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Creating Map Symbology Module 2 PowerPoint Presentation
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Creating Map Symbology Module 2

Creating Map Symbology Module 2

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Creating Map Symbology Module 2

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  1. Creating Map Symbology Module 2 ESRI Virtual Campus Learning ArcGIS Desktop Training Course ESRI ArcGIS

  2. Creating Map Symbology • Have you ever noticed that some maps are easier to understand than others? • Difference can be due to mapmaker's choice and arrangement of symbols and text. • A map is most effective when symbols are easy to distinguish and their meaning is intuitive. • Your choice of symbols and labels will be influenced by the type of map you are making.

  3. Creating Map Symbology • Maps can be divided into two main categories: • Reference maps • Also called general maps • Show the location of features • Useful for multiple purposes • Examples - atlas maps and topographic maps • Thematic maps • Show the structure and distribution of one or more phenomena • Examples -maps of world population, today's weather, and rice production in the Philippines

  4. Learning Objectives • Choose symbols for point, line, and polygon features. • Modify symbol properties such as color, size, and outline. • Label map features using an attribute and by adding text. • Symbolize features to show type, rank, or amount. • Group features into classes and apply symbols to each class. • Compare different methods of grouping features into classes. • Correct visual distortion caused by differences in area. • Show proportional amounts on a map by normalizing data. • Symbolize features to show density.

  5. Working with Map Symbols and Labels • When a layer is added to a map a default symbol is used to represent the layer's features. • It may not be the one you want, so you need to know how to change it • Effective symbols take advantage of common associations that people make, • such as blue for water and green for vegetation. • People also make associations based on symbol size • street drawn with a thick line is easily understood to be busier or more important than one drawn with a thinner line • Text may be used to provide a feature's name or other attribute, or to draw attention to a feature or an area of interest.

  6. Working with Map Symbols and Labels • On a map, symbols are used to show feature locations. • Using pictoral symbols can provide more information • i.e. a car symbol indicates a parking lot. • Adding text such as a feature's name or function provides even more information.

  7. Types of Symbols • Symbol properties can be changed to suit a particular map. • i.e. can change the size or angle of a marker symbol used to represent a point feature • Can change the width of a polygon symbol's outline

  8. Symbol Properties

  9. Types of Symbols • When a map document is saved • Layer symbology is saved with it. • Layer file • To easily reuse a layer's symbology in other map documents • A good way to ensure that everyone in an organization uses the same symbology • Can be especially important if organization or industry employs standard symbols • Can also save time --- don't have to create the symbology over again each time a particular layer is used

  10. Choosing Symbols • ArcGIS has thousands of symbols for common map features • Organized into more than 25 symbol sets • Can also import additional symbol sets or create your own • General-purpose symbol sets • Like the ESRI symbol set • Specialized symbol sets • Reflect the needs or standards of different industries

  11. Choosing Symbols • A few of the point (marker) symbols that come with ArcMap. • From ESRI, Crime Analysis, Utilities, and Forestry symbol sets • Clockwise from upper left

  12. Labeling Map Features • Text on a map can serve many purposes • One of most important functions of map text is to describe, or label, features. • Most common labels are names • i.e. street names, place names, and names of landforms or water bodies • In ArcMap, label text comes from a field in a layer's attribute table.

  13. Labeling Map Features • The source of the labels in this map is the CNTRYNAME field in the Countries attribute table.

  14. Labeling Map Features • Labels can be added in two ways • Dynamically • Generated on the fly for all the features in a layer at once • Can specify label properties such as • font, size • Color • position in relation to the feature being labeled (such as top left, bottom center, top right • Interactively • Created by clicking individual features in the map • May use same label properties specified for the layer, or can set different ones

  15. Labeling Map Features • What if you want to label something that isn't actually represented in a layer? • i.e. a layer of mountain peaks and you want to label the whole mountain range. • You can do this by manually adding the desired text to the map.

  16. Labeling Map Features • Annotation • Text added manually • Each piece of annotation has its own properties that are stored either in a map document or in a database • Always stays at the position where you place it, but you can reposition it as desired • Dynamic label • Location is determined by ArcMap and is based on the current map extent and the number of features being displayed in that extent. • As the map is zoomed in and out, the position will change as ArcMap determines the best placement for them. • May move, appear, or disappear as the available space on the map changes. • An easy way to label many features at once. • Can convert dynamic to annotation if you need to edit the appearance or placement of individual labels.

  17. Exercise • Display and label map features

  18. Symbolizing Features Based on Attributes • Features can also be symbolized based on an attribute • Thematic map • Features have been symbolized based on an attribute • Often communicate more information. • i.e. vegetation polygons symbolized by a type attribute to indicate different areas such as forest, grassland, or marsh. • Individual tree locations could be symbolized by a diameter attribute to show the distribution of trees by size.

  19. Symbolizing Features Based on Attributes • Pine trees have been symbolized based on their diameter • Vegetation polygons have been symbolized based on their type. • Now you can see that the largest trees occur in just one cluster. • You can also see that pine trees are not found in marsh areas.

  20. Symbolizing Features Based on Attributes • Type of symbology used to create a thematic map depends on whether an attribute's values are • categories (e.g., type) or • quantities (e.g., diameter)

  21. Drawing Features to Show Categories • Category attributes are • Names • Types • Ranks • Each unique attribute value represents a different category. • The values can be • Text • Numbers

  22. Drawing Features to Show Categories

  23. Drawing Features to Show Categories • When a layer is symbolized based on a category attribute • Features in different categories are represented with a different symbol. • Exactly how the symbols differ from one another depends on is being mapped • i.e. if symbolizing roads according to the number of lanes • use line symbols with different widths to represent the different lane categories • If mapping roads according to surface type • show paved roads with a solid line and gravel roads with a dashed line

  24. Drawing Features to Show Categories • Two ways to symbolize a hurricane path by categories • Left • different colors are used to symbolize the paths by name • Right • different line widths are used to symbolize the paths by hurricane strength

  25. Drawing Features to Show Quantities • Quantity attributes are always numeric. • Numbers represent • Counts • Amounts • Rates • Measures

  26. Drawing Features to Show Quantities • Feature quantities typically represented by • Creating groups of features with similar values (classes) • And assigning a different symbol to each class. • Even though symbols are different • usually change gradually from one class to another • forming a series. • Graduated size and graduated color are two most common ways to symbolize quantities

  27. Drawing Features to Show Quantities • Drawing features using symbols in a graduated series permits map readers to visualize geographic distribution patterns in quantity data. • i.e. if a map is drawn with colors ranging from yellow to orange to red • red areas can quickly be interpreted to represent greater values than yellow ones • Likewise, smaller symbols represent smaller quantities than larger symbols.

  28. Drawing Features to Show Quantities • The countries in this map are displayed with graduated shades of green. • The darker the shade, the greater the country's population.

  29. Drawing Features to Show Quantities • When choosing graduated colors, it is important to be aware of common color associations that people make. • People will easily understand a temperature map drawn with • blue symbols for cold • orange symbols for warm • The opposite way would be frequently confused.

  30. Exercise • Display features with categories and features

  31. Classifying Data • What process is used to create the classes? • What determines whether a particular attribute value falls into one class or another? • When symbolizing features based on quantities - three things must be decided: • How many classes to have • What method to use for placing the values into classes • What kind of symbology to use • e.g., graduated colors or graduated symbols

  32. Classifying Data • This graduated color map was created by classifying population values into four classes.

  33. Grouping Attribute Values Into Classes • In ArcMap, can classify features using one of several standard classification methods • Can also define own classes.

  34. Grouping Attribute Values Into Classes • Classification methods include: • Natural breaks • Identifies groupings of values that are inherent in your data. • Is the default method because it is appropriate for most data. • Equal interval • This method is like a ruler: the interval between each class is the same. • i.e. you might have classes with intervals of 10 percent (1-10%, 11-20%, 21-30%, etc.)

  35. Grouping Attribute Values Into Classes • Quantile • each class contains an equal number of values (features) • i.e. you might have 15 provinces grouped into three classes • Each class would contain five provinces regardless of the attribute values. • Manual • each class has the range you specify • This method is useful when you want the classes to reflect specific criteria or data. • i.e. if you have temperature data, you might want to specify a break between classes at 32 degrees Fahrenheit (freezing point).

  36. Grouping Attribute Values Into Classes • Natural Breaks • uses a statistical formula to find breaks that are inherent in the data. • In this example, there is a clear natural break between 19 and 29 (a difference of 10), but not between 29 and 30 (a difference of 1)

  37. Grouping Attribute Values Into Classes • Equal Interval • Evenly divides the entire value range into the number of classes you choose.

  38. Grouping Attribute Values Into Classes • Quantile • Places an equal number of values into each class.

  39. Grouping Attribute Values Into Classes • Manual • Uses class breaks that you define.

  40. Deciding Which Classification Scheme to Use • When mapping quantities, you may ask yourself: • Which classification method should I choose? • How many classes should I have? • There are no "correct" answers. • The best classification scheme for a given map layer depends on • Purpose of the map • Characteristics of the data • Cartographic considerations • such as how easily the resulting map can be understood

  41. Deciding Which Classification Scheme to Use • One approach let the data inform your decision. • When looking for patterns in data • try different classification methods and visually analyze the resulting maps • then select the method that seems best. • To evaluate classification schemes before mapping them • use a histogram

  42. Deciding Which Classification Scheme to Use • The classification histogram charts the number of attributes (features) for each attribute value. • Bottom axis shows attribute values • Side axis shows frequency of values • Height of gray bar indicates number of times a given value occurs in the table (frequency) • When deciding on the number of classes, there is one rule of thumb you can use: • Fewer is generally better • Three to seven classes is usually best.

  43. Deciding Which Classification Scheme to Use • A classification histogram helps visualize how attribute values are distributed across the overall range of values • Blue lines show current class breaks • Highest attribute value in each class • Data in this histogram is grouped into three classes.

  44. Deciding Which Classification Scheme to Use • Another approach • choose a classification scheme first • And let the attribute values fall where they may. • There may be a scientific or statistical reason for using a particular classification method with particular data. • Or, you might have predetermined standards or criteria that dictate the method or number of classes.

  45. Deciding Which Classification Scheme to Use • General guidelines for choosing an appropriate classification scheme.

  46. Exercise • Explore methods of classifying data

  47. Mapping Density and Proportion • Sometimes mapping an attribute with graduated colors or symbols can be misleading. • i.e. when polygon features vary greatly in area. • Patterns may be perceived in a graduated color map and assumed to represent variation in the attribute being mapped, when in fact they reflect the variation in the area of the features. • You can avoid such misperceptions by mapping density—the quantity per unit of area.

  48. Mapping Density and Proportion • Example • Each polygon represents a pasture in a goat farm. The small pastures are each 1 hectare and the large one is 4 hectares in area. This map shows the goat pastures This map seems to show that goats are concentrated in the north half of the farm. There are actually more goats in the south half of the farm. Mapping density results in a map that is likely to be perceived correctly.

  49. Mapping Density and Proportion • Another situation is when mapping the proportion of one quantity to another is more important than mapping them individually. • In the goat farm example, the proportion of female to male goats in each pasture might be more important than the total number of goats.

  50. Mapping Density Using Attribute Values • One way to map density is data normalization • Divide the attribute values by the area of each polygon feature • ArcMap calculates the density values • Choose a value field and an area field • You still must choose a classification method for grouping the density values and symbolizing them with graduated colors or graduated symbols