1. Lecture 4, Wednesday 27th August 2014
DEPARTMENT OF GEOGRAPHY AND ENVIRONMENT
UNIVERSITY OF DHAKA
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6. Most popular DBMS model for GIS
Based on a set of mathematical principals called relational algebra
More of a concept than a data structure
Internal architecture varies substantially from one RDBMS to another
Link the complex spatial relationships between objects
Type of relation:
1.One to one
2.One to many
3.Many to many
4.Many to one
9. Advantage
1.There is no data redundancy
- type of building of an owner can be changed without destroying the relation between type and rate
- a new type of building can be inserted such as “clay”
2. The most flexible data model
Disadvantage
1. Most RDBMS data manipulation languages require the user to know the contents of relations
10. In this concept, each individual piece of data can be linked directly anywhere in the database
This is developed in mid 1960s as part of work of CODASYL which proposed programming language COBOL (1966) and then network model (1971)
Example:
A hospital database has three record types:
-Patient: name, date of admission etc.
-doctor: name etc.
-ward: number of beds, name of staff nurse etc.
•We need to link patients to doctor, also to ward
•Doctor record can own many patient records
•Patient record can be owned by both doctor and ward records
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12. Advantage
1.Can handle many to many relations
2.Much greater flexibility of search
3.Reduce redundancy of data
Disadvantage
1.Links between records of the same type are not allowed
2.While a record can be owned by several record of different types, it cannot be owned by more than one record of the same type (patient can have only one doctor, only one word)
3.Need more storage in the computer
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14. A set of record “types”
- e.g. supplier record type, department record type, part record type
A set of links connecting all record types in one data structure diagram “tree”
At most one link between two record types, hence links need not be named
- e.g. every county has exactly one state, every part has exactly one department
No connections between occurrences of the same record type
- cannot go between records at the same level unless they share the same parent
In geographic database, quadtree can be an example of hierarchical data model
15. Advantage
1.High speed of access to large datasets and eases of updating
2.The model is based on one to one and many to one relationships
Disadvantage
1.Linkages are only possible vertically but not horizontally or diagonally, that means there is no relation between different trees at the same level unless they share the same parent
1.Restricted to branch to network itself such as many to many relationship
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17. Uses functions to model spatial and non-spatial relationships of geographic objects and the attributes
An object is an encapsulated unit which is characterized by attributes, a set of orientations and rules
Includes four basic elements:
1.Object oriented user interfac
2.Object oriented programming languages
3.Object oriented analysis and design methodologies
4.Object oriented database management
18. Generic properties: there should be an inheritance relationship
Abstraction: objects, classes and super classes are to be generated by classification, generalization, association and aggregation
Adhoc queries: user can order spatial operations to obtain spatial relationships of geographic objects using a special language
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20. Refers to the fitness for use of data for intended application
Qualitative criteria for high quality data:
1.Data must be accurate and reliable
2.Current and up to date
3.Complete and precise
4.Concise and intelligible
5.Conventionally handled (maintained, transmitted, distributed, classified, resampled, retrieved and updated)
Other factors:
a.Must be projected to the real world
b.Must be captured at a scale using a classification scheme
c.Cartographic properties
d.Transfer format
21. Accuracy
Degree to which data agree with the values or descriptions of the real-world features that they represent.
Measure of how “close” data match the true values or descriptions.
Accuracy is related to cost of data acquisition.
22. Data accuracy is often grouped into three forms:
1. thematic accuracy
2. positional accuracy
3. temporal accuracy
23. How “exact” data are measured and stored
In mathematics, the exactness of representation is the number of significant digits used to record data. But for digital geographic data, this is the number of “bits” and the form (long integer; floating point etc.) used for data capture and storage.
24. Comparison of the precision of storing data by the three storage formats in PC
Format
Bits of storage
Significant digits of precision
True floating point decimals
Long integer
16
9
No
Single precision floating point
32
7
Yes
Double precision floating point
64
13
Yes
25. The deviation between two values-
1. measured value
2. value of the real world feature
Three types of error that may occure in measurement and observation:
1. gross error: blunders and mistakes
2. systematic error
3. random error: (normal distribution and least square adjustment)
27. Can be divided into three basic groups:
1. Original source maps
- Map projection
- Map scale
- Cartographic generalisations
- Cartographic revision
- Feature classification/ coding
- Field survey measurements
- Photogrammetric measurements
- Image analysis
- Sampling design
- Aging maps
28. 2. Data automation and compilation
- digitizing
- attribute data inpute
- format translation
- map projection transformation
- vectorization of raster data
29. 3. data processing and analysis
- numerical rounding in computing
- Overlay analysis
- Classification and re-classification
- Generalization and aggregation
- Interpolation
- Inappropriate use of algorithm
On top of the above, Vitek et al. (1984) grouped them into two categories:
1.Inherent errors
2.operational errors
30. Components of spatial data quality
Lineage of spatial data
Positional accuracy
Attribute accuracy
Error matrix/ confusion matrix
Kappa coefficient
Temporal accuracy
Semantic accuracy
