-(Urban)-Mixed build up area 9.9088 0.20 3
Buildup-(Urban)-Vegetated Area 0.9636 0.02 2
Buildup-Mining/Industrial Area-Ash/Cooling/Tailing 0.175 0.001 1
Built Up-Mining /Industrial Area-Mine/Quarry 14.74 0.30 1
Forest – Scrub Forest 399.16 8.03 2
Forest Deciduous (Dry/Moist/Thorn)- Open 369.85 7.44 2
Forest Deciduous(Dry/Most/Thorn-Dense) 532.13 10.71 2
Tree Clad Area 13.95 0.28 1
Wasteland- Barren Rock/Stony waste 198.284 3.99 8
Wasteland- Scrub land –open scrub 319.46 6.43 8
Wasteland-Gullied/Ravinous land –Shallow ravenous 0.1288 0.003 8
Wasteland-Scrub land Dense scrub 12.93 0.26 8
Water bodies –Lakes/Ponds-Dry- Kharif extent 9.02 0.18 1
Water bodies-Lakes/ponds-Dry-Rabi extent 1.51 0.03 1
Water bodies-River/Stream-Dry 31.52 0.63 1
Water bodies-River/Stream-Perennial 49.27 0.99 1
Water bodies-Reservoir/Tanks-Dry Kharif extent 0.0039 0.001 1
Total 4968.65 100

Fig 3.1: LULC Map

3.2 Geomorphology Map
Table 3.2 weightage for geomorphology map
Classes Area (km2) Area (%) Suitability score
Alluvial plain gullied 2.72 0.054765 8
Alluvial plain moderate (5-20M) 40.01 0.805562 9
Alluvial plain shallow (<5M) 82.11 1.653204 10
Buried channel 1.66 0.033422 4
Channel Bar 0.166 0.003342 1
Denudational hill 271.35 5.463364 3
Dyke Ridge 0.131 0.002638 3
Fracture Line valley 2.47 0.049731 2
Hill top weathered 9.69 0.195099 2
Inselberg 14.33 0.28852 2
Intermontane valley 40.47 0.814823 6
Linear ridge 16.27 0.32758 2
Mesa 2.94 0.059194 2
Oxbow lake 0.12 0.002416 1
Pediment 29.64 0.596772 3
Pediment-inselberg complex 380.135 7.653643 4
Pediplain shallow weathered (<5M) 5.51
0.110938 4
Plateau – Gullied 33.50 0.674489 7
Plateau Moderate Dissected 61.12 1.230591 7
Plateau slightly dissected 2.86 0.057583 8
Plateau weathered moderate (5-20M) 2051.25
41.29989 7
Plateau weather shallow(<5M) 1232.61 24.81738 7
Point bar 2.02 0.040671 1
Quartz Reff 3.15 0.063422 2
Residual Hill 22.79 0.458854 2
River/Water Body 31.95 0.643282 0
River Sand 60.44 1.2169 0
Shear Zone 1.25 0.025168 1
Structural Hill 277.30 5.583162 1
Valley Fill Shallow (<5M) 286.76 5.773629 4
Total 4966.72km2 100

Fig 3.2 Geomorphology map Fig 3.3 Groundwater map
3.3 Ground Water Map
Table 3.3 weightage for groundwater map
3.4 Slope Map
The aim of this study is to utilize the remotely
sensed data and GIS techniques for slope
assessment for site suitability of Industry setup at
Giridih district. DEM is used to classified the
area in 16 slope classes (slope in degree) and
then weightage is assigned which is shown in the
table 3.4 and fig 3.4
Table 3.4 weightage for slope map
Slope classes (degree) Weightage
0-4 10
4-8 8
8-12 7
12-16 6
16-20 4
20-24 3
24-28 2
28-32 1
32-36 1
36-40 1
Classes Area
(km2)
Area
(%)
Suitable
score
River/Water Body 92.39 1.86 0
Run off Zone 35.12 0.71 1
Yield 400-800
LPM, Depth< 30m
3.84
0.08. 10
Yield 200-400
LPM, Depth < 30m
40.01
0.81 8
Yield 200-400
LPM, Depth 30-
80m
102.45
2.06 7
Yield 200-400
LPM, Depth>80m
65.83
1.33 4
Yield 100-200
LPM, Depth<30m
81.25
1.64 6
Yield 100-200
LPM, Depth 30-
80m
1207.15
24.30 7
Limited Prospects 571.44 11.51 5
Yield 50-100 LPM,
Depth 30-80m
863.95
17.39 6
Yield 50-100 LPM,
Depth>80m
1449.10
29.18 3
Yield 10-50 LPM,
Depth 30-80m
83.22
1.68 2
Yield 10-50 LPM,
Depth>80m
370.94
7.47 0
Total 4966.69 100

40-44 1
44-48 1
48-52 1
52-56 1
56-60 1
Fig 3.4: slope map
3.5 Road Map
The Road network was prepared from toposheet
map. Considering the road network five buffer
zone was created which is shown in figure 4.5.
This buffer zone helps to find out the site for
industry development where road network is
existing.
Table 3.5: weightage for Road Map
Fig 3.5: Road Map
3.6 Rail Map
The rail network was prepared from topographic
map. Considering the rail network five buffer
zone was created which is shown in figure 4.6.
this buffer zone helps tofind out the site for
industry development where rail network existing
Table 3.7 :weighage for Rail Map
Rail Distance(in Meters) Suitability score
0-1000 1
0-2000 2
0-3000 5
0-4000 7
0-5000 10
Roads Distance(In meters) Suitability score
0-200 8
0-400 7
0-600 6
0-800 5
0-1000 4

Fig 3.6: Rail Map
3.7 River Map
The river map was created from the topographic
map. Four buffer zone was created which is
shown in the figure 4.7.
Table 3.6 weightage for rail map
3.8 Suitable site mapping
Maps like land use land cover, geomorphology,
ground water zone, distance buffer from major
roads, distance buffer from major river, slope
map, and their suitability scores are given in the
figures 3.1,3.2,3.3,3.4,3.5,3.6,3.7 and tables 3.1,
Fig 3.6: River Map
3.2, 3.3, 3.4, 3.5, 3.6, 3.7 respectively. raster
datasets for different layers having different score
were overlayed and the scores of each After
projection and topology creation all feature
classes like geomorphology, ground water, slope
railway network, river and road were converted to
raster files and separate datasets were created
using weightage and rank. For the analysis all the
composite class were added using raster
Calculator tool of spatial analyst extension of Arc
GIS 9.3. the final score were reclassified to
generate the output map showing various classes
of suitable site for industrial development. After
the analysis of using all thematic layer total area
in our study including 4966 Km2
. The results
River Distance(in Meters) Suitability score
0-200 1
0-400 1
0-600 6
0-800 8
0-1000 10

show that 160.85 km2
areas are highly suitable, Table 3.8 high, Moderate and Less Suitable areas for Industrial site
Selection
407.85 km2
areas is moderately suitable, 4398.30
km2
area is less suitable. Suitable area obtained
in the analysis is shown in the table 3.8 and the
suitability map is shown in the figure 3.8
Sevensites were selected as the high suitable
industry setup site distributed throughout the
study area. Location of all seven places is shown
in table 3.9. These areas are either Wasteland,
Scrub land, Open scrub, Barren Rocky and Stony
waste all the seven sites are very close to main
road and connected to branch road.
Table 3.9: Identified industrial sites in giridih district, Jharkhand
Class Area Covered (Sq
km)
Highly Suitable 160.85
Moderately suitable 407.85
Less Suitable 4398.30
Location Geomorphology Land cover
types
Ground
water
Distance
from main
road(m)
Distance from
river
Area (sq km)
Site1 86°0'3.53"E
24°38'35.924
"N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Scrub land-
Open scrub
Yield 100-
200 LPM,
Depth<30m
0-200 0-800 0.818177
Site 2 85°54'25.403
"E
24°20'48.5"N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Scrub land-
Open scrub
Yield 50-100
LPM, Depth
30-80m
0-200 0-1000 0.615
Site3 86°19'1.803"
E
24°2'38.567"
N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Barren
Rocky/Stony
waste
Yield 200-
400 LPM,
Depth 30-
80m
0-200 0-1000 0.815903
Site 4 86°18'47.078
"E
24°18'25.096
"N
PLATEAU
WEATHERED
SHALLOW (<5 M)
Wasteland-
Barren
Rocky/Stony
waste
Yield 100-
200 LPM,
Depth<30m
0-200 0-800 0.087538
Site 5 86°4'16.722"
E
24°26'16.444
"N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Scrub land-
Open scrub
Yield 400-
800 LPM,
Depth< 30m
200-400 0-1000 16.1385
Site 6 86°7'54.273"
E
24°10'23.888
"N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Barren
Rocky/Stony
waste
Yield 200-
400 LPM,
Depth 30-
80m
0-200 0-1000 0.815903
Site 7 86°3'27.276"
E
24°18'23.911
"N
PLATEAU
WEATHERED
MODERATE (5-20 M)
Wasteland-
Scrub land-
Open scrub
Yield 400-
800 LPM,
Depth< 30m
200-400 0-800 0.818177

Fig 3.8: Identified industrial sites in Giridih district, Jharkhand
IV. Conclusion
Satellite remote sensing offers opportunity to
obtain current information over large areas and
GIS can be utilized to further analyze this
information through simple models to answer the
specific questions.
1. Giridih is one of the leading mineral
producing states in the country and occupies
unique position in mineral production and
mineral based industries. The mines areas are
going to increase in near future. At the same
time this area is also highly dominated by
forest resources. The complex environmental
matrix, large scale mining and industrial
activities, huge mineral resources still
available and ever depleting environmental
quality along with flora and fauna, has
attracted attention at both national and
international level.
2. Remote Sensing and GIS has been used to
assess the LULC in spatial and temporal
domain. This has been illustrated in the
present study particularly in view of
examines an approach for identifying the new
industrial zone.
3. Abundance of various mineral resources has
led to the extensive, but haphazard quarrying
activities for sustaining various industries set up
in the region. Lack of sincere conservation efforts
following the unplanned mineral excavation has
resulted in environmental degradation. Remote

sensing data analysis in this study has helped to
derive quantitative information on spatial and
temporal relationships of land use/land cover and
its potential sites for industry development.
4. The studies illustrate the importance of RS
and GIS technology in the present days. RS
5. and GIS technology, as an information tool,
has helped in the acquisition of recent land
use information study aimed at solving
problems. Information on different aspects
for this study like land use land cover,
geomorphology, Ground water, slope, road,
rail, river etc has been derived using this
techniques. Further integrating this data using
GIS has helped in the analysis of the study,
which would have been otherwise been
difficult to do manually using the
conventional method. The involvement of
such factors or criteria requires adequate
database of different dimensions. So adequate
attention is required for data management to
ensure the performance of the decision based
methodology.
6. A multi criteria approach was employed in
conjunction with GIS-based overlay analysis
to identify the new industrial zone. The study
was based upon a set of key criteria, which
were selected based upon the already
available knowledge from research literature
as well as the pre-existing local level factors
of the area. A set of new industrial zone were
identified after subsequent screening and
refinement on the basis of analysis and field
check.
7. Outcome generated through the GIS analysis
shows that 160.85 km2
areas is very highly
suitable, 407.85 km2
area is moderately
suitable; 4398.30 km2
area is less suitable, for
industry setup.
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7 Arc GIS Resource, “How Weighted Overlay works”

[IJET-V1I5P1] Authors :Ahmed Mohamed Abushnafa, R. K. Pandeyb, Deepak Lalc

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[IJET-V1I5P1] Authors :Ahmed Mohamed Abushnafa, R. K. Pandeyb, Deepak Lalc