Michelle Koo, Carol Spencer, David Bloom, Nelson Rios Museum of Vertebrate Zoology (UC Berkeley), VertNet, & Tulane University Georeferencing Introduction: Collaboration to Automation

1. Georeferencing 2. Collaborations 3. Automation

What is a georeference? A numerical description in a coordinate system of a place.

IDSpecies Locality 1Lynx rufusDawson Rd. N Whitehorse 2Pudu pudacerca de Valdivia 3 Canis lupus 20 mi NW Duluth 9Ursus arctosBear Flat, Haines Junction 4Felis concolorPichi Trafúl 5Lama alpacanear Cuzco 6Panthera leoSan Diego Zoo 7Sorex lyelliLyell Canyon, Yosemite 8Orcinus orca1 mi W San Juan Island What we have: Localities we can read

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” “point method” Coordinates: Horizontal Geodetic Datum: NAD27 Coordinates: Horizontal Geodetic Datum: NAD27

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” “bounding-box method” Coordinates: Horizontal Geodetic Datum: NAD27 Coordinates: Horizontal Geodetic Datum: NAD27

“Davis, Yolo County, California” “point-radius method” Coordinates: Horizontal Geodetic Datum: NAD27 Maximum Uncertainty: 8325 m Coordinates: Horizontal Geodetic Datum: NAD27 Maximum Uncertainty: 8325 m

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”

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 Method Comparison probability accurate representation complex, non-uniform

Parallels of Latitude Meridians of Longitude Graticular Network Georeferencing Using MaNIS/HerpNET/ORNIS Guidelines

MaNIS/HerpNET/ORNIS (MHO) Guidelines ► 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).

 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. Extents:

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.

 Geodetic Datum: defines the position of the origin, scale, shape, and orientation of a 3- dimensional 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 Geographical Concepts:

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.

 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. Georeferencing Concepts

Sources of uncertainty:  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) 20° 30’ N 112° 36’ W ScaleUncertainty (ft)Uncertainty (m) 1:1, ft1.0 m 1:2, ft2.0 m 1:4, ft 4.1 m 1:10, ft8.5 m 1:12, ft10.2 m 1:24, ft 12.2 m 1:25, ft12.8 m 1:63, ft32.2 m 1:100, ft50.9 m 1:250, ft127 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 (10 9 ) ~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 GeoLocate DIVA-GIS Georeferencing Calculator BioGeomancer Classic