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L 7 –Maps & Data Entry Chapter 4 – pp 153 -End Lecture 7 L 7 –Maps & Data Entry Chapter 4 – pp 153 -End Lecture 7 1

When do we need a transformation? Digitizing from legacy maps Digitizing from suitable aerial When do we need a transformation? Digitizing from legacy maps Digitizing from suitable aerial photos Lecture 7 2

Coordinate Transformation • Also called registration, as it registers the map layers to a Coordinate Transformation • Also called registration, as it registers the map layers to a map coordinate system. • Requires a set of control points. – Must be as accurate as the desired outcome. – Evenly distributed over the area. – Sufficient number. • Commonly used to convert newly digitized data to a standard coordinate system. Lecture 7 3

Control Points How many are enough? – 12 to 30 recommended How should they Control Points How many are enough? – 12 to 30 recommended How should they be distributed? – at least 3 in each quadrant Best to have an independent, higher order set – the control data should be at least as accurate (hopefully 10 times more accurate) than the data to be transformed. Lecture 7 4

Equiarea Transformation • Equiarea (congruence) Transformation: – The method allows rotation of the rectangle Equiarea Transformation • Equiarea (congruence) Transformation: – The method allows rotation of the rectangle and preserves its shape and size. Lecture 7 5

Similarity Transformation • Similarity Transformation: – The method allows rotation of the rectangle and Similarity Transformation • Similarity Transformation: – The method allows rotation of the rectangle and preserves its shape but not size. Lecture 7 6

Projective Transformation • Projective Transformation: – The method allows angular and length distortion, thus Projective Transformation • Projective Transformation: – The method allows angular and length distortion, thus allowing the rectangle to be transformed into an irregular quadrilateral. Lecture 7 7

Topological Transformation • Topological Transformation: – The method preserves the topological properties of an Topological Transformation • Topological Transformation: – The method preserves the topological properties of an object but not shape, thus allowing the rectangle to be transformed into a circle. – Also called rubber sheeting Lecture 7 8

Affine Transformation • Affine Transformation: – The method allows angular distortion but preserves the Affine Transformation • Affine Transformation: – The method allows angular distortion but preserves the parallelism of lines. – While preserving line parallelism, the affine transformation allows rotation, translation, skew, and differential scaling on the rectangular object. Lecture 7 9

Developing the Transformation Equations Coordinates in the source system Coordinates in the target system Developing the Transformation Equations Coordinates in the source system Coordinates in the target system Estimate equations that allow us to calculate the target coordinates given any set of source coordinates Lecture 7 10

Affine Transformation Target coordinates a first-order linear function of source coordinates Known as an Affine Transformation Target coordinates a first-order linear function of source coordinates Known as an Affine Transformation: Easting = Te + a 1 x + a 2 y Northing = Tn + b 1 x + b 2 y T shifts origin bi & ai changes scale & rotation Lecture 7 11

Example • Road intersection: – Real world coordinates: E=500, 000 & N=4, 800, 000 Example • Road intersection: – Real world coordinates: E=500, 000 & N=4, 800, 000 – Digitized coordinates: x=125 & y= 100 • Each control point provides two equations. Lecture 7 12

Lecture 7 13 Lecture 7 13

RMSE = e 21 + e 22 + e 23… n Lecture 7 14 RMSE = e 21 + e 22 + e 23… n Lecture 7 14

Lecture 7 15 Lecture 7 15

Lecture 7 16 Lecture 7 16

Higher order polynomial transformation • Named for the largest exponent in the transformation equation. Higher order polynomial transformation • Named for the largest exponent in the transformation equation. • Arc. Map supports first to third order transformation. • Command line supports first to twelfth order transformation. • Use the lowest order transformation that provides acceptable results Lecture 7 17

Lecture 7 18 Lecture 7 18

Raster Geometry and Resampling • Data must often be resampled when converting between coordinate Raster Geometry and Resampling • Data must often be resampled when converting between coordinate systems or changing the cell size of a raster data set. • Common methods: – Nearest neighbor – Bilinear interpolation – Cubic convolution Lecture 7 19

Lecture 7 20 Lecture 7 20

What if the cells aren’t “well behaved” Lecture 7 21 What if the cells aren’t “well behaved” Lecture 7 21

Orientation and/or Cell Size May Differ Lecture 7 22 Orientation and/or Cell Size May Differ Lecture 7 22

Resampling - Distance-weighted averaging bilinear interpolation Lecture 7 23 Resampling - Distance-weighted averaging bilinear interpolation Lecture 7 23

Map Transformation - Summary • • • From 2 -d to 2 -d system Map Transformation - Summary • • • From 2 -d to 2 -d system Requires mutually identified control points Linear (affine) transformation is best Sufficient, well-distributed control points Should not be used in place of a map projection! Lecture 7 24

Types of GIS Output • Maps: Everyone recognizes this most common output from a Types of GIS Output • Maps: Everyone recognizes this most common output from a GIS. • Cartograms: These special maps that distort geographic features based on their output values rather than their size. • Charts: GIS can produce pie charts, histograms (bar charts), line charts, and even pictures in addition to maps. Lecture 7 25

Types of GIS Output • Directions: Another common output, directions show you how to Types of GIS Output • Directions: Another common output, directions show you how to get from one place to another. • Customer lists: Business GIS applications often produce customer lists, sometimes with printed mailing labels. • 3 D diagrams and movies: These forms of GIS output help you see the results of your work realistically and dramatically. Lecture 7 26

Maps as Output • The map is still the most common form of output. Maps as Output • The map is still the most common form of output. • Map design elements to be considered: – Frame of reference – Projection – Features to be mapped – Level of generalization – Annotations – Symbolism • Maps should show only as much detail as necessary to get the point across. Lecture 7 27

Cartographic Design • Most design choices are compromises • Design is a process – Cartographic Design • Most design choices are compromises • Design is a process – Stage 1 – type of map, data to be represented, size, shape, basic layout. • Data type is the most important factor in determining map type and symbols – Stage 2 – kinds of symbolism, number of classes, class limits, color, line weights. – Stage 3 – define all symbols, typography (font, size, positions etc. ) Lecture 7 28

Making Great Maps Lecture 7 29 Making Great Maps Lecture 7 29

Making Better Map Layouts with Arc. GIS (1 hour) https: //www. youtube. com/results? search_query= Making Better Map Layouts with Arc. GIS (1 hour) https: //www. youtube. com/results? search_query= Arc. GIS+making+great+maps Lecture 7 30

Legends Qualitative Data Make symbols as intuitive as possible Use professional standards whenever possible Legends Qualitative Data Make symbols as intuitive as possible Use professional standards whenever possible Lecture 7 31

Contrast – bad example Lecture 7 32 Contrast – bad example Lecture 7 32

Contrast – good example Lecture 7 33 Contrast – good example Lecture 7 33

Typography & Lettering Use concise formulated captions • Avoid using more than four fonts Typography & Lettering Use concise formulated captions • Avoid using more than four fonts • Establish a typographic hierarchy • Develop legibility Black lettering on yellow ---- most legible • Red lettering on green ---- least legible • Lecture 7 34

Example: hello world Hard to read better Lecture 7 35 Example: hello world Hard to read better Lecture 7 35

Text Placement • Placing text on a map is one of the most time Text Placement • Placing text on a map is one of the most time consuming tasks, as much as 50% of the final map production time. • Poor placement of text affects the readability of the map, this is especially true in regions where map symbols are densely clustered. • Situations often arise in which text must overwrite other symbols with which it has no logical association. Lecture 7 36

Automated Name Placement • Components of name placement systems: – – Specification of map Automated Name Placement • Components of name placement systems: – – Specification of map features and text characteristics. Generation of trial name positions. Selection of optimal labels. Scale at which labels will be displayed • Font type, color and size must also be specified. • It is desirable to name as many features as possible, while recognizing that some features will remain unlabeled. • Named features should be ranked in some way to resolve conflicts. Lecture 7 37

Non-Traditional Maps • • • Cartogram Multimedia output Hybrid – Map overlaying an image Non-Traditional Maps • • • Cartogram Multimedia output Hybrid – Map overlaying an image 3 D Virtual GIS Lecture 7 38

Cartogram Lecture 7 39 Cartogram Lecture 7 39

Cartogram 2008 Election Results by State Results on A Population Cartogram http: //www-personal. umich. Cartogram 2008 Election Results by State Results on A Population Cartogram http: //www-personal. umich. edu/~mejn/election/2008/ Lecture 7 40

http: //amphibiaweb. org/amphibian/cartogra ms/ Lecture 7 41 http: //amphibiaweb. org/amphibian/cartogra ms/ Lecture 7 41

Figure 8. 9 Example of multimedia content in GIS displays Source: Screenshot shows ESRI Figure 8. 9 Example of multimedia content in GIS displays Source: Screenshot shows ESRI Graphical User Interface (GUI). Arc. Map, Arc. View and Arc. Info Graphical User Interfaces are the intellectual property of ESRI and is used herein with permission. Copyright © 2005 ESRI all rights reserved Lecture 7 42

Maps and Images Lecture 7 43 Maps and Images Lecture 7 43

3 D Maps http: //www. vidiani. com/? p=10431 Lecture 7 44 3 D Maps http: //www. vidiani. com/? p=10431 Lecture 7 44

THE OUTPUT FROM GIS ANALYSIS TABLES AND CHARTS • Used with maps or alone THE OUTPUT FROM GIS ANALYSIS TABLES AND CHARTS • Used with maps or alone to improve understanding of cartographic results • Whenever map output is less immediately understood by audience – Tables and charts are generally more understood by general public than maps are • Map is not appropriate for the output • Show summaries of attribute data and relationships among them – Explicitly spatial – Implicitly spatial Lecture 7 45

THE OUTPUT FROM GIS ANALYSIS TABLE AND CHART DESIGN • Should be readily understood THE OUTPUT FROM GIS ANALYSIS TABLE AND CHART DESIGN • Should be readily understood with minimal explanations • Appropriate titles for each table and chart presented • Label axes on all graphs • Provide legends wherever appropriate • Use fonts types and sizes that are easily read – Arial • Chose colors wisely as not to mislead audience – E. g. human eye is drawn to reds much more readily than to whites • Using red lines against white ones will draw the eye towards one and away from the other – is that what you wish? • Lecture 7 Avoid plotting more than 3 distinct attributes per plot 46

Bar Chart Good for comparing values and showing trends 47 Lecture 7 Bar Chart Good for comparing values and showing trends 47 Lecture 7

Column Chart Good for comparing values and showing trends Lecture 7 48 Column Chart Good for comparing values and showing trends Lecture 7 48

Area Chart Good for showing the relative value for each Lecture 7 category as Area Chart Good for showing the relative value for each Lecture 7 category as well as the total. 49

Cumulative Bar Chart Combines features of both the bar and area charts 50 Lecture Cumulative Bar Chart Combines features of both the bar and area charts 50 Lecture 7

Pie Charts Shows relationships between the parts and the whole, particularly useful for showing Pie Charts Shows relationships between the parts and the whole, particularly useful for showing proportions Lecture 7 51 and ratios.

Line Charts Emphasizes rate of change. Particularly good for Lecture 52 representing trends over Line Charts Emphasizes rate of change. Particularly good for Lecture 52 representing trends over a 7 period of time.

Scatter Charts Reveals trends or patterns in the data. Can help reveal associations, sometimes Scatter Charts Reveals trends or patterns in the data. Can help reveal associations, sometimes cause-and-effect Lecture 7 relationships. 53

The Geodatabase Lecture 7 54 The Geodatabase Lecture 7 54

What is the geodatabase? • An Arc. GIS geodatabase is a collection of geographic What is the geodatabase? • An Arc. GIS geodatabase is a collection of geographic datasets of various types held in a common file system folder: – a Microsoft Access database, – A multiuser relational database (such as Oracle, Microsoft SQL Server, Postgre. SQL, Informix, or IBM DB 2). Lecture 7 55

Fundamental datasets in the geodatabase • A key geodatabase concept is the dataset. • Fundamental datasets in the geodatabase • A key geodatabase concept is the dataset. • It is the primary mechanism used to organize and use geographic information in Arc. GIS. • The geodatabase contains three primary dataset types: – Feature classes – Raster datasets – Tables Lecture 7 56

A feature class is stored as a table. Each row represents one feature. In A feature class is stored as a table. Each row represents one feature. In the polygon feature class table below, the Shape column holds the polygon geometry for each feature. The value Polygon is used to specify that the field contains the coordinates and geometry that defines one polygon in each row. Lecture 7 57

Data in a Geodatabase Lecture 7 58 Data in a Geodatabase Lecture 7 58

Feature Class • Conceptual representation of a category of geographic features. • Includes point, Feature Class • Conceptual representation of a category of geographic features. • Includes point, line, poly & annotation • When shapefiles are added to a GDB their computer representation is changed • This is why you cannot drag and drop a shapefile into a GDB. • You have to load it or Import it. Lecture 7 59

Feature Dataset • A collection of feature classes that share the same spatial reference. Feature Dataset • A collection of feature classes that share the same spatial reference. • It is because they share the same spatial reference that they can participate in topological relationships with each other. • Several feature classes with the same geometry may be stored in the same feature dataset. • Object geometry and relationship classes can also be stored in a feature dataset Lecture 7 60

Geodatabase Feature Dataset Lecture 7 61 Geodatabase Feature Dataset Lecture 7 61

Line(arc) poly Anno Table } Lecture 7 point Cover 62 Line(arc) poly Anno Table } Lecture 7 point Cover 62

Catalog View WE view Lecture 7 63 Catalog View WE view Lecture 7 63

WE view Catalog View Lecture 7 64 WE view Catalog View Lecture 7 64

Advantages • Can be moved as a unit, regardless of how much stuff is Advantages • Can be moved as a unit, regardless of how much stuff is in it. • Faster • Can get at it through Microsoft Access, if you know what you are doing, • Stores topology Lecture 7 65

Advantages • TOPOLOGY? = the arrangement that defines how point, line, and polygon features Advantages • TOPOLOGY? = the arrangement that defines how point, line, and polygon features share coincident geometry. • Examples: – Fire hydrants must fall on water mains, – Adjacent soil polygons must share their common boundaries. Lecture 7 66

Topology • Many datasets have features that could share boundaries or corners • By Topology • Many datasets have features that could share boundaries or corners • By creating a Topology you set up rules defining how features share their geometries. • Editing a boundary or vertex shared by two or more features updates the shape of all of them. Lecture 7 67

Topology Rules • Govern the relationships between features within a FC or features in Topology Rules • Govern the relationships between features within a FC or features in different FCs • Example: moving a slope boundary in in one FC could update two slope class polys AND update a forest stand boundary in another FC. • Topology editing tools in Arc. Map are used to create and change the rules Lecture 7 68

Geometric Networks • Some vector datasets need to support connectivity tracing and network connectivity Geometric Networks • Some vector datasets need to support connectivity tracing and network connectivity rules – Communications – Pipelines – Transportation (roads, railroads, canals) • Geometric networks allow you to turn simple point and line features into network edge and junction features Lecture 7 69

Creating a Geodatabase • In Arc. Catalog! • Point to where you want to Creating a Geodatabase • In Arc. Catalog! • Point to where you want to put the new GDB • Click New>Personal GDB • Type in a new name Lecture 7 70

Adding Data • In Catalog… Right click and select New • You get Lecture Adding Data • In Catalog… Right click and select New • You get Lecture 7 71

Copying Data • You can copy/paste data between GDBs • OR • You can Copying Data • You can copy/paste data between GDBs • OR • You can import shapefiles, coverages, computer-aided drafting (CAD) data, and Geo. Database FCs into a GDB Lecture 7 72

Importing Shapefiles • feature class that's in another coordinate system. – You MUST project Importing Shapefiles • feature class that's in another coordinate system. – You MUST project to the spatial definition of the GDB – Then right click on GDB and select Import ----- Lecture 7 73

Planning for Your Geodatabase • What is the problem? • What data is needed Planning for Your Geodatabase • What is the problem? • What data is needed (scale, extent, etc. 0? • What kinds of relationships are needed between FC? • How will the data be organized (FDS)? Lecture 7 74

Summary • The Geodatabase is a container for all types of geographic data. • Summary • The Geodatabase is a container for all types of geographic data. • A feature dataset contains features that share a projection and geographic space. Lecture 7 75