Page 1 of 6
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 05
May 2019
Available online:https://ejbss.org/ P a g e | 1001
Development Of A Framework To Planand Monitor Rural Roads Using GIS
S. NAGANATHAN
DEPARTMENT OF CIVIL ENGINEERING
PRIST (Deemed to be University), THANJAVUR
Abstract
The fundamental data required by urban planners and policy makers is accurate information
on current landuse practices in a city or town and how it changes over the past for carrying
out various urban planning and management activities. The free satellite imagery provided in
global landcover facility (GLCF) which can be used to prepare the landuse maps as attempted
in many studies has certain limitations. The images are of lower or medium resolution type
and in many cases it may not be possible to obtain the latest image. To overcome this, one
has to buy latest high resolution satellite image which is more expensive to purchase and
sometimes it may not be possible to get the data due to security reasons. An alternative
solution is to utilize Google earth imagery which is open source and provides clear view of
buildings, roads, etc. and hence can be best utilized for urban related applications.
Introduction
Urbanization is a major concern in most of
the metropolitan cities in the world. It is
said that, between 2010 and 2050, the
number of people living in the world’s
urban areas is expected to grow by 80
percent, i.e., from 3.5 billion in 2010 to 6.3
billion in 2050 (Moss and Neill, 2012).
This twofold rise may lead to many urban
related problems in world’s cities and
India is no exception to this. More people
are migrating from rural to urban areas for
better job opportunities and living
conditions in recent decades due to
economic growth in the country. Next to
Maharashtra and Gujarat, in Tamilnadu,
50% of the total population of the state
was living in major cities of the state,
which is one of the highest in the country
(State Planning Commission, 2012). This
shows that most of the cities in the state
are experiencing rapid urbanization in
recent decades. Urbanization is
unavoidable in a developing country like
India. However if it is not controlled
properly may result in loss of productive
agricultural land, deforestation, crowded
habitats, water distribution and sewage
treatment problems, air and noise
pollution, traffic congestion, etc. Accurate
and current urban landuse information is
an essential data required by planners and
Page 2 of 6
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 05
May 2019
Available online:https://ejbss.org/ P a g e | 1002
policy makers for carrying out various
activities in urban planning and
management. For example, the landuse
data is useful for urban planners and
researchers in preparation of master plan,
planning of smart cities and satellite
towns, provision of basic amenities and
urban infrastructure facilities, analyze the
changes that have occurred in the landuse
over the past years, prediction of future
landuse, urban sprawl analysis, etc. In
recent decades, the use of satellite data has
replaced the traditional field survey
methods in preparing urban landuse maps
due to advancements in remote sensing
and geographic information systems (GIS).
Many studies have reported in India and
abroad, in which the authors have
collected multi temporal satellite images
and using image processing techniques
such as unsupervised and/or supervised
classification, maps showing various
landuse categories at different time periods
were prepared(Sudhira et al., 2004; Sun et
al.
The GLCF provides satellite data at free of
cost to promote research in the use of
remotely sensed data. However it has
certain limitations. The images are having
only lower and medium spatial resolution
(size of each pixel on the ground) in the
range of 30m to 80m collected from
sensors such as Landsat Multispectral
Scanner (MSS), Landsat Thematic Mapper
(TM), Enhanced Thematic Mapper Plus
(ETM+), etc. Another limitation is that it
may not be possible to obtain a latest
satellite data or the image for the current
year. In GLCF, one can get satellite
images only upto 2010 or before. The
solution to overcome the above limitations
with GLCF is to purchase the latest high
resolution satellite imagery having spatial
resolution less than or equal to 1m either
from Indian remote sensing satellites like
Cartosat-2 or US based satellites like
Worldview-2 or Quickbird. But it may be
more expensive to purchase such high
resolution images. An alternative solution
is to download Google Earth (Google,
2015) and use the satellite images
provided in that for preparing the land use
map for the region of interest. The
advantage of using Google earth is that it
provides the latest satellite imagery having
spatial resolution less than 1m. In recent
years, most popular image processing and
GIS softwares like ERDAS IMAGINE,
ENVI, ArcGIS, etc. have provided tools to
visualize and import Google earth images.
Another advantage of Google earth is that
it provides images taken at different time
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Page 3 of 6
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 05
May 2019
Available online:https://ejbss.org/ P a g e | 1003
periods which will be very useful for urban
planners to perform landuse change
detection studies. The only limitation of
Google earth is that it may not be possible
to obtain the original multispectral band
data. That means it is not possible to get
the actual pixel numbers or the
brightness/reflectance values and hence
image classification using unsupervised or
supervised techniques cannot be carried
out. However, as the spatial resolution is
very high, it is possible to visually see on
the image, buildings, roads, water bodies,
etc. and on-screen digitizing in GIS can
easily be performed to prepare the landuse
map. Hence in the present study, an
attempt has been made to prepare the
landuse map using Google earth imagery
for Vellore in Tamil Nadu, which
experiences tremendous urban growth in
recent decades. A detailed step-by-step
procedure on how to download the satellite
images from Google earth, import them,
mosaicking, clipping and performing
onscreen digitizing is presented in this
paper for the preparation of landuse map.
Literature review
A review of important studies which
utilized the satellite images in landuse
classification for urban related applications
was attempted and presented in this
section. Sudhira et al. (2004) used satellite
image from LISS-3 sensor of Indian
remote sensing satellite (IRS) having
spatial resolution of 23.5m to prepare the
landuse map through supervised
classification. The landuse map was used
to study the urban sprawl along the
highway connecting Mangalore and Udupi
in Karnataka. Jat et al. (2008) used images
from various sensors like Landsat MSS
(79m. resolution), TM, ETM+ and IRS
LISS 3 for preparation of maps depicting
landuse across various years and used it to
study the urban growth and sprawl pattern
of Ajmer city in Rajasthan. Guzelmansur
and Kilic (2010) studied the urban landuse
changes using the satellite images from
Landsat MSS, TM and ETM+ through
image classification method. Basawaraja et
al. (2011) studied the temporal changes in
landuse pattern using IRS LISS-3 satellite
images of Raichur city in Karnataka.
Rahman et al. (2011) used IRS LISS-3
satellite image of 2005 to prepare the
landuse map through supervised
classification technique. The authors
mentioned that due to the high cost of very
high resolution satellite images such as
Worldview-2 having a spatial resolution of
0.46 m with eight spectral bands, it is not
