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77 Cards in this Set
- Front
- Back
what makes spatial data special |
spatial data has... Location Multidimensionality Scale dependency to be sampled Spatial / temporal autocorrelation Uncertainty Special analysis methods Great volume Many origins high expense and maintenance |
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RDBMS |
Relational Database Management |
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Define Object Class |
A table ina geodatabase for keeping attribute data that relate to spatial features. Can be associated with behaviour. |
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what advantages does the geodatabase offeR? |
Custom features, multiuser editing, enhanced topoloy and validation attribute validation (domains, subypes) scalable storage solutions relationships |
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UML |
Unified Modelling Language |
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DBMS |
Database Management Systems |
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DBMS capabilities |
1 Data definition Language (DDL) 2 Data manipulation and query lanuage 3 Data model that supports: standard types, specialized data types 4 Must support multiple views of data 5 Security 6 Concurrency control 7 Database administration tools (DBA) DB design tools Programmable API |
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Importance of GIS data, what does it determine |
Data is the foundation of a GIS installatino It determines: What you can analyse Where your analysis focuses Types of analysis Quality of your analysis |
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Why is spatial info so special |
It includes a locational dimension to its description of real world things. Spatial data can be: multidimensional (link time, place, attributes) voluminous expensive and time consuming to update compiled from multiple sources requrie special analysis methods Scale dependent Sampled data spatial autocorrelation temporal autocorrelation uncertain |
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what are the 3 components of spatial uncertainty |
Error: the unkonwn uncertainty due to systematic & human lmiitations Randomness: some things can never be modelled directly like tiny variations in the surface Vagueness: uncertianty associated with a spatial or attribute concept. |
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Sources of positional error |
Map projection, datum, parameters... Improper representation of objects Primary measurements eg Surveying methods Secondary data acquisition errors: instrument related, media related, human operator. like a scanner or something. |
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What is a shapefile |
a vector data storage format for location, shape, attributes of features |
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Components of a geodatabase |
Feature = spatial entity (vector, raster,TIN) Object = nonspatial entity (ie table) Feature Class = collectiopn of single geometric type of features. |
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Define Feature Dataset |
A feature dataset is a collection of related feature classes that share a common coordinate system. Feature datasets are used to spatially or thematically integrate related feature classes |
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intelligent features: Attribute Domains |
rules that give allowable values for a field type. Can be coded values eg Class 1 Class 2 Class3 or a range of values 0-500m |
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Intelligent FeaureS: Validation Rules |
Validation rules verify that the data a user enters in a record meets the standards you specify before the user can save the record Maintain integrity of feaures and attribues Are subtypes of feature/object attributes. |
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what can subtypes introduce.. |
simple behaviour, |
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Intelligent features: Relationship Classes |
An association between 2 object classes or 2 feature classes. Object class - define th cardinality between tables eg M:1, 1:M Feature Class - eg; a pole can have 0, 1, or 2 transformers.other values are not permitted. |
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what is an object class
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A table in a geodatabase to keep descriptive data that relate to spatial features. Can be associated with a behaviour eg: Object class of landowners is joined with a polygon feature class of parcels. |
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What is a relationship class? |
A table that stores relationships between 2 features in feature classes, or two objects in 2 tables. eg: how a feature changes when its related object changes |
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what does ArSDE stand for |
Arc Spatial Database Engine |
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Comparions of geodatabase file vs ArcSDE |
file: single user project based 1TB limit Separate dataset files ArcSDE: Scalable client/server architecture Multiuser access and editing No limit to size Data centralised to help admin, user access, backup etc.. |
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Advantages of a geodatabase |
Multiple editing Enhanced topology and validation Attribute validation (domains, subtypes) Scalable storage solutions Relationships Custom featues |
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What does coverage topology rely on? |
Planar enforcement concept. eg various types of soil polygons cannot overlap |
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What topology figures connectivity, contiguity, and area definition |
Arcnode & polygon arc topology |
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ArcNode topology rules. what do these rules enable? |
1. Arcs start with a Fromnode and end with a Tonode 2. Arcs have a direction (based on from/to nodes 3. Connecting arcs share a common node. these rules allow paths to be determined through a netowrk of connected arcs. Can ensure polygon features are closd. |
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Polygon-Arc topology rules |
1. Polygons stored as a list of arcs (polylines) that make the boundary. 2. Polygons have a single label point that links to an attribute table. 3. Based on Ac direction, left/right polygons are identified |
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Topology in a geodatabase is set from how many inegrity rules? |
32. |
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What does a user specify, wtihin a a given Feature Data Set for rulebased topology |
How many topology objects are created The rules used in each topology Feature classes the rules are applied to Cluster tolerances Rankings of feature classes Permissible exceptions to topology rules. |
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Types of edge and junction connections (4) |
Simple edge - connecito to 2 junctions a ach end Complex edge- connection to 2 junctions at each end wtih more juncitons in beween User defined junction - defined from users feature data source Orphan junction - created when edges are created. |
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Dijkstra's Algorithm, how does it work? |
1: Every node set a tentative distance value. Initial node = 0, every other node = infinit 2: Keeps two sets of nodes: visited & unvisited 3: For the current node, the distance to each neighbouring node is calculated plus the distance to the current node. 4: If this distance value is les than their tentative value (which begins at infinite), then replace. 5: When all neighbours checked, mark current node as visited, and remove from unvisited. 6: Set the unvisited node with the smallest tentative distance as the next current node. 7: Repeat from 3. Finished if the destination node has been marked visited. |
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What is point attern analysis concerned with? |
The location of events, want to know about the distribution of these points |
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what is the distribution of point features described by? |
Frequency / density geometric centre Spatial dispersion Spatial arrangement - autocorrelation, clustering |
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Frequency / Density determined how? |
Geometric centre and dispersion. Geometric centre - mean of X and Y. dispersion = standard deviation. A mean with large standard deviation is not a reliable indicator of the distribution o centre |
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What are the three basic types of point patterns (Spatial Arrangement) |
Clustered Scattered Random |
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how does Nearest Neighbour Index measure dispersion |
measures dispersion based on minimum interfeature distance. The average distance between points in a clustered pattern is most likely less than in a scattered pattern. |
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what does spatial autocorelatino measure? |
measures the extent to which the occurence of one feature is influenced by the distribution of similar features nearby. |
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what does a positive autocorrelation indicate? |
Occurs if the existence of one feature attracts similar features to its neighbourhood. |
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Types of cluster detection? |
Hierarchical: start with all patters as single cluster. Splitting and merging until threshold met. results in ree or dendogram. Partitional: eg kmeans or kmedoid result in spherical cluster. Gridbased and density based types |
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Define Object |
object is a structure that represents a single entity. Describes its information content (attribute/properties = its state) and its behaviour. |
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Define classes: |
every object belongs to a class. defines a structure and set of operations that are common to a group of objects. |
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what is an individual object of a given class called? |
an instance |
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Object = |
State + Behaviour |
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UML |
Unifid Modelling Language |
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Advantages of UML |
UML is a graphical modelling language Supports object oriented design Standard, widely used |
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OOGIS contains: |
Graphical characeristics Geographic location all other associated data |
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Two othe properties of object orientation |
Encapsulation: ability of an object to hide its internal structure ensures data independence Inheritance: Object classes defined hierarchically Generall classes define the structure of generic objects, then specialised by creating subclasses. Subclasses get all parent properties/methods and may add their own. |
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Ina relational data model, how do you deal with missing information? |
NULL marker for missing info. this is best to avoid. why? Because things then cant be meaningfully compared, theres issues wiht logical comparisons, why have an attribute if it can be missing??? |
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What is a tuple? |
A colleciton of zero or more associated attributes |
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What is a relation? |
A collecitn of structurally identical tuples |
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What is the structural bassis of a realational data model? |
Tuple Relation Attributes |
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Identifying factors of relations |
Look like tables Tuples ina relation are unique Attributes are single valued Relations are not ordered |
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What is Degree, in reference to relational data models |
the number of attributes |
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What is Cardinality, when part of a relationaldatamodel? |
the number of tuples |
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Properties of Primary Keys. (PKs) |
Only one per relation Comprise of one or more attributes (composite vs not) No nulls - no missing vlaues No unnecessary attributes (if you have IRD, not much point having IRD + name) Stable - not change over time May be generated (surrogate) |
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Primary Key examples |
Property - valuation number Vehicel, registration Student, student ID |
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Properties of Foreign Keys |
zero or more per relation comprise one or more attributes must reference a OK in another relation, or must be completely missing May or may not be unique. Often change over time. (as papers change as customers change) Can overlap with other FKs and PKs |
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Foreig Key examples? |
Employee: department ocde, manager ID Customer: salesrep ID Lecture: paper code, room code |
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What is data integrity? |
Ensure consistanc of data. data values must: make sense, satisfy all specified business rules, avoid unnecessary double ups |
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Basic operations of relational data? |
Projeciton REstriction Join Set union: intersection, difference |
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What does the Projection operation of rational data do? |
extracts some subset of the attributes of a relation. duplicate tuples are automatically deleted. |
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What does the Restriction operation of rational data do? |
extract some specified subset of the typles of a relation |
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What does the Join operation of rational data do? |
combins associated tuples fom different relations |
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What does the Set operation of rational data do? |
combine tuples from two instances of the same relation |
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What does the Union operation of rational data do? |
tuples that appear in either one relation or the other |
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What does the Intersection set operation of rational data do? |
tuples that appear in both relations at once |
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What does the difference set operation of rational data do? |
tuples that appear in one relation bt not the other |
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Quick summary of relational model. |
Is predominant abstract model for attribute data. Robust, flexible, theoretically sound. Strong data integrity protection. Basis for all modern database management systems. |
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What is a DBMS |
Database Management System is a computer system that allows users to access a database without knowledge of how data are studied physically. |
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Capabilities of DBMS |
1. Data Definition Language: Used to dfine and describe the contents of the database. Provides a useraccessible data dictionary 2. Data manipulation and query language: The syntax (language) used to for commands for input, edit, analysis, output, reformatting etc. Semi standardized eg SQL 3. Data model that supports: Standardized types: integers, real, character, date May include specialised data. 4. Most support ultiple views of data. Users should only see the data they need. 5. security 6. Concurreny control Manage multi user access to data and contorl updates 7. Database administration tools. to set the database structure 8. DB design tools 9. Programmable API allows direct access to the database form other applications |
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What is a data model? |
A DATA MODEL REPRESENTS ALL ENTITIES AND RELATIONSHIPS OF INTEREST TO A USER GROUP |
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What are some formal modelling techniques? |
Data dictionaries:
a for of metadata that lists the data sets in a system. Data flow Diagrams (DFDs): describe flows of data within systems Entity-Releationship Diagrams ERDs: Define relationships between database objects. Unified MOdellingLanguage UML: graphical and object oriented database modelling. Data flow diagrams: provide topdown definition of logical data processes and data flows ina asystem. emphasize links between data organisation and processes which create, modify, or use data stores. Entity Rleationship diagrams ERDs define entities, attributes, and the relationships between entities. this is in comparison to; DFDs which focus on processes that create,modify or delete data. |
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How to avoid N:M relationships? |
can transform an N:M relationship into a 1:M by creating an associate entity. |
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What is the importance of database design? |
Proper database design avoids: storing ireelevent data or omitting required data. inability ot extend the desing bad representation of entities lack of integration with other databases/applicatinos lack of consistency 'lock in' to a particular format |
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SQL Joins do what? |
allow tables to be related together ina temporary view based on common field values. |
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Two basic approaches of volume preserving areal inteprolation? |
Overlay Pycnophylactic |
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What does toblers approach assume? |
a smooth density funciton, takes into account the effect of adjacent source zones. It forces local areas to deviate only a litte |