Methods to acquire GIS databases, particularly via the Internet
Methods to create new GIS databases
Processes to edit existing GIS databases
Types and sources of error potentially associated with GIS databases
Capitol Tech U Doctoral Presentation - April 2024.pptx
Chapter3 is344(gis)(acquiring, creating, and editing gis db )
1. 1
Abdisalam Issa-Salwe, Taibah University
Michael G. Wing and Pete Bettinger (2008): Geographic Information Systems: Applications in Natural Resource Management,
2nd Editon. Oxford University Press.
Acquiring, Creating, and
Editing GIS Databases
(IS344)
Chapter 3
Abdisalam Issa-Salwe
Information Systems Department
College of Computer Science & Engineering
Taibah University
Chapter 3 Objectives
Methods to acquire GIS databases,
particularly via the Internet
Methods to create new GIS databases
Processes to edit existing GIS databases
Types and sources of error potentially
associated with GIS databases
2. 2
Four general cases of GIS databases at
most organizations
The data necessary for project work
Don’t exist
Do exist but were created for other general uses and
may not be completely suitable for your project
Do exist but were created for other specific uses and
may not be completely suitable for your project
The data are in place and in good order for your
project!
Typically, you’ll have to acquire data
Hire a contractor to create or edit GIS data
Use a GPS or other device to capture data
Modifying an existing database
Create a new GIS database
Digitizing
Using/buying data from another organization
Downloading data from the Internet
3. 3
Acquisition processes
Using an Internet browser to select and
download
FTP- File Transfer Protocol
Transfer on hardware
Tape
External harddrive
CD or DVD
USB key
Floppy
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Figure 3.1. Measurement reference points for the Daniel
Pickett forest to enable digitizing of additional
landscape features or the creation of new GIS
databases.
Roads
Stands
Reference points
(with associated
X and Y
coordinates)
4. 4
Figure 3.2. A landslide drawn on a map with a regular
sharpened pencil (upper left), a marker (upper right), a
sharpened pencil, yet in a sloppy manner – the landslide area
is not closed (lower left), a marker, yet in a sloppy manner - the
landslide area is barely closed (lower right).
(a) (b)
(c)
Figure 3.3. A timber stand (a) in vector format, from the
Brown Tract, scanned (b) or converted to a raster
format using 25 m grid cells, then converted back to
vector format (c) by connecting lines to the center of
each grid cell.
5. 5
Editing GIS databases
Reasons for editing
Changing a spatial projection
Edge matching GIS databases to other databases
Generalization and transformation processes
necessary to convert a GIS database to a specific
format or resolution
In natural resources, updates may occur
annually to keep pace with timber inventory
Growth, disturbance, harvesting
Updating processes
Can be laborious and error-prone
Verification protocols can help
Assures that data variables are reasonable or
meet some standard
Should be in place for spatial and attribute
characteristics
Should involve multiple people
6. 6
Figure 3.4. A
generalized process for
updating a forest
inventory GIS database.
Delineate changes
to be made to
inventory
Inventory forester
Check data for
mistakes and
omissions
Digitize changes
to spatial data,
encode inventory
Integrate into
GIS
database
Information systems
analysts
Check data for
mistakes and
omissions
Check data for
mistakes and
omissions
Check data for
mistakes and
omissions
maps, data files
maps, data files
GIS
databases
maps, data files
maps, data files
GIS
databases
maps, data files
Verification
process #1
Verification
process #2
Verification
process #3
Verification
process #4
Editing attributes
Attributes are the values used to describe
landscape features in a GIS database
Fields, variables, columns, data, etc.
Attributes may need to be updated overtime
Vegetation type, basal area, age, volume (mbf)
Easy to make mistakes, particularly with major
updates
Verification processes can check whether values
are in the appropriate range
7. 7
Editing spatial position
As the locations or shapes of spatial features
change, their coordinates will need to be
changed within the GIS database
Editing procedures for this purpose vary widely
among software products
Typically, a database is first made “editable”
The user then makes edits
Points, lines, and/or polygons moved, copied, created, or
deleted
The edits are saved
Often, a time-consuming procedure
Consistency in spatial position
When updating or creating new data,
inconsistencies may result as the data are
incorporated into existing databases
8. 8
Inconsistency
Roads
Timber
stands
Figure 3.6. Spatial
inconsistency
between a timber
stand GIS database
and a roads GIS
database.
Figure 3.5. A timber stand drawn more
precisely (top) and less precisely (bottom).
Note that the lines on the south and eastern
portion of the figures are different.
Error in GIS databases
Errors arise from many sources:
Editing, encoding, hardware, and others
Three primary sources of error in GIS data
Systematic
Human
Random
9. 9
Systematic errors
Caused by problems in the processes
and/or tools used to measure spatial
locations or attribute data
Sometimes called cumulative errors since
they add up during data collection
Sometimes called instrumental
Can be removed if identified and
quantified
Human errors
Sometimes called gross errors or blunders
As the name suggests, these are
introduced through carelessness or other
inattention
Verification processes can be used to
control human errors
Data collection and editing protocols can
also assist in limiting human errors
10. 10
Random errors
An almost unavoidable by-product of measuring
and describing landscape data
No matter how careful we are in data collection
procedures, there will almost always be some
slight variance from the true measurement
Random errors are the errors that remain after
systematic and human errors have been
removed
Managing random errors
We assume that random errors follow a normal
(Gaussian) distribution
They cluster around a mean value or center
Least squares adjustments can distribute and
minimize the error among all measurements in a
feature
More frequently, and especially in forestry, we
assume that random errors will cancel each
other out
For this reason, random errors are sometimes called
compensating errors
11. 11
Types of errors in GIS databases
Positional errors occur when things are in the
wrong place
Can result from poor registration or inaccurate
coordinate input during the digitizing process
Are sometimes handled with accuracy
statements: “90 percent of landscape features
are within 150 meters of their true position”
A root mean square error (RMSE) is sometimes
used to set or describe an accuracy standard
A RMSE assesses the error between a mapped point
and its on-the-ground (true) equivalent
Digitized road segment
Real-world representation #1
Real-world representation #2
Real-world representation #3
Figure 3.7.
Uncertainty of
the local shape of
a road segment
(after Schneider
2001).
12. 12
Other types of errors
Attribute errors
Incorrect values assigned to features
Can result from keyboard entry
Verification processes can help alleviate these
Computational errors
Can be introduced during procedures
Generalization
Vector-to-raster transformations
Interpolations
Results should be carefully considered to judge
appropriateness of procedures