Cartography and Geovisualization Chapters 12 and 13 of your textbook
Why cartography? Maps are the principle means of displaying spatial data Exploration: visualization, leading to conceptualization of patterns and processes. (Chap 13) Communication: convey information and findings that are difficult to express verbally. (Chap 12)
The Connected States of America illustrates the emerging communities based on the social interactions defined by the anonymous cellphone usage data on AT&T s network. One can find that the communities defined by human networks do not always coincide with the administrative boundaries. Exploration and Communication
Cartographic communication Synthesis Presentation Confirmation Exploration
Why cartography? To become a complete GIS analyst, you need to become familiar with the basic elements of cartography and, in particular, map design. http://liam.avenza.com
Maps are not infallible. Maps must lie in order to convey information. All maps introduce distortion: shape (conformance) size (equivalence) direction distance Often mistakes are made: "The image on a map is drawn by human hands, controlled by operations in a human mind. John Kirkland Wright 1942 Sometimes errors are made deliberately.
How do they lie? Through: Simplification: choosing to take a complicated feature and make it simple Displacement: moving things from their true location Smoothing: making jagged shapes rounded Selection: Choosing what to show Enhancement: causing features to look like we expect, rather than how they really are Aggregation: merging features together Orientation (N/S or arbitrary rotation [to maximize use of page]) Think of how mandates would influence each of those processes.
Map design criteria What is the motive, intent or goal of the map? Who will read the map (the audience)? What are Map design criteria? How will the map be used: stand alone, in a report, or simply for your viewing? What things / circumstances would require you to design a map differently? Real world Conceptualization Measurement & representation Analysis Interpretation, validation & exploration
Cartographic transformations Three stages in the transformation of the Earth's surface from reality to map can be recognized: Primary: geometric -- map projections Going from 3-D reality to 2-D cartographic representation requires several transformations. What would they be? Secondary: semi-geometric -- geoid to ellipsoid (Datums) Tertiary: generalization Generalization is a non-reversible process, and therefore must be carefully considered.
Cartographic transformations Three stages in the transformation of the Earth's surface from reality to map are generally recognized: Primary: geometric -- map projections Secondary: semi-geometric -- geoid to ellipsoid (Datums) Tertiary: generalization Generalization is a non-reversible process, and therefore must be carefully considered.
Generalization Generalization has four main components: Simplification: excluding unwanted, enhancing desired Classification: reduces complexity (qualitative, quantitative) Symbolization: implicit or explicit, mimetic or abstract Induction: logical inference--integration of parts into a whole What are the main concepts / requirements / processes Mandates & the involved scale at which in generalization? the data will be displayed are a prime consideration.
Generalization? Simplification Topology? Classification Both processes reduce the detail
Simplification Impact of simplification tolerance Simplification routines are available in most GISystems. The first image: ungeneralized data set, the second: generalized at an 0.1 foot tolerance, the third: generalized at a 10 foot tolerance. A necessary process as the scale changes ArcMap s simplify line ArcMap s Generalization toolset
Classification Categorical (nominal, ordinal) vs numerical (interval, ratio) data [NOIR] Categorical classification: mostly qualitative Numerical classification: quantitative Number of classes? (4-6 is considered best)
Classification schemes Dividing up data: numerical classification Exogenous schemes Arbitrary schemes (e.g., equal interval) Ideographic schemes (e.g., natural breaks, quantiles) Serial schemes (e.g., standard deviation) Unclassified schemes When looking at numerical data, what ways of grouping the data can you think of? You should always explore your data (e.g., histograms) and try different class schemes before settling on one. Know your data!
Symbolization components (PGEs) Can you identify ways in which graphic components can be varied in order to distinguish different graphic elements? (Such as allowing a reader to distinguish different lines, different areas.)
Symbolization components (PGEs) In creating symbols, what can you vary? Primary Graphic Elements Is the data quantitative or qualitative? A useful site that explains statistics.
Bertin s graphic primitives, extended from seven to ten variables (the variable location is not depicted) [Info here] PGEs You must also consider how the spatial primitives (point, line, area) interact with the Primary Graphic Elements (PGEs). Source: MacEachren 1994 (from Visualization in Geographical Information Systems, Hearnshaw H.M. and Unwin D.J. (eds.). Reproduced by permission of John Wiley & Sons, Ltd.)
Qualitative data symbolization Abstract vs mimetic (Implicit vs explicit)
Ternary plots http://soiltexture.r-forge.r-project.org/
Visual hierarchy Other cartographic concerns, such as the visual hierarchy, are also important. The proper use of type is also very important.
Every map must contain some fundamental elements Inset map Scale Author North Arrow Map Body Data Source All maps should be enclosed by a neat line. Title Grid Legend Projection Depending on the scale, you may or may not need a grid and an inset map.
Map design is an art It is easy to make a map, but making a great looking map... requires consideration of all of the elements, and a sense of design. http://landtrustgis.org/technology/advanced/design
Dasymetric maps Dasymetric maps use the intersection of two datasets to obtain a more precise estimate of a spatial distribution. For example, census tracts often contain large tracts of land whereon people cannot live (e.g., parks, industrial areas). Excluding those areas when determining statistics such as population density can make a significant difference to the values.
Summary Cartography is both an art and a science. Maps are fundamental to any GIS project. Modern advances in GISoftware make it very easy to produce both good and bad maps. Any map is just one of all possible maps. Complex maps can be difficult to understand.
Summary We have only scratched the surface with respect to the elements of cartography that are important in presenting the results of your GIS-based analyses. The quality of the map will determine, to a large extent, the reception of your work. A poorly produced map suggests that the analyses were also poorly handled. A quality map suggests that the analyses were also done properly and with due care.