Georeferencing Introduction:
Collaboration to Automation
Michelle Koo, Carol Spencer, David Bloom, Nelson Rios
Museum of Vertebrate Zoology (UC Berkeley), VertNet,
& Tulane University
1. Georeferencing
2. Collaborations
3. Automation
What is a georeference?
A numerical description in a coordinate
system of a place.
What we have:
Localities we can read
ID
1
2
3
4
5
6
7
8
9
Species
Lynx rufus
Pudu puda
Canis lupus
Felis concolor
Lama alpaca
Panthera leo
Sorex lyelli
Orcinus orca
Ursus arctos
Locality
Dawson Rd. N Whitehorse
cerca de Valdivia
20 mi NW Duluth
Pichi Trafúl
near Cuzco
San Diego Zoo
Lyell Canyon, Yosemite
1 mi W San Juan Island
Bear Flat, Haines Junction
What we want:
Localities we can map
Darwin Core
•Metadata standards initially built off of Dublin Core
Metadata Standards
•Collections of any kind of biological objects or data.
•Terminology associated with biological collection data.
•Striving for compatibility with other biodiversity-related
standards.
•Facilitating the addition of components and attributes of
biological data.
Darwin Core Location Terms
 HigherGeography
 waterbody, island, islandGroup
 continent, country, countryCode,
stateProvince, county, municipality
 locality
 minimumElevationInMeters,
maximumElevationInMeters,
minimumDepthInMeters,
maximumDepthInMeters
Darwin Core Georeference Terms










decimalLatitude, decimalLongitude
geodeticDatum
coordinateUncertaintyInMeters
coordinatePrecision
pointRadiusSpatialFit
footprintWKT, footprintSRS, footprintSpatialFit
georeferencedBy, georeferenceProtocol
georeferenceSources
georeferenceVerificationStatus
georeferenceRemarks
What is a georeference?
A numerical description of a place that
can be mapped.
“Davis, Yolo County, California”
Coordinates:
38.5463
-121.7425
Coordinates:
38.5463
-121.7425
Horizontal
Geodetic
Datum:
NAD27
Horizontal
Geodetic
Datum:
NAD27
“point method”
Data Quality
data have the potential to be used in ways
unforeseen when collected.
 the value of the data is directly related to the fitness
for a variety of uses.
 “as data become more accessible many more uses
become apparent” – Chapman 2005
 the MaNIS/HerpNET/ORNIS guidelines follow best
practices (Chapman and Wieczorek 2006) to enhance
data quality and value

What is an acceptable georeference?
A numerical description of a place that
can be mapped
and that describes the spatial extent of a
locality
and its associated uncertainties.
“Davis, Yolo County, California”
Coordinates:
Coordinates:
38.5486
-121.7542
38.5486
-121.7542
38.545
-121.7394
38.545
-121.7394
Horizontal
Geodetic
Datum:
NAD27
Horizontal
Geodetic
Datum:
NAD27
“bounding-box method”
“Davis, Yolo County, California”
Coordinates:38.5468
38.5468-121.7469
-121.7469
Coordinates:
HorizontalGeodetic
GeodeticDatum:
Datum:NAD27
NAD27
Horizontal
MaximumUncertainty:
Uncertainty:8325
8325mm
Maximum
“point-radius method”
What is an ideal georeference?
A numerical description of a place that
can be mapped
and that describes the spatial extent of a
locality
and its associated uncertainties
as well as all possibilities.
“Davis, Yolo County, California”
“shape method”
“20 mi E Hayfork, California”
“probability method”
Method Comparison
point
easy to produce
no data quality
bounding-box
simple spatial queries
difficult quality assessment
point-radius
easy quality assessment
difficult spatial queries
shape
accurate representation
complex, uniform
probability
accurate representation
complex, non-uniform
Georeferencing Using
MaNIS/HerpNET/ORNIS
Guidelines
Parallels of
Latitude
Meridians of
Longitude
Graticular
Network
MaNIS/HerpNET/ORNIS (MHO) Guidelines
http://manisnet.org/GeorefGuide.html
► uses point-radius representation of
georeferences
► circle encompasses all sources of uncertainty
about the location
► methodology formalizes assumptions,
algorithms, and documentation standards
that promote reproducible results
► methods are universally applicable
MHO Guidelines
► Think of georeferencing as “many-stepped process”
– MHO projects produced a first pass. Then
validation and refinement should be done using
itineries, field notes, collector verification and by
mapping the localities and making these maps
available on-line.
Data Quality
►
“Fitness of use” of the data
►
As a collector, you may have an intended use for the data
you collect but data have the potential to be used in
unforeseen ways…. The value of your data is directly
related to the fitness for a variety of uses.
►
As data become more accessible many more uses become
apparent. – Chapman 2005, Chapman and Wieczorek 2006
►
We are using the MHO methods as a tool to enhance data
quality
Maximum Error Distance from
Uncertainties:
►
Uncertainty is a “measure of the incompleteness of one’s
knowledge or information about an unknown quantity whose
true value can be established if a perfect measure device were
available.” (Cullen & Frey 1999)
►
In MHO Guidelines, this is defined as the numerical value for
the upper limit of the distance from the coordinates of a
locality to the outer extremity of the area within which the
whole of the described locality must lie (i.e., what can be
mistaken for that locality based on the description given).
Extents:
Extent-
the geographic
range, magnitude or distance
that a location may actually
represent. (With a town, the
extent is the polygon that
encompasses the area inside
the town’s boundaries.)
Linear
extent- what we use
for the Point-Radius Method.
Defined as the distance from
the geographic center of the
location to the furthest point of
the geographic extent of the
location.
Precision and Accuracy:
Always use as many decimal places as given by the coordinate
source.
► A measurement in decimal degrees given to five decimal
places is more precise than a measurement in degrees
minutes seconds.
► False precision will result if data are recorded with a greater
number of decimal points (e.g., when converting from DMS to
decimal degrees).
► Always record the accuracy of your GPS readings (how well
the GPS measures the true value of the location). The
accuracy is given at the same time as the coordinate, but
usually will not be recorded with the coordinates when you
output them on recreational GPS units. Otherwise, default
accuracy is assumed 30 m, so stating your accuracy is better.
►
Geographical Concepts:

Geodetic Datum: defines
the position of the origin,
scale, shape, and
orientation of a 3dimensional model of the
earth. Example: WGS84.

Coordinate System: defines
the “units of measure” of
position with respect to the
datum. Example: latitude,
longitude in degrees,
minutes, seconds
Map Projections:

Mathematical transformations of
the 3-D model of the surface of the
earth onto a 2-D map.

Many different kinds (e.g., conical,
cylindrical, azimuthal) – all are
compromises in distortions (either
area, shape, distance, or direction),
but some preserve areas or
distances.

When measuring distances on
paper maps, use an equal distance
projection, if available, otherwise
understand the implications.
Georeferencing Concepts
Named place: a place of
reference in a locality
description. Example: “Davis”
in “5 mi N of Davis”
Areal extent: the geographic
area covered by a named place
(feature). Example: the area
inside the boundaries of a
town.
Linear extent: the distance
from the geographic center to
the furthest point of the areal
extent of a named place.
Georeferencing Concepts
► Offset: the distance
from a named place.
Example: “5 mi” in “5 mi
NE of Beatty”.
► Heading: the direction
from a named place.
Example: “NE” in “5 mi
NE of Beatty”.
Georeferencing Concepts
► coordinateUncertaintyInMeters:
“The horizontal distance (in meters) from the given
decimalLatitude and decimalLongitude describing the
smallest circle containing the whole of the Location.
Leave the value empty if the uncertainty is unknown,
cannot be estimated, or is not applicable (i.e., there are
no coordinates). Zero is not a valid value for this term.”
(from Darwin Core)
► Maximum Error Distance: same as
coordinateUncertaintyInMeters, except the units are the
same as in the locality description, not necessarily
meters.
Sources of uncertainty:
Scale
20° 30’ N 112° 36’ W
Coordinate Uncertainty
Map scale
The extent of the locality
GPS accuracy
Unknown datum
Imprecision in direction
measurements
Imprecision in distance
measurements
(e.g., 1 km vs. 1.1 km)
Uncertainty (ft)
Uncertainty (m)
1:1,200
3.3 ft
1.0 m
1:2,400
6.7 ft
2.0 m
1:4,800
13.3 ft
4.1 m
1:10,000
27.8 ft
8.5 m
1:12,000
33.3 ft
10.2 m
1:24,000
40.0 ft
12.2 m
1:25,000
41.8 ft
12.8 m
1:63,360
106 ft
32.2 m
1:100,000
167 ft
50.9 m
1:250,000
417 ft
127 m
1. Georeferencing
2. Collaborations
3. Automation
Collaborative Distributed
Database Portals for Vertebrates
Collaborations
MaNIS Localities Georeferenced
n = 326k localities (1.4M specimens)
r = 14 localities/hr (point-radius method)
t = 3 yrs (~40 georeferencers)
ORNIS Localities Georeferenced
n = 267k localities (1.4M specimens)
r = 30 localities/hr (point-radius method)
t = 2 yrs (~30 georeferencers)
HERPNET Localities Georeferenced
n = 646 k localities (1.8 M specimens)
r = 15 localities/hr (point-radius method)
t =5 yrs (111 georeferencers)
Scope of the Problem for
Natural History Collections
~2.5 Billion (109)
~6 records per locality*
~14 (30) localities per hour*
~15,500 (7,233) years
* based on the MaNIS (ORNIS) Project
The Collaboration continues…
1. Georeferencing
2. Collaborations
3. Automation
Automation
Tools for Georeferencing
BioGeomancer Classic
GeoLocate
Georeferencing Calculator
DIVA-GIS
http://www.biogeomancer.org