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Midterm Review

by: Maddy Moldenhauer

Midterm Review GPY 200

Maddy Moldenhauer
GPA 3.9
Computer Cartography

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About this Document

Midterm Review for Computer Cartography
Computer Cartography
Study Guide
Computer, Cartography, maps
50 ?




Popular in Computer Cartography

Popular in Geography

This 0 page Study Guide was uploaded by Maddy Moldenhauer on Wednesday February 3, 2016. The Study Guide belongs to GPY 200 at Grand Valley State University taught by Sun in Winter 2016. Since its upload, it has received 57 views. For similar materials see Computer Cartography in Geography at Grand Valley State University.


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Date Created: 02/03/16
II GPY 200 Review Computer Cartography Midterm Introduction to Cartography What is a map A scaleddown simplified graphic representations of the real world What are the functions of maps A way of recording amp storing information A means of analyzing locational distributions amp spatial patterns A method of presenting information amp communicating ideas What are general reference maps Small scale large area or Large scale small area maps that Show the locations of geographic features such as places topography roads political boundaries etc What is a thematic map Map the focuses on a specific geographic feature or theme Physical temperature pollution etc Cultural religion population etc What is Cartography The study and making of maps Maps as a form of visual communication Map design Map Essential elements 1 Title 2 Legend 3 Scale 4 Direction 5 Projection 6 Sources of info amp how processed 7 Cartographer 8 Date of Production Selective elements I Neatlines I Locator maps I Inset maps I Index maps etc 111 Exploratory Data Analysis I Data exploration I Numerical summaries 0 Measures of central tendency Indicate where the data is concentrated mode median mean 0 Measures of dispersion Show how data are spread out range variance standard deviation interquartile range I Outliers Unusual Values I Graphs Univariate one variable histograms box plot Bivariate two variables scatterplot More variables scatterplot matrix parallel coordinate plot I Dynamic Graphics dynamically linked to the map and table IV Cartographic Abstraction amp Data Classi cation Maps are reduction of realities Selection Generalization I grouping features by their attributes amp attribute values eliminating unwanted detail which keep and which to discard enhance or emphasize important characteristics of the attributes using graphic marks symbols to encode he information for visualization Types of geographic data I Discrete Spatial data that is individually separateonly at certain locations on map EX Distribution of coalfields in US I Continuous Data that is unbrokencovers whole map EX Land cover temperature Classi cation methods in ArcGIS I Natural breaks J enks Default method creates classes according to clusters amp gaps in the data Minimizes variation Within classes amp maximizes variation between classes I Equal Interval Creates classes of equal value ranges or equal intervals I Defined Interval Where you decide the interval for each class and the method determines the of classes I Geometrical Interval Class breaks are based on class intervals that have a geometric series With a constant coefficient I Quantile creates classes containing and equal number of data points I Standard Deviation creates classes according to a specified number of standard deviations from the mean value I Manual you can set Whatever class breaks you like V Cartographic Symbolization Cartographic symbolization is essentially a graphic encoding process Cartographic symbolization I Pictorial vs abstract symbols s mbols look like the features they represent in shape and color s mbols may be any geometric shape assigned to represent a feature Dimensionality of geographic features 0dimensiona1 data 1dimensional data 2dimensional data 3dimensional data Three 3 basic symbol types 0dimentional data 1dimentional data 2dimentional data 3dimentional data Levels of measurement of data I lowest level uses category type but NO ordering qualitative diff EX River road boundary pipeline I ordering or ranking contains some quantitative measure EX Living Conditions Poor moderate excellent I distance between ranks must use standard unit can express he amount of difference in terms of unit NO TRUE ZERO POINT Ex Temperature I True Zero starting point zero indicates absence of What is measured Ex Salary Precipitation Population Qualitative data shows differences in type or quality Quantitative Measurable data Indicates differences in amount amp is expressed numerically Six categories of visual variables I Shape I Size I Orientation I pattern textile I hue color I hue value color shade gradient Which visual variables seem tted for portraying qualitative data Point symbols of different shapes amp hues not different sizes Line amp Area Symbols varying in pattern and hue Which visual variables seem better tted for portraying quantitative data Symbolization of various levels of measurement of data I ordinal data I and intervalratio data


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