Data acquisition and integration Section 1

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Data acquisition and integration Section 1

• Lecture notes
• Helena Mitasova,
• NCSU MEAS

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Outline

• mapping data acquisition
• coordinate systems and transformations
• geospatial data models

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Data acquisition

• Mapping technologies
• which you have used for your work?

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Data acquisition

• Mapping technologies
• which you have used for your work?
• Passive and active aerial and satellite sensors
• On-ground surveys (RTK)GPS, total station,
  laser scanner
• In situ thematic data collection climate and air
  quality stations, water sampling stations,
  species mapping, soil sampling georeferencing
  usually through GPS

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Data acquisition Remote Sensing

• Sensors
• Satellite examples ?
• Airborne examples ?

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Data acquisition Remote Sensing

• Sensors
• Satellite examples
• LANDSAT 1-7
• SPOT, ASTER
• AVHRR, MODIS
• Iconos, Quickbird
• SRTM, ICESAT I
• Airborne examples
• Photogrammetry
• Lidar

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Data acquisition Remote Sensing

• Satellite examples
• LANDSAT 1-7 (since 1972), 30m multispec., 15m
  panchrom.
• SPOT 1-5 (20-2.5m image, 30m DEM, France),
• AVHRR(Adv. Very High Res. Radiometer 1km),
• Terra MODIS (500m, temp, aerosol), ASTER (30m,
  temp, DEM)
• Iconos, Quickbird (0.60-2.4 m resolution)
• SRTM Shuttle Radar Topography Mission, lidar
  (ICESAT I)
• Airborne examples
• Photogrammetry ortho, oblique, infrared,
  multispectral
• Lidar
• Future UAV, on-board processing, sensor networks

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Satellite Remote Sensing
Sensors
Data
SRTM
LANDSAT
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Airborne Remote Sensing
Sensors
Data x,y,z points
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Data acquisition ground-based

• GPS, RTK-GPS
• terrestrial photogrammetry static and mobile
• laser scanners static or mobile on cars/robots
• discipline specific monitoring and sampling
  stations (econet station, ISCO sampler)
• Products georeferenced points with attributes or
  streetview imagery

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Data acquisition ground based
Ground based imagery

• Satellite imagery

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Data acquisition ground based
Data

• Equipment

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Data acquisition ground based

• Surveying robot with optical
• camera and laser scanner

Real time trafic data from webcam
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From mapping to GIS

• Mapped data (imagery or points) are transformed
  into georeferenced, discrete representations of
  landscape, atmospheric or marine features,
  objects or phenomena
• Workflow?

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From mapping to GIS

• Workflow
• georeferencing (real-time during mapping with
  GPS)
• feature or theme extraction
• building GIS data model representation (raster or
  vector with attribute database)

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Georeferencing

• Georeferenced data location on Earth is
  represented in a Coordinate Referenced System
• Many coordinate systems exist, they evolve over
  time as accuracy of the Earth measurements
  improves

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Coordinate systems

• Geographic coordinate system
• (learn it if you don't know it!)
• geoid -gt ellipsoid gt (sphere) -gt
  latitude/longitude
• GPS, large regions, data exchange (USGS, Google)
• units are ? degree-minutes-seconds
• requires complex algorithms for distances, areas

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Coordinate systems

• Projected Reference Systems - cartesian
  coordinate systems based on projections
• geoid ellipsoid - developable surface plane
  x,y
• developable surfaces ?
• type of distortion ?

image from NetelerMitasova, 2008
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Cartographic Projections

• Projected Reference Systems - cartesian
  coordinate systems based on projections
• geoid ellipsoid - developable surface plane
  x,y
• developable surfaces
• conic, cylindrical, azimuthal (plane)
• type of distortion
• conformal, equidistant, equal area

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Cartographic Projections

• Projected Reference Systems - cartesian
  coordinate systems based on projections

www.progonos.com/furuti/MapProj/Normal/TOC/cartTOC
.html
excellent, easy to understand material about
projections and map properties with lots of
graphics and mathematical foundations, see also
links to references
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National and state systems

• National/State Coordinate systems defined by
• Reference spheroid/geoid and datum?
• Vertical datum ?
• Projection ?
• Goal was to minimize distortions on maps that
  were used to measure distances and areas less
  important now when distances and areas are
  computed directly from data

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National and state systems

• Reference geoid and datum
• North American Clarke 1866 - NAD27, Grs80 -
  NAD83
• World geodetic system WGS84
• Vertical datums NGVD29 - National Geodetic
  Vertical Datum 1929, NAVD88 North american
  Vertical Datum 1988
• Projections
• Lambert Conformal Conic (LCC) states
• Universal Transverse Mercator (UTM) USGS,
  military
• Albers Equal Area (conic) USGS national map

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On-line mapping systems

• Spherical Mercator cylindrical on sphere, large
  distortions
• Official name Popular Visualization CRS and
  sphere
• Used by Google, Microsoft and others

EPSG (group that maintains standardized list of
parameters for official georeference coordinate
systems ) did not like it We have reviewed
the coordinate reference system used by
Microsoft, Google, etc. and believe that it is
technically flawed. We will not devalue the EPSG
dataset by including such inappropriate geodesy
and cartography. In 1989, seven North American
professional geographic organizations adopted a
resolution that called for a ban on all
rectangular coordinate maps (especially
Mercator). http//geography.about.com/library/week
ly/aa030201b.htm http//demonstrations.wolfram.com
/WorldMapProjections/
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Popular visualization CRS
The reference system was eventually included
under the code 3785 - not recommended for
professional work
Winkel tripel projection - hybrid, for world only
http//www.math.ubc.ca/israel/m103/mercator/merca
tor.html
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Coordinate systems in GIS

• Representation of coordinate systems in GIS
• Metadata file
• ESRI PRJ file
• EPSG codes provided by OGP - Int. Org. of Oil and
  Gas Producers Surveying and Positioning
  Committee, formerly EPSG european petroleum
  survey group
• http//mapserver.gis.umn.edu/docs/faq/epsg_codes
• Vertical datum support often missing in GIS
  specialized tools

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Coordinate systems in GIS

• Coordinate system definitions for the dataset
  used for assignments
• ESRI PRJ file (readable ASCII)
• PROJCS"NAD_1983_StatePlane_North_Carolina_FIPS_32
  00",
• GEOGCS"GCS_North_American_1983",DATUM"D_North_Am
  erican_1983",
• SPHEROID"GRS_1980",6378137.0,298.257222101,
• PRIMEM"Greenwich",0.0,UNIT"Degree",0.0174532925
  199433,
• PROJECTION"Lambert_Conformal_Conic",
• PARAMETER"False_Easting",609601.22,
  PARAMETR"False_Northing",0.0,
• PARAMETER"Central_Meridian",79.0,
• PARAMETER"Standard_Parallel_1",34.3333333333333
• PARAMETER"Standard_Parallel_2",36.16666666666666
  ,
• PARAMETER"Latitude_Of_Origin",33.75,UNIT"Meter"
  ,1.0
• EPSG translated to input parameters of the PROJ
  software
• NAD83(High Accuracy Reference Network HARN) /
  North Carolina
• lt3358gt projlcc lat_136.16666666666666
  lat_234.33333333333334 lat_033.75 lon_0-79
  x_0609601.22 y_00 ellpsGRS80 unitsm
  no_defs

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Coordinate transformations

• Data often come in different coordinate systems
• USGS, federal agencies ?
• State agencies ?
• Older data may have different datums?
• Coordinate transformations
• x,y -gt ??? -gt x,y
• on-fly transformation may be time consuming,
  especially for raster resampling/reinterpolatio
  n to regular grid is required

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Coordinate transformations

• Data often come in different coordinate systems
• USGS, federal agencies Geographic coordinates,
  Albers equal area, UTM
• State agencies State Plane
• Older data may have different datums (NAD27,
  NAD83)
• Coordinate transformations
• x,y -gt longitude, latitude -gt x,y
• on-fly transformation may be time consuming,
  especially for raster resampling/reinterpolatio
  n to regular grid is required

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Geospatial data models

• Mapped, georeferenced data are transformed into
  discrete GIS representations
• Two different types of objects/phenomena
• continuous fields wf(x,y), wf(x,y,z)
• properties and representations?
• discrete objects/features lines, points or areas
  with attributes
• properties and representations?

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Geospatial data models

• Mapped, georeferenced data are transformed into
  discrete GIS representations
• Two different types of objects/phenomena
• continuous fields wf(x,y), wf(x,y,z)
• each point in space is assigned a distinct value,
  change between two neighboring points is
  relatively small elevation, precipitation
• represented as raster layers, but meshes, TIN,
  isolines or points are also used.
• discrete objects/features lines, points or areas
  with attributes
• represented as geometry(shape) with attribute
  table or object based (geodatabase) raster
  representation is also used roads, streams,
  census blocks, land use, schools

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Geospatial data models

• continuous fields discrete
  objects/features

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Summary and references

• Data acquisition
• Bolstad GIS fundamentals, Ch. 5,
• Chang Ch. 5.2, 6
• Coordinate systems and transformations,
  georeferencing
• Bolstad ch. 3, Chang Ch. 2,7, Neteler Ch.2.2,
  others
• Data models raster / vector, continuous /
  discrete
• Chang Ch. 3,4,5, Neteler Ch. 2.1, 4.1.1 and 4.2.1
• links on the relevant slides