SlideShare ist ein Scribd-Unternehmen logo
1 von 38
GIS Data Structures
How do we represent the world in
a GIS database?
Basic Data Structures for GIS
1. Vector
2. Raster
3. TIN (triangulated
irregular network)
4. Tabular Information
(attribute table)
Vector Data Structure
lines
polygons
In vector data layers, the feature layer is linked to
an attribute table. Every individual feature
corresponds to one record (row) in the attribute
table.
Vector Data Structure
About Image Files
• Image files contain no
data
• They are the background
• You can create data
based on images
• Not considered a “data”
structure
Raster Data Structure (Grid)
A raster grid can store values that represent categories, for example,
vegetation type
The basic grid attribute table has a value and
count field
The value field has a code or some real number
representing information about the grid cell. In
this case it is a code for vegetation.
The count field shows how many grid cells have
that same value.
Raster Data Structure
A raster grid can store values that represent categories, for example,
vegetation type
A grid table can also have additional information,
in this case the name of the vegetation type. But
is always has the value and count fields.
Raster Data Structure
Grids can also store continuous values like elevation
Raster Data Structure
Elevation grid for area north of Kirkuk, Iraq
From space shuttle radar topography mission (SRTM)
Zoom in and you see the grid cells
These are called:
Digital Elevation Models (DEM)
Raster Data Structure
So 2 ways of representing elevation:
Vector contour lines Raster grid
Raster Data Structure
Sources of raster data
Interpreted
satellite imagery,
e.g., land cover
Conversion of vector to raster data
Raster Data Structure
Sources of raster data Spatial analysis performed on vector data
A point layer of crime reports
A density grid derived from
the same crime data –
interpolation of point data
over a continuous surface
Raster Data Structure
Sources of raster data
Although an digital aerial photo is in raster format, it has no data.
Raster Data Structure
Raster Data Structure
Raster and Vector Data Structures
Point
Line
Polygon
Vector Raster
Raster data are described by a cell grid, one value per cell
Zone of cells
• Features with discrete
shapes and
boundaries (e.g.,
street, land ownership
parcel, well)
• Database
management
• Database query and
reporting
• Network analysis
• High quality maps
• Continuous surfaces
with fuzzy boundaries
or with qualities that
change gradual over
space (e.g., soil, land
cover, vegetation,
pollution)
• Spatial analysis and
modeling (e.g.,
agricultural suitability)
Vector Raster
A 3rd data structure for representing surfaces:
Triangulated Irregular Network (TIN)
TIN Data Structure
Elevation points
connected by
lines to form
polygons that
contain
topographic
information
TIN Data Structure
Elevation points
connected by
lines to form
polygons that
contain
topographic
information
TIN Data Structure
TIN Data Structure
TIN Data Structure
• Linear geographic features such as streams and
ridges are more accurately represented in a TIN
• Less points are needed to represent the
topography – less hard disk space is needed
• Points can be concentrated in important areas
where the topography is more variable, or where
more detail is required (e.g., small areas of land)
• Survey data and known elevations can easily be
incorporated into a TIN
• Some functions cannot be performed with DEM
data, but are easily done with a TIN
TIN Data Structure
Advantages
3 GIS Spatial Data Structure Types
Attribute table
“Flat File” with columns and rows
Row = geographic feature record
Column = attribute field (item of information about a feature)
Attribute Data Structure
Attribute field general types
• Numeric (integer or decimals)
• Text (string)
• Date
• Blob (binary large object)
Attribute data types
• Categorical (name):
– nominal
• no inherent ordering
• land use types, county names
– ordinal
• inherent order
• road class; stream class
Note: often coded to numbers (eg. SSN)
but can’t do arithmetic
• Numerical
Known difference between values
– interval
• No natural zero
• can’t say ‘twice as much’
• temperature (Celsius or
Fahrenheit)
– ratio
• natural zero
• ratios make sense (e.g. twice
as much)
• income, age, rainfall
Note: may be expressed as integer
[whole number] or floating point [decimal
fraction]
Attribute data tables can contain locational information, such as addresses
or a list of X,Y coordinates. ArcView refers to these as event tables. However,
these must be converted to true spatial data (shape file), for example by
geocoding, before they can be displayed as a map.
Topology
When you edit features in an electric utility
system, you want to be sure that the ends of
primary and secondary lines connect exactly and
that you are able to perform tracing analysis on
that electric network.
Features need to be connected using specific rules.
Network Topology
Planar topology
Property parcels of land must adjoin each other
exactly, without gaps or overlaps. This two-
dimensional graph is called a planar topology.
Topological relationships
The relationships that do not change if you imagine a map being
on a rubber sheet and you pull and stretch the rubber sheet in
different directions.
Vector and TIN data can have topological structure.
Raster and images can not have a topological structure.
For a project
• What data layers
• Vector, raster, TIN, image?
• Topological structure (network connectivity
or planar topology)?
• Attributes?
• Minimum required accuracy?
Some objects are non-topological and can be freely placed in a
geographic area.
Examples?
Many objects are primarily stored in a GIS for the purpose of
background display on a map, so it is usually not necessary to
store them in a topological format.
If roads are a background layer in your GIS, they will probably
be simple features. If roads are part of an analysis of a
transportation system, they should be topological features.
Should a data layer be topologically structured?
ArcGIS Major Data Formats
• Coverages (Arc/Info)
– Older
– Used with ArcInfo versions 7 and older
• Shape files
– Developed when ArcView was released
– ArcView merged with ArcInfo at version 8
• Geodatabases
– Developed when ArcGIS was released (version 8)
– Shapefiles are still used, but the move is toward
geodatabases
Arc/Info Coverages
Coverages are an older data structure in which topology could be modeled.
You will still find many data sets in Arc/Info coverage data formats.
But for new data, you should use geodatabase or shapefile formats.
Shape files
Shape files can be created with ArcView software.
Geodatabases
Geodatabases can be created with ArcGIS 8.x , 9.x, and 10
Geodatabases give you more power to specify rules for features
and structure topology
Summary
• 3 Spatial Data Structure Types in GIS
– Vector
– Raster
– TIN
• Attribute Data Structure – Tables of
columns and rows
• Topology – needed for spatial data to
“know” where other data is

Weitere ähnliche Inhalte

Was ist angesagt?

Application of Remote Sensing in Land Use and Land Cover.ppt
Application of Remote Sensing in Land Use and Land Cover.pptApplication of Remote Sensing in Land Use and Land Cover.ppt
Application of Remote Sensing in Land Use and Land Cover.pptKhushbooGodara3
 
Introduction to ArcGIS
Introduction to ArcGISIntroduction to ArcGIS
Introduction to ArcGISKate Dougherty
 
Remote Sensing: Georeferencing
Remote Sensing: GeoreferencingRemote Sensing: Georeferencing
Remote Sensing: GeoreferencingKamlesh Kumar
 
GIS & RS in Forest Mapping
GIS & RS in Forest MappingGIS & RS in Forest Mapping
GIS & RS in Forest MappingKamlesh Kumar
 
An introduction to geographic information systems (gis) m goulbourne 2007
An introduction to geographic information systems (gis)   m goulbourne 2007An introduction to geographic information systems (gis)   m goulbourne 2007
An introduction to geographic information systems (gis) m goulbourne 2007Michelle Goulbourne @ DiaMind Health
 
Gis Geographical Information System Fundamentals
Gis Geographical Information System FundamentalsGis Geographical Information System Fundamentals
Gis Geographical Information System FundamentalsUroosa Samman
 
Cadastral mapping akshay galav
Cadastral mapping  akshay galavCadastral mapping  akshay galav
Cadastral mapping akshay galavAkshay Galav
 
QGIS Training.pptx
QGIS Training.pptxQGIS Training.pptx
QGIS Training.pptxSeemaAjay7
 
Spatial Database and Database Management System
Spatial Database and Database Management SystemSpatial Database and Database Management System
Spatial Database and Database Management SystemLal Mohammad
 
Basic of gis concept and theories
Basic of gis concept and theoriesBasic of gis concept and theories
Basic of gis concept and theoriesMohsin Siddique
 
Introduction to GIS systems
Introduction to GIS systemsIntroduction to GIS systems
Introduction to GIS systemsVivek Srivastava
 
Spatial vs non spatial
Spatial vs non spatialSpatial vs non spatial
Spatial vs non spatialSumant Diwakar
 

Was ist angesagt? (20)

Application of Remote Sensing in Land Use and Land Cover.ppt
Application of Remote Sensing in Land Use and Land Cover.pptApplication of Remote Sensing in Land Use and Land Cover.ppt
Application of Remote Sensing in Land Use and Land Cover.ppt
 
Introduction to ArcGIS
Introduction to ArcGISIntroduction to ArcGIS
Introduction to ArcGIS
 
Remote Sensing: Georeferencing
Remote Sensing: GeoreferencingRemote Sensing: Georeferencing
Remote Sensing: Georeferencing
 
GIS & RS in Forest Mapping
GIS & RS in Forest MappingGIS & RS in Forest Mapping
GIS & RS in Forest Mapping
 
An introduction to geographic information systems (gis) m goulbourne 2007
An introduction to geographic information systems (gis)   m goulbourne 2007An introduction to geographic information systems (gis)   m goulbourne 2007
An introduction to geographic information systems (gis) m goulbourne 2007
 
Types of GIS Data
Types of GIS DataTypes of GIS Data
Types of GIS Data
 
Gis Geographical Information System Fundamentals
Gis Geographical Information System FundamentalsGis Geographical Information System Fundamentals
Gis Geographical Information System Fundamentals
 
Cadastral mapping akshay galav
Cadastral mapping  akshay galavCadastral mapping  akshay galav
Cadastral mapping akshay galav
 
Introduction to GIS
Introduction to GISIntroduction to GIS
Introduction to GIS
 
Functions of GIS
Functions of GISFunctions of GIS
Functions of GIS
 
GIS
GISGIS
GIS
 
QGIS Training.pptx
QGIS Training.pptxQGIS Training.pptx
QGIS Training.pptx
 
Photogrammetry-part 1
Photogrammetry-part 1Photogrammetry-part 1
Photogrammetry-part 1
 
GIS
GISGIS
GIS
 
Photogrammetry
PhotogrammetryPhotogrammetry
Photogrammetry
 
Spatial Database and Database Management System
Spatial Database and Database Management SystemSpatial Database and Database Management System
Spatial Database and Database Management System
 
Basic of gis concept and theories
Basic of gis concept and theoriesBasic of gis concept and theories
Basic of gis concept and theories
 
Introduction to GIS systems
Introduction to GIS systemsIntroduction to GIS systems
Introduction to GIS systems
 
Spatial vs non spatial
Spatial vs non spatialSpatial vs non spatial
Spatial vs non spatial
 
Geodatabases
GeodatabasesGeodatabases
Geodatabases
 

Ähnlich wie UNIT - III GIS DATA STRUCTURES (1).ppt

Arc gis introduction-ppt
Arc gis introduction-pptArc gis introduction-ppt
Arc gis introduction-pptAshok Peddi
 
spatial databases ADBMS ppt
spatial databases ADBMS pptspatial databases ADBMS ppt
spatial databases ADBMS pptRitaThakkar1
 
Assignment vector raster
Assignment vector rasterAssignment vector raster
Assignment vector rasterfredsk2006
 
Vector data model
Vector data model Vector data model
Vector data model Pramoda Raj
 
Vector data model
Vector data modelVector data model
Vector data modelPramoda Raj
 
Data models in geographical information system(GIS)
Data models in geographical information system(GIS)Data models in geographical information system(GIS)
Data models in geographical information system(GIS)Pramoda Raj
 
ppt spatial data
ppt spatial datappt spatial data
ppt spatial dataRahul Kumar
 
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptx
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptxUG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptx
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptxNancyVerma72
 
the title of this course is Entitles as GIS and Remote sensing
the title of this course is Entitles as GIS and Remote sensingthe title of this course is Entitles as GIS and Remote sensing
the title of this course is Entitles as GIS and Remote sensingmulugeta48
 
DATA in GIS and DATA Query
DATA in GIS and DATA QueryDATA in GIS and DATA Query
DATA in GIS and DATA QueryKU Leuven
 
gislec1.ppt
gislec1.pptgislec1.ppt
gislec1.pptfelip19
 
GettingKnowTo ArcGIS10x
GettingKnowTo ArcGIS10xGettingKnowTo ArcGIS10x
GettingKnowTo ArcGIS10xmukti subedi
 
What is Geography Information Systems (GIS)
What is Geography Information Systems (GIS)What is Geography Information Systems (GIS)
What is Geography Information Systems (GIS)John Lanser
 
Unit 4 Data Input and Analysis.pptx
Unit 4 Data Input and Analysis.pptxUnit 4 Data Input and Analysis.pptx
Unit 4 Data Input and Analysis.pptxe20ag004
 

Ähnlich wie UNIT - III GIS DATA STRUCTURES (1).ppt (20)

Arc gis introduction-ppt
Arc gis introduction-pptArc gis introduction-ppt
Arc gis introduction-ppt
 
Raster data and Vector data
Raster data and Vector dataRaster data and Vector data
Raster data and Vector data
 
Gis basic
Gis basicGis basic
Gis basic
 
spatial databases ADBMS ppt
spatial databases ADBMS pptspatial databases ADBMS ppt
spatial databases ADBMS ppt
 
Assignment vector raster
Assignment vector rasterAssignment vector raster
Assignment vector raster
 
Vector data model
Vector data model Vector data model
Vector data model
 
Vector data model
Vector data modelVector data model
Vector data model
 
Data models in geographical information system(GIS)
Data models in geographical information system(GIS)Data models in geographical information system(GIS)
Data models in geographical information system(GIS)
 
Día 3
Día 3Día 3
Día 3
 
ppt spatial data
ppt spatial datappt spatial data
ppt spatial data
 
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptx
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptxUG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptx
UG6thSem_major_GIS Data Structures.pptx DR P DAS.1.pptx
 
Spatial data for GIS
Spatial data for GISSpatial data for GIS
Spatial data for GIS
 
Geoinformatics.pptx
Geoinformatics.pptxGeoinformatics.pptx
Geoinformatics.pptx
 
the title of this course is Entitles as GIS and Remote sensing
the title of this course is Entitles as GIS and Remote sensingthe title of this course is Entitles as GIS and Remote sensing
the title of this course is Entitles as GIS and Remote sensing
 
DATA in GIS and DATA Query
DATA in GIS and DATA QueryDATA in GIS and DATA Query
DATA in GIS and DATA Query
 
gislec1.ppt
gislec1.pptgislec1.ppt
gislec1.ppt
 
Essentials of R
Essentials of REssentials of R
Essentials of R
 
GettingKnowTo ArcGIS10x
GettingKnowTo ArcGIS10xGettingKnowTo ArcGIS10x
GettingKnowTo ArcGIS10x
 
What is Geography Information Systems (GIS)
What is Geography Information Systems (GIS)What is Geography Information Systems (GIS)
What is Geography Information Systems (GIS)
 
Unit 4 Data Input and Analysis.pptx
Unit 4 Data Input and Analysis.pptxUnit 4 Data Input and Analysis.pptx
Unit 4 Data Input and Analysis.pptx
 

Mehr von RamMishra65

UNIT - III GIS DATA STRUCTURES (2).ppt
UNIT - III GIS DATA STRUCTURES (2).pptUNIT - III GIS DATA STRUCTURES (2).ppt
UNIT - III GIS DATA STRUCTURES (2).pptRamMishra65
 
Basic Geodesy.pdf
Basic Geodesy.pdfBasic Geodesy.pdf
Basic Geodesy.pdfRamMishra65
 
OE7302 syllabus.pdf
OE7302 syllabus.pdfOE7302 syllabus.pdf
OE7302 syllabus.pdfRamMishra65
 
Casting for 2022 GATE ESE PSUs by S K Mondal .pdf
Casting for 2022 GATE ESE PSUs by S K Mondal .pdfCasting for 2022 GATE ESE PSUs by S K Mondal .pdf
Casting for 2022 GATE ESE PSUs by S K Mondal .pdfRamMishra65
 
NTMM for GATE IES PSUs 2023 by S K Mondal.pdf
NTMM for GATE IES PSUs 2023 by S K Mondal.pdfNTMM for GATE IES PSUs 2023 by S K Mondal.pdf
NTMM for GATE IES PSUs 2023 by S K Mondal.pdfRamMishra65
 
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdf
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdfPowder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdf
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdfRamMishra65
 
4209-Article Text-20296-1-10-20210531.pdf
4209-Article Text-20296-1-10-20210531.pdf4209-Article Text-20296-1-10-20210531.pdf
4209-Article Text-20296-1-10-20210531.pdfRamMishra65
 
Powder_Metallurgy__Part_II_with_anno.pdf
Powder_Metallurgy__Part_II_with_anno.pdfPowder_Metallurgy__Part_II_with_anno.pdf
Powder_Metallurgy__Part_II_with_anno.pdfRamMishra65
 
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdf
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdfPowder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdf
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdfRamMishra65
 

Mehr von RamMishra65 (10)

UNIT - III GIS DATA STRUCTURES (2).ppt
UNIT - III GIS DATA STRUCTURES (2).pptUNIT - III GIS DATA STRUCTURES (2).ppt
UNIT - III GIS DATA STRUCTURES (2).ppt
 
Basic Geodesy.pdf
Basic Geodesy.pdfBasic Geodesy.pdf
Basic Geodesy.pdf
 
gis.pdf
gis.pdfgis.pdf
gis.pdf
 
OE7302 syllabus.pdf
OE7302 syllabus.pdfOE7302 syllabus.pdf
OE7302 syllabus.pdf
 
Casting for 2022 GATE ESE PSUs by S K Mondal .pdf
Casting for 2022 GATE ESE PSUs by S K Mondal .pdfCasting for 2022 GATE ESE PSUs by S K Mondal .pdf
Casting for 2022 GATE ESE PSUs by S K Mondal .pdf
 
NTMM for GATE IES PSUs 2023 by S K Mondal.pdf
NTMM for GATE IES PSUs 2023 by S K Mondal.pdfNTMM for GATE IES PSUs 2023 by S K Mondal.pdf
NTMM for GATE IES PSUs 2023 by S K Mondal.pdf
 
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdf
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdfPowder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdf
Powder_Metallurgy__Part_I__Doubt_Clearing_Session_with_anno.pdf
 
4209-Article Text-20296-1-10-20210531.pdf
4209-Article Text-20296-1-10-20210531.pdf4209-Article Text-20296-1-10-20210531.pdf
4209-Article Text-20296-1-10-20210531.pdf
 
Powder_Metallurgy__Part_II_with_anno.pdf
Powder_Metallurgy__Part_II_with_anno.pdfPowder_Metallurgy__Part_II_with_anno.pdf
Powder_Metallurgy__Part_II_with_anno.pdf
 
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdf
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdfPowder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdf
Powder_Metallurgy__Part_III__Doubt_Clearing_Session_no_anno.pdf
 

Kürzlich hochgeladen

ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfKamal Acharya
 
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Wakad Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance Bookingroncy bisnoi
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Arindam Chakraborty, Ph.D., P.E. (CA, TX)
 
UNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its PerformanceUNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its Performancesivaprakash250
 
22-prompt engineering noted slide shown.pdf
22-prompt engineering noted slide shown.pdf22-prompt engineering noted slide shown.pdf
22-prompt engineering noted slide shown.pdf203318pmpc
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Bookingdharasingh5698
 
Introduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaIntroduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaOmar Fathy
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptMsecMca
 
Bhosari ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
Bhosari ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...Bhosari ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...
Bhosari ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...tanu pandey
 
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...soginsider
 
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoor
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoorTop Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoor
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoordharasingh5698
 
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...roncy bisnoi
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdfKamal Acharya
 
Block diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptBlock diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptNANDHAKUMARA10
 
chapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineeringchapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineeringmulugeta48
 
Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VDineshKumar4165
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE  and Energy Efficient BUILDINGS ptxCOST-EFFETIVE  and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxJIT KUMAR GUPTA
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayEpec Engineered Technologies
 

Kürzlich hochgeladen (20)

ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
 
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak HamilCara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
 
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Wakad Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Wakad Call Me 7737669865 Budget Friendly No Advance Booking
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
 
UNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its PerformanceUNIT - IV - Air Compressors and its Performance
UNIT - IV - Air Compressors and its Performance
 
22-prompt engineering noted slide shown.pdf
22-prompt engineering noted slide shown.pdf22-prompt engineering noted slide shown.pdf
22-prompt engineering noted slide shown.pdf
 
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 BookingVIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
VIP Call Girls Ankleshwar 7001035870 Whatsapp Number, 24/07 Booking
 
Introduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaIntroduction to Serverless with AWS Lambda
Introduction to Serverless with AWS Lambda
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.ppt
 
Bhosari ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
Bhosari ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...Bhosari ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...
Bhosari ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
 
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
 
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoor
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoorTop Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoor
Top Rated Call Girls In chittoor 📱 {7001035870} VIP Escorts chittoor
 
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdf
 
Block diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptBlock diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.ppt
 
chapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineeringchapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineering
 
Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - V
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE  and Energy Efficient BUILDINGS ptxCOST-EFFETIVE  and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power Play
 

UNIT - III GIS DATA STRUCTURES (1).ppt

  • 1. GIS Data Structures How do we represent the world in a GIS database?
  • 2. Basic Data Structures for GIS 1. Vector 2. Raster 3. TIN (triangulated irregular network) 4. Tabular Information (attribute table)
  • 4. In vector data layers, the feature layer is linked to an attribute table. Every individual feature corresponds to one record (row) in the attribute table. Vector Data Structure
  • 5. About Image Files • Image files contain no data • They are the background • You can create data based on images • Not considered a “data” structure
  • 7. A raster grid can store values that represent categories, for example, vegetation type The basic grid attribute table has a value and count field The value field has a code or some real number representing information about the grid cell. In this case it is a code for vegetation. The count field shows how many grid cells have that same value. Raster Data Structure
  • 8. A raster grid can store values that represent categories, for example, vegetation type A grid table can also have additional information, in this case the name of the vegetation type. But is always has the value and count fields. Raster Data Structure
  • 9. Grids can also store continuous values like elevation Raster Data Structure
  • 10. Elevation grid for area north of Kirkuk, Iraq From space shuttle radar topography mission (SRTM) Zoom in and you see the grid cells These are called: Digital Elevation Models (DEM) Raster Data Structure
  • 11. So 2 ways of representing elevation: Vector contour lines Raster grid Raster Data Structure
  • 12. Sources of raster data Interpreted satellite imagery, e.g., land cover Conversion of vector to raster data Raster Data Structure
  • 13. Sources of raster data Spatial analysis performed on vector data A point layer of crime reports A density grid derived from the same crime data – interpolation of point data over a continuous surface Raster Data Structure
  • 14. Sources of raster data Although an digital aerial photo is in raster format, it has no data. Raster Data Structure
  • 16. Raster and Vector Data Structures Point Line Polygon Vector Raster Raster data are described by a cell grid, one value per cell Zone of cells
  • 17. • Features with discrete shapes and boundaries (e.g., street, land ownership parcel, well) • Database management • Database query and reporting • Network analysis • High quality maps • Continuous surfaces with fuzzy boundaries or with qualities that change gradual over space (e.g., soil, land cover, vegetation, pollution) • Spatial analysis and modeling (e.g., agricultural suitability) Vector Raster
  • 18. A 3rd data structure for representing surfaces: Triangulated Irregular Network (TIN) TIN Data Structure
  • 19. Elevation points connected by lines to form polygons that contain topographic information TIN Data Structure
  • 20. Elevation points connected by lines to form polygons that contain topographic information TIN Data Structure
  • 23. • Linear geographic features such as streams and ridges are more accurately represented in a TIN • Less points are needed to represent the topography – less hard disk space is needed • Points can be concentrated in important areas where the topography is more variable, or where more detail is required (e.g., small areas of land) • Survey data and known elevations can easily be incorporated into a TIN • Some functions cannot be performed with DEM data, but are easily done with a TIN TIN Data Structure Advantages
  • 24. 3 GIS Spatial Data Structure Types
  • 25. Attribute table “Flat File” with columns and rows Row = geographic feature record Column = attribute field (item of information about a feature) Attribute Data Structure
  • 26. Attribute field general types • Numeric (integer or decimals) • Text (string) • Date • Blob (binary large object)
  • 27. Attribute data types • Categorical (name): – nominal • no inherent ordering • land use types, county names – ordinal • inherent order • road class; stream class Note: often coded to numbers (eg. SSN) but can’t do arithmetic • Numerical Known difference between values – interval • No natural zero • can’t say ‘twice as much’ • temperature (Celsius or Fahrenheit) – ratio • natural zero • ratios make sense (e.g. twice as much) • income, age, rainfall Note: may be expressed as integer [whole number] or floating point [decimal fraction] Attribute data tables can contain locational information, such as addresses or a list of X,Y coordinates. ArcView refers to these as event tables. However, these must be converted to true spatial data (shape file), for example by geocoding, before they can be displayed as a map.
  • 28. Topology When you edit features in an electric utility system, you want to be sure that the ends of primary and secondary lines connect exactly and that you are able to perform tracing analysis on that electric network. Features need to be connected using specific rules.
  • 30. Planar topology Property parcels of land must adjoin each other exactly, without gaps or overlaps. This two- dimensional graph is called a planar topology.
  • 31. Topological relationships The relationships that do not change if you imagine a map being on a rubber sheet and you pull and stretch the rubber sheet in different directions. Vector and TIN data can have topological structure. Raster and images can not have a topological structure.
  • 32. For a project • What data layers • Vector, raster, TIN, image? • Topological structure (network connectivity or planar topology)? • Attributes? • Minimum required accuracy?
  • 33. Some objects are non-topological and can be freely placed in a geographic area. Examples? Many objects are primarily stored in a GIS for the purpose of background display on a map, so it is usually not necessary to store them in a topological format. If roads are a background layer in your GIS, they will probably be simple features. If roads are part of an analysis of a transportation system, they should be topological features. Should a data layer be topologically structured?
  • 34. ArcGIS Major Data Formats • Coverages (Arc/Info) – Older – Used with ArcInfo versions 7 and older • Shape files – Developed when ArcView was released – ArcView merged with ArcInfo at version 8 • Geodatabases – Developed when ArcGIS was released (version 8) – Shapefiles are still used, but the move is toward geodatabases
  • 35. Arc/Info Coverages Coverages are an older data structure in which topology could be modeled. You will still find many data sets in Arc/Info coverage data formats. But for new data, you should use geodatabase or shapefile formats.
  • 36. Shape files Shape files can be created with ArcView software.
  • 37. Geodatabases Geodatabases can be created with ArcGIS 8.x , 9.x, and 10 Geodatabases give you more power to specify rules for features and structure topology
  • 38. Summary • 3 Spatial Data Structure Types in GIS – Vector – Raster – TIN • Attribute Data Structure – Tables of columns and rows • Topology – needed for spatial data to “know” where other data is