4-Gis Data Models

Prepared by: Mdm.Siti Aekbal SallehPrepared by: Mdm.Siti Aekbal Salleh 11

TOPIC 4:TOPIC 4:GIS DATA MODELSGIS DATA MODELS

Data Types and ModelsData Types and Models


GIS DataGIS Data

The backbone of GIS is good data. Inaccurate The backbone of GIS is good data. Inaccurate data can result in inaccurate models and maps, data can result in inaccurate models and maps,

skewing the results of your analysis and skewing the results of your analysis and ultimately resulting in poor decisions. "Garbage ultimately resulting in poor decisions. "Garbage

in, garbage out," as the adage says.in, garbage out," as the adage says.

The wide availability of the GIS data makes it The wide availability of the GIS data makes it critical to understand what GIS data is, how it is critical to understand what GIS data is, how it is used, and how to select the right data for your used, and how to select the right data for your

needs.needs.


DATA MODELSDATA MODELS

Data models are the rules the GIS follows, such Data models are the rules the GIS follows, such as "county lines do not overlap," and are as "county lines do not overlap," and are essential for defining what is in the GIS as well essential for defining what is in the GIS as well as supporting the use of GIS software. All spatial as supporting the use of GIS software. All spatial data models fall into two basic categories: data models fall into two basic categories: Vector data model.Vector data model. Discrete features, such as Discrete features, such as

customer locations and data summarized by area, are customer locations and data summarized by area, are usually represented using the vector model.usually represented using the vector model.

Raster data model.Raster data model. Continuous numeric values, such Continuous numeric values, such as elevation, and continuous categories, such as as elevation, and continuous categories, such as vegetation types, are represented using the raster vegetation types, are represented using the raster model.model.


GIS Data ModelGIS Data Model

A GIS stores information about the world as a A GIS stores information about the world as a collection of thematic layers that can be linked collection of thematic layers that can be linked together by geography. This simple but together by geography. This simple but extremely powerful and versatile concept has extremely powerful and versatile concept has proven invaluable for solving many real-world proven invaluable for solving many real-world problems from tracking delivery vehicles, to problems from tracking delivery vehicles, to recording details of planning applications, to recording details of planning applications, to modeling global atmospheric circulation. modeling global atmospheric circulation.

The thematic layer approach allows us to The thematic layer approach allows us to organize the complexity of the real world into a organize the complexity of the real world into a simple representation to help facilitate our simple representation to help facilitate our understanding of natural relationships. understanding of natural relationships.


Data Types Data Types

Geography data comes in three basic forms: Geography data comes in three basic forms: Map dataMap data.. Map data contains the location and shape Map data contains the location and shape

of geographic features. of geographic features. Attribute dataAttribute data.. Attribute (tabular) data is the Attribute (tabular) data is the

descriptive data that GIS links to map features. descriptive data that GIS links to map features. Attribute data is collected and compiled for specific Attribute data is collected and compiled for specific areas like states, census tracts, cities, and so on and areas like states, census tracts, cities, and so on and often comes packaged with map data. often comes packaged with map data.

Image dataImage data.. Image data ranges from satellite images Image data ranges from satellite images and aerial photographs to scanned maps (maps that and aerial photographs to scanned maps (maps that have been converted from printed to digital format). have been converted from printed to digital format).


GIS Data TypeGIS Data Type

The basic data type in a GIS reflects traditional The basic data type in a GIS reflects traditional data found on a map. Accordingly, GIS data found on a map. Accordingly, GIS technology utilizes two basic types of data. technology utilizes two basic types of data. These are:These are:Spatial dataSpatial data describes the absolute and relative location of describes the absolute and relative location of

geographic features. geographic features. Attribute dataAttribute data describes characteristics of the spatial features. describes characteristics of the spatial features.

These characteristics can be quantitative and/or These characteristics can be quantitative and/or qualitative in nature. Attribute data is often referred to qualitative in nature. Attribute data is often referred to as tabular data.as tabular data.


The coordinate location of a forestry stand would The coordinate location of a forestry stand would be spatial, the characteristics of that forestry be spatial, the characteristics of that forestry stand, e.g. cover group, dominant species, stand, e.g. cover group, dominant species, crown closure, height, etc., would be attribute crown closure, height, etc., would be attribute data. data.

Depending on the specific content of the data, Depending on the specific content of the data, image dataimage data may be considered either spatial, may be considered either spatial, e.g. photographs, animation, movies, etc., or e.g. photographs, animation, movies, etc., or attribute, e.g. sound, descriptions, narration's, attribute, e.g. sound, descriptions, narration's, etc etc


The thematic layer approach allows us to organize thecomplexity of the real world


SPATIAL DATASPATIAL DATA

Spatial data model falls into two main Spatial data model falls into two main categories:categories: Raster-based formatRaster-based format Vector-based formatVector-based format

This results to two GIS categories known This results to two GIS categories known as:as: Raster-based GISRaster-based GIS Vector-based GISVector-based GIS

Functions available in ArcGISFunctions available in ArcGIS


Raster or Vector?Raster or Vector?

While any feature type can be represented While any feature type can be represented using either model, discrete features, such using either model, discrete features, such

as customer locations, pole locations or as customer locations, pole locations or others; and data summarized by area, others; and data summarized by area,

such as postal code areas or lakes; are such as postal code areas or lakes; are usually represented using the vector usually represented using the vector

model. Continuous categories, such as model. Continuous categories, such as soil type, rainfall, or elevation, are usually soil type, rainfall, or elevation, are usually

represented using the raster model.represented using the raster model.


Vector Data ModelVector Data Model The vector data model represents each feature as a row The vector data model represents each feature as a row

in a table, and feature shapes are defined by in a table, and feature shapes are defined by x, yx, y locations in space (the GIS connects the dots to draw locations in space (the GIS connects the dots to draw lines and outlines). Features can be discrete locations or lines and outlines). Features can be discrete locations or events, lines, or polygons.events, lines, or polygons.

Vector data includes points, lines, and polygons.Vector data includes points, lines, and polygons. Points represent anything that can be described as an Points represent anything that can be described as an x, yx, y

location on the face of the earth, such as shopping centers, location on the face of the earth, such as shopping centers, customers, utility poles, hospitals, or cellular towers. customers, utility poles, hospitals, or cellular towers.

Lines represent anything having a length, such as streets, Lines represent anything having a length, such as streets, highways, and rivers. highways, and rivers.

Polygons describe anything having boundaries, whether natural, Polygons describe anything having boundaries, whether natural, political or administrative, such as the boundaries of countries, political or administrative, such as the boundaries of countries, states, cities, census tracts, postal zones, and market areas. states, cities, census tracts, postal zones, and market areas.


Vector storage implies the use of vectors Vector storage implies the use of vectors (directional lines) to represent a geographic (directional lines) to represent a geographic feature. Vector data is characterized by the use feature. Vector data is characterized by the use of sequential points or of sequential points or verticesvertices to define a linear to define a linear segment. Each vertex consists of an X segment. Each vertex consists of an X coordinate and a Y coordinate. coordinate and a Y coordinate.

Vector lines are often referred to as Vector lines are often referred to as arcs arcs and and consist of a string of vertices terminated by a consist of a string of vertices terminated by a nodenode. .

A node is defined as a vertex that starts or ends A node is defined as a vertex that starts or ends an arc segment. Point features are defined by an arc segment. Point features are defined by one coordinate pair, a vertex one coordinate pair, a vertex


Polygonal features are defined by a set of closed Polygonal features are defined by a set of closed coordinate pairs. coordinate pairs.

In vector representation, the storage of the vertices for In vector representation, the storage of the vertices for each feature is important, as well as the connectivity each feature is important, as well as the connectivity between features, e.g. the sharing of common vertices between features, e.g. the sharing of common vertices where features connect.where features connect.

The most popular method of retaining spatial The most popular method of retaining spatial relationships among features is to explicitly record relationships among features is to explicitly record adjacency information in what is known as the topologic adjacency information in what is known as the topologic data model.data model.

Topology is a mathematical concept that has its basis in Topology is a mathematical concept that has its basis in the principles of feature adjacency and connectivity. the principles of feature adjacency and connectivity.


STORING VECTOR DATASTORING VECTOR DATA

Topological data structureTopological data structure is often referredt to as an is often referredt to as an intelligent data structureintelligent data structure because spatial relationships because spatial relationships between geographic features are easily derived when between geographic features are easily derived when using them.using them.

The secondary vector data structure that is common The secondary vector data structure that is common among GIS software is the among GIS software is the computer-aided drafting computer-aided drafting (CAD) data structure(CAD) data structure. This structure consists of listing . This structure consists of listing elements, not features, defined by strings of vertices, to elements, not features, defined by strings of vertices, to define geographic features, e.g. points, lines, or areas. define geographic features, e.g. points, lines, or areas. There is considerable redundancy with this data model There is considerable redundancy with this data model since the boundary segment between two polygons can since the boundary segment between two polygons can be stored twice, once for each feature. be stored twice, once for each feature.


Raster Data ModelRaster Data Model

The raster data model represents features The raster data model represents features as a matrix of cells in continuous space. as a matrix of cells in continuous space. Each layer represents one attribute Each layer represents one attribute (although other attributes can be attached (although other attributes can be attached to a cell). Most analysis occurs by to a cell). Most analysis occurs by combining the layers to create new layers combining the layers to create new layers with new cell values. with new cell values.


Raster data models incorporate the use of a Raster data models incorporate the use of a grid-cellgrid-cell data structure where the geographic area is divided into data structure where the geographic area is divided into cells identified by row and column. This data structure is cells identified by row and column. This data structure is commonly called commonly called rasterraster. While the term raster implies a . While the term raster implies a regularly spaced grid other regularly spaced grid other tessellated tessellated data structures do data structures do exist in grid based GIS systems.exist in grid based GIS systems.

A raster data structure is in fact a matrix where any A raster data structure is in fact a matrix where any coordinate can be quickly calculated if the origin point is coordinate can be quickly calculated if the origin point is known, and the size of the grid cells is known. Since known, and the size of the grid cells is known. Since grid-cells can be handled as two-dimensional arrays in grid-cells can be handled as two-dimensional arrays in computer encoding many analytical operations are easy computer encoding many analytical operations are easy to program. This makes tessellated data structures a to program. This makes tessellated data structures a popular choice for many GIS software. popular choice for many GIS software.


The following diagram reflects the two primary spatial data encoding The following diagram reflects the two primary spatial data encoding techniques. These are vector and raster. Image data utilizes techniques. These are vector and raster. Image data utilizes techniques very similar to raster data, however typically lacks the techniques very similar to raster data, however typically lacks the internal formats required for analysis and modeling of the data. internal formats required for analysis and modeling of the data. Images reflect Images reflect picturespictures or or photographsphotographs of the landscape. of the landscape.


Image DataImage Data

Image data is most often used to represent graphic or Image data is most often used to represent graphic or pictorial data. The term pictorial data. The term image image inherently reflects a inherently reflects a graphic representation, and in the graphic representation, and in the GIS worldGIS world, differs , differs significantly from raster data. significantly from raster data.

Most often, image data is used to store remotely sensed Most often, image data is used to store remotely sensed imagery, e.g. satellite scenes or orthophotos, or ancillary imagery, e.g. satellite scenes or orthophotos, or ancillary graphics such as photographs, scanned plan graphics such as photographs, scanned plan documents, etc. Image data is typically used in GIS documents, etc. Image data is typically used in GIS systems as background display data (if the image has systems as background display data (if the image has been rectified and georeferenced); or as a graphic been rectified and georeferenced); or as a graphic attribute.attribute.


Remote sensing software makes use of image data for Remote sensing software makes use of image data for image classification and processing. image classification and processing.

Typically, this data must be converted into a raster Typically, this data must be converted into a raster format (and perhaps vector) to be used analytically with format (and perhaps vector) to be used analytically with the GIS.the GIS.

Image data is typically stored in a variety of de facto Image data is typically stored in a variety of de facto industry standard proprietary formats. These often reflect industry standard proprietary formats. These often reflect the most popular image processing systems. the most popular image processing systems.

Other graphic image formats, such as TIFF, GIF, PCX, Other graphic image formats, such as TIFF, GIF, PCX, etc., are used to store ancillary image data. Most GIS etc., are used to store ancillary image data. Most GIS software will read such formats and allow you to display software will read such formats and allow you to display this data. this data.


MODISMODIS


Landsat TM Landsat TM (False Color Composite)(False Color Composite)


SPOT (2.5 m)SPOT (2.5 m)


QUICKBIRD (0.6 m)QUICKBIRD (0.6 m)


IKONOS (4 m Multispectral) IKONOS (4 m Multispectral)


IKONOS (1 m Panchromatic)IKONOS (1 m Panchromatic)


LIDAR LIDAR (Light Detection and Ranging)(Light Detection and Ranging)

Image: Bainbridge Island, WA courtesy Pudget Sound LIDAR Consortium, 2005


VECTOR ADVANTAGES AND VECTOR ADVANTAGES AND DISADVANTAGES DISADVANTAGES

Vector Data Advantages :Vector Data Advantages : Data can be represented at its original resolution and Data can be represented at its original resolution and

form without generalization. form without generalization. Graphic output is usually more aesthetically pleasing Graphic output is usually more aesthetically pleasing

(traditional cartographic representation); (traditional cartographic representation); Since most data, e.g. hard copy maps, is in vector Since most data, e.g. hard copy maps, is in vector

form no data conversion is required. form no data conversion is required. Accurate geographic location of data is maintained. Accurate geographic location of data is maintained. Allows for efficient encoding of topology, and as a Allows for efficient encoding of topology, and as a

result more efficient operations that require result more efficient operations that require topological information, e.g. proximity, network topological information, e.g. proximity, network analysis. analysis.


Vector Data Disadvantages:Vector Data Disadvantages: The location of each vertex needs to be stored explicitly. The location of each vertex needs to be stored explicitly. For effective analysis, vector data must be converted into For effective analysis, vector data must be converted into

a topological structure. This is often processing intensive a topological structure. This is often processing intensive and usually requires extensive data cleaning. As well, and usually requires extensive data cleaning. As well, topology is static, and any updating or editing of the vector topology is static, and any updating or editing of the vector data requires re-building of the topology. data requires re-building of the topology.

Algorithms for manipulative and analysis functions are Algorithms for manipulative and analysis functions are complex and may be processing intensive. Often, this complex and may be processing intensive. Often, this inherently limits the functionality for large data sets, e.g. a inherently limits the functionality for large data sets, e.g. a large number of features. large number of features.

Continuous data, such as elevation data, is not effectively Continuous data, such as elevation data, is not effectively represented in vector form. Usually substantial data represented in vector form. Usually substantial data generalization or interpolation is required for these data generalization or interpolation is required for these data layers. layers.

Spatial analysis and filtering within polygons is impossible Spatial analysis and filtering within polygons is impossible


RASTER ADVANTAGES AND RASTER ADVANTAGES AND DISADVANTAGES DISADVANTAGES

Raster Data Advantages :Raster Data Advantages : The geographic location of each cell is implied by its position in The geographic location of each cell is implied by its position in

the cell matrix. Accordingly, other than an origin point, e.g. the cell matrix. Accordingly, other than an origin point, e.g. bottom left corner, no geographic coordinates are stored. bottom left corner, no geographic coordinates are stored.

Due to the nature of the data storage technique data analysis is Due to the nature of the data storage technique data analysis is usually easy to program and quick to perform. usually easy to program and quick to perform.

The inherent nature of raster maps, e.g. one attribute maps, is The inherent nature of raster maps, e.g. one attribute maps, is ideally suited for mathematical modeling and quantitative ideally suited for mathematical modeling and quantitative analysis. analysis.

Discrete data, e.g. forestry stands, is accommodated equally Discrete data, e.g. forestry stands, is accommodated equally well as continuous data, e.g. elevation data, and facilitates the well as continuous data, e.g. elevation data, and facilitates the integrating of the two data types. integrating of the two data types.

Grid-cell systems are very compatible with raster-based output Grid-cell systems are very compatible with raster-based output devices, e.g. electrostatic plotters, graphic terminals.devices, e.g. electrostatic plotters, graphic terminals.


Raster Data Disadvantages:Raster Data Disadvantages: The cell size determines the resolution at which the data is The cell size determines the resolution at which the data is

represented.; represented.; It is especially difficult to adequately represent linear features It is especially difficult to adequately represent linear features

depending on the cell resolution. Accordingly, network linkages depending on the cell resolution. Accordingly, network linkages are difficult to establish. are difficult to establish.

Processing of associated attribute data may be cumbersome if Processing of associated attribute data may be cumbersome if large amounts of data exists. Raster maps inherently reflect only large amounts of data exists. Raster maps inherently reflect only one attribute or characteristic for an area. one attribute or characteristic for an area.

Since most input data is in vector form, data must undergo Since most input data is in vector form, data must undergo vector-to-raster conversion. Besides increased processing vector-to-raster conversion. Besides increased processing requirements this may introduce data integrity concerns due to requirements this may introduce data integrity concerns due to generalization and choice of inappropriate cell size. generalization and choice of inappropriate cell size.

Most output maps from grid-cell systems do not conform to high-Most output maps from grid-cell systems do not conform to high-quality cartographic needs.quality cartographic needs.


NON-SPATIAL DATANON-SPATIAL DATA

Also known as ATTRIBUTE DATA Also known as ATTRIBUTE DATA MODELS.MODELS.

These data models is a separate data These data models is a separate data model is used to store and maintain model is used to store and maintain attribute data for GIS software.attribute data for GIS software.

These data models may exist internally These data models may exist internally within the GIS software, or may be within the GIS software, or may be reflected in external commercial Database reflected in external commercial Database Management Software (DBMS). Management Software (DBMS).


The topologic model is often confusing to initial The topologic model is often confusing to initial users of GIS. users of GIS. ““Topology is a mathematical approach that allows Topology is a mathematical approach that allows

us to structure data based on the principles of us to structure data based on the principles of feature adjacency and feature connectivity. It is in feature adjacency and feature connectivity. It is in fact the mathematical method used to define fact the mathematical method used to define spatial relationships”spatial relationships”

Without a topologic data structure in a vector Without a topologic data structure in a vector based GIS most data manipulation and analysis based GIS most data manipulation and analysis functions would not be practical or feasible.functions would not be practical or feasible.

Topology refers to the relationships or Topology refers to the relationships or connectivity between spatial objects.connectivity between spatial objects.

TOPOLOGYTOPOLOGY


Geometry and TopologyGeometry and Topology


Common Topological Data Common Topological Data Structure Structure

This model contains two basic entities, the This model contains two basic entities, the arcarc and the and the nodenode..

The arc is a series of points, joined by straight The arc is a series of points, joined by straight line segments, that start and end at a node. line segments, that start and end at a node.

The node is an intersection point where two or The node is an intersection point where two or more arcs meet. Nodes also occur at the end of more arcs meet. Nodes also occur at the end of a a danglingdangling arc, e.g. an arc that does not connect arc, e.g. an arc that does not connect to another arc such as a dead end street. to another arc such as a dead end street.

Isolated nodes, not connected to arcs represent Isolated nodes, not connected to arcs represent point features. A polygon feature is comprised of point features. A polygon feature is comprised of a closed chain of arcs. a closed chain of arcs.


Simply defineSimply define

Node :Node : an intersect of more than two lines or an intersect of more than two lines or strings, or start and end point of string with node strings, or start and end point of string with node number number

Chain Chain : a line or a string with chain number, start : a line or a string with chain number, start and end node number, left and right neighbored and end node number, left and right neighbored polygons polygons

PolygonPolygon : an area with polygon number, series : an area with polygon number, series of chains that form the area in clockwise order of chains that form the area in clockwise order (minus sign is assigned in case of anti-clockwise (minus sign is assigned in case of anti-clockwise order). order).


Topological Relationships between Topological Relationships between Spatial Objects Spatial Objects

In practical applications of GIS, all possible relationships In practical applications of GIS, all possible relationships in spatial data should be used logically with more in spatial data should be used logically with more complicated data structures.The following topology complicated data structures.The following topology relationships are commonly defined. relationships are commonly defined. Point-Pont RelationshipPoint-Pont Relationship

"is within" : within a certain distance"is within" : within a certain distance"is nearest to" : nearest to a certain point "is nearest to" : nearest to a certain point

Point-Line RelationshipsPoint-Line Relationships"on line" : a point on a line"on line" : a point on a line"is nearest to" : a point nearest to a line "is nearest to" : a point nearest to a line

Point-area RelationshipsPoint-area Relationships"is contained in’’ : a point in an area"is contained in’’ : a point in an area"on border of area" : a point on border of an area "on border of area" : a point on border of an area


Cont…Cont…

Line-Line RelationshipsLine-Line Relationships"intersects" : two lines intersect"intersects" : two lines intersect"crosses" : two lines cross without an intersect"crosses" : two lines cross without an intersect"flow into" : a stream flows into the river"flow into" : a stream flows into the river

Line-Area RelationshipLine-Area Relationship"intersects" : a line intersects an area"intersects" : a line intersects an area"borders" : a line is a part of border of an area "borders" : a line is a part of border of an area

Area-Area RelationshipsArea-Area Relationships"overlaps" : two areas overlap"overlaps" : two areas overlap"is within" : an island within an area"is within" : an island within an area"is adjacent to" : two area share a common boudary"is adjacent to" : two area share a common boudary


Example of Topological Example of Topological RelationshipRelationship


Geometric and Topological Geometric and Topological ModellingModelling


Advantages vs. DisadvantagesAdvantages vs. Disadvantages

The advantages of the topological data The advantages of the topological data model are to avoid duplication in digitizing model are to avoid duplication in digitizing common boundaries of two polygons and common boundaries of two polygons and to solve problems when the two versions to solve problems when the two versions of the common boundary do not coincide. of the common boundary do not coincide.

The disadvantages are to have to build The disadvantages are to have to build very correct topological data sets without very correct topological data sets without any single error and to be unable to any single error and to be unable to represent islands in a polygon.represent islands in a polygon.


TYPES OF DATABASE MODELSTYPES OF DATABASE MODELS

A variety of different data models exist for the storage A variety of different data models exist for the storage and management of attribute data. The most common and management of attribute data. The most common are:are: Tabular Tabular Hierarchial Hierarchial Network Network Relational Relational Object OrientedObject Oriented

The tabular model is the manner in which most early GIS The tabular model is the manner in which most early GIS software packages stored their attribute data. The next software packages stored their attribute data. The next three models are those most commonly implemented in three models are those most commonly implemented in database management systems (DBMS). The object database management systems (DBMS). The object oriented is newer but rapidly gaining in popularity for oriented is newer but rapidly gaining in popularity for some applications. some applications.


Tabular ModelTabular Model The simple tabular model stores attribute data The simple tabular model stores attribute data

as sequential data files with fixed formats (or as sequential data files with fixed formats (or comma delimited for ASCII data), for the location comma delimited for ASCII data), for the location of attribute values in a predefined record of attribute values in a predefined record structure. structure.

This type of data model is outdated in the GIS This type of data model is outdated in the GIS arena. arena.

It lacks any method of checking data integrity, as It lacks any method of checking data integrity, as well as being inefficient with respect to data well as being inefficient with respect to data storage, e.g. limited indexing capability for storage, e.g. limited indexing capability for attributes or records, etc. attributes or records, etc.


Hierarchical ModelHierarchical Model The hierarchical database organizes data in a The hierarchical database organizes data in a treetree

structure. structure. Data is structured downward in a Data is structured downward in a hierarchyhierarchy of tables. of tables.

Any level in the hierarchy can have unlimited Any level in the hierarchy can have unlimited childrenchildren, , but any but any childchild can have only one can have only one parentparent. .

Hierarchial DBMS have not gained any noticeable Hierarchial DBMS have not gained any noticeable acceptance for use within GISacceptance for use within GIS. They are oriented for . They are oriented for data sets that are very stable, where primary data sets that are very stable, where primary relationships among the data change infrequently or relationships among the data change infrequently or never at all. never at all.

Also, the limitation on the number of parents that an Also, the limitation on the number of parents that an element may have is not always conducive to actual element may have is not always conducive to actual geographic phenomenon.geographic phenomenon.


Network ModelNetwork Model

The network database organizes data in a The network database organizes data in a network or network or plexplex structure. Any column in a structure. Any column in a plex structure can be linked to any other. plex structure can be linked to any other. Like a tree structure, a plex structure can Like a tree structure, a plex structure can be described in terms of be described in terms of parentsparents and and childrenchildren. .

This model allows for children to have This model allows for children to have more than one parent.more than one parent.


Network DBMS have not found much more Network DBMS have not found much more acceptance in GIS than the hierarchical acceptance in GIS than the hierarchical DBMSDBMS. .

They have the same flexibility limitations as They have the same flexibility limitations as hierarchical databases; however, the more hierarchical databases; however, the more powerful structure for representing data powerful structure for representing data relationships allows a more realistic modelling of relationships allows a more realistic modelling of geographic phenomenon. geographic phenomenon.

However, network databases tend to become However, network databases tend to become overly complex too easily. In this regard it is overly complex too easily. In this regard it is easy to lose control and understanding of the easy to lose control and understanding of the relationships between elements.relationships between elements.


Relational ModelRelational Model

The relational database organizes data in The relational database organizes data in tablestables. . Each table, is identified by a unique table name, Each table, is identified by a unique table name, and is organized by and is organized by rowsrows and and columnscolumns. .

Each column within a table also has a unique Each column within a table also has a unique name. Columns store the values for a specific name. Columns store the values for a specific attribute, e.g. cover group, tree height. Rows attribute, e.g. cover group, tree height. Rows represent one record in the table. represent one record in the table.

In a GIS each row is usually linked to a separate In a GIS each row is usually linked to a separate spatial feature, e.g. a forestry stand. spatial feature, e.g. a forestry stand.

Accordingly, each row would be comprised of Accordingly, each row would be comprised of several columns, each column containing a several columns, each column containing a specific value for that geographic feature. specific value for that geographic feature.


There are many different designs of DBMSs, but in GIS the relational There are many different designs of DBMSs, but in GIS the relational design has been the most useful. In the relational design, data are design has been the most useful. In the relational design, data are stored conceptually as a collection of tables. Common fields in stored conceptually as a collection of tables. Common fields in different tables are used to link them together. This surprisingly different tables are used to link them together. This surprisingly simple design has been so widely used primarily because of its simple design has been so widely used primarily because of its flexibility and very wide deployment in applications both within and flexibility and very wide deployment in applications both within and without GIS without GIS


The relational DBMS is attractive because of its:The relational DBMS is attractive because of its: Simplicity in organization and data modelling. Simplicity in organization and data modelling. Flexibility - data can be manipulated in an ad hoc Flexibility - data can be manipulated in an ad hoc

manner by joining tables. manner by joining tables. Efficiency of storage - by the proper design of data Efficiency of storage - by the proper design of data

tables redundant data can be minimized; and the tables redundant data can be minimized; and the Non-procedural nature - queries on a relational Non-procedural nature - queries on a relational

database do not need to take into account the internal database do not need to take into account the internal organization of the data. organization of the data.


Object-Oriented ModelObject-Oriented Model

The object-oriented database model manages The object-oriented database model manages data through data through objectsobjects. .

An object is a collection of data elements and An object is a collection of data elements and operations that together are considered a single operations that together are considered a single entity. entity.

The object-oriented database is a relatively new The object-oriented database is a relatively new model. This approach has the attraction that model. This approach has the attraction that querying is very natural, as features can be querying is very natural, as features can be bundled together with attributes at the database bundled together with attributes at the database administrator's discretion. administrator's discretion.


To date, only a few GIS packages are promoting To date, only a few GIS packages are promoting the use of this attribute data model. the use of this attribute data model.

However, initial impressions indicate that this However, initial impressions indicate that this approach may hold many operational benefits approach may hold many operational benefits with respect to geographic data processing. with respect to geographic data processing.

Fulfilment of this promise with a commercial GIS Fulfilment of this promise with a commercial GIS product remains to be seen.product remains to be seen.


Georelational Data ModelGeorelational Data Model

Geographical referenced data:Geographical referenced data: Spatial and attribute (component)Spatial and attribute (component)

Georelational data model:Georelational data model: Stores spatial and attribute data separately Stores spatial and attribute data separately

but have a link in a split systembut have a link in a split system Called RELATIONAL DATA BASECalled RELATIONAL DATA BASE


Object-based Vector Data ModelObject-based Vector Data Model

Stores spatial and attribute data together in a Stores spatial and attribute data together in a systemsystem

Geometry data are stored along with their Geometry data are stored along with their attributesattributes

Its eliminates the use of split system and the Its eliminates the use of split system and the needs for data synchronizationneeds for data synchronization

Model treats spatial data as an objectModel treats spatial data as an object Object can represents spatial feature (road and Object can represents spatial feature (road and

lake), layer or the coordinate system on which lake), layer or the coordinate system on which the layer is basedthe layer is based


The Evolution/DevelopmentThe Evolution/Development

ESRI INC.ESRI INC. ArcINFO – coveragesArcINFO – coverages ArcVIEW – ShapefilesArcVIEW – Shapefiles ArcGIS – GeodatabaseArcGIS – Geodatabase

Georelational data model (ArcINFO and Georelational data model (ArcINFO and ArcVIEW)ArcVIEW)

Object-Based data model (ArcGIS)Object-Based data model (ArcGIS)


EXAMPLESEXAMPLES

4-Gis Data Models

Documents

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