Generating Globe

Tissot’s Indicatrix

Semi major axis -a

Semi minor axis - b

baS

Lecture 6 5

Lecture 6 6

Lecture 6Maps & Data EntryChapter 4 – pp 131-153

Lecture 67

http://what-is-questions.blogspot.com/2013/10/first-world-map-ever-made-who-made.html

Lecture 6 8

Lecture 6 9

Graticule Grid

Lecture 6 10

Types of Maps

• There are many different types of maps.• Feature maps are the simplest as they

map points lines or areas.• Choropleth maps depict quantitative

information for areas.• Dot-density maps also depict quantitative

information.• Isopleth maps/contour maps display lines

of equal value.

Lecture 6 11

Feature Map

Lecture 6 12

Choropleth Unique Value

Lecture 6 13

Graduated Color Maps

The most important assumption in choropleth mapping is that the value in the enumeration unit is spread uniformly throughout the unit.

Lecture 6 14

Graduated Color Maps

• It is traditional to use ratios instead of total values when creating graduated color maps.

• Most mapping areas are unequal. The varying sizes and their values will alter the impression of the distribution.

Lecture 6 15

Proportional and Graduated Symbol Maps

• Guidelines– Circles are the most common symbol used due to

the ease with which they are interpreted.– All symbols should generally be the same color.– The difference between the largest and smallest

symbols should be great enough to show differences in data values.

– Largest symbols should not overlap so much that they obscure patterns on the map.

Lecture 6 16

Proportional and Graduated Symbol Maps

• What are they?– Proportional Symbol

• The size of a point symbol varies from place to place in proportion to the quantity that it represents.

– Graduated Symbol• Size of a point symbol

is based on which class the features value falls within.

Lecture 6 17

Chart

Lecture 6 18

Dot Density Maps

• What are they?– Dot density

maps use a dot to indicate one or more occurrences of a phenomena.

Lecture 6 19

Dot Density MapsGuidelines

Select a dot value that is easily understood such as 5, 100, 1000, etc.

Choose a dot value that results in two or three dots being placed in the area with the least mapped quantity.

The dots should coalesce in the statistical area that has the highest density of the mapped value.

Lecture 6 20

Dot Density Maps

• Advantages– Easily understood

by the reader– Illustrates spatial

density– Original data can

be recovered from the map if the dots represent the actual locations of the phenomena 1 dot = 5 births

Therefore 6 dots = 30 births

Lecture 6 21

Dot Density Maps

• Disadvantages– A dot map that is

computer generated typically involves a random distribution of dots within an enumeration area.

– Solution - Use census blocks over tracts, counties over states, etc.

Population

1 dot = 5000 persons

Population

1 dot = 5000 persons

Lecture 6 22

Isopleth Maps

• Isopleth maps are used to visualize phenomena that are conceptualized as fields, and measured on an interval or ratio scale.

• We can, however, also color them in such a way as to represent ordinal and nominal data as well.

Lecture 6 23http://enb110-ert-2012.blogspot.com/2012/08/maps-chloropleth-map-is-used-as-way-to.html

Lecture 6 24

Result of a T-test performed to identify areas of significant change in deer harvest.

Statistical Analysis

Lecture 6 25

Images

Lecture 6 26

3-D

Lecture 6 27

•The amount of reduction that takes place in going from real-world dimensions to the new mapped area on the map plane.

•Defined as the ratio of map distance to earth distance, with each distance expressed in the same units of measurement.

Map SCALE

Lecture 6 28

Concepts of Scale

• Representative fraction – when the scale value is given as a fraction with a numerator as 1.

1250

1000,100

1

Lecture 6 29

Large Scale e.g. 1:1000 Small Scale e.g. 1:250000

11000 1

250000

•The terms “large scale” and “small scale” refer to scale shown as a fraction.

•1:1000 is a relatively small denominator, yet it is a much bigger fraction (and thus a larger scale) than 1:250000

•Large scale map features are relatively large. Small scale map features are relatively small.

Large Scale vs. Small Scale

Lecture 6 30

Lecture 6 31

•Shows a relatively small portion of the earth’s surface

•Provides detailed information

•Usually maps that are 1:24000 or larger are considered large scale

e.g. 1:24000 - quad scale

e.g. 1:12000 - quarter quad scale

e.g. 1:2400 - tidelands maps

Large Scale

Lecture 6 32

•Shows relatively large areas of the earth

•Provides limited detail

•Generally maps smaller than 1:24000 are considered small scale.

e.g. 1:250,000 - Hudson county

e.g. 1:3,300,000 - State of New Jersey

Small Scale

Lecture 6 33

One foot equals 24000 feet

One inch equals one mile

•Useful for a quick sense of ground units in familiar units.

•Unreliable, subject to misinterpretation, invalidated by reduction and enlargement.

Verbal Scales

Lecture 6 34

•Most effective

•Map user can better measure and interpret distances within the map area.

•Expands or shrinks along with other map distances, so it remains valid over all reductions and enlargements.

Bar Scales

Lecture 6 35

Map Generalization

• Maps are abstractions of reality.

• This abstraction introduces map generalization, the approximation of features.

Lecture 6 36

Penobscot Bay at Different Scales and Different Generalizations

Large Scale Map Small Scale Map

Lecture 6 37

Types of Map Generalization

Road

Gr ouped

O mit t ed

Road

T r ut h

Road

Road

O ff set

E x agger at ed

T r ue S cale Road W idt h

S t andar d S ymbol Road W idt h

Cat egor iz ed

f en

wat er

wat er

f en

f en

swamp

wat er

mar sh

Lecture 6 38

Map Boundaries

• Hard copy maps have edges, and discontinuities often occur at edges.

• Most digital maps have been digitized from hardcopy maps so edge discontinuities have been carried into the present.

• These errors are being corrected as newer data are being collected by digital means.

• Differences in time of data collection for different map sheets can also cause errors at the edges.

Lecture 6 39

Analogue vs. Digital Data

• Analogue (hardcopy)– Paper maps– Tables of statistics– Hard copy aerial photographs

• Digital data is already in computer readable format and can come from a variety of sources:– The internet– Digital imagery– Data collection devices

• If data were all in the same format, type, scale and resolution, encoding would be simple.

Lecture 6 40

Spatial Data Input from Hardcopy Sources

Common Input Methods:

•keyboard entry

•manual digitizing

•automatic digitizing

•scanning

•format conversion

Lecture 6 41

Data Encoding

• The process of getting data into the computer.• Spatial data

– Different sources– Different formats– Input via different methods

• As a result, GIS data must be corrected or manipulated to be sure they can be structured according to the desired data model.

Lecture 6 42

Problems to Be Addressed

• Reformatting

• Reprojection

• Generalization of complex data

• Edge matching of adjacent map sheets

Lecture 6 43

Figure 5.1 The process of data encoding may be referred to as the data stream

Heywood, Cornelius & Carver – Geographical Information Systems (4th Ed.)

Lecture 6 44

Tabular Data

• Attribute data

• Spatial data– Coordinate data

• Add x,y data – it comes in as an event theme• Export to shapefile or feature class

– Address data (requires a road file)• Geocoding converts addresses to x,y data

Lecture 6 45

Geocoding

• Geocoding is the process of finding associated geographic coordinates (often expressed as lat/long) from other geographic data.

• Address matching is the most common form of geocoding.

Lecture 6 46

Applications of Geocoding

• Internet Services: Google, Yahoo, Mapquest

• Business: market/area analysis, real estate

• Emergency Services

• Crime Analysis

• Public Health Services

Lecture 6 47

Manual Digitizing

Tracing the location of “important” coordinates

Done from an image or map source

Lecture 6 48

Manual Digitization – Map Digitization

Digitizing TabletOn-screen Digitizing/

Heads-up Digitizing

Lecture 6 49

Manual Digitizing Processfrom hardcopy map:

1. Fix map to digitizer table2. Digitize control points (tics,

reference points, etc.) of known location

3. Digitize feature boundaries in stream or point mode.

4. Proof, edit linework5. Transform or register to

known system (may also be done at start)

6. Re-edit, as necessary Accuracies of between 0.01

and 0.001 inches

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#Y#Y

#Y

#Y #Y#Y

#Y

#Y#Y

#Y

#Y

#Y

#Y

12

34 5

6

7

89

10

11

12

13

A well-distributed, precisely identifiable set of control points

Lecture 6 51

Lecture 6 52

Figure 5.4 Point and stream mode digitizing (Heywood, Cornelius & Carver)

Lecture 6 53

Digitize Primarily from Cartometric Maps

Based on coordinate surveys

Plotted and printed carefully

Lecture 6 54

Manual Map Digitization, Pros and Cons

Advantages•low cost •poor quality maps (much editing, interpretation)•short training intervals•ease in frequent quality testing•device ubiquity

Disdvantages•upper limit on precision •poor quality maps (much editing, interpretation)•short training intervals•ease in frequent quality testing•device ubiquity

Lecture 6 55

DATA SOURCES, INPUT, AND OUTPUT

Problems with source maps:

Dimensional stability (shrink, swell, folds)Boundary or tiling problemsMaps are abstractions of RealityFeatures are generalized:

•classified (e.g., not all wetlands are alike)•simplified (lakes, streams, and towns in a scale example)•moved (offsets in plotting)•exaggerated (buildings, line roadwidths, etc).

Lecture 6 56Figure 5.13 Examples of spatial error in vector data (Heywood, Cornelius and Carver)

Manual Digitizing common errors that require editing

Lecture 6 57

Digitizing Accuracy

Lecture 6 58

Editing

Manual editing: Line and point locations are adjusted on a graphic display, pointing and clicking with a mouse or keyboard. Most controlled, most time-consuming .

Interactive rubbersheeting:Anchor points are selected, again on the graphics screen, and other points selected and dragged around the screen. All lines and points except the anchor points are interactively adjusted.

Lecture 6 59

Figure 5.20 Rubber sheeting (Heywood, Cornelius & Carver)

Lecture 6 60

Figure 5.15 Radius topology feature snapping (Heywood, Cornelius and Carver)Source: 1Spatial. Copyright © 2005 1Spatial Group Limited. All rights reserved

Lecture 6 61

Snapping Errors

Lecture 6 62

Manual Digitizing – Vertex Density

Lecture 6 63

To Few Vertices – Spline

Interpolation

Create smooth, curving lines by fitting piecewise polynomial functions

Lecture 6 64

Too Many Vertices - Line Thinning

Lecture 6 65

Figure 5.18 The results of repeated line thinning (Heywood, Cornelius and Carver)Sources: (a–f): From The Digital Chart of the World. Courtesy of Esri. Copyright © Esri. All rights reserved; (inset): From Esri, ArcGIS online help system, courtesty of Esri. Copyright © 2011 Esri. All rights reserved

Lecture 6 66

Common problem:

Features which occur on several different maps rarely have the same position on each map

What to do?

1. Re-drafting the data from conflicting sources onto the same base map, or

2. Establish a "master" boundary, and redraft map or copy after digitizing

Lecture 6 67

Digitizing Maps - Automated Scanners

•Main alternative to manual digitizing for hardcopy maps

•Range of scanner qualities, geometric fidelity should be verified

•Most maps are now available digitally – however many began life as paper maps

Lecture 6 68

Figure 5.7 Types of scannerSources: (a) Epson (UK) Ltd used by permission; (b) Stefan Kuhn, www.webkuehn.de; (c) Colortrac, www.colortrac.com

(Heywood, Cornelius and Carver)

Lecture 6 69

Practical Problems of Scanning

• Optical distortion from flatbed scanners.

• Unwanted scanning of handwritten information.

• The selection of appropriate scanning tolerances.

• The format of files produced for GIS input

• The amount of editing required to produce data suitable for analysis.

Lecture 6 70

Lecture 6 71

Digitizing Maps - Automated Scanners

•Suitable threshholding allows determination of line or point features from the hardcopy map.

•Scanners work best when very clean map materials are available. •Significant editing still required (thinning, removing unwanted features)

Lecture 6 72

Cell Thinning and Vectorizing– After Scan-Digitizing

Lecture 6 73

Georeferencing

• In order to display images with shapefiles or features, it is necessary to establish an image-to-world transformation that converts the image coordinates to real-world coordinates. This transformation information is typically stored with the image.

Lecture 6 74

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Rectified Image

• GeoTiff - store the georeferencing information in the header of the image file. ArcView uses this information if it is present.

• World Files - However, other image formats store this information in a separate ASCII file. This file is generally referred to as the world file, since it contains the real-world transformation information used by the image. World files can be created with any editor.

Lecture 6 79

World Files

• It’s easy to identify the world file which should accompany an image file: world files use the same name as the image, with a "w" appended. For example, the world file for the image file mytown.tiff would be called mytown.tiffw or mytown.wtf

Lecture 6 80

The Contents of the World File

20.17541308822119 (x-scale factor)

0.00000000000000 (rotation)

0.00000000000000 (rotation)

-20.17541308822119 (y-scale factor)

424178.11472601280548 (x-translation)

4313415.90726399607956 (y-translation)• When this file is present, ArcView performs the

image-to-world transformation.