Mapping GIS Data

How maps portray the world Point features Line features Polygon features Annotation features

Talking about map scale A large denominator gives a small fraction  a small scale map. It shows a large area. A small denominator gives a larger fraction  a large scale map. It shows a small area. 1 -------- 50,000,000 1 -------- 500,000 1 -------- 5,000

Generalization and Scale Small scale map Intermediate scale map Large scale map

Scale and precision S: main way (60m) P: local road (20m) 1:100,000 scale map S: main way (60m) P: local road (20m) Let S be the size of the main way (with 60m width) represented by a 2 mm line symbol: 2 mm = 1 S 100000 S = 200,000 mm = 200 m ≠ 60 m Let P be the size of the local way (with 20 m width) represented by a 1 mm line symbol: 1 mm = 1 P 100000 P = 100,000 mm = 100 m ≠ 20 m

Estimating precision from scale Denominator of scale / 1000 gives approximate precision for a 1-mm thick line: 1:5,000 5 m 1:24,000 24 m 1:100,000 100 m 1: 1 million 1000 m

Source scale and display scale Most GIS data have an intrinsic scale inherited from the source

Display vs source scale Once in GIS data may be displayed at any scale. BUT Original scale of the map does impact the precision and accuracy of the data. Original scale 1:5 million Original scale 1:25 million You should not display or analyze data at scales very different from the original source data.

Scale and resolution Resolution is the sampling distance of the stored x-y values. A larger scale map generally has a finer sampling distance and better spatial resolution. It can represent features with better precision. 1:5M scale 1:25M scale

Map Types and Data Types Single symbol map Unique values map Quantities maps: Graduated color map Graduated symbol map Dot density map Chart map Nominal data Categorical data Numeric data

Nominal data Names or ID Number State names Owner of parcel Tax ID number Parcel ID Number Usually portrayed on a map as labels

Single symbol maps Display all features with the same symbol Combine with labels to portray nominal data

Categorical data Places features into defined number of distinct categories Portrayed by different symbol for each category

Unique values maps Different symbol for each category or value Volcano types Road types Geologic units

Numeric data Interval data : Temperature, Elevation Ratio data : Population, Rainfall

Numeric data Numeric data that divided into classes Mapped using variations in symbol size, thickness, or color

Quantities Classed maps Graduated color map Graduated symbol map

Colors for choropleth maps Generally use change in saturation or close hues to indicate increase Avoid using too many colors which tend to mask increase

Dot density map Numeric data that did not divide into classes, mapped using Dot density map.

Chart Maps Proportional chart map