Lecture 2 - Data Models for GIS

I. Introduction

II. Data models

III. Data Management System

IV. Data Models for Spatial Data

I. Introduction

1. Positions: referencing of an entity to a coordinate system (i.e. UTM, state plane ... etc).
   
2. Data description:
1. data as entities: geographic data often described in phenomenological concepts such as roads, towns, rives floodplains, eoctypes, soil associations, ... etc. These concepts are often referred to as entities.
2. entity hierarchy: Data is often hierarchical in form (i.e. country > state > county > village; forest > deciduous/coniferous > upland/lowland)
3. gradients between entities: separations between some entities are not always clear cut and there may be a transitional zone between entities (ecotones).
4. Geographic data can be represented using three basic topological concepts, the point, the line and the area. Every geographical phenomena can in principle be represented by these three concepts plus a label or attribute that defines it.
5. What is a map? "A map is a set of points, lines and areas that are defined by their spatial location with respect to a coordinate system and by their non-spatial attributes" (Burrough 1986). A map legend links the non-spatial attributes to the spatial attributes.
3. Data concepts:
1. a record is a data structure containing information about an entity that can be manipulated as a unit.
2. a pointer is a memory address that references the start of data in the RAM
4. Structuring data
1. simple lists: unstructured data, each item is placed at the end of a list, search time (n + 1)/2.
2. ordered sequential files: additions placed in proper position (insertion). Binary search is possible reducing search time log2(n+1). Item found in set of 65,535 + 1 items in 16 tries.
3. indexed files:

1. direct: Rapid data retrieval according to key attribute (i.e. dictionary spelling. Key attribute + additional information). In direct files the data items themselves provides means of ordering (soil series name with index to location of each name beginning with a particular letter)
2. indirect: May have ordered soil profiles but may want info on soil depth, drainage, ph, texture or erosion. If the poorly drained soils need to be identified we must use a linear search unless we invert the file. Inverted files are initially ordered using a linear search. An example of an inverted file is a topic index in a book.

1. limitations of simple structures: file modification is difficult, a new record is added to the end of a file, then the index is updated. Data can be accessed only via a key contained in the indexed file, while other types of information requires a sequential search

These data structures provide very efficient access to information pertaining to a single entity. But we need more. We need to relate different entities.

II. Data Models (Laurini and Thompson, 1992 and ANSI/X3/SPARC, 1978)

As data management became more complex a framework was need to understand the transformation of real world systems and processes into structures that could be implemented in a computer.

1. External model: provide the basis for understanding the real world (e.g. non-spatial: a set entities; spatial: the world as a constantly varying surface; the world as a discrete set of objects in space or as a set of thematic layers)

III. Data Base Management Systems (DBMS)

1- Definition: Data Base Management Systems: A system used to organize, access, maintain and manipulate object or entity data. A DBMS controls input, output, storage and retrieval of entity data. Essential features of a data base are fast access and cross referencing of entities.

2- Requirements for a DBMS

A DBMS should provide:

1. Data Independence: the data base can change with little or no impact on the user programs
2. Data Sharing: must have coordinated simultaneous access. Concurrency control mechanism.
3. Maintenance of Data Integrity: DBMS helps enforce certain consistency constraints (i.e. coordinate has both lat and long, # of seats sold on an airplane <= # seats on plane)
4. Security: DBMS provides mechanism for security/authorization from disclosure/destruction of data.
5. Centrality of Control: DB administrator to resolve conflicts and meet user requirements
6. Reduce Application Development Time

3- E-R data model: a conceptual data model in which information is represented by entities and relationships between entities

4- Terminology

a. entity - a distinguishable object in the real world (people, forest stand, watershed, ...etc.)
b. relationship - a correspondence or association between two or more entities.
c. attributes - the properties which describe an entity.
d. functionality - how many entities from one entity set can be associated with another set
e. primary key - main key for entity identification, one record per indexed attribute.
f. secondary key - may have multiple record occurrences per index attribute.

5- Hierarchical data model - one to many relationship.

6- Network data model - many to many relationships.

7- Relational data model: data stored as records known as tuples grouped together in two-dimensional tables known as relations. Whereas hierarchical structures rely on the hierarchy and networks depend on pointers to associate entities, the relational model uses data redundancy in the form of unique keys that identify records in each file. Simplifies data maintenance because data for an entity type is stored in simple tables. Relational joins are used to cross reference entities using a primary key in one table and a foreign key in another table. Thus, in order to perform relational joins there needs to be at least one column in common between tables being related.

 

The relational model is design to reduce redundancy of data whenever possible. A set of rules called the normal forms were developed by Codd (1970) to guide this process.

8- Integration of DBMS with the spatial data models

IV. Data Models for Spatial Data

Data structures are complex for GIS because they must include information pertaining to entities with respect to: position, topological relationships, and attribute information. It is the topologic and spatial aspects of GIS that distinguish it from other types of data bases.

1.  Introduction: There are presently three types of representations for geographic data: raster vector, and objects.

2.  Raster Data model

Definition: realization of the external model which sees the world as a continuously varying surface (field) through the use of 2-D Cartesian arrays forming sets of thematic layers. Space is discretized into a set of connected two dimensional units called a tessellation.

+ reduced storage.
+ variable resolution.
+ overlay of variable resolution data.
+ fast search.

Morton Sequencing

Morton Sequencing Overlay

Morton Homework

3.  Vector data model

Definition: realization of the discrete model of real world using structures for storing and relating points, lines and polygons in sets of thematic layers.

a. Introduction

1. represents an entity as exact as possible.
2. coordinate space continuous (not quantized like raster).
3. Structured as a set of thematic layers

1. Point entities: geographic entities that are positioned by a single x,y coordinate. (historic site, wells, rare flora. The data record consists for x,y - attribute.
2. Line Entity: (rivers, roads, rail)

1. all linear feature are made up of line segments.
2. a simple line 2 (x,y) coordinates.
3. an arc or chain or string is a set of n (x,y) coordinate pairs that describe a continuous line. The shorter the line segments the closer the chain will approximate a continuous curve. Data record n(x,y).
4. a line network gives information about connectivity between line segments in the form of pointers or relations contained in the data structure. Often build into nodes pointers to define connections and angles indicating orientation of connections (fully defines topology).

    3.  Area Entity: data structures for storing regions. Data types, land cover, soils, geology, land tenure, census tract, etc.

1. Cartographic spaghetti or "connect the dots". Early development in automated cartography, a substitute for mechanical drawing. Numerical storage, spatial structure evident only after plotting, not in file.
2. Location list

• describe each entity by specifying coordinates around its perimeter.
• shared lines between polygons.
• polygon sliver problems.
• no topology (neighbor and island problems).
• error checking a problem.

   c.  Point dictionary

• unique points for entire file, no sharing of lines as in location lists (eliminate sliver problem) but still has other problems.
• expensive searches to construct polygons.

   d.  Dime Files (Dual Independent Mapping and Encoding)

• designed to represent points lines and areas that form a city though a complete representation of network of streets and other linear features.
• allowed for topologically based verification.
• no systems of directories linking segments together (maintenance problem).

• same topological principles as the DIME system.
• DIME defined by line segments, chains based on records of uncrossed boundary lines (curved roads a problem for DIME).
• chains or boundaries serve the topological function of connecting two end points called a node and separating two zones.
• points between zones cartographically not topologically required (generalization possible).
• solves problems discussed above (neighbor, dead ends, weird polygons).
• can treat data input and structure independently.

Definition: realization of the discrete model of real world using an object centered approach in which an object has both physical (attribute) and geometric characteristics. Different types of objects can interact because they are not confined to separate layers.

The biggest single difference between the object-oriented conceptual model and the vector-layered based conceptual model, for representing geographic information, is that in the object model, the real world object is the basis for abstraction, not its geometry. In other words, the objects not the geometric components of layers are the "units" for modeling and interactions