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MODELLING LANDUSE CHANGES OF GURUPAVANAPURI AND
ENVIRONS, THRISSUR, KERALA, INDIA
CENTER FOR ENVIRONMENT AND DEVELOPMENT
SHARIK SHAMSUDHIEN
INTRODUCTION
• Urbanization refers to the increasing number of people that live in
urban areas. Land-use change is often associated with a change in land
cover.
• There are different factors and mechanisms drive land use and land
cover transformation such as climate, technology, and economics.
• GIS is a technology that enhances the users’ application to visualize
the spatially distributed nature of the data. GIS allows us to view,
understand, and interpret data in many ways that reveal relationships,
pattern and trends in the form of maps, charts and reports.
• The present study is using a Remote sensing data to monitor the
landuse changes through time.
STUDY AREA
• Gurupavanapuri and environs is one of the most developing cities and fast
growing city in the Guruvayoor.
• The study addressing the land-use and land-cover to determine land use
pattern and estimate the changes that have taken place between 2002 and
2017, Gurupavanapuri and environs, Thrissur, Kerala
• The total area is 50.8259 ha (approx. half a km. sq.) bounded by N. Lat 10° 35'
51.61"and N 10° 35' 37.11"and E. Long. 76° 2' 12.68" and 76° 2'
42.17“
• Many of these changes can be quantified from satellite measurements,
Google Earth, Aerial photographs.
Fig. 1. Location map, AOI
Kerala India
Chavakkad Taluk Gurupavanapuri
Fig: 2 Toposheet (1:250000)
Fig: 3 SOI Toposheet (1:50000)
Objectives
The main objectives of the research are as following:
• Monitoring of the urbanization expansion and land cover changes
since 2002 till 2017 in Gurupavanapuri and environs, Thrissur District
• Topography contour map and detecting the slope for the area.
• Preparing TIN model and drainage map.
• Preparing Bathymetry and Oceanic bedrock Surface Off - Thrissur
• Gain the knowledge of handling the spatial data by remote sensing
and GIS.
METHODOLOGY
• Considering the remotely sensed data of the two period times to
extract information about the LULC.
• Literature review of the LULC of any area as well.
• Remote Sensing data collection, such as SRTM DEM, ETOPO1 data
(Bathymetry and Oceanic bedrock surface), Google Earth images of
the area for 2002 and 2017 and other relevant materials.
• Data verification, preparation/processing Re-projection/setting of
coordinate system, clipping, digitizing, classification, etc. and
importing in personal/file Geodatabases.
Fig.4 . The flow chart
of adopted
methodology
Fig. 2. Google Earth image 2003 of Block 1
Fig.4 . Google Earth image 2002 ,Gurupavanapuri and environs
Fig.5 . Google Earth image 2017 ,Gurupavanapuri and environs
Land use -Land cover
• To achieve this study the two different land covers and land use
classes of years 2002 and 2017 were analyzed.
• The values is estimated from digitization quantify the change in each
land cover category.
• The LULC of the study area that is being estimated is categorized in
to three classes
 Building footprint
 Open space
 Vegetation
 Water body
Fig.6 . LULC - 2002
Landuse - 2002
24%
9%
1%
66%
Buildings
Open area
Water body
Vegetation
LANDUSE - 2002
Fig: 7 Pie Diagram , LULC - 2002
Fig.8 . LULC - 2017
Landuse - 2017
42%
5%
1%
52%
Buildings
Open area
Pond
Vegetation
LANDUSE - 2017
Fig: 9 Pie Diagram , LULC - 2017
2002
2017Fig: 10 LULC – 2002, 2017
Comparison of the land use and land cover extent in 2002 and 2017
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Buildings Open area Vegetation Water body
2002
2017
10
15
5
20
25
30
35
Inhectares(ha)
Contour map or Topographic Maps
These are general-use maps at medium scales that present elevation (contour lines),
hydrography, geographic place names, and a variety of cultural features.
Fig.11 Contour map,Thrissur District (includes AOI).
Digital Elevation Model (DEM)
is a specialized database that represents the relief of a surface between points of known
elevation as a layer in GIS symbolized by a color ramp to produce new surfaces such as slope
and aspect.
Fig.12 DEM model,Thrissur District (includes AOI).
Triangular Irregular Networks (TIN)
TINs are a form of vector-based digital geographic data and are constructed by triangulating a
set of points connected by edges. Visual representation of a topographical features and
appearance of the physical land surface.
Fig.13 TIN model,Thrissur District (includes AOI).
Drainage Pattern
It is the study of the way in which the pattern of streams in a drainage basin is organized
Fig.14 Drainage network,Thrissur District (includes AOI).
Slope
A slope is a surface that is at an angle, so that one end is higher than the other.
Fig.14 Slope map,Thrissur District (includes AOI).
Bathymetry
Bathymetry is the study of underwater depth of lake or ocean floors.
Fig.15 Bathymetry Off-Thrissur District .
Oceanic bedrock Surface
Oceanic bedrock is the oceanic crust which is the uppermost layer of the oceanic portion of a tectonic plate
Fig.16 Oceanic bedrock surface Off-Thrissur District .
CONCLUSIONS
• Remote sensing and GIS is a valuable technique for handling the
spatial data.
• The built-up growth shows radical urban growth when compared to
that of the built-up where it has almost doubled in the year 2002.
• All these observations point towards the change in the land use pattern
and the study clearly defines this change, which can be used in the
future planning of Gurupavanapuri and similar areas.
ACKNOWLEDGMENTS
• I express my gratitude to Dr. Babu Ambat, Executive Director, Centre for
Environment and Development (CED).
• I sincerely thank Dr. Thrivikramji K. P. Professor Emeritus and Program Director for
his invaluable guidance and constant encouragement.
• I express my whole hearted gratitude to all faculty members of CED, viz., Dr. Vinod
T. R., Dr. Sabu T. and Mrs. Radha S.
• I am indebted to Dr. Chrips N. R., Research Associate and Mr. Prasood S. P., for their
steady and immeasurable help, valuable comments and fruitful discussions during
this project work.
• I am grateful to all my course mates for their co-operation and support during the
project work.
• 1 also wish to thank all the staff of CED who had helped me directly or indirectly for
the successful completion of my studies.
Thank You

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Application of GIS in Modelling Landuse Changes Of Gurupavanapuri, Kerala, India

  • 1. MODELLING LANDUSE CHANGES OF GURUPAVANAPURI AND ENVIRONS, THRISSUR, KERALA, INDIA CENTER FOR ENVIRONMENT AND DEVELOPMENT SHARIK SHAMSUDHIEN
  • 2. INTRODUCTION • Urbanization refers to the increasing number of people that live in urban areas. Land-use change is often associated with a change in land cover. • There are different factors and mechanisms drive land use and land cover transformation such as climate, technology, and economics. • GIS is a technology that enhances the users’ application to visualize the spatially distributed nature of the data. GIS allows us to view, understand, and interpret data in many ways that reveal relationships, pattern and trends in the form of maps, charts and reports. • The present study is using a Remote sensing data to monitor the landuse changes through time.
  • 3. STUDY AREA • Gurupavanapuri and environs is one of the most developing cities and fast growing city in the Guruvayoor. • The study addressing the land-use and land-cover to determine land use pattern and estimate the changes that have taken place between 2002 and 2017, Gurupavanapuri and environs, Thrissur, Kerala • The total area is 50.8259 ha (approx. half a km. sq.) bounded by N. Lat 10° 35' 51.61"and N 10° 35' 37.11"and E. Long. 76° 2' 12.68" and 76° 2' 42.17“ • Many of these changes can be quantified from satellite measurements, Google Earth, Aerial photographs.
  • 4. Fig. 1. Location map, AOI Kerala India Chavakkad Taluk Gurupavanapuri
  • 5.
  • 6. Fig: 2 Toposheet (1:250000)
  • 7. Fig: 3 SOI Toposheet (1:50000)
  • 8. Objectives The main objectives of the research are as following: • Monitoring of the urbanization expansion and land cover changes since 2002 till 2017 in Gurupavanapuri and environs, Thrissur District • Topography contour map and detecting the slope for the area. • Preparing TIN model and drainage map. • Preparing Bathymetry and Oceanic bedrock Surface Off - Thrissur • Gain the knowledge of handling the spatial data by remote sensing and GIS.
  • 9. METHODOLOGY • Considering the remotely sensed data of the two period times to extract information about the LULC. • Literature review of the LULC of any area as well. • Remote Sensing data collection, such as SRTM DEM, ETOPO1 data (Bathymetry and Oceanic bedrock surface), Google Earth images of the area for 2002 and 2017 and other relevant materials. • Data verification, preparation/processing Re-projection/setting of coordinate system, clipping, digitizing, classification, etc. and importing in personal/file Geodatabases.
  • 10. Fig.4 . The flow chart of adopted methodology
  • 11. Fig. 2. Google Earth image 2003 of Block 1 Fig.4 . Google Earth image 2002 ,Gurupavanapuri and environs
  • 12. Fig.5 . Google Earth image 2017 ,Gurupavanapuri and environs
  • 13. Land use -Land cover • To achieve this study the two different land covers and land use classes of years 2002 and 2017 were analyzed. • The values is estimated from digitization quantify the change in each land cover category. • The LULC of the study area that is being estimated is categorized in to three classes  Building footprint  Open space  Vegetation  Water body
  • 14. Fig.6 . LULC - 2002
  • 16. 24% 9% 1% 66% Buildings Open area Water body Vegetation LANDUSE - 2002 Fig: 7 Pie Diagram , LULC - 2002
  • 17. Fig.8 . LULC - 2017
  • 19. 42% 5% 1% 52% Buildings Open area Pond Vegetation LANDUSE - 2017 Fig: 9 Pie Diagram , LULC - 2017
  • 20. 2002 2017Fig: 10 LULC – 2002, 2017
  • 21. Comparison of the land use and land cover extent in 2002 and 2017 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Buildings Open area Vegetation Water body 2002 2017 10 15 5 20 25 30 35 Inhectares(ha)
  • 22. Contour map or Topographic Maps These are general-use maps at medium scales that present elevation (contour lines), hydrography, geographic place names, and a variety of cultural features. Fig.11 Contour map,Thrissur District (includes AOI).
  • 23. Digital Elevation Model (DEM) is a specialized database that represents the relief of a surface between points of known elevation as a layer in GIS symbolized by a color ramp to produce new surfaces such as slope and aspect. Fig.12 DEM model,Thrissur District (includes AOI).
  • 24. Triangular Irregular Networks (TIN) TINs are a form of vector-based digital geographic data and are constructed by triangulating a set of points connected by edges. Visual representation of a topographical features and appearance of the physical land surface. Fig.13 TIN model,Thrissur District (includes AOI).
  • 25. Drainage Pattern It is the study of the way in which the pattern of streams in a drainage basin is organized Fig.14 Drainage network,Thrissur District (includes AOI).
  • 26. Slope A slope is a surface that is at an angle, so that one end is higher than the other. Fig.14 Slope map,Thrissur District (includes AOI).
  • 27. Bathymetry Bathymetry is the study of underwater depth of lake or ocean floors. Fig.15 Bathymetry Off-Thrissur District .
  • 28. Oceanic bedrock Surface Oceanic bedrock is the oceanic crust which is the uppermost layer of the oceanic portion of a tectonic plate Fig.16 Oceanic bedrock surface Off-Thrissur District .
  • 29. CONCLUSIONS • Remote sensing and GIS is a valuable technique for handling the spatial data. • The built-up growth shows radical urban growth when compared to that of the built-up where it has almost doubled in the year 2002. • All these observations point towards the change in the land use pattern and the study clearly defines this change, which can be used in the future planning of Gurupavanapuri and similar areas.
  • 30. ACKNOWLEDGMENTS • I express my gratitude to Dr. Babu Ambat, Executive Director, Centre for Environment and Development (CED). • I sincerely thank Dr. Thrivikramji K. P. Professor Emeritus and Program Director for his invaluable guidance and constant encouragement. • I express my whole hearted gratitude to all faculty members of CED, viz., Dr. Vinod T. R., Dr. Sabu T. and Mrs. Radha S. • I am indebted to Dr. Chrips N. R., Research Associate and Mr. Prasood S. P., for their steady and immeasurable help, valuable comments and fruitful discussions during this project work. • I am grateful to all my course mates for their co-operation and support during the project work. • 1 also wish to thank all the staff of CED who had helped me directly or indirectly for the successful completion of my studies.