Spatio-temporal analysis of the study area is done based on the satellite images of Landsat 4, 5 and 8 for the years 1991, 2006 and 2020 respectively.
The main parameters/types taken here for studying land-use change are:
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Vegetation cover
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Buit-up area
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Grassland
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Water-bodies
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Transport
Analysis For 1991 Image : After doing the composite image with suitable band combinations of 3,2,1 (RGB) the ISO unsupervised classification taking fifty classes was done was on the rectified composite image as shown in Fig. 2. The fifty classes were clubbed into five classes as mentioned to achieve the following results.
In the classes, the colours denoted some features. They are as follows: pink denoted built-up area, light blue denoted water bodies, black denoted transport, green denoted vegetation and yellow denoted grassland
From the classes as shown in Fig. 3, it was found that Built-up area and vegetation covers the maximum portion of the area of the ward. The area in sq.km have been calculated for each classes using the 'measure' tool in arc map.
Vegetation is the dominant land-use type with a total area of 1.002635 square kilometres (sq.km), followed by built-up (0.8321sq.km), grassland (0.5523sq.km) and transport (0.12385), water bodies (0.04115sq.km) respectively.
Analysis For 2006 Image
For 2006 image classification as shown in Fig. 4 certain color codes were used. They are as follows: pink denotes built-up area, light blue denotes water-bodies, black denotes transport, green denoted vegetation and red denotes grassland
Here the dominant land-use type is the built up area (1.55302sq.km) followed by grassland (1.42634 sq.km),transport network (0.19523sq.km), vegetation (0.138253sq.km) waterbodies (0.070902 sq.km) respectively.
ANALYSIS OF 2020 IMAGE
ISO maximum likelihood classification was done with training samples for the five classes as shown in Fig. 5.
For the 2020 image classification, the following colour codes represented the following features. Brown denoted built-up area, light blue for water-bodies, white for transport, green for vegetation and pink for grassland
The built-up area constitutes the major type of land-use with an area of 1.9962sq.km.,grassland (0.96804sq.km.),transport (0.1901sq.km),vegetation(0.14102sq.km) and water bodies (0.025sq.km) as shown in Fig. 6.
From these classification, it has been extremely clear that there has been an increase in the built-up area from 1991 to 2006 as shown in Fig. 7. at the cost of vegetation. The vegetation cover which constituted 1.0023635sq.km in the year 1991 have been cut off and its major portion is given to built-up areas and grasslands for better accessibility. Increase in grassland i.e. twenty two percent in the year 1991 to thirty nine percent in 2006. While there is an increase in the urban built-up space i.e. thirty two percent in the year 1991 to forty percent in the year 2006, there has been a decrease in vegetation i.e. thirty nine percent to four percent in 2006 which signifies the building of high class residences which promises to give a green space in the form of open space which was once covered with vegetation The percentage of built-up areas and transport have increased i.e. five percent to six percent in 2006) at the cost of natural vegetation from 1991 to 2006 due to rise in population.
In 2020 there has been a decrease in grassland cover and increase in the urban built-up area with the built-up area in 2006 was only forty nine percent and in the year 1991 and thirty two percent respectively. The area under grassland have decreased from thirty nine percent in the year 2006 to twenty eight percent. The areas under water-body have shrunk from two percent to one percent (2006–2020). Hence by comparing the land-uses from 1991–2020 we can understand that the concrete areas are increasing at the cost of natural elements of land-cover namely water-bodies, vegetation, grassland.
DIAGRAMS SHOWING COMPARISON OF LANDUSE OF IMAGES DATED 1991, 2006. 2020
Normalised Difference Vegetation Index (NDVI) has been performed in these images for validation and to check whether the aforesaid decline in the vegetative areas and grassland areas are for real or not. It basically shows the density of vegetation and acts as a supportive base to co-relate with our analysis.
Normalized Difference Vegetation Index (NDVI) is a standardized index which generates an image displaying greenness (relative biomass). This index takes advantage of the contrast of
the characteristics of two bands from a multispectral raster dataset—the chlorophyll pigment absorptions in the red band and the high reflectivity of plant materials in the near-infrared (NIR) band.
The documented and default NDVI equation is as follows:
NDVI = ((IR - R)/(IR + R))
This index outputs values between − 1.0 and 1.0, mostly representing greenness, where any negative values are mainly generated from clouds, water, and snow, and values near zero are mainly generated from rock and bare soil. Very low values (0.1 and below) of NDVI correspond to barren areas of rock, sand, or snow. Moderate values (0.2 to 0.3) represent shrub and grassland, while high values (0.6 to 0.8) indicate temperate and tropical rainforests
The NDVI values for 1991 ranges as shown in Fig. 8 from − 0.15 to 0.483871 which clearly shows that the area is at the juncture between forest and grassland. The darker pixels signify builtup areas and the lighter pixels represents reflectance from vegetation as in the NIR band the reflectance from vegetation is the most
Whereas the NDVI performed for the 2006 image shows a distinctively different result. The NDVI value for 2006 range as shown in Fig. 9, that from − 0.1304 to 0.38 which clearly means that there is a detoriation in the "healthiness" of a vegetation as there is a decline in the NDVI value from 0.4838 to 0.38 from 1991 as there is massive decline in the vegetative cover and vegetative cover have been transformed into grassland which has lower reflectance than vegetative cover due to decrease in chlorophyll as has been stated previously in this report. The NDVI value of 0.38 fully corresponds with the given range for grassland which is evident in our 2006 image.
Thus comparing the land-use change from 1991 to 2006 it can be inferred that the areas which were under vegetation have been transformed to built-up areas and grassland for human habitation. There is also increase in the total percentage of transport network from 1991to 2006 as shown with the help of pie diagrams in the above sections.
However between 2006 and 2020 it has been observed there is an increase in the NDVI value but decline in the grassland cover. It is mainly because the image has been taken in summer season when the chlorophyll content in plants were high hence more reflectance in the infrared bands unlike the other two images which taken winter. The NDVI value of 2020 as shown in Fig. 10. ranges from 0.408076 to 0.00243636. The highest NDVI is however value for 2020 which is quite low from 1991 which proves that there is decline in vegetative index i.e. quality of vegetation
To validate and check the accuracy of the result, accuracy assessment was performed on the ISO maximum likelihood supervised classified image of 2020 by:
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creating 30 random points
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exporting the layer to KML file
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Overlaying the KML file into google earth image of 2020
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Each random point was was clicked and was tallied with google earth image
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with the help of the above points we have computed a matrix to find out the overall accuracy and kappa index to to see the accuracy level
Table 1 Showing Matrix Of Accuracy Assessment
|
Wb (8)
|
U(5)
|
G(1)
|
Tr(9)
|
V(11)
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Row total
|
Wb
|
0
|
0
|
0
|
0
|
0
|
0
|
U
|
0
|
4
|
4
|
0
|
0
|
8
|
G
|
0
|
0
|
8
|
0
|
1
|
9
|
Tr
|
0
|
0
|
3
|
1
|
0
|
4
|
V
|
0
|
1
|
5
|
1
|
3
|
10
|
Column total
|
0
|
5
|
20
|
2
|
4
|
|
Wb = waterbody, U = urban, G = grassland, Tr = transport, V = vegetation.
Sum of diagonal = 16 Total no. of random points = 30
Overall accuracy = Percent of random points that are same in both the image(google and raster)
= 53percent
Kappa index have also been calculated to check the accuracy level.
k = observed-expected/1-expected
expected = product matrix/cumulative product matrix = diagonal values of summation
= 0.2842
Thus, according to the accuracy assessment results fifty three percent of the classified types of land-use are presently in their same place as classified in the image. With the help of the accuracy levels, NDVI values and calculating the area for the types of landuses of the respective years it has been inferred that there is a shrinkage in the elements of land-cover i.e. vegetation, grassland and water-bodies and increase in the built-up space and transport network. Thus, the noteworthy changes over the years are as follows:
From 1991 to 2020 there has been shrinkage in areas under
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Vegetation
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Grassland
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Water-bodies
From 1991 to 2020 there has been increase in areas under
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Built-up area
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Road network
There has been decline in the healthiness of a vegetation as shown through the NDVI values due to continuous built-up area, vegetative areas have shrunken.The dominant land-use now is the built-up area.
The study area is thereby undergoing environmental change at a great extent as the areas under vegetation, grassland, water-bodies have shrunk to a great extent. It will sooner or later result in the fall in the piezometric levels due to decline in percent of areas under water-bodies vegetation, grassland (roots of trees and grass acts as percolating agent and binds soil) as well concretisation will impede the infiltration rate.