Landuse mapping for Chennai using ArcGIS

1. LANDUSE MAPPING FOR
CHENNAI
SUPERVISOR: PROF. VAANI N
Members:
ADITYA ANAND (13BCL0145)
ACHINKYA DIXIT (13BCL0067)
ARINDAM BANERJEE (13BCL0042)
FINAL REVIEW (02.05.2017)

2. OBJECTIVES
• Delineation of study area
• To prepare a Landuse Map of Chennai
• To find the total area of various landuse classes
using the prepared landuse map
• To segregate the total area into Taluks and
calculating the area of each landuse classes of each
Taluk
2

3. IMPORTANCE OF STUDY
• 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.
3

4. Lack of adequate and affordable housing
• As of 2012, in Chennai an estimated population of 11,116 (0.16 percent)
were homeless. The landuse map can be helpful in selecting the appropriate
locations for building new shelters for the homeless.
• As Per 2011 census, about 26,000 households live in houses without any
room and another 427,000 families (with an average size of five members)
live in small dwelling units with only one room.
• There is a need to generate about 420,000 units for low-income groups by
2016. This shows us the importance of proper town planning and it can only
be achieved with the help of a Landuse map.
Stressed Water bodies
• Chennai has three rivers and many lakes spread across the city.
Urbanization has led to shrinkage of water bodies and wetlands. The quantity
of wetlands in the city has decreased from 650 to only 27 currently.
• Environmentalist Foundation of India is a volunteering group working towards
wildlife conservation and habitat restoration. They can use this Landuse map
for proper restoration of rivers and for wildlife conservation and habitat
restoration purpose.
Contd...
4

5. INTRODUCTION
• The land use classification system we are using in the present
study is the more generalized level I. It contains:
 Built-up area
 Agricultural area
 Water Bodies
 Open Land
• In addition to this the Road and Railway network have also
been added.
Levels of Landuse Classification
GIS & Landuse Mapping
• A geographic information system (GIS) is a computer system
for capturing, storing, and displaying data related to positions
on Earth's surface.
• So, GIS is very useful for landuse mapping & classification.
5

6. SOFTWARE USED
• ArcGIS
• Google Earth
• Elshayal Smart
DATA USED
• Google Earth Imagery
6

7. METHODOLOGY
Digitization of boundary
• The boundary of the Chennai was digitized and then it was
converted from ArcGIS shape file format (.shp) to Google earth
compatible format (.kml).
Image extraction using Elshayal Smart
• Elshayal Smart was used to extract the Google earth images with
coordinates.
Image Mosaicking & GIS Analysis
• A total of 735 images acquired covering the entire study area
were downloaded.
• The individual images were then mosaicked to form one single
image.
7

8. • Then it was converted from geographic coordinate system
(latitude/longitude) to projected coordinate system
(northing/easting) using Universal Transverse Mercator (UTM)
projection in Arc GIS.
• The image covered within the corporation boundary was clipped
as shown in Fig. 1 using the digitized corporation boundary
map.
Preparation of landuse map & Area estimation
• Finally onscreen digitizing of various landuse classes was
performed to prepare the landuse map and area under various
landuse classes was estimated.
Contd...
8

9. Fig. 1 Clipped image of the study area after the mosaicking process
9

10. RESULTS & DISCUSSION
10

11. Fig. 2 Landuse Map of Chennai City prepared using Google Earth
11

12. Landuse Class Area (sq.km) Percentage Split (%)
Built-up Area 126.58 77.65
Agricultural Area 16.44 10.08
Open Land 12.80 07.85
Water Bodies 07.19 04.42
Table 1 Area of various Landuse classes and there percentage split
78%
10%
8%
4%
Built-up Area
Agricultural
Area
Open Land
Water Bodies
Fig. 3 Percentage split of various Landuse classes in Chennai city
12

13. Landuse Area (sq.km) Percentage Split (%)
Built-up Area 126.58 73
AgriculturalArea 16.44 09
Open Land 12.80 07
Water Bodies 07.19 04
Road Network 07.87 05
Railway Network 03.17 02
Table 2 Area of various Landuse classes along with road and railway network and there
percentage split
73%
9%
7%
4%
5% 2%
Built-up Area
Agricultural Area
Open Land
Water Bodies
Road Network
Railway Network
Fig. 4 Percentage split of various Landuse classes along with road and railway network 13

14. Taluk-wise Landuse classification
14
• The Taluk wise percentage split of various landuse classes is
shown in the figures below.
83%
4%
1%
4%
7%
1%
Ayanavaram
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies 89%
2%
2%
3%
3%
1%
Egmore
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies

15. 72%
7%
4%
5%
9%
3%
Purasaiwalkam
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
70%
7%
1%
4%
10%
8%
Mylapore
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
60%
6%1%
4%
23%
6%
Velachery
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
44%
40%
0%
2% 13%
1%Guindy
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
15

16. 85%
5%
0%
5%
3% 2%
Aminjikarai
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
69%
15%
2% 3%
6%
5%
Perambur
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
61%17%
6%
3%
5%
8%
Tondiarpet
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
91%
2%
0% 3% 2%2%
Mambalam
Built-up Area
Open Land
Rail N/W
Road N/W
Agricultural Area
Water Bodies
16

17. CONCLUSION
• GIS is an versatile tool that can be used for land use mapping,
classification & evaluation.
• Google earth images provide an alternative to costly satellite
images.
• Land use mapping & classification is inevitable for proper urban
planning in the wake of rapid urbanization and increasing
stresses on the environment.
• It is observed that even though built-up area comprises of more
than 75% on an average of total area, there is still a dearth of
housing infrastructure, especially for the Low income groups.
• Moreover, there is need of paying attention to the dwindling
water bodies and proper drainage planning is needed, taking
help of the landuse map, in order to tackle water scarcity and
urban flooding problems.
17

18. REFERENCES
• Alaguraja .P, Durairaju.S, Yuvaraj .D, Sekar.M Muthuveerran.P
Manivel .M, Thirunavukkarasu.A. "Land Use and Land Cover
Mapping – Madurai District, Tamilnadu, India Using Remote
Sensing and GIS Techniques" International Journal of Civil and
Structural Engineering.
• Andrew Jacobson, Jasjeet Dhanota, Jessie Godfrey, Hannah
Jacobson, Zoe Rossman, Andrew Stanish, Hannah Walker, Jason
Riggio, 2015. "A novel approach to mapping land conversion using
Google Earth with an application to East Africa." Environmental
Modelling & Software 72 (2015) 1 -9.
• Basawaraja, R., et al. "Analysis of the impact of urban sprawl in
altering the land-use, land-cover pattern of Raichur City, India,
using geospatial technologies." Journal of Geography and
Regional Planning 4.8 (2011): 455.
• Elshayal, M., 2015. Elshayal Smart GIS ver. 5.15.
18

19. Contd...
• Google: Google earth ver.7.1.7.
• K. Malarvizhi, S.Vasantha Kumar, P.Porchelvan "Use of High
Resolution Google Earth Satellite Imagery in Landuse Map
Preparation for Urban Related Applications." International
Conference on Emerging Trends in Engineering, Science and
Technology (ICETEST - 2015). Procedia Technology 24 (2016).
• Jamal Mohamed Salih Irhoumah, V. C. Agarwal, Deepak Lal.
"Land Use/Land Cover Mapping Of Allahabad City by Using
Remote Sensing & GIS" International Journal Of Modern
Engineering Research (IJMER).
• James R. Anderson, Ernest E. Hardy, John T. Roach, and Richard
E. Witmer. "A Land Use And Land Cover Classification System For
Use With Remote Sensor Data" Geological Survey Professional
Paper.
• Jat, M.K., Garg, P.K., Khare, D., 2008. "Monitoring and modelling
of urban sprawl using remote sensing and GIS techniques."
International Journal of Applied Earth Observation and
Geoinformation 10, 26-43.
19

20. Thank You