Lecture 5 - Vector Data

Question 1

What is vector representation?

Answer 1

• complex rep based on primitive objects

- represents spatial location of features explicitly

Question 2

What are the different ways that vector data can be put together into a vector data model?

Answer 2

1. Spaghetti model
2. Vertex dictionary
3. Dual independent map encoding (DIME)
4. Arc/node topological model

Question 3

What is a TIN model?

Answer 3

A triangular irregular network is a vector model used to represent continuous surfaces

Question 4

Explain the spaghetti model

Answer 4

• simple (one point and polygon)
• easy to manage & understand
• no topology
• lots of duplication (large storage space needed
• data model is map expressed as a list of cartesian (x, y) coordinates)
• no inherent structure (messy like spaghetti)

Question 5

Explain what a point, line, and polygon would look like in spaghetti data model

Answer 5

Point: identifier and single x,y coordinate pair
Line: identifier and list of x,y coordinate pairs
Polygon: identifier and list of x,y coordinate pair identical to first pair (closed loop)

Question 6

What are the weaknesses of the spaghetti model?

Answer 6

• redundancy: common boundaries recorded twice
• no topological info (connectivity): no automatic error checking; spatial relationships must be derived by computation
• nested polygons: polygon order important for graphic display; area measures may be incorrect
• slivers/gaps: logical errors occur if boundaries are not listed the same

Question 7

Explain the vertex dictionary/ whole polygon model

Answer 7

• polygons described by listing coordinates of points in order as you “walk around” outside boundary of polygon
• vertices stored in one file while lines/polygons stored in another
• no duplication but model still does not use topology

Question 8

What are the weaknesses of the vertex dictionary model?

Answer 8

• coordinates/borders for adjacent polygons stored twice (can result in slivers/gaps)
• no topological info about polygons

Question 9

Explain the DIME model

Answer 9

• nodes (line intersections) are identified with codes
• assigns a direction code (a “from node” and a “to node”)
• street addresses and UTM coordinates explicitly defined for each link
• polygons described by listing ID numbers of points in order as you “walk around” outside boundary
• second file lists all points and their coordinates
• solves duplicate coordinate/border problem
• still no topological info

Question 10

Explain the Arc/Node topological model

Answer 10

• uses topology
• overcomes major weaknesses of spaghetti model (allowing for GIS analysis, like overlaying, network, etc.)
• requires all lines to be connected, polygons closed, and loose ends removed

Question 11

What is topology?

Answer 11

• relationships in spatial terms b/w connected or adjacent geographical objects
• connectivity: point-line relationship; line-line connection
• area definition: line-polygon relationship
• contiguity: polygon-polygon adjacency
• mathematical model used to define spatial relationships

Question 12

Why is topology important?

Answer 12

• connections/relationships b/w objects that are independent of their coordinates (geometry changes under transformations)

Question 13

Explain point, arc, vertices, node, and polygon in terms of vector primitives/features

Answer 13

• point: defined by single x,y pair
• arc: line defined by ordered set of x,y pairs (can be straight of curved)
• vertices: points on an arc that are not nodes
• node: end points of an arc, or intersection of two arcs
• polygon: area defined by arcs making up its boundary

Question 14

What are the advantages of the topological model?

Answer 14

• spatial analysis: performed without using coordinate data but using topological data alone (more efficient)
• data validation: ensures that associated data form a consistent and clean topological fabric (reduces data set size and additional items can be added to attribute tables)

Question 15

What are the disadvantages of the topological model?

Answer 15

• when data later is inputted or edited, the topology must be updated (can be time-consuming, but ArcGIS does for you)
• originally did not deal well with continuous surfaces (TIN model helps with)

Question 16

What are the stages of database creation?

Answer 16

1. Input of spatial data
2. Input of attribute data
3. Linking spatial and attribute data

Question 17

Explain what a digitizing table is

Answer 17

It is like a printer scanner (has electrodes) and control points with a mouse to trace to digitize paper maps

• automatic editing helps get rid of errors
• edge-matching process to combine several maps

Question 18

Describe attribute tables

Answer 18

• handled separately from spatial data (non-spatial)
• resides in database tables (rows for spatial entity and columns for variable)
• GIS provides linkage b/w spatial and non-spatial data
  (ex. location - what is there?)

Question 19

What is a DBSM

Answer 19

Database Management Systems

• computer programs that control creation, maintenance, and use of database in comp platform
• sits b/w data files and applications
• programs interact directly with data files

Question 20

What are the 3 types of database models?

Answer 20

1. Flat file/spreadsheet
2. Hierarchial
3. Relational

Question 21

What is an ideal database model?

Answer 21

• easy to access
• versatile (maximizes uniqueness of every feature)
• minimizing quantity of data

Question 22

Explain terminology meaning of data item and record

Answer 22

• data item (attribute): reps occurrence of particular characteristic pertaining to an entity (ex. person/thing/event); smallest unit of stored data
• record: group of related data items; occurrences of diff characteristics pertaining to same person/thing/event

Question 23

Explain the flat file database model

Answer 23

• simple method
• fast data retrieval
• data stored in single table (all records have same number of fields; individual records have diff data in each filed; one field serves as key to locate particular record)

Question 24

What are the problems with the flat file database model?

Answer 24

• cumbersome to search
• can only search by key field
• adding fields means reprogramming entire database
• adding new records time consuming
• slow data retrieval w/o key

Question 25

Explain the hierarchical file database model

Answer 25

- data stored in more than one type of record - like a family tree (parent-child/ one-to-many) relationship - one field is key to all records, but data in one record does not have to be repeated in another (records with similar attributes associated together) - records linked to each other by a key field

Question 26

What are the advantages of the hierarchical file database model?

Answer 26

- relationship clearly defined and queries follow standard routine - efficient data structure (access to diff records readily available) - adding/deleting records easy

Question 27

What are the disadvantages of the hierarchical file database model?

Answer 27

- uni-directional: must access master record in order to link downward to access other records - repetitive data - large amount of storage

Question 28

Explain the relational file database model

Answer 28

- data files organized as tables (matrices of tables used to store info) - connect diff files without using internal pointers/keys - common link of data is used to join/associate records (not hierarchical) - enables user to form new inquiries and data outputs - simple data organization into set of relations or tables

Question 29

Explain relational model terminology: tuple, attribute/item, domain, relation, cardinality, degree, key

Answer 29

- tuple: row - attribute/item: column - domain: range of possible values defined for each attribute - relation: entire table - cardinality: uniqueness; number of tuples it contains at any point in time - degree of relation: number of attributes in table - key of relation: subset of attributes which uniquely identify each tuple in the relation (ex. ID number)

Question 30

What is a relational join?

Answer 30

- operation of relating/physically merging 2 attribute tables using common column - required to do relational query (ex. what are taxes on property x? links property id with tax rates)

Question 31

What are the advantages of the relational file database model?

Answer 31

- flexibility: data can be manipulated by joining tables - simplicity: organization and modelling - efficiency of storage: redundant data minimized - non-procedural nature: queries do not need to take into account internal data organization - easy to use

Question 32

What are the disadvantages of the hierarchical file database model?

Answer 32

- new relations require considerable processing - sequential access slow - easy to make logical mistakes due to flexibility

Question 33

What are the advantages of the vector data structure?

Answer 33

- good for transportation, utilities, marketing (many purposes - provides precise positioning of features in space - intuitive representation - good rep of entity data models - compact data structure - topology explicitly described - coordinate transformation easy - accurate graphic rep at all scales

Question 34

What are the disadvantages of the vector data structure?

Answer 34

- complex data structures - some analytical functions are complex/difficult - display and plotting time consuming and expensive - spatial analysis within units like polygons impossible b/c internally homogenous