In this lecture we'll consider how space is conceptualized (e.g., fields and objects or entities) and how those concepts are implemented as GIS data models (and the advantages and disadvantages of the two fundamental models of space--grids or rasters and vectors); basically, how is geography represented in a GISystem? You text covers this material in Chapter 3 (Representing geography), where the discussion is centred around the conceptualization of space (although note that it does cover topics such as generalization which we covered in the lecture on cartography) and in Chapter 8 (Geographic data modeling), where the discussion is centred around the implementation of models of space in a computer. You could say that Chapter 3 is presented more from the GIScience perspective while Chapter 8 is presented more from the GISystems perspective.

It is important to recognize that your conceptual view of the world should be independent of the programmatic view of the world (that is, how we conceptualize things should not be constrained a priori by how things are represented in the computer).

ESRI has published a number of podcasts that describe, in detail, many of the different features available in ArcMap as well as providing demonstrations on how to, for example, produce high quality maps. The listing of podcasts is available here; a podcast that discusses network analyst can be found here.

The NCGIA has several notes which cover the concepts of grids (as rasters are sometimes referred to) and vectors in some detail. If you wish to delve deeply into these concepts, the following notes cover the two fundamental spatial data types in detail:

Learning objectives

• Understand the concepts of fields and objects and their fundamental significance;
• Know what raster and vector representation entails and how these data structures affect many GIS principles, techniques, and applications;
• Describe the art (e.g., conceptualization) and science (e.g., topological structures) of representing real-world phenomena in GIS;
• Define what geographic data models are and discuss their importance in GIS;
• Understand how to undertake GIS data modeling (e.g., ESRI's water utilities data model);
• Outline the main geographic models used in GIS today and their strengths and weaknesses;
• Understand key topology concepts and why topology is useful for data validation, analysis, and editing (ESRI's discussion on topology).

Text: Chapter 3: Representing geography and Chapter 8: Geographic data modeling [Overheads: 1 per page; 3 per page]

Key words: fields, objects, raster, vector, object-oriented (see also this), ontology, epistemology, tessellation, semantics, axioms, ArcMap's raster compression described (lossy versus lossless?)