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ftp://edacftp.unm.edu/outgoing/pub/spenman/geog581L/exam ples_visualization EDAC FTP SITE
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SHAWN L. PENMAN EARTH DATA ANALYSIS CENTER UNIVERSITY OF NEW MEXICO DATA VISUALIZATION
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When Maps Lie (CityLab) Posted on UNMLearn ADDITIONAL READING http://www.citylab.com/design/2015/06/when-maps-lie/396761/
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Your personal style is the default location for new symbols and style elements to be saved to. It is empty to begin with but can be used to organize your style contents. It will always be referenced by ArcMap. On Windows XP, it is located at :\Documents and Settings\ \Application Data\ESRI\Desktop10.0\ArcMap. On Windows Vista and Windows 7, it is located at :\Users\ \AppData\Roaming\ESRI\Desktop10.0\ArcMap. STYLE LOCATION
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CLASSIFYING FEATURES
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QUALITATIVE VS QUANTITATIVE Qualitative Data classified or shown by category, rather than amount or rank eg. soil by type animals by species Different types of disasters Quantitative Data grouped or shown by measurements of number or amount eg. population per unit area percentages amount of damage caused by disaster
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Equal intervalNatural breaks QuantileStandard deviation CLASSIFYING QUANTITATIVE VALUES
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CLASSIFICATION TOOL
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Automatic or default settings by software are almost never appropriate Different classification can create a very different “look” of your data – you want control over this Certain classifications for certain data sets can be plain wrong, or very misleading at best Proper classification techniques assist in making the “map speak for itself” WHY CLASSIFY DATA?
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Natural breaks Quantile Equal interval Standard deviation
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Equal interval divides the range of attribute values into equal- sized subranges. This allows you to specify the number of intervals, and ArcGIS will automatically determine the class breaks based on the value range. For example, if you specify three classes for a field whose values range from 0 to 300, ArcGIS will create three classes with ranges of 0–100, 101– 200, and 201–300. Equal interval is best applied to familiar data ranges, such as percentages and temperature. This method emphasizes the amount of an attribute value relative to other values. For example, it will show that a store is part of the group of stores that make up the top one-third of all sales. EQUAL INTERVAL
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Natural Breaks classes are based on natural groupings inherent in the data. Class breaks are identified that best group similar values and that maximize the differences between classes. The features are divided into classes whose boundaries are set where there are relatively big differences in the data values. Natural breaks are data-specific classifications and not useful for comparing multiple maps built from different underlying information. NATURAL BREAKS
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Each class contains an equal number of features. A quantile classification is well suited to linearly distributed data. Quantile assigns the same number of data values to each class. There are no empty classes or classes with too few or too many values. Because features are grouped in equal numbers in each class using Quantile classification, the resulting map can often be misleading. Similar features can be placed in adjacent classes, or features with widely different values can be put in the same class. You can minimize this distortion by increasing the number of classes. QUANTILE
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The Standard deviation classification method shows you how much a feature's attribute value varies from the mean. ArcMap calculates the mean and standard deviation. Class breaks are created with equal value ranges that are a proportion of the standard deviation—usually at intervals of 1, ½, ⅓, or ¼ standard deviations using mean values and the standard deviations from the mean. A two-color ramp helps emphasize values above the mean (shown in blue) and values below the mean (shown in red). STANDARD DEVIATION
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Standard deviation of daily mean (1948-1997) precipitation (units: mm day -1 ) in the URD for JFM, AMJ, JAS and OND. http://www.cpc.ncep.noaa.gov/research_papers/ncep_cpc_atlas/7/atlas_7.html
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Understand what your data represents are there any categories or values of importance? what underlying distribution could you expect? Study the distribution e.g. use the histogram in the classification tool Try out a couple of different approaches this is very quick…. Always consider a manual classification as an option Identify outliers and select how to deal with them: place them into a separate class group them with the next closest class create a special symbol for them CHOOSING A CLASSIFICATION
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DATA SPECIFIC CLASSIFICATION EPA Arsenic Levels Arsenic-rich ground strata are common in many parts of New Mexico and ground water arsenic is routinely found in the range of 10-50 ug/L. USEPA Arsenic drinking water standard is 10 micrograms per liter.
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HOW MANY CLASSES? 3 7 5 9
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Maximum = 7 most map readers can distinguish up to 7 different colors on a color ramp or gray scale, so more than 7 classes will make it difficult to identify features in the same class more than 7 classes can be used for continuous data (e.g. elevation, temperature) Minimum = 3 fewer than 3 classes will not show much variation Strategy first determine the proper classification scheme than start with large number of classes reduce number stepwise and select the minimum number of classes which still shows the spatial pattern in sufficient detail DECIDING HOW MANY CLASSES
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The values of the class should be meaningful 73.857 % is too detailed 73.9 or 74 % is probably OK 70% may not be detailed enough You can use standard classification schemes but typically it is better to force rounding to a certain number of digits. For example: 17386.346 17386.34 17386.3 17386 17390 17400 17000 20000 MAKING CLASSES EASIER TO READ
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Select classification method Set number of classes Use Exclusion tool for missing or incorrect data Manually move, add or delete breaks Right-click the histogram to: Zoom in/out Insert/Delete breaks Center the histogram USING THE CLASSIFICATION HISTOGRAM
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http://resources.arcgis.com/en/help/main/10.1/index.html#// 00s500000029000000 http://resources.arcgis.com/en/help/main/10.1/index.html#// 00s500000029000000 DON’T FORGET ABOUT ARCMAP HELP (DESKTOP OR ON-LINE)
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LABELING FEATURES
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Label all features dynamically using attribute values LABELING FEATURES - DYNAMIC
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LABEL PROPERTIES CONTROL APPEARANCE AND POSITION
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LABEL STYLES
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LABEL MANAGEMENT Labeling Toolbar
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LABEL MANAGEMENT Labeling Toolbar Maplex Labeling Engine – better way to label
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MAPLEX
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PLACEMENT PROPERTIES
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LABELING FEATURES – INTERACTIVE (OR ONE AT A TIME)
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Essential labeling concepts http://resources.arcgis.com/en/help/main/10.1/index.html#//00s800 00000t000000 http://resources.arcgis.com/en/help/main/10.1/index.html#//00s800 00000t000000 Maplex help http://resources.arcgis.com/en/help/main/10.1/index.html#//00s800 000054000000 http://resources.arcgis.com/en/help/main/10.1/index.html#//00s800 000054000000 ARCGIS HELP LABELING
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ftp://edacftp.unm.edu/outgoing/pub/spenman/geog581L/exam ples_visualization EDAC FTP SITE
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USA Counties Graduated colors – Asian Normalization – sqmi NM Gross Receipts Classify on Rates - look at histogram, notice how intervals change when different methods selected Equal interval Natural Breaks Quantile Standard Deviation Label the political unit (use Name attribute field) Use standard label engine Use Maplex label engine – what is the difference? DEMO/PRACTICE
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South American Earthquakes Graduated symbol map of Magnitude Only show records 3-6 Option 1 – Exclusion of unwanted data DEMO/PRACTICE
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South American Earthquakes Graduated symbol map of Magnitude Only show records 3-6 Option #2 – Definition Query DEMO/PRACTICE Write Query Query Fewer Records http://resources.arcgis.com/en/help/main/10.1/index.html#//00s50000002z000000
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School District Boundaries Schools Label School Districts Label Schools – Change Scale Range so school labels only show up at appropriate scale. DEMO/PRACTICE
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