ACCENTS Transactions on Image Processing and Computer Vision
ISSN (online): 2455-4707
Volume-1 Issue-1 November-2015
Simulation of Spatial Concentration of Urban Built-up Lands through GIS
and Remote Sensing Techniques: A Study of Mysore City, Karnataka, India
M.Vinay*, Ramu and B. Mahalingam
Centre for Geoinformatics Technology, DOS in Geography, Maanasagangothri, University of Mysore, Mysore,
Karnataka, India
Abstract have used different methods to assess the spatial
concentration of landscape such as among those
The present study is conducted to simulate the Relative Shannon Entropy is familiar and provides a
spatial concentration of urban built up lands in meaningful result and it is widely accepted in GIS
Mysore City. In order to model the urban and Remote sensing environment. So, the study have
concentration, the method of Shannon entropy were followed Shannon Entropy method to assess the
utilized which gives degree of compactness or spatial concentration of urban built-up lands that
degree of dispersion. The formulae have brought to indicates either compacted built-up or dispersed
the Geographical Information System environment. built-up land.
Study used 3 set of remote sensing Landsat data
with 11 years temporal resolution such as 1992, 2. Study Area
2003 and 2014. The Urban built up land were
extracted using the visual image interpretation and The study area (map1) named Mysore City which is
supervised classification scheme with set of sample located in Mysore District and it is second largest city
signature file. Then 150m fishnet have created to in Karnataka apart from Bangalore.
define an equidistant zones. After all, Landscape
metrics of Shannon entropy have computed and the
Shannon entropy for the year 1992, 2003 and 2014
showed the value 0.99880, 0.96945 and 0.9437
respectively, which indicates the concentration of
Urban built up lands is compacting year to year.
Keywords
Simulation, Shannon Entropy, Urban Area, Built-up
Lands, Geographical Information System, Remote
Sensing.
1. Introduction
Urban and Urbanization both are dynamic activity in
land use phenomenon. The Urban centres have the
unique characteristics that they pull in populations
from the rural areas due to the availability of
employment, education and health centres which
therefore increases the population. This increasing
population converts open spaces and vegetation into
built areas (B.Mahalingam et. al 2014). So, there is a
need of understanding the dynamicity of changing
landscape and their growth. Several researchers
(McGarigal 1995, Yeh&Li 2000, McGarigal 2005)
Figure 1:Location of Study Area
*Author for correspondence
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ACCENTS Transactions on Image Processing and Computer Vision
ISSN (online): 2455-4707
Volume-1 Issue-1 November-2015
Mysore City geographically extends from 12˚15’10”
to 12˚21’10” Latitude and from 76˚36’0” to
76˚42’20” longitude. It consists of area with 84.35
Km2. The present study is important for these kind of
urban area for monitoring and managing built up
lands in an efficient way.
3. Methodology
The methodology starts with base data acquisition of
Landsat imagery from http://earthexplorer.usgs.gov/
for the year 1993, 2003, 2014. The pre-processing
were done by applying atmospheric correction using
ACTOR 2. Then False Color Composite (FCC)
image were generated with band combination of 4, 3,
2. Then The Urban built up land were extracted using
the visual image interpretation and supervised Where Pi is the proportion of occurrence in ith zone,
classification scheme with set of sample signature Xi is the observed value (built-up area) of the
file. Yeh&Li, (2001), Sudhira (2003) and Heng.S phenomenon in the ith zone (i.e., area of built-up land
(2007) have used multi-ring buffer from the city within one Fishnet Grid 150m and it is found by
centre. But uneven distribution of buffer size will dividing the area of built-up land to the area of
makes the result problematic and could not able to fishnet). The value of entropy ranges from zero to
shows spatially through raster format. So, that new loge (n). Suppose the distribution is extremely
method is followed by creating 150m fishnet to concentrated in one zone (one fishnet grid of 150m),
define an equidistant zones. Totally 3937 fishnet the lowest value of zero will be obtained and if the
grids have created. Then to find out the area of built distribution is dispersed means the value up to loge
up lands within the one fishnet grid, Polygon in (n) will be obtained(Yeh&Li, 2001). Also Relative
Polygon Analysis is performed with the help of entropy can be used to scale the entropy value into a
Hawth’s Toolbox. Then the relative Shannon entropy value from 0 to 1(Thomas, 1981).
is computed.
By using the Relative Shannon Entropy method the
4. Results and Discussion result have found as shown in Map4 and summation
of all fishnet grids for the year 1992, 2003 and 2014
Built-up Extraction: For extracting a built-up land, found to be 0.99880, 0.96945 and 0.9437
Landsat imagery for the year 1992, 2003 and 2014 respectively.
have downloaded with sensors of Landsat TM,
Landsat ETM+ and Landsat OLI respectively. The 5. Conclusion
supervised classification of Maximum likelihood
classification have performed with set of training The GIS and Remote Sensing is a Key tool for asset
signature files for (Map2). Then classified built-up management and for efficient urban planning and
image were converted to feature class (Map3). For development. The spatial concentration of Mysore
the year 1992 it was 15.74 Km2, for 2003 it was city is assessed through the Landscape metrics of
34.93 Km2 and for the year 2014 the built-up land Shannon Entropy method. The entropy is quite
found to be 44.13 Km2 to proceed for the next simple and efficient to assess the distribution of
process. certain phenomena. The entropy value of Shannon
index for study area is compacting year to year and
Shannon Entropy for Measuring Urban found to be 0.99880, 0.96945 and 0.9437 for the year
Concentration: Shannon’s entropy (Hn) can be used 1992, 2003, 2014 respectively. The Mysore City is
to measure the degree of spatial concentration or compacting in urban built-up lands year to year and it
degree of spatial dispersion of a geographical needs to be frequently monitored and to be managed
variable (Xi) among n zones (Theil, 1967; Thomas, to meet urban sustainability.
1981; Yeh&Li 2001). It is calculated by
9
ACCENTS Transactions on Image Processing and Computer Vision
ISSN (online): 2455-4707
Volume-1 Issue-1 November-2015
Figure 2: False Color combination(4,3,2) of landsat Imageries
Figure 3: Extracted Builtupland Feature from landsat Imageries
Figure 4: Spatial Concentration of Urban Builtuplands, Mysore City, karnataka
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ACCENTS Transactions on Image Processing and Computer Vision
ISSN (online): 2455-4707
Volume-1 Issue-1 November-2015
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