Advanced GIS GEOG 475 – Flashcards

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Object Relational DBMS

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OR-DMBS

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relational databases that incorporate ADTs and other principles of the object oriented design
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SDBMS

 

Spatial Database Management System

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  • a software module that can work with an underlying DBMS
  • SDBMS support multiple spatial data models, commensurate spatial abstract data types, and a query language from which these ADTs are callable
  • SDBMS support spatial indexing, efficient algorithms for spatial operations and domain specific rules for query optimization
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Topology
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branch of mathematics exclusively devoted to the study of relationships which do not change due to elastic deformation of underlying space
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Space taxonomy
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refers to the many descriptions that are available to organize space
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Data Model
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a rule or set of rules to identify and represent objects referenced by space
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Object vs. Field Model
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  • object model is conceptual, it is mapped onto the computer using the vector data structure. a vector data structure maps regions into polygons, lines into polylines, and points to points
  • Raster data structure implements the filed data model on a computer
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Query Language
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current functionality of relational query language and has to be extended to handle spatial data
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Query Processing
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the sequence of steps that DBMS will initiate to processs the query
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Query Optimization
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very efficiently executes queries
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Data Mining
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systematic search for potentially useful info embedded in digital data
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Set Oriented
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union, intersection, containment, and membership
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topological
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meet is an example of a topological property; area is not

 

 

find all objects that have topological relation r to a given object

 

What is the topological relation between A and B

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Entities
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are things or objects that have an independent physical or conceptual existence
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key
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an attribute or set of attributes that uniquely identifies instances of an entity
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Relationships
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the way Entities interact or connect with each other
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One to One Relationship
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each instance of one entity can relate to only one instance of the other participating entity.
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Many to One Relationship
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can potentially connect many instances of one entity with one instance of the other entity participating in the relationship
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Many to Many Relationships
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many instances of one entity can be related to many instances of the other participating entity
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Entities are

 

Attributes are

 

Relationships are

 

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represented as boxes

 

as ovals connected to boxes

 

as diamond boxes

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domains
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datatypes of the attributes
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Key constraint
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speciefies that every relation must have a primary key.
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primary key
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one that is used to identify many tuples in a relation
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entity integrity constraint
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no primary key can be null
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Referential integrity constraint
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enforcement of such constraint maintains logically consistent relationships between the different relations
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pictogram
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miniature representation of an object inserted inside of a box.
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shape
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basic graphical element in a pictogram, which represents the elements in the in the spatial data model
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Basic Shape
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point, line, polygon
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Multishape
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elements that cannot be defined by one of the basic shapes.

 

Cardinality is used to quantify multiple shapes

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Relationship Pictogram
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used to model relationships between entities
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adjacent
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function may be applied to land parcels to determine if they share a common boundary
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Row Type
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a type for a relation, it specifies the schema of a relation
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Relational Algebra
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formal query language associated with the relational model. It is rarely if ever implemented in a commercial system but forms the core of SQL.
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SQL
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most widely implemented query language, a declarative language in that the user only has to speccify the result of the query rather than means of arriving at the results. It extends relational algebra with many other important functions, including aggregate functions to analytically process queried data
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OGIS
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standard recommends a set of spatial datatypes and functions that are considered crucial for spatial data querying
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ANSI SQL with 

 

 

JET SQL with

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shared geodatabase data

 

 

personal geodatabase data

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How a Geodatabase extends a database
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  • represents discrete objects as vector features, continuous phenomena as rasters, surfaces as TINs, and references to places as locators and addresses
  • stores shapes of features and ArcInfo provides functions for performing spatial operations such as finding objects nearby, touching, or intersecting
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Reasons to use ArcSDE
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  • limitless flexibility in scaling databases
  • utilize the relational database of your choice
  • can serve geographic data from UNIX or Windows
  • can build OGC
  • can build SQL
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Submarkets
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areas within the larger market that "stand out", or can be characterized in a significant manner
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Urban Form
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pattern of land use and land values
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urban morphology
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study of urban form over time
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Market Forces
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transportation, spatial equillibrium, government, real estate cycles, information and technology
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geodemographics
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descriptive characteristics of a population, arranged and ordered by a scale of geography that is meaningful to the analysis
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Brian J. L. Berry (1960s)
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first commercially available Lifestyle segmentation profile ( LSP)
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Spatial Equilibrium
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no incentive to move to or from a location; balance of push and pull factors
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Opportunity
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when urban area and submarkets are not in spatial equilibrium
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Steps in Real Estate Market Analysis
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  1. establish trade area size and boundary
  2. estimate competing supply
  3. measure demand
  4. compile report and present the analysis
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Trade area
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geographic region from which a real estate project draws most of its customers
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William Applebaum
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1930s geographer

 

uses analog and customer spotting methods

 

factors for evaluating store sites and how location quality affects store rents

 

enables consideration of unserved trade areas and overlapping trade areas

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range
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distance customers will travel to patronize a store
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Distance decay
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how density of customers decreases with increasing distance from real estate project
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Primary Trade Area
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geographic core, accounts for majority of business
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secondary Trade Area
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next highest percentage of customers
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tertiary trade area
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at market-are fringe accounts for less than 15% of all customers
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Economies of agglomeration
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benefits that firms obtain when locating near one another. Think of two ice cream shops located on the beach, sharing best profits when located right next to each other.
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Analog Method
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Applebaum- first systematic retail forecasting system based on empirical data

 

performances can be measured by market share and per capita sales penetration

 

Many explanatory variables can be included in assessment

 

Potential development sites can be compared and ranked according to expected performance

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Geographically delineating trade areas
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Radial Distance approach - rings, convenient but not accurate

 

Drive-time approach - transportation network strongly influences customer travel behavior

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W. J. Reilly
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used Newton's gravity model to compute market surrounding shopping center (economic geography application in real estate analysis and marketing)
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Tij = PiPj / dij

 

 

Gravity Model Relationship

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Tij - total interaction between places i and j

 

P- population count for place i

 

Pj - population count for place j

 

dij - distance seperating places i and j

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Reilly Model
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  • allows us to draw trade area boundaries around cities using the distance between the cities and the population of each city

 

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Kernel method
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  • mapping customer density and identifying market boundaries
  • based on location customer areas to determine trade area, rather than physical store location and characteristics
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NEWMAP = f(oldmap)
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the new map is a function of the old map, implies a transformation, has the same geometric properties as the old map.
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object
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representation of reality
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feature
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an entity being represented by an object
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CLEAN
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uses a fuzzy tolerance when processing, which allows it to detect and create intersections
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Build
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does not use fuzzy tolerance, the coordinates will not be adjusted while topology is being built
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Levels at which databases can be described
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Logical Level

 

Conceptual Level

 

Research Area

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Logical Level
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level at which users view the database
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Conceptual level
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concerned with info design (e.g. where data are stored across a network other design issues etc.)
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Research Area
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Middleware that connects individual databases to other applications programs and reconciles the different terms use d among the various databases
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Disk Drives
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rated by seek and read times
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Arc Spatial database Engine
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relational model based on tables

 

ex. oracle, informix, IBMD32, Microsoft Access

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Entity
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like an object or a thing
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Entity Set
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like a class = set of similar entities 

 

represented by a rectangle

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Attributes
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properties of entities in an entity set

 

 

represented by an oval

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Relationships
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connect two or more entity sets

 

 

represented in the table

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Focal
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up to n-1 gridcells

 

N = number of cells in a grid

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High Pass Filter
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edge detector
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Low Pass Filter
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Smoothing 7x7 = more smoothing
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Optimal complexity
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complex enough to adequately represent the phenomena but not complex enough
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Overlay Cover
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  • Put one layer on top of second
  • new values are the non-zero top layer values and the bottom layer values where the top is zero
  • top layer - not zero - opaque
  • bottom layer - zero - transparent

 

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Local Combination
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determines every possible combination of values and assigns a sequential new class to each combination. Each combination gets its own value
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Capability/Suitability Mapping
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determining the land units that are capable of supporting an activity or land units that are most suitable of supporting an activity. This process may involve determining the degree of capability/suitability
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Capability
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physical potential of land unit to support activity
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suitability
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social or economic potential of land unit to support an activity
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Factor
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category of info that will be used to define limiting criteria

- annual, precip, costs of land, population

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Constraint
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threshold value that must be met for acceptability
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Rating
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Value depicting the relative suitability of a parcel with characteristics for factors
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Rating Schedule
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table of ratings for the different characteristics of a factor
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Factor Constraint
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constraint value for a factor
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Factor Rating
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rating for a factor
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score
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numerical, suitability, capability value that represents the (higher value represents more suitable/capable)
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Trade Off
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A low rating for one factor may be compensated by a high value of another factor
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Pass Fail Screening
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based on constraint establishing acceptability of the unit for a given factor

 

Advantageous because it is simple and easy to understand and technique is mandatory for planning applications

 

disadvantageous because all factors are treated as equally important

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Ordinal Combination
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graduated screening

 

addition of factors

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Steps for Suitability/Capability Modeling
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  1. Determine Factors important for evaluating places
  2. Collect Accurate Data representing factors
  3. select appropriate suitability/capability technique and implement
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Selection of Weights
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  1. Management Applications
  2. Physical process models (parameters)

Real world observations

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key
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set of attributes whose values can belong to at most one entity
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WEak entity set
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sometimes a key for an entity set comes incomplete from its own attributes but from the keys of one or more entity sets to whch it is linked by a relationship
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Table
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relation
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column headers
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attributes
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rows
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tuples
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beers
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name/manf
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Relation schema
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equivalent of attributes + other structural info such as keys

 

order of attributes is arbitrary

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Relation Instance
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current set of rows for a relation schema
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database schema
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collection of relation schema
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Selection
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picking rows (tuples) from a relation
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projection
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picking columns from a table (relation)
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products and joins
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for composing different relations here, relation schemas do not have to be the same
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renaming
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renames relationships and their attributes.
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Aside Normalization
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how to fix relations that are in violation of BCNF 

 

split relation into 2 or more smaller relations

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Argument
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variables and constraints for representing relations
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expressions
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applying operators to arguments, plus parenthesis
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