Lecture 4:

GIS Data Input Methods and

Techniques

GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

Geographic Data in GIS

Can be obtained from various sources in

different formats

Can be inputted into a GIS using different

methods

Some Sources of Data for GIS

Maps

Census and Survey Data

Aerial Photographs

Satellite Images

Ground/Land Survey Data

GPS Data

Map

Gender Quickstat

(An Update of NSO's Most Requested Sex-

disaggregated Statistics)

as of 1st Quarter 2005

60

.2

295,

056

39

.8

195,

185

490,

241

80

and

over

56

.7

286,

734

43

.3

218,

622

505,

356

75 -

79

years

54

.7

436,

356

45

.3

361,

614

797,

970

70 -

74

years

53

.2

605,

374

46

.8

533,

469

1,13

8,84

3

65 -

69

years

51

.9

847,

013

48

.1

786,

137

1,63

3,15

0

60 -

64

years

50

.5

960,

516

49

.5

943,

133

1,90

3,64

9

55 -

59

years

49

.7

1,30

3,68

4

50

.3

1,31

8,63

2

2,62

2,31

6

50 -

54

years

49

.0

1,63

3,34

2

51

.0

1,69

6,71

2

3,33

0,05

4

45 -

49

years

49

.1

2,04

3,18

0

50

.9

2,12

0,31

4

4,16

3,49

4

40 -

44

years

49

.1

2,40

4,20

2

50

.9

2,49

6,82

1

4,90

1,02

3

35 -

39

years

49

.4

2,74

1,77

2

50

.6

2,80

4,52

2

5,54

6,29

4

30 -

34

years

49

.7

3,01

7,47

3

50

.3

3,05

3,61

6

6,07

1,08

9

25 -

29

years

50

.2

3,54

6,88

5

49

.8

3,52

2,51

8

7,06

9,40

3

20 -

24

years

49

.9

3,99

9,46

8

50

.1

4,01

7,83

0

8,01

7,29

8

15 -

19

years

49

.3

4,40

8,41

7

50

.7

4,54

1,19

7

8,94

9,61

4

10 -

14

years

48

.8

4,73

2,76

8

51

.2

4,96

2,01

3

9,69

4,78

1

5 -

9

years

48

.8

4,71

7,57

0

51

.2

4,95

1,93

2

9,66

9,50

2

2000

0 -

4

years

49

.6

37,9

79,8

10

50

.4

38,5

24,2

67

76,5

04,0

77

May

Total

Popul

ation

DEMOGRAPHY (Source: Census of Population

and Housing)

Pe

rc

en

t

Nu

mb

er

Pe

rc

en

t

Nu

mb

er

Nu

mbe

r

Year

Female Male

Bot

h

Sex

es

DATA

REF

ERE

NCE

PERI

OD

INDIC

ATOR

Census and Survey Data

May be spatial in character if each item

has a spatial reference, allowing its

location on the Earth to be identified

Usually in tabular format

Examples: population census,

employment data, agricultural census

data, marketing data

Aerial Photographs

First method of remote sensing

A ‘snapshot’ of the Earth at a particular instant in time

May be used as a background or base map for other data in a GIS

Provides spatial context and aids in interpretation

Versatile, relatively inexpensive and detailed source of data for GIS

Disadvantage: not spatially referenced; should be spatially referenced using other data (ex. Maps, GPS data, Land survey data)

Important Characteristics of Aerial

Photos for GIS (Curran 1989)

Wide availability

Low cost compared with other

remotely sensed images

Wide area views

Time-freezing ability

High spectral and spatial resolution

Three-dimensional perspective

Satellite Images

Collected by sensors on board a satellite, which are then relayed to ground stations and then computer-processed to produce images

Can be used to detect features not readily apparent to the naked eye (ex. Sedimentation, moisture content, ground temperature variations)

Processing is needed for data reduction, georeferencing, enhancing, and data integration

Examples: Landsat, SPOT, Ikonos, Quickbird, AVHRR

Advantages of Satellite Images

Easy to transfer/transport -- always available in digital form

Specific features can be highlighted by manipulating the displayed wavebands

Repeated converage of the Earth – important for temporal analysis and continuous monitoring

Large coverage area – useful for regional or national mapping applications

Low cost compared with other data sources

Ability to acquire current/timely images

Accurate and complete

Uniform standards across areas

Ground/Land Surveying Data

Using tapes, transits, theodolites, total

stations, etc.

Used to collect field data such as

coordinates, elevations, and distances

Data collected are in analog format (written

down in paper) which still need to be

transformed to digital format for use in GIS

GPS (Global Positioning

Systems) Data

Relatively new technique of field data collection

Radio waves/signals from GPS satellites are used to pinpoint location

Originally designed for real-time navigation

Can store collected coordinates and associated attribute information, which may be downloaded directly into a GIS database

Accuracy ranges from 100 meters to a few centimeters

Categories of Geographic Data

Acquisition

Primary – collected through first-hand

observation

Secondary – data collected by another

individual or organization; most are published

data

Primary Raster and Vector Data

Raster Data

satellite images

scanned aerial photographs

Vector Data

Land survey points

GPS observation data

Methods of Data Acquisition

1. Raster Data Acquisition

Scanning

Photogrammetry

Remote sensing

2. Vector Data Acquisition

Manual digitizing

Computer-assisted digitizing

Field surveying

GPS surveying

3. Attribute Data Acquisition

Keyboard entry

Scanning

Most commonly used method when

raster data is required

Accuracy depends on the scanner

quality (resolution), quality of the

image processing software used to

process the scanned data, and

quality/complexity of source

document

Manual Digitizing

Most common method of encoding

geographic features from paper

maps to vector GIS

Used when topology of features is

important

May be used for extraction of spatial

features from maps and aerial

photos

Uses a Table Digitizer which is

linked to a computer

Manual Digitizing

One of the main sources of positional error in

GIS

Accuracy depends on scale/resolution of source

map and quality of equipment and software used

Errors are usually due to:

Incorrect registration of map features on the

digitizer table (‘hand-wobble’)

Lack of experience of the digitizer

Time-consuming and tedious, especially for a

large amount of data

Manual Digitizing Procedures

1. Preparation

2. Creation of a digitizing template

3. Map digitizing

4. Post digitizing data processing

Preparation

Getting the map and digitizer ready

Check quality of map/s to be digitized,

identifying control points for georeferencing,

checking/calibrating digitizer

Establish specifications of feature codes, line

types, and approaches to data capture,

according to acceptable data standards

Creation of a Digitizing

Template

Digitizing template – contains tic marks, neat

lines, and graphical elements common to all

layers (ex. Boundaries and water bodies)

Enables multiple layers to be registered

perfectly with each other

Minimizes amount of work

Map Digitizing

Begins by registering map mounted on the

digitizing table to the digital map on the

computer screen

Not necessary to follow a particular sequence

for digitizing graphical elements

No need to digitize points at which lines

intersect

Intersecting lines will be automatically broken

down into line segments during topology building

Using a Manual Digitizing Table

1. Registration – map is fixed firmly on the

table; five or more control points are

identified on the map, their coordinates are

noted, and they are digitized

2. Digitizing point, line, and polygon features

3. Adding attribute information – to be linked to

the digitized features

Post Digitizing Data Processing

Checking for errors/omissions done in the

digitizing process

When errors/omissions are detected, it is

sometimes necessary to go back to the

digitizing process

Map must remain in its original position to retain

the registration previously made

Modes for Manual Digitizing

1. Point Mode A start and end node is recorded to define a line

Points between the start and end nodes are recorded for more complex lines/curves

More popular because it allows more operator control

Results in a smaller data file

2. Stream Mode Requires more skill than point mode digitizing

Generates larger files compared to point mode

The digitizer is set to record points according to a pre-determined time interval or distance interval

Generation of points begins upon the recording of the start node and terminates once the end node is recorded

Number of points is determined by the speed at which the mouse cursor is moved over a line/feature

Computer-Assisted Digitizing

Heads-up or On-screen digitizing

May be automatic or semi-automatic

Used instead of manual digitizing when a large number of complex maps is to be digitized in a short period of time

Popularity has grown considerably due to improved hardware design, software capabilities, and data-compression techniques

Very efficient and time-saving

Proprietary hardware and software are required very expensive

Semi-Automatic Digitizing

Process

1. Scanning map to the computer (raster format)

2. Operator moves cursor to a position at the start

of a line/contour and activates the software

3. Software automatically converts the raster data

to vector by following the pixels until it

encounters a break

4. Operator moves the cursor to another position

Keyboard Entry/Keycoding

Used for entering tabular/attribute data, which are commonly

only available in paper form, into the GIS database

Examples: vegetation classes, polygon identifiers, soil

types, topographic detail, etc.

May involve numeric, alphanumeric, or logical data

May be done through keyboard entry or text scanning (OCR)

Manageable for a small amount of data

Disadvantages:

Not feasible for a large amount of data

Prone to typographical errors

Electronic Data Transfer

Used when data is already in digital form

Usually followed by data conversion,

particularly when the transferred data is in a

different format than what is required

Data Editing

Errors and inaccuracies during data

acquisition and input translate into errors in

the GIS

Before further analyses are made, these

errors should be corrected to prevent the

errors from propagating to generated

information

Common Errors in Geographic

Data

Error Description

Missing entities Missing points, lines or

boundary segments

Duplicate entities Features that have been

digitized twice

Mislocated entities Features digitized in the

wrong place

Missing labels Unidentified polygons

Common Errors in Geographic

Data

Error Description

Duplicate labels Two or more identification

labels for a single polygon

Digitizing artifacts Undershoots, overshoots,

misplaced nodes, loops and

spikes

Noise

Irrelevant data entered

during digitizing, scanning or

data transfer

Raster Data Editing

Refers to correcting specific contents of

raster images

To produce a clean raster image which will

meet data-processing standards

Can better be done using digital image

processing packages, instead of GIS

packages

Raster Data Editing Functions

Filling holes and gaps

Edge smoothing and boundary simplification

– remove or fill single-pixel irregularities

along line edges

Deskewing – rotate the image by a small

angle to align with axis to be used

Speckle removal or filtering – remove noise

or random pixels

Raster Data Editing Functions

Erase or delete – manually removing unwanted

pixels/speckles

Thinning – reduce the width of linear features to

a single cell

Clipping/Subsetting – cut/remove a specific

portion of the image to have a new, smaller

image

Drawing and Rasterization – add vector graphics

or text to a raster image and convert them to a

raster form

Common Raster Editing

Functions for GIS

Vector Data Editing

Post digitizing process designed to ensure

integrity of the data before using them in the

GIS

Steps in Vector Data Editing

1. Setting the editing environment

2. Topology building

3. Data editing and error correction

4. Joining adjacent layers

Setting the Editing Environment

Defining standards for editing, such as

tolerance

Edit tolerance cursor is able to select a point

when it is clicked within the defined tolerance

Weed tolerance digitized arcs shorter than

weed tolerance are filtered/removed

Grain tolerance digitized points too close to

one another are removed

Topology Building

Most important process in graphical data editing

A repetitive process a layer can only have a complete and final topology building when there are no more errors

Builds the topological structure and relationships for the graphical elements on a layer By assigning an internal identifier to each identified

graphical element and creating an associated attribute table

Important for error identification and automating corrections Errors are highlighted by the topology building commands

and may be corrected automatically

Data Editing and Error

Correction

Includes selecting, deleting, copying and

adding graphical elements, as well as

changing their properties

Important in topology building

Error-prone and time-consuming process

Joining Adjacent Layers

Needed when there are multiple map sheets

to be used

Ensures that all layers form a continuous

geographic database when joined together

Attribute Data Editing

Attribute errors – most difficult to detect since

the GIS doesn’t know which attributes are

correct and incorrect

Usually involves missing attribute values,

incorrect attribute values, or misplaced

attribute values

Generally done manually

Data Conversion

After input and editing of individual datasets,

it is usually necessary to process the data

before integrating them all into a single GIS

Process of converting data on one form to a

more useful format for the specific GIS

application

One of the most tedious, time-consuming,

and error-prone processes in GIS

Digital Data Conversion Process

1. Acquisition – digitizing existing maps, purchasing ready-made products, collecting new data using field surveying, GPS, photogrammetry, or remote sensing

2. Editing – cleaning acquired digital data to meet certain specifications

3. Formatting/Translating – converting digital data into the specific physical database format of the GIS

4. Linking – associating attribute data with the graphical data

Raster to Vector Conversion

Vectorization

Converting scanned raster images to vector

features (point, line, or polygons)

Results are visually problematic most of the

time

Vectorization Process

1. Raster Line-Thinning

2. Vector Line Extraction

3. Topological Reconstruction

4. Line Smoothing

Raster Line Thinning

‘skeletonizing’

Process of reducing raster linear features into

unit width

Vector Line Extraction

4-connect reconstruction -- search the 4

surrounding cells and join center points if present

8-connect reconstruction -- search the 8

surrounding cells and join center points if present

8-connect w/ redundancy elimination -- draw diagonal from 8-

cell search only if not already connected by orthogonal from

4-cell search

Topological Reconstruction

involves the creation of nodes at line

junctions, construction of arcs, and polygon

definition

Line Smoothing

Employed to make the resulting vectors more

visually appealing

during raster to vector conversion, the results are

usually jagged/crooked (especially for diagonal

lines)

Vectorization Methods

1. Manual – user selects and picks out

features to be converted

2. Automatic – entire raster image is

converted by the computer software

without user intervention

3. Semi-automatic – combination of

manual point picking and computerized

line tracing

– produces best results

Post Scanning Processing

1. Raster to vector conversion

2. Raster text conversion

3. Raster symbol conversion

4. Graphical data editing

5. Attribute data tagging

Raster to Vector Conversion

Changing raster images into vector graphics

May be done manually, automatically, or

semi-automatically

Major limiting factor is the map quality

Raster Text Conversion

Characters in the raster image are converted

to alphanumeric data using character

recognition (ex. OCR)

Involves a large amount of manual

verification of the results and correction of

errors

Raster Symbol Conversion

Cartographic symbols in the raster image are

converted to alphanumeric codes

Largely a manual task

Automated symbol recognition is a much more

difficult task than character recognition

No available standards in the form, size, and

codes of cartographic symbolss

Graphical Data Editing

Cleaning graphics by removing data

conversion errors

Attribute Data Tagging

Adding attribute data (e.g., feature identifiers,

feature codes, and contour labels) to the

graphical data

Vector to Raster Conversion

Rasterization

process of converting vector data (points,

lines and polygons) into raster data (series of

cells each with a discrete value)

Produces visually satisfactory results

May be problematic in terms of the attributes

assigned to pixels

Most evident along edges/boundaries (partial

cells)

Rasterization Process

1. Superimpose a grid (cell values initially

zero) on the vector map

2. Code/assign a value to the cells based on

the contained feature (whether point, line, or

polygon)

3. Fill the interior of the polygon outline with

the corresponding polygon value assigned

to the boundary

Rasterization of Lines

Data Integration

Combining data from various sources and in

various formats to be able to extract

more/better information

Two types of spatial data

integration:

1. Horizontal

Integration – ‘tiling’;

merging of adjacent

data sets

2. Vertical Integration –

map overlay;

stacking of data

sets/layers

Map Overlay

Examples of Adjustments

Required for Data Integration Mathematical Transformations – translation, scaling, rotation, or

skewing

Rectification – rearrangement of the location of objects to correspond to a specific (geodetic) reference system

Registration – rearrangement of the location of objects of one set so they correspond with those of another, without referring to a specific reference system

Rubber Sheeting – data set/layer is differentially ‘stretched’ so that tic points on the layer are moved to approximate the location of the corresponding ground control points or corresponding tic points in another layer

Edge Matching – employed to properly connect or line-up corresponding features in adjacent map sheets to create a seamless model

Mathematical Transformations

translatio

n

differentia

l scaling

rotation skewing

Rubber Sheeting

ground control

map locations

GIS file

POEC 1359 “Introduction to GIS” by Ron Briggs

Thank you!