Title: GIS Data Capture: Getting the Map into the Computer some background and extra material in Chapter 9, Longley et al
1GIS Data CaptureGetting the Map into the
Computersome background and extra material in
Chapter 9, Longley et al
2Overview
- Introduction
- Primary data capture
- Secondary data capture
- Data transfer
- Capturing attribute data
- Managing a data capture project
- Error and accuracy
3Data Collection
- Can be most expensive GIS activity
- Many diverse sources
- Two broad types of collection
- Data capture (direct collection)
- Data transfer
- Two broad capture methods
- Primary (direct measurement)
- Secondary (indirect derivation)
4Data Collection Techniques
Field/Raster Object/Vector
Primary Digital remote sensing images GPS measurements including VGI
Primary Digital aerial photographs Survey measurements
Secondary Scanned maps Topographic surveys
Secondary DEMs from maps Toponymy data sets from atlases
5Haiti Earthquake DisasterWeb Site of the Week
6Stages in Data Collection Projects
7Primary Data Capture
- Capture specifically for GIS use
- Raster remote sensing
- e.g., SPOT and IKONOS satellites and aerial
photography, echosounding at sea - Passive and active sensors
- Resolution is key consideration
- Spatial
- Spectral, Acoustic
- Temporal
8(No Transcript)
9Vector Primary Data Capture
- Surveying
- Locations of objects determines by angle and
distance measurements from known locations - Uses expensive field equipment and crews
- Most accurate method for large scale, small areas
- GPS
- Collection of satellites used to fix actual
locations on Earths surface - Differential GPS used to improve accuracy
10Total Station
11GPS Handhelds
text
geographic coordinates
photos
video
audio
Bluetooth, WiFi
12cell towers /- 500 m Google db of tower locations
Wi-Fi /- 30 m Skyhook servers and db
GPS /- 10 m iPhone uses reference network
Graphic courtesy of Wired, Feb. 2009
13Power to the PeopleVGI PPGIS
- Volunteered Geographic Information
- Wikimapia.org
- Openstreetmap.org
- Public Participation GIS
- GEO 599, Fall 2007
- Papers still online at dusk.geo.orst.edu/virtual/
14Example A Boon for International Development
Agencies
Kinshasa, Democratic Republic of Congo
Robert Soden, www.developmentseed.org
15International Development, Humanitarian Relief
Mogadishu, Somalia
Robert Soden, www.developmentseed.org
16Haiti Disaster, MapAction.org
17Citizen Sensors
UCLA Center for Embedded Networked Sensing,
http//peir.cens.ucla.edu
18Societal Issues(privacy, surveillance,
ethics)e.g., Google StreetView
Early and late May 2008
19More surveillance (electronic, video, biological,
chemical) integrated into national system
From Chris Peterson, Foresight Institute As
presented at OSCON 2008, Portland
20From Chris Peterson, Foresight Institute As
presented at OSCON 2008, Portland
Graphic Gina Miller
21Sewer monitoring has begun
The test doesnt screen people directly but
instead seeks out evidence of illicit drug abuse
in drug residues and metabolites excreted in
urine and flushed toward municipal sewage
treatment plants.
From Chris Peterson, Foresight Institute As
presented at OSCON 2008, Portland
22Secondary Geographic Data Capture
- Data collected for other purposes, then converted
for use in GIS - Raster conversion
- Scanning of maps, aerial photographs, documents,
etc. - Important scanning parameters are spatial and
spectral (bit depth) resolution
23Scanner
24Vector Secondary Data Capture
- Collection of vector objects from maps,
photographs, plans, etc. - Photogrammetry the science and technology of
making measurements from photographs, etc. - Digitizing
- Manual (table)
- Heads-up and vectorization
25Digitizer
26GEOCODING
- spatial information ---gt digital form
- capturing the map (digitizing, scanning)
- sometimes also capturing the attributes
- mapematical calculation, e.g.,
- address matching
WSW
27Managing Data Capture Projects
- Key principles
- Clear plan, adequate resources, appropriate
funding, and sufficient time - Fundamental tradeoff between
- Quality, speed and price
- Two strategies
- Incremental
- Blitzkrieg (all at once)
- Alternative resource options
- In house
- Specialist external agency
28The Role of Error
- Map and attribute data errors are the data
producer's responsibility, - GIS user must understand error.
- Accuracy and precision of map and attribute data
in a GIS affect all other operations, especially
when maps are compared across scales.
29Accuracy
- closeness to TRUE values
- results, computations, or estimates
- compromise on infinite complexity
- generalization of the real world
- difficult to identify a TRUE value
- e.g., accuracy of a contour
- Does not exist in real world
- Compare to other sources
30Accuracy (cont.)
- accuracy of the database accuracy of the
products computed from database - e.g., accuracy of a slope, aspect, or watershed
computed from a DEM
31Positional Accuracy
- typical UTM coordinate pair might be
- Easting 579124.349 m
- Northing 5194732.247 m
- If the database was digitized from a 124,000 map
sheet, the last four digits in each coordinate
(units, tenths, hundredths, thousandths) would be
questionable
32Positional Accuracy
A useful rule of thumb is that positions measured
from maps are accurate to about 0.5 mm on the
map. Multiplying this by the scale of the map
gives the corresponding distance on the ground.
33Testing Positional Accuracy
- Use an independent source of higher accuracy
- find a larger scale map (cartographically
speaking) - use GPS
- Use internal evidence
- digitized polygons that are unclosed, lines that
overshoot or undershoot nodes, etc. are
indications of inaccuracy - sizes of gaps, overshoots, etc. may be a measure
of positional accuracy
34Precision
- not the same as accuracy!
- repeatability vs. truth
- not closeness of results, but number of decimal
places or significant digits in a measurement - A GIS works at high precision, usually much
higher than the accuracy of the data themselves
35Accuracy vs. Precision
36Accuracy vs. Precision
37Components of Data Quality
- positional accuracy
- attribute accuracy
- logical consistency
- completeness
- lineage
38Midterm
39Midterm
- Multiple choice on scantron/bring 2 pencil
- Major concepts moreso than details
- Reviewing LECTURES is key ?PPT files
- background extra in Chapters 1, 3-4, 9, 20 in
Longley et al. - Will not include
- Web Sites of the Week (WSWs)
- Labs
- Learning Assessment/Practice Questions on class
web site