In this section we discuss best practices for capturing and recording information so that it can be georeferenced and shared in the most productive and efficient way, following standard guidelines and methodologies. This will lead to improved consistency in recording, sharing, and use of data.
Collecting data in the field sets the stage for good georeferencing procedures (Museum of Vertebrate Zoology 2006). Many techniques now exist that can lead to well documented georeferenced locations. It is important, however, that the locations be recorded correctly in order to reduce the likelihood of [error]. We recommend that all new collecting events use a GPS for recording [coordinates] wherever possible, and that the GPS be set to a relevant [datum] or [coordinate reference system] (see Coordinate Reference System). There are many issues that need to be considered when collecting data in the field and in this section we provide recommendations for best practice.
{marine} MARINE. The principles as laid out in this document apply equally to marine data as to terrestrial and other data. For example, recording [uncertainty] for marine data is just as important as recording it for terrestrial systems. This is particularly important for legacy data, data from historic voyages, scientific expeditions, etc. There is also uncertainty for all recordings of a georeference － however small that may be with modern equipment. Note that there are a number of issues that apply only to marine information. We refer those working in marine systems to other parts of this document for issues such as [depth], [distance above surface], dealing with non-natural occurrences, recording [extent] of diving activities, etc. Where there are differences that specifically apply to marine locations, we will identify those with the {marine} icon.
{ecological} ECOLOGICAL DATA. Georeferencing ecological data, from surveys, trapping, species counts, etc. should be treated in a similar way to specimen and observation data. Often ecological data are recorded using a [grid], or [transect], and may have a starting [locality] and an ending locality as well as start time and end time. Where there are differences that specifically apply to ecological data, we will identify those with the {ecological} icon.
{caves} CAVES. Events in subterranean locations, such as in caves, tunnels and mines, pose special problems in determining the [location]. Where there are differences that specifically apply to these data, we will identify those with the {caves} icon.
When recording data in the field, whether from a map or when using a GPS, it is important to record descriptive [locality] information as an independent validation of a [georeference]. The extent to which validation can occur depends on how well the locality description and its spatial counterpart describe the same place. The highest quality locality description is one contributing the least amount of [uncertainty] possible. This is equally important for retrospective georeferencing, where locality descriptions are given and georeferences are not, and for georeferencing in the field.
Provide a descriptive [locality], even if you have [coordinates]. The locality should be as specific, succinct, unambiguous, complete, and as accurate as possible, leaving no room for multiple interpretations.
Features used as reference points should be stable, i.e. places (permanent landmarks, trig points, etc.) that will remain unchanged for a long time after the [event] is recorded. Do NOT use temporary features or waypoints as the key reference locality.
To facilitate the validation of a locality, use reference features that are easy to find on maps or in gazetteers. At all costs, avoid using vague terms such as "near" and "center of" or providing only an [offset] without a distance, such as "West of Jiuquan", or worse "W Jiuquan".
In any locality that contains a feature that can be confused with another feature of a different type, specify the feature type in parentheses following the feature name, for example, "Clear Lake (populated place)".
If recording locations on a [path] (road, river, etc.), it is important to also record whether the distances were measured along the actual path (e.g. ‘by road’) or as a direct line from the origin (e.g. ‘by air’).
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The most specific localities are those described by a) a distance and heading along a [path] from a nearby and well-defined intersection, or b) two cardinal offset distances from a single persistent nearby [feature] of small [extent]. |
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It is good practice not to use quotation marks ("") in locality descriptions as this can generate problems down the line if using open text files, spread sheets, etc. |
By describing a [location] in terms of a distance along a [path], or by two orthogonal distances from a [feature], one removes [uncertainty] due to imprecise headings, which, when the distances are great, can be the biggest contributing factor to overall uncertainty. Choosing a reference feature with small [extent] reduces the uncertainty due to the size of the reference feature, and by choosing a nearby reference feature, one reduces the potential for [error] in measuring the [offset] distances, especially along paths. The Museum of Vertebrate Zoology at the University of California, Berkeley has published a guide to recording good localities in the field that follows these principles. Following is an example locality from that document (copied with permission).
Locality: Modoc National Wildlife Refuge, 2.8 mi S and 1.2 mi E junction of Hwy. 299 and Hwy. 395 in Alturas, Modoc Co., Calif.
Lat/Long/Datum: 41.45063, −120.50763 (WGS84)
Elevation: 1330 ft
GPS Accuracy: 24 ft
Radial: 150 ft
References: Garmin Etrex Summit GPS for coordinates and accuracy, barometric altimeter for elevation.
When recording a [location] that does not have a [feature] that can be easily referenced, for example a {marine}dive location in the middle of the ocean (see [entry point]) or using some other marker that may only be recorded as a [latitude] and [longitude], also record the provenance of the location (e.g. device or method used to determine the [coordinates] such as "transcription from ship’s log", etc.).
The [extent] of a [location] is the totality of the space it occupies. The extent is a simple way to alert the user that, for example, all of the specimens collected or observations made at the stated [coordinates] were actually within an area of up to 0.5 kilometers from that point. It can be quite helpful at times to include in your field notes a large-scale (highly detailed) map of the local vicinity for each [locality], marking the area in which events actually occurred.
The extent may be a linear distance, an area or a volume represented by one or more buffered points (i.e. a [point-radius]), buffered lines (e.g. transects, stratigraphic sections), polygons, or other geometries in two or three dimensions (sphere, cube, etc.).
A [location] can be anchored to a position (as [coordinates], potentially in combination with [elevation], [depth] and [distance above surface]) within the [extent]. This may be the corner or center of a [grid], the center of a polygon, the center of a circle, etc.
The [geographic extent] is the space occupied by the location when projected onto a 2D [coordinate reference system] in [geographic coordinates] (e.g. [latitude] and [longitude] in [decimal degrees] in [WGS84] [datum] on Google Maps). The [geographic radial] is the line segment from the [corrected center] of the [location] to the furthest point on the [boundary] of the geographic extent of that location. This simplified representation may be convenient for many uses, as long as the references to the [extent] are not lost. With the [coordinates] alone, the nature of the [extent] and the variety of conditions found therein will be lost, thus sacrificing the utility of the spatial information about the location and the contexts in which the data can be used.
When recording observations, whether by people or from fixed recording instruments such as camera traps (Cadman & González-Talaván 2014), sound recorders, etc., the [extent] should include the effective field of view (for camera traps) or area of detectable signals covered by the sound recorders, etc. In these cases the most faithful representation of the [location] (the one that would allow for the least [maximum uncertainty distance]) should have the [coordinates] at the center of the extent of the field of detection, not at the position of the recording device or person. The true location may need to be calculated from the coordinates of the device using the [radial] and [point-radius] [georeferencing method]. If the position of the device or person is the only practical way to give the coordinates, then the radial for the location is the length of the furthest distance in the field of detection.
For {marine}diving activities, the [coordinates] are recorded as an [entry point] into the water and the [locality] is recorded with reference to that entry point. For example, "sampling was conducted in a rough sphere of 30 meters diameter, whose center was located 300 meters due west of the entry point at a [depth] between 50 and 100 meters". In these cases the [radial] must be big enough to encompass the position within the [extent] farthest from the entry point (see Recording the location of an underwater event. E denotes the entry point, the surface location at which the geographic coordinates are recorded. x is the water depth, y is the horizontal offset (distance and direction) from E to the center of the location. Extent e is the three-dimensional location covered by the event. The corrected center cc is the point within the 3D shape that minimizes the length of the geographic radial gr. Minimum depth d1 and maximum depth d2 are the upper and lower limits of the location.).
{ecological}{marine}For a [location] that is a [transect], record both the start and end points of the line. This allows the orientation and [direction] of the transect to be preserved. If the events associated with the transect occur within a given maximum distance from the transect, it is better to represent the [location] as a polygon (see Polygons). If the events associated with the transect can be reasonably separated into their individual locations, it is better to do so, as these will be more specific than the transect as a whole. If that is done, however, ensure that you document that each individual location is part of a transect.
If the [locality] is recorded as the center of the [transect] and half the length of the transect is then used to describe [uncertainty], information about the orientation of the transect is lost, and the description essentially becomes equivalent to a circle.
Not all linear-based locations are transects or straight lines. We use the term [path] to highlight this broader concept. Illustrative examples are: ad-hoc observations while walking along a trail, an inventory or count of species while travelling along a river, tracking an individual animal’s movements. {marine}Marine transects, tracks, tows, and trawls, are further examples. Paths should be described using shapes (see discussion under [Shape Method]) as connected line segments (a polygonal chain), with the [coordinates] of the starting point followed by the coordinates of each segment beginning and finishing with the end point. One simple way to store and share these is through Well-Known Text (WKT) (ISO 2016, De Pooter et al. 2017, OBIS n.d., W.Appeltans, personal communication 15 Apr 2019).
To determine the [uncertainty] of a described [path] using the [point-radius] [georeferencing method], one needs to determine the [corrected center] – i.e. the point on the [path] that describes the [smallest enclosing circle] that includes the totality of the path ("c" on A path (river) showing the center of the smallest enclosing circle x, the mid point between the ends of the river y, the corrected center c, and the radial r.). This is very seldom the same place as the center of a line joining the two ends of the path ("y" on A path (river) showing the center of the smallest enclosing circle x, the mid point between the ends of the river y, the corrected center c, and the radial r.), nor the center of the extremes of [latitude] and [longitude] (the [geographic center]) of the path ("x" on A path (river) showing the center of the smallest enclosing circle x, the mid point between the ends of the river y, the corrected center c, and the radial r.).
When collecting or recording data from an area, for example, bird counts on a lake, a set of nesting or roosting sites on an offshore coral cay, or a buffered [transect] – the [location] is best recorded as a polygon. Polygons can be stored using the [Darwin Core] (Wieczorek et al. 2012b) field called term:dwc[dwc:footprintWKT], in which a [geometry] can be stored in the Well-Known Text format (ISO 2016). For the [point-radius] [georeferencing method], if the polygon has a concave shape (for example a crescent), the center may not actually fall within the polygon (The town of Caraguitatuba in São Paulo, Brazil (a complicated polygon), showing the center x of the smallest enclosing circle encompassing the whole of the town, and the corrected center c – the nearest place on the boundary to x. r is the geographic radial of the larger, red circle.). In that case, the [corrected center] on the [boundary] of the polygon is used for the [coordinates] of the location and the [geographic radial] is measured from that point to the furthest extremity of the polygon. Note that the circle based on the [corrected center] (red circle in The town of Caraguitatuba in São Paulo, Brazil (a complicated polygon), showing the center x of the smallest enclosing circle encompassing the whole of the town, and the corrected center c – the nearest place on the boundary to x. r is the geographic radial of the larger, red circle.) will always be greater than the circle based on the [geographic center] (black circle in The town of Caraguitatuba in São Paulo, Brazil (a complicated polygon), showing the center x of the smallest enclosing circle encompassing the whole of the town, and the corrected center c – the nearest place on the boundary to x. r is the geographic radial of the larger, red circle.).
Complex polygons, such as donuts, self-intersecting polygons and multipolygons create even more problems, in both documentation and storage.
Grids may be based on the lines of [latitude] and [longitude], or they may be cells in a Cartesian [coordinate system] based on distances from a reference point. Usually grids are aligned North-South, and if not, their [magnetic declination] is essential to record. If the [extent] of a [location] is a grid cell, then the ideal way to record it would be the polygon consisting of the corners of the grid (i.e. a [bounding-box]). The [point-radius] method can be used to capture the [coordinates] of the grid cell center and the distance from there to one of the furthest corners, but given that the geometries for grid cells are so simple, it is best to also capture them as polygons. Often grid cells (e.g. geographic grids) are described using the coordinates of the southwest corner of the grid. Using the southwest corner as the coordinates for a point-radius [georeference] is wasteful, since the [geographic radial] would be from there to the farthest corner, which would be twice as far as it would be if the center of the grid cell was used instead. In any case, the characteristics of the grid should be recorded with the [locality] information.
It is important when converting gridded data to [geographic coordinates] to also check the [locality] description. Locality information may allow you to refine the [location] as in Two options for georeferencing gridded data, 1) circle c with center at a for just the grid cell, and 2) circle d with center at b using the part of the grid cell constrained to be on Northey Island. where just having the grids without the locality information (i.e. "on Northey Island") would lead to the circle (c) with its center (a) at the center of the grid. Knowing that the record is on Northey Island, however, allows you to refine the location to the smaller circle (d) with its center at (b). Note that other criteria (such as a change of [datum], map scale, etc.) may add to the [uncertainty].
Township, Range and Section (TRS) or Public Land Survey System (PLSS) is a [grid]-like way of dividing land into townships in the midwestern and western USA. Sections are usually one mile on each side and townships usually consist of 36 sections arranged in a [grid] with a specific numbering system. Not all townships are square, however, as there may be irregularities based on administrative boundaries, for example. For this reason, though these systems resemble grids, they are best treated as individual polygons. Similar subdivisions are used in other countries
Quarter Degree Grid Cells (QDGC) (Larsen et al. 2009, Larsen 2012) and their predecessor Quarter Degree Squares (QDS) have been used in many historical African biodiversity atlas projects and continue to be used for current South African biodiversity projects such as the Atlas of South African birds (Harrison et al. 1997). It has also been recommended as the method to use for generalizing sensitive biodiversity data in South Africa (SANBI 2016, Chapman 2020).
The QDGC method for recording grids follows an earlier system (QDS) that was developed for South Africa, and only worked in southern Africa, i.e. in the southern and eastern hemispheres. Larsen et al. (2009) provided an extension to the QDS standard that allowed the methodology to be used across the world in all hemispheres. To do this, they adapted the reference system to address locations independent of the hemisphere. This required the addition of characters delimiting north/south and east/west positions. An extra Zero was added to east/west references to pad to three characters. They changed the reference position for the grids to that which is closest to the Prime Meridian and the Equator (i.e., in northern hemisphere Africa, for example to the bottom left, while retaining the top left for southern Africa). The code is designated by:
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A symbol denoting the eastern or western hemispheres (E or W).
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The three-digit degree of longitude.
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A symbol denoting the northern or southern hemisphere (N or S).
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The two digit degree of [latitude].
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Each degree square is then divided into sixteen quarter-degree squares, each 15’ x 15’. These are given two additional letters as indicated. Thus in Recording data using Quarter Degree Grid Cells (QDGC). The filled green grid cell is referenced as QDCC E032S18CB. Image with permission from RePhotoSA., the green square is represented by the code E032S18CB.
The earlier Quarter Degree Square (QDS) methodology references this square as 3218CB. The QDS methodology is still commonly used in southern Africa, but is easily translatable to the QDGC system.
Most terrestrial locations are recorded with reference to the terrestrial surface as [geographic coordinates], sometimes with [elevation]. Some types of {marine}marine events such as dives and trawls, benefit from explicit description in three dimensions.
{marine}Diving events are commonly recorded using the geographic coordinates of the point on the surface where the diver entered the water, called [entry point] or point of entry. The underwater [location] should be recorded as a horizontal distance and [direction] along with water [depth] from that surface location (see Recording the location of an underwater event. E denotes the entry point, the surface location at which the geographic coordinates are recorded. x is the water depth, y is the horizontal offset (distance and direction) from E to the center of the location. Extent e is the three-dimensional location covered by the event. The corrected center cc is the point within the 3D shape that minimizes the length of the geographic radial gr. Minimum depth d1 and maximum depth d2 are the upper and lower limits of the location.). Below the surface the diver may then begin a collection/observation exercise in three dimensions from that point including a horizontal component and a minimum and maximum water depth. These should all be recorded. The reference point should be the [corrected center] of the 3D-shape that includes the [extent] of the location. The [geographic radial] would be the distance from the corrected center of the 3D shape (the three dimensions projected perpendicularly onto the surface) to the furthest extremity of the projection of the 3D-shape in the horizontal plane (i.e. on the [geographic boundary]).
{marine}There are many different types of trawls and tows, including bottom and mid-water trawls. The 3D nature should be captured as above. The geographic reference points would be line segments tracing the route of the trawl, and would be more akin to paths and captured as a [shape] as described in §2.3.2.
Whenever practical, provide the [coordinates] of the [location] where an [event] actually occurred (see Extent of a Location) and accompany these with the [coordinate reference system] of the coordinate source (map or GPS). The two coordinate systems most commonly used by biologists are based on [geographic coordinates] (i.e. [latitude] and [longitude]) or [UTM] (i.e. [easting], [northing] and UTM zone).
A [datum] is an essential part of a [coordinate reference system] and provides the frame of reference. Without it the [coordinates] are ambiguous. When using both maps and GPS in the field, set the coordinate reference system or datum of the GPS or [GNSS] receiver to be the same as that of the map so that the GPS coordinates for a [location] will match those on the map. Be sure to record the coordinate reference system or datum used.
Geographic coordinates are a convenient way to define a [location] in a way that is not only more specific than is otherwise possible with a [locality] description, but also readily allows calculations to be made in a GIS. Geographic coordinates can be expressed in a number of different coordinate formats ([decimal degrees], degrees minutes seconds, degrees decimal minutes), with decimal degrees being the most commonly used. Geographic coordinates in decimal degrees are convenient for georeferencing because this succinct format has global applicability and relies on just three attributes, one for [latitude], one for [longitude], and one for the [geodetic datum] or [ellipsoid], which, together with the coordinate format, make up the [coordinate reference system]. By keeping the number of recorded attributes to a minimum, the chances for transcription errors are minimized (Wieczorek et al. 2004).
When capturing geographic coordinates, always include as many decimals of [precision] as given by the coordinate source. Coordinates in decimal degrees given to five decimal places are more precise than a measurement in degrees-minutes-seconds to the nearest second, and more precise than a measurement in degrees and decimal minutes given to three decimal places (see [table-uncertainty]). Some new GPS/[GNSS] receivers now display data in decimal seconds to two decimal places, which corresponds to less than a meter everywhere on Earth. This doesn’t mean that the GPS reading is accurate at that scale, only that the coordinates as given do not contribute additional [uncertainty].
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Decimal degrees are preferred when capturing coordinates from a GPS, however, where reference to maps is important, and where the GPS receiver allows, set the recorder to report in degrees, minutes, and decimal seconds. |
[UTM] is a system for assigning distance-based [coordinates] using a Mercator [projection] from an idealized [ellipsoid] of the surface of the Earth onto a plane. In most applications of the UTM system, the Earth is divided into a series of six-degree wide longitudinal zones extending between 80°S and 84°N and numbered from 1-60 beginning with the zone at the Antimeridian (Snyder 1987). Because of the latitudinal limitation in extent, UTM coordinates are not usable in the extreme polar regions of the Earth. A map of UTM zones can be found at UTM Grid Zones of the World (Morton 2006).
UTM coordinates consist of a zone number, a hemisphere indicator (N or S), and [easting] and [northing] coordinate pairs separated by a space with 6 and 7 digits respectively, and all in the order given here. For example, for Big Ben in London (latitude 51.500721, longitude −0.124430), the UTM reference would be: 30N 699582 5709431.
Latitude bands are not officially part of UTM, but are used in the Military Grid Reference System (MGRS). They are used in many applications, including in Google Earth. Each zone is subdivided into 20 latitudinal bands, with letters used from South to North starting with "C" at 80°S to "X" (stretched by an extra 4 degrees) at 72°N (to 84°N) and omitting "O". All letters below "N" are in the southern hemisphere, "N" and above are in the northern hemisphere. When using latitudinal bands, "north" and "south" need to be spelled out to avoid confusion with the latitudinal bands of "N" and "S" respectively. Using the latitudinal band method, the [coordinates] for Big Ben would be: 30T 699582m east 5709431m north.
National and local [grid] systems derived from UTM, but which may be based on different ellipsoids and datums, are basically used in the same way as UTMs. For example, the Map Grid of Australia (MGA2020) uses UTM with the GRS80 ellipsoid and Geocentric Datum of Australia (GDA2020) (Geoscience Australia 2019b). An example of a [location] in MGA2020 is "MGA Zone 56, x: 301545 y: 7011991"
When recording a [location], or databasing using UTM or equivalent coordinates, a zone should ALWAYS be included; otherwise the data are of little or no value when used outside that zone, and certainly of little use when combined with data from other zones. Zones are often not reported where a region (e.g. Tasmania) falls completely within one UTM zone. This is OK while the database remains regional, but is not suitable for exchange outside of the zone. When exporting data from databases like these, the region’s zone should be added prior to export or transfer. Better still, modify the database so that the zone remains with the coordinates.
Note that [Darwin Core] (Wieczorek et al. 2012b) supports UTM coordinates only in the term:dwc[verbatimCoordinates] field. There are several tools to convert UTM coordinates to [geographic coordinates], including Geographic/UTM Coordinate Converter (Taylor 2003)–see Georeferencing Tools. For details on georeferencing, see {gqg}#coordinates-universal-transverse-mercator-utm[Coordinates – Universal Transverse Mercator (UTM)] in Georeferencing Quick Reference Guide (Zermoglio et al. 2020).
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If using UTM coordinates, always record the UTM zone and the datum or coordinate reference system. |
Except under special circumstances (the poles, for example), [coordinates] without a [coordinate reference system] do not uniquely specify a [location]. Confusion about the coordinate reference system can result in positional errors of hundreds of meters. Positional shifts between what is recorded on some maps and [WGS84], for example, may be between zero and 5359 m (Wieczorek 2019).
An unofficial (not governed by a standards body) set of [EPSG] (IOGP 2019) codes are often used (and misused) to designate datums. There are EPSG codes for a variety of entities (coordinate reference systems, areas of use, prime meridians, ellipsoids, etc.) in addition to datums, and the codes for these are often confused. For example, the code for the WGS84 coordinate reference system is epsg:4326, while the code for the WGS84 datum is epsg:6326 and the code for the WGS84 ellipsoid is epsg:6422. The EPSG code has the advantage (when properly chosen) that it is explicit which type of entity it refers to, unlike the common name alone (e.g. "WGS84" alone could refer to the coordinate reference system, the datum, or the ellipsoid). Increasingly, GPS units are reporting coordinate reference systems as EPSG codes. Knowing the EPSG code for the coordinate reference system, one can determine the datum and ellipsoid for that system. It is thus recommended to record the EPSG code of the coordinate reference system if possible, otherwise, record the EPSG code of the datum if possible, otherwise, record the EPSG code of the ellipsoid. If none of these can be determined from the coordinate source, record "not recorded". This is important, as it determines the [uncertainty] due to an unknown datum (see [Uncertainty from Unknown Datum]) and has potentially drastic implications for the [maximum uncertainty distance].
Sources of EPSG codes include epsg.io (Maptiler 2019), Apache 2019, EPSG Dataset v9.1 (IOGP 2019) and Geomatic Solutions 2018. When using a GPS, it is important to set and record the EPSG code of the coordinate reference system or datum. See discussion below under [Calculating Uncertainties].
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If you are not basing your locality description on a map, set your GPS to report coordinates using the WGS84 datum or a recent local datum that approximates WGS84 (that may, for example, be legislated for your country) or the appropriate Coordinate Reference System (EPSG Code). Record the datum used in all your documentation. |
GPS (Global Positioning System) technology uses triangulation between a GPS/[GNSS] receiver and GPS or GNSS satellites (Kaplan & Hegarty 2006, Van Sickle 2015, Novatel 2015). As the GNSS satellites are at known positions in space, and the GPS/GNSS receiver can determine the distances to the detected satellites, the position on earth can be calculated. A minimum of four GNSS satellites is required to determine a position on the earth’s surface ({mcelroy_et_al_2007}[McElroy et al. 2007^], Van Sickle 2015). This is not generally a limitation today, as one can often receive signals from a large number of satellites (up to 20 or more in some areas). Note, however, that just because your GNSS receiver is showing lots of satellites, it doesn’t mean that all are being used as the receiver’s ability to make use of additional satellites may be limited by its computational power (Novatel 2015). In the past, many GPS units only referenced the GPS (USA) satellites of which there are currently 31 (April 2019), but now many GPS/GNSS receivers are designed to access systems from other countries as well – such as GLONASS (Russia), BeiDou-2 (China), Galileo (Europe), NAVIC (India), and QZSS (Japan), making a total of about 112 currently accessible satellites (2019) with a further 23 to be brought into operation over the next few years. This number is increasing rapidly every year (Braun 2019). Prior to the removal of Selective Availability in May 2000, the [accuracy] of handheld GPS receivers in the field was around 100 meters or worse ({mcelroy_et_al_2007}[McElroy et al. 2007^], Leick 1995). The removal of this signal degradation technique has greatly improved the [accuracy] that can now generally be expected from GPS receivers (GPS.gov 2018).
To obtain the best possible [accuracy], the GPS/GNSS receiver must be located in an area that is free from overhead obstructions and reflective surfaces and have a good field of view to a broad portion of the sky (for example, they do not work very well under a heavy forest canopy, although new satellite signal technology is improving the [accuracy] in these locations (Moore 2017)). The GPS/GNSS receiver must be able to record signals from at least four GNSS satellites in a suitable geometric arrangement. The best arrangement is to have "one satellite directly overhead and the other three equally spaced around the horizon" ({mcelroy_et_al_2007}[McElroy et al. 2007^]). The GPS/GNSS receiver must also be set to an appropriate [datum] or [coordinate reference system] (CRS) for the area, and the datum or CRS that was used must be recorded (Chapman 2005a).
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Set your GPS to report locations in decimal degrees rather than make a conversion from another coordinate system as it is usually more precise (see [table-uncertainty]), better and easier to store, and saves later transformations, which may introduce error. |
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An alternative where reference to maps is important, and where the GPS receiver allows it, is to set the recorder to report in degrees, minutes, and decimal seconds. |
One of the most important issues for consideration when choosing a GPS or [GNSS] receiver is the antenna. An antenna behaves both as a spatial and frequency filter, therefore, selecting the right antenna is critical for optimizing performance (Novatel 2015). One of the drawbacks with smartphones, for example, is the limited size of the GNSS antenna.
For information on issues to consider when selecting an appropriate [GNSS] antenna and/or GPS receiver, we refer you to Chapter 2 in Novatel 2015 and Chapter 10 in NLWRA 2008.
Most GPS devices are able to report a theoretical horizontal [accuracy] based on local conditions at the time of reading (atmospheric conditions, reflectance, forest cover, etc.). For highly specific locations, it may be possible for the potential [error] in the GPS reading to be on the same order of magnitude as the [extent] of the location. In these cases, the GPS [accuracy] can make a non-trivial contribution to the overall [uncertainty] of a [georeference].
The latest US Government commitment (US Deptartment of Defense and GPS Navstar 2008) is to broadcast the GPS signal in space "with a global average user range error (URE) of ≤7.8 m (25.6 ft.), with 95% probability". In reality, actual performance exceeds this, and in May 2016, the global average URE was ≤ 0.715 m (2.3 ft), 95% of the time (GPS.gov 2017). Though it does not mean that all receivers can obtain that accuracy, the accuracy of GPS receivers has improved and today most manufacturers of handheld GPS units promise errors of less than 5 meters in open areas when using four or more satellites. The need for four or more satellites to achieve these accuracies is because of the inaccuracies in the clocks of the GPS receivers as opposed to the much more accurate satellite clocks (Novatel 2015). The accuracy can be improved by averaging the results of multiple observations at a single location ({mcelroy_et_al_2007}[McElroy et al. 2007^]), and some modern GPS receivers that include averaging algorithms can bring the accuracy to around three meters or less. According to GISGeography 2019a, “A well-designed GPS receiver can achieve a horizontal accuracy of 3 meters or better and vertical accuracy of 5 meters or better 95% of the time. Augmented GPS systems can provide sub-meter accuracy”. Another method to improve accuracy is to average over more than one GPS unit. Note that some GPS/[GNSS] receivers can record up to 20 decimal places of [precision], but that doesn’t mean that is the accuracy of the unit.
The use of Differential [GNSS] (DGNSS) (incorporating Differential GPS (DGPS)) can improve [accuracy] considerably. DGNSS references a GNSS Base Station (usually a survey control point) at a known position to calibrate the receiving GNSS signal. The Base Station and handheld GNSS receiver reference the satellites’ positions at the same time and thus reduces [error] due to atmospheric conditions, as well as (to a lesser extent) satellite ephemeris (orbital location) and clock error (Novatel 2015). The handheld GNSS instrument applies the appropriate corrections to the determined position. Depending on the quality of the receivers used, one can expect an accuracy of <1 meter (USGS 2017). This accuracy decreases as the distance of the receiver from the Base Station increases. It is important to note that differential technology is not available in all areas – for example, in remote locations and remote islands, and the resulting accuracy may be less than expected. Again, averaging can further improve on these values ({mcelroy_et_al_2007}[McElroy et al. 2007^]). It is important to note, however, that most DGNSS is post-processed. Records are stored in the GPS/GNSS unit and then post-processing software is run to improve the measurements once connected to a computer. Post processing is not as commonly used since the introduction of real-time DGNSS, such as the Satellite Based Augmentation System, see the next subsection below), and is now used mostly in surveying applications where high accuracy is required.
{marine}Marine horizontal position [accuracy] requirements are 2-5 meters (at a 95 percent confidence level) for safety of navigation in inland waters, 8-20 meters (95%) in harbor entrances and approaches, and horizontal position accuracies of 1-100 meters (95%) for resource exploration in coastal regions (Skone et al. 2004, Skone & Yousuf 2007). While DGNSS horizontal [error] bounds are specified as 10 meters (95%) studies have shown that under normal operating conditions accuracies fall well within this bound.
DGNSS accuracies are susceptible to severe degradation due to enhanced ionospheric effects associated with geomagnetic storms. Degradation can be in the order of 2-30 times in some areas and depending on the severity of the storm.
Satellite Based Augmentation System (SBAS) is a collection of geosynchronous satellites originally developed for precision guidance of aircraft (Federal Aviation Administration 2020) and more recently to provide services for improving the [accuracy], integrity and availability of basic [GNSS] signals (Novatel 2015). SBAS receivers are inexpensive examples of real-time differential correction. SBAS uses a network of ground-based reference stations to measure small variations in the GNSS satellite signals. Measurements from the reference stations are routed to master stations, which queue the received Deviation Correction (DC) and send the correction messages to geostationary satellites. Those satellites broadcast the correction messages back to Earth, where SBAS-enabled GPS/GNSS receivers use the corrections while computing their positions to improve accuracy. Separate corrections are calculated for ionospheric delay, satellite timing, and satellite orbits (ephemerides), which allows [error] corrections to be processed separately, if appropriate, by the user application.
The first [SBAS] system was [WAAS] (Wide Area Augmentation System), which was originally developed to provide improved GPS [accuracy] and a certified level of integrity to the US aviation industry, such as to enable aircraft to conduct [precision] approaches to airports and for coastal navigation. It was later expanded to cover Canada and Mexico, providing a consistent coverage over North America.
The European Geostationary Navigation Overlay Service (EGNOS) was developed as an augmentation system that improves the [accuracy] of positions derived from GPS signals and alerts users about the reliability of the GPS signals. Originally developed using three geostationary satellites covering European Union member states, EGNOS satellites have now also been placed over the eastern Atlantic Ocean, the Indian Ocean, and the African mid-continent.
More recently, other [SBAS]s have been, or are in the process of being developed to cover other parts of the world, including MSAS (Japan and parts of Asia), GAGAN (India), SDCM (Russia), SNAS (China), AFI (Africa) and SACCSA (South and Central America) (ESA 2014). Australia and New Zealand are in the process of developing an SBAS system that will provide several decimeter accuracy across Australia and its marine areas, and one decimeter accuracy across New Zealand. The system will provide three services to users – an L1 system with sub one-meter horizontal [accuracy] for aviation purposes; a Dual-Frequency Multi-Constellation (DFMC) with sub one-meter accuracies; and a Precise Point Position (PPP) service (see Precise Point Positioning) with accuracies of 10-15 cm (Guan 2019). Testing is scheduled for completion in July 2020 (Geoscience Australia 2019a).
A study in 2016 determined that, over most of the USA, the [accuracy] of [WAAS]-enabled, single-frequency GPS units was on the order of 1.9 meters at least 95 per cent of the time (FAA 2017). This may be lower in other parts of the world where [SBAS] stations are less common. Note that as most SBAS satellites are geostationary, blocked line of sight towards the equator (southwards in the northern hemisphere, or northwards in the Southern hemisphere) by buildings or heavy canopy cover will reduce the accuracy of SBAS correction, Also, during solar storms, the accuracy deteriorates by a factor of around 2.
Despite early indications that WAAS can significantly improve positional [accuracy] during the most severe period of geomagnetic storms, more recent studies in the USA and Canada have shown that the sparseness of WAAS stations and ionospheric grids do not lead to a significant improvement. (Skone & Yousuf 2007). With reference stations needing to have separations within 100 km, improvements are only likely in coastal and near coastal areas of North America and Europe in the foreseeable future.
Ground Based Augmentation Systems (GBAS), also known as Local Area Augmentation Systems (LAAS), provide differential corrections and satellite integrity monitoring in conjunction with VHF radio, to link to [GNSS] receivers. A GBAS consists of several GNSS antennas placed at known locations with a central control system and a VHF radio transmitter. GBAS is limited in its coverage and is used mainly for specific applications that require high levels of [accuracy], availability and integrity, and is the system largely used for airport navigation systems.
Precise Point Positioning (PPP) depends on [GNSS] satellite clock and orbit corrections, generated from a network of global reference stations to remove GNSS system [error] and provide a high level (decimeter) of positional [accuracy]. Once the corrections are calculated, they are delivered to the end user via satellite or over the Internet.
Although similar to [SBAS] systems (see above), they generally provide a greater [accuracy] and have the advantage of providing a single, global reference stream as opposed to the regional nature of an SBAS system. Whereas SBAS is free, the use of PPP usually incurs a charge to access the corrections, so it is unlikely that the increased accuracy of PPP when compared to that of SBAS, will be a consideration for most biological applications.
Static GPS uses high [precision] instruments and specialist techniques and is generally employed only by surveyors. Surveys conducted in Australia using these techniques reported accuracies in the centimeter range. These techniques are unlikely to be extensively used with biological record collection due to the cost and general lack of requirement for such precision.
High-end dual and multi-frequency GPS/[GNSS] devices can bring [accuracy] to the centimeter level, and even mm level over the long-term (GPS.gov 2017). One of the ways this is done is by removing one of the largest contributors to overall satellite [error] － error due to the ionosphere (known as ionosphere error) (Novatel 2015).
GPS-enabled smartphones are typically accurate to within 4.9 m (16 ft.) under open sky, however, their accuracy worsens near buildings, bridges, and trees (GPS.gov 2017). A study by Tomaštik et al. 2017 found that the accuracy of smartphones in open areas was around 2-4 m. This decreased to 3-11 m in deciduous forest without leaves, and 3-20 m in deciduous forest with leaves. There are reports that the accuracy in some GPS-enabled smartphones will soon be improved to <1 meter (Moore 2017) and that accuracy in areas with restricted satellite view within cities will be improved drastically with inbuilt 3D smartphone apps and probabilistic shadow matching (Iland et al. 2018). In general, the [GNSS] chipsets in smartphones are quite good, and any loss of accuracy is usually due to the quality of the antenna, whose chief failing is due to their poor multipath suppression (Pirazzi et al. 2017). In some smartphones where good satellite coverage is unavailable (e.g. in cities and forests), the phone may introduce errors from [bias] in its internal clock (Pirazzi et al. 2017), leading to occasional large inaccuracies (Arturo Ariño Oct 2019, pers. comm.). Already the technology for better than 1 meter smartphone accuracy exists, but it is not available to the public due to the difficulty and cost of incorporating the technology into small smartphones (Braun 2019). The accuracies reported in most publications refer to studies in the USA, Europe, coastal Australia, India or Japan where good differential stations are plentiful. More studies are needed to test smartphone accuracies in remote locations and where differential stations are not available.
Smartphone GPS technology is changing rapidly and there is likely to be new and updated information even before this document is published.
We are not aware of the characteristics of the [accuracy] of GPS-enabled cameras, but we expect the accuracy to be similar to that of smartphones. One study, using three different cameras, showed variation between the three and the true [location] to be less than 3 m from the reported location (Doty 2017). {marine}Note that GPS-enabled cameras that are used for snorkeling and diving activities, will only give new GPS readings each time the camera is brought to the surface.
{marine}Over the years, a number of methods for tracking a diver underwater with a GPS have been tried with limited success. These included using a floating GPS receiver over the diver’s bubbles, and a GPS receiver on a raft towed by the diver that recorded intermittent readings to provide a dive [transect] (Schories & Niedzwiedz 2011). The most successful to date has been the use of a GPS antenna on a floating buoy that is attached by a cable to a diver-held GPS. These diver-towed underwater GPS/[GNSS] handheld receivers have been used for underwater monitoring studies for several years. Most dives using this method are at <20 meters as the signal deteriorates with cable length giving a maximum practical depth of 50 meters (Niedzwiedz & Schories 2013). One problem is cable drag, and it is almost impossible to determine the buoys [offset] exactly although Niedzwiedz & Schories 2013 provide formulae for attempting to do so. A study by the same authors (Schories & Niedzwiedz 2011) showed displacement of 2.3 m at a [depth] of 5 m, 3.2 m at 10-m depth, 4.6 m at 20-m depth, 5.5 m at 30-m depth, and 6.8 m at 40-m depth. These are in addition to GPS [accuracy] discussed under GPS Accuracy.
Supplement the [locality] description with [elevation] information if this can be easily obtained. Elevation can be determined from a variety of sources while in the field, including altimeters, maps (both digital and paper), and GPS/[GNSS] receivers, each with associated uncertainties. Elevation can be estimated after the fact using Digital Elevation Models at the [coordinates] of the [location]. In any case, record the method used to determine the elevation.
Elevation markings can narrow down the area in which you place a point. More often than not, however, they seem to create inconsistency. While elevation should not be ignored, it is important to realize that elevation was often measured inaccurately and/or imprecisely, especially early in the 20th century. One of the best uses of elevation in a locality description is to pinpoint a location along a road or river in a topographically complex area, especially when the rest of the locality description is vague.
When adding elevation after the fact be aware that the elevation can vary considerably over a small area (especially in steep terrain) and that the uncertainty of the [georeference] must be taken into account when determining the elevation. Do not use the coordinates on their own.
A barometric altimeter uses changes in air pressure as a proxy for changes in elevation, and can be a reliable source of elevation if properly calibrated. Calibration requires that the elevation of the altimeter be set to a known starting elevation, which could be determined from a map, for example. Thereafter, as the altimeter goes higher or lower in elevation, it estimates the new elevation directly from the air pressure it experiences. Since weather conditions can change the air pressure independently of changes in elevation, it is important to re-calibrate the altimeter frequently, either by recording the elevation when you stop moving and resetting to that same elevation before starting out again, and/or by recalibrating to known elevations whenever you encounter them.
In theory it would be possible to use a barometric altimeter to determine elevations when in a {caves}subterranean [location] (cave, mine, etc.), but these situations are particularly prone to changes in air pressure independent from elevation changes (especially in caves with narrow openings), so recalibration would have to be particularly careful.
Elevation can be determined using the contours and spot height information from a suitable scale map of the area. In general, the uncertainty in the elevation when read from a map is half the contour interval.
For information on determining accuracy from a map, see [Uncertainty in Paper Map Measurements].
Elevation [accuracy] as reported from a GPS has improved markedly in recent years, but elevation accuracy is not usually reported by GPS/[GNSS] receivers. As a general rule, for most non-[SBAS] or [WAAS] enabled GPS/GNSS receivers, elevation [error] is approximately 2-3 times the horizontal error (USGS 2017). It is hard to find definitive information for smartphones, but it would appear that this same multiplier is a good rule for those as well. With WAAS-enabled GPS, the FAA reports that 95 per cent of the time vertical error is less than 4 meters (FAA 2019). However, the elevation reported on the GPS receiver or smartphone is not necessarily referring to [mean-sea-level] (MSL) as reported, but to the zero elevation of the [ellipsoid] of the [datum] – see discussion below.
Note that GPS elevation readings can represent one of at least two different values, depending on the method used by the GPS. Elevation reported can be the geometric height. This is the only value that GPS devices can actually measure, and is the height based on the ellipsoid of the datum. The elevation reported can also be the elevation above MSL, or orthometric height. These values are not directly measured by the GPS, but are calculated as the difference between the geometric height (measured) and the [geoid] height. The geoid height depends on the geoid and the datum you are trying to compare it against. Thus, to understand the potential difference between elevations based on MSL and those based on the geometric model, the geometric model (datum) must be known. To calculate the potential error using [WGS84] datum at a given geographic [location], use the Geoid Height Calculator (UNAVCO 2020). For further discussion about these methods, consult Eos Positioning Systems 2018. For a good explanation of the differences between the geoid and mean sea level, we refer you to GISGeography 2019b.
In 2022, the USA will release a new geometric reference frame and geopotential [vertical datum] that will replace existing USA geometric vertical datums. Similarly, over the next five years, Australia will move to a new generation height reference frame – the Australian Gravimetric Quasigeoid 2017 (AGQG 2017) (McCubbine et al. 2019). The new reference frames will rely primarily on Global Navigation Satellite Systems ([GNSS]), as well as on an updated gravimetric [geoid] model (National Geodetic Survey 2018). The new method of calculating vertical datums will improve vertical accuracies to around 1-2 cm, will provide more accurate GPS-determined elevations (Ellingson 2017), and will allow for dynamic updating. Other jurisdictions are likely to move to new methods of calculating vertical datums over time, meaning that within five years most users will be able to position themselves vertically using mobile Global Navigation Satellite Systems ([GNSS]) technology with sub-decimeter accuracy (Brown et al. 2019).
Digital Elevation Models (DEM) are based on elevations above [mean-sea-level] (or more recently, the [geoid]). The models are calculated using sophisticated interpolations and do not necessarily correspond to the actual surface elevation. DEM vertical [accuracy] is influenced by several factors such as [grid] size, slope, land cover, and geolocation (horizontal) [error], as well as other biases due to the original DEM data collection (e.g. satellite imaging geometry) and/or production method (Mukherjee et al. 2013, Mouratidis & Ampatzidis 2019). Global DEMs such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM V2 (Meyer 2011) and the Shuttle Radar Topography Mission (SRTM) are based on 1 arc-second grids (about 30 m x 30 m) (Farr et al. 2007) and have an accuracy of better than 17 m and 10 m respectively (except for in steep terrain such as mountains, and areas with very smooth sandy surfaces with low signal to noise ratio, such as the Sahara Desert (Farr et al. 2007)). Local and regional DEMs may have a smaller grid size. For example, a 5 m grid in Australia, which has a vertical accuracy better than one meter, and even to 0.3 meter in some areas (Geoscience Australia 2018) or the European Digital Elevation Model, which has an accuracy of better than three meters (Mouratidis & Ampatzidis 2019). Note also that satellite image-based DEMs, being radar based, vary greatly over different land surfaces, forests, shrub or herbaceous vegetation, agricultural areas, bare areas, rocky surfaces, wetlands, and artificial surfaces such as cities. Also the radar can penetrate into areas of snow, ice, and sand (as in deserts) (Mouratidis & Ampatzidis 2019).
Some smartphones, whether they incorporate GPS capabilities or not, use apps that provide [elevation] values based on a DEM. With smartphone GPS apps, be aware that some devices and apps incorrectly record the method used. The [uncertainty] in elevation due to an unknown elevation source can be up to 100 meters. For example, the difference with [datum] [WGS84] between the [ellipsoid] and [geoid] or [mean-sea-level] methods of reporting elevation is shown in Figure 6. Note also that these uncertainties are in addition to the uncertainties associated with the measurements themselves. The only true way of determining what your GPS receiver or smartphone is recording is to test it against a known elevation. Some preliminary studies by the authors show elevation [accuracy] from smartphones varies greatly in different areas of the world. In areas in the USA, Europe, Australia, Japan, etc. (where most published results are from) errors are generally within 10 meters or so, but in more remote areas (such as on a remote island in Fiji), errors in the order of ±60 meters are not uncommon. Using two different mobile applications at sea level at one location resulted in reported elevations from −24 m to +58.9 m. These studies are preliminary and more research is needed in different areas of the world.
GPS-enabled digital cameras are like smartphones with respect to positional accuracy as they have similar sized in-board antennas. To conserve battery life, most GPS-enabled digital cameras have options to set positional update intervals. Depending on the camera, these can range from once every second to once every five minutes. The setting of this interval may have significant implications with respect to both [coordinates] and [uncertainty].
Underwater digital cameras only update their position when the diver or snorkeler takes the camera above the surface long enough for the GPS to fix its position.
Using a large sample size (n>20,000) of GPS benchmarks in a variety of terrains in the United States, Wang et al. 2017 found that elevations in the Google Earth terrain model had a boundary of [error] interval at 95 per cent (BE95) of ±44 m, with worst-case scenarios around 200 m. The same study found that Google Earth terrain model had a BE95 of ±6 m along highways. Though we find no data for elsewhere in the world at this time, we recommend using the values extracted from the work of Wang et al. 2017 as estimates of elevational [uncertainty] when the source is the Google Earth terrain model. A second study using Google Earth to determine elevation in three regions of Egypt (El-Ashmawy 2016) on flat, medium, and steep terrains concluded that elevation data is more accurate in flat areas or areas with small height difference, with an accuracy of approximately 1.85 m (RMSE) and an [error] range of less than 3.72 m (and in some findings less than 1 m). Increasing the difference in height leads to decrease in the obtained accuracy with the RMSE rising to 5.69 m in steep terrain.
Compass directions (also known as headings) can be rather ambiguous. North, for example, might be any direction between northwest and northeast if more specific information is not provided. There are several ways to avoid ambiguity when recording headings. One way is to qualify the direction with "due" (e.g. "due north") if the heading warrants it. A second way to avoid ambiguity is to use two orthogonal headings in [locality] descriptions, making implicit that both components are "due". Finally, ambiguity can be reduced if headings are given in degrees from north (0° is north, 90° is east, 180° is south, and 270° is west).
It is important to record headings based on True North (true heading) and not on Magnetic North (magnetic heading). The differences between True North and Magnetic North vary throughout the world, and in some places can vary greatly across a very small distance (NOAA 2019, NOAA/NCEI & CIRES 2019). For example, in an area about 250 km NW of Minneapolis in the United States, the anomalous [magnetic declination] (the difference between the declination caused by the Earth’s outer core and the declination at the surface) changes from 16.6° E to 12.0° W across a distance of just 6 km (Goulet 2001).
The differences between True North and Magnetic North also change over time (NOAA n.d.a). The National Oceanic and Atmospheric Administration (NOAA) has an online calculator that can calculate the anomalous or geomagnetic declination (adjustment needed to convert the magnetic reading to a reading based on True North) for any place on earth and at any point in time. If you need to make adjustments, we suggest that you use this calculator to determine the magnetic declination for the area in question. Otherwise determine your heading using a reliable map and always report your methods. Note that some smartphone apps will make that calculation for you, and allow you to set your app to record either Magnetic North or True North.
An [offset] is a displacement from a reference point, named place, or other [feature], and is generally accompanied by a direction (or [heading], see Headings). One of the best ways to describe a [locality] is with orthogonal offsets from a small, persistent, easy to locate feature (see Localities). Using an offset at a very specific heading is a second option, though the [uncertainty] still grows with the offset distance. Offsets along a [path] are a third reasonable option for describing a locality, though they tend to be much harder to measure after the fact. Other locality types that use offsets (e.g. an offset [direction] without a distance, or an offset distance without a direction) tend to introduce excessive [uncertainty] and should be avoided.
A [locality] consisting of an [offset] from a [feature] without a [heading] may arise as a result of an [error] when recording the locality in the field or through data entry. If the feature is small (such as a [trig point]) then the overall [uncertainty] will be largely due to the offset. With larger features (such as a town, or a lake), both the offset from, and the [extent] of the feature may contribute significantly to the overall uncertainty. The original collection catalogues or labels may contain information that can make the locality more specific. If not, a "Distance only" locality (e.g. "5 km from Lake Vättern, Sweden") might be envisioned as a band running around the reference feature at a distance given in the locality description. The problem is, we don’t know what was being used as the reference – some place in the lake, or some place on the edge — nor do we know if the offset was perpendicular to an edge or at some oblique angle to it. Because of these confounding factors, it is recommended to treat the locality as if it was a feature enlarged on all sides by the combination of all the sources of uncertainty (see {gqg}#offset-distance-only[Offset – Distance only^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^]).
A [locality] with a [heading] from a [feature], but with no distance (e.g. "East of Albuquerque"), is particularly ambiguous and very subjective to [georeference]. With no additional information to constrain the distance , there is no clear indication of how far one might have to go to reach the [location] – to the next nearest feature; the next nearest feature of equivalent size, to a place where there is a major change in biome (such as a coast), or just keep going?
Note that seldom is such locality information given alone. For example, the locality may have administrative geography information (e.g. ‘East of Albuquerque, Bernalillo County, New Mexico’). This gives you a stopping point (e.g. the county border), and should allow you to georeference the locality (see {gqg}#offset-heading-only[Offset – Heading only^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^]). In any case, it is highly recommended not to record locality descriptions in this way.
A [locality] that contains an [offset] in a given direction to or from a [feature] is treated here as an "offset at a [heading]". There are several variations on such localities. One difficulty in determining a [georeference] for this type of locality description is knowing how the offset was determined – for example, by air, or along a [path] such as a road or river. Therefore, whenever a locality with an offset at a heading is described, be sure to be explicit about what is intended.
It is not uncommon for {marine}marine locality descriptions to use an azimuth – a heading toward a target feature, for example, "25° to Waipapa Point Lighthouse". In these cases the referenced feature is the starting point, and the heading from there should be 180 degrees on the compass away from the compass reading given in the locality description. This is known as a "back azimuth" or "backsighting".
Where the sense of the offset cannot be determined from the locality description or additional information and there is no obvious major path that can be followed in the rough direction and distance given, then it is best to assume the collector measured the distance by air. Whatever the decision, document the assumption in the georeference remarks (e.g. ‘Assumed "by air" – no roads E out of Yuma’, or ‘Assumed "by road" on Hwy. 80’) and georeference accordingly (see {gqg}#offset-distance-at-a-heading[Offset – Distance at a Heading^] and {gqg}#offset-distance-along-a-path[Offset – Distance along a Path^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^]).
The addition of an adverbial modifier to the distance part of a locality description (such as "about 25 km"), while an honest observation, should not affect the determination of the [geographic coordinates] or the maximum uncertainty. Treat the uncertainty due to distance [precision] normally (see [Uncertainty Related to Offset Precision]).
Sometimes it is convenient to describe a [locality] as a distance along a curvilinear [feature] — a [path] such as a road, river, trail, etc. (see {gqg}#offset-distance-along-a-path[Offset – Distance along a Path^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^]). One advantage of a description of this kind is that it avoids the [uncertainty] due to an imprecise [heading]. It might also be easy to register, such as when tracking distance with the odometer of a car while driving. However, a disadvantage is that it may not be quite as easy to determine the same location afterwards from maps alone during the georeferencing process. One reason is that you have to trace the facsimile of the path on a map. The map may have errors, loss of resolution due to map scale, inconsistencies with conditions at the time of the [event], or might not even be present. There is also a difference between distance on the topographic surface and distance on a map, though for most normal situations (along roads and navigable waterways) the difference is <1% (see {gqg}#offset-distance-along-a-path[Offset – Distance along a Path^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^]). Worse, the path may have changed over time, making it even more difficult to find the exact locality retrospectively.
If the [locality] references a river, such as in the example "16 mi downstream from St Louis on the left bank of the Mississippi River", it is reasonable to assume that the [offset] is along the river. In this example, the [locality] is on the east side of the river, in Illinois, rather than on the west side, in Missouri, as the reference to "left bank" is conventionally taken to be in the orientation looking downstream.
This type of [locality] refers to rectilinear distances in two orthogonal directions from a [feature], for example, "2 mi E and 1.5 mi N of Kandy" (see {gqg}#offset-distance-along-orthogonal-directions[Offset – Distance along Orthogonal Directions^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^] and [img-orthogonal-distances-from-feature]). This way of describing a locality can be very effective, as it tends to remove one of the potentially largest sources of [uncertainty], the ever-expanding uncertainty of direction with distance. Using orthogonal directions removes all directional [uncertainty], as orthogonality implies directly in the orthogonal directions "by air". It is for this reason that this [locality type] is highly recommended for locality descriptions.
Water [depth] should be recorded as a range; i.e. as minimum and maximum positive distances in meters below the air-water interface of the water body ({marine}ocean, sea, lake, river, etc.). Maximum depth will always be a positive number greater than or equal to the minimum depth. If the depth measurement is specific rather than a range, use the same value for the minimum and maximum depths.
{marine}The [depth] of the benthic surface in large water bodies is called [bathymetry] or bathymetric depth. It is usually recorded in one of two ways – as a gridded surface (Digital Terrain Model), or as contours. The accuracy of the bathymetry depends on how it was determined, and is generally much more accurate near the coasts, or in harbors, than it is in the deeper ocean.
Since 2003, the most commonly used global coverage of bathymetry has been the One Minute General Bathymetric Chart of the Oceans (GEBCO 2019a), however, in 2019, a much finer, and more detailed, 15 arc-second [grid] coverage was released (GEBCO 2019b). The 3,732,480,000 grids (86,400 rows by 43,200 columns) cover from 89°59'52.5'' N, 179°59'52.5'' W to 89°59'52.5'' S, 179°59'52.5'' E, with [elevation] given for each pixel center. There are many criteria that determine the vertical accuracy of these grids, including the presence of steep canyons, water depth and turbidity (affects instrument penetration and acoustic beams get wider, the deeper they go), and methodology (satellite, single beam echo sounders (SES), multibeam echo sounders (MES), airborne laser (LADS), Light Detection and Ranging (LIDAR), etc.) (Wolf et al. 2019).
Bathymetric contours have generally only been available for harbors, coastal and near inshore areas, in some places extending to the edges of the continental slope. Where bathymetric contours (also called depth contours or isobaths) do exist, they are generally quite coarse (except in areas like the North Sea, and in harbors), and get wider apart as the depth increases. For example, the 2009 bathymetric contours for Australia are at 20 m, 40 m, 100 m, 200 m and 400 m. In some harbors, the contour interval is as small as one meter (Data.gov.au 2018). In 2019, the GEBCO_2019 global bathymetric contour dataset was derived from the GEBCO_2019 15 arc-second grid mentioned above. At large scales (1:5,000,000 and closer), the contour interval is 500 m; at medium scales (1:5,000,000 to 1:30,000,000) the contour interval is 1000 m; and at small scales (1:30,000,000 and greater), the contour interval is 2000 meters. Supplementary contours are shown in shallow waters (less than 500 m) (NCEI-NOAA 2019).
Very few studies have been carried out on the accuracy of either the bathymetric grids or contours – especially with GEBCO_2019 as the dataset has only recently been published. The authors have not been able to find any definitive information on accuracies that we can report on a general basis, but the contour intervals give an indication of the [uncertainty] inherent in the grids. In coastal, near inshore areas, harbors, and inland reservoirs and lakes, more intensive and different bathymetric surveys have generally been carried out (see the Bathymetric Data Viewer (NCEI 2020)) and [accuracy] studies have been conducted in some of these areas. In shallow-water areas there is less interference due to water depth and higher sound wave frequencies can be used for multibeam bathymetric surveying. The accuracy is much better than in other deeper-water areas, and thus these studies cannot be extrapolated to the broader ocean. For contours, as with land maps, uncertainty in the elevation is half the contour interval.
{marine}There are three methods for determining [depth] that are generally used by divers, i.e. dive computers, dive watches and depth gauges. All work on ambient pressure to determine the depth. Dive computers need to be calibrated before dives and set depending on the water density – i.e. saltwater or freshwater, etc. — and, if calibrated correctly, are reported by manufacturers to be accurate to within 0.3 meters.
A study of 47 brands of dive computers at depths of 10 m, 20 m, 30 m, 40 m and 50 m in both seawater and freshwater showed that the majority of depth estimates were in the ± 1 meter range, and that if the salinity is known and the instrument is properly calibrated, accuracies of around 1 per cent could or should be expected (Azzopardi & Sayer 2012). The accuracy of diver-held depth gauges are of a similar order. Dive watches are generally thought less accurate, but with reports for some watches of depth accuracy, at depths of up to 100 meters, as ± 1 per cent of displayed value + 0.3 meter (when used at constant temperature). Accuracy can be influenced by changes in ambient temperature and water salinity.
Distance above surface should be recorded in meters in a vertical direction from a reference point, with a minimum and a maximum distance to cover a range. Examples include the height above the ground of a soaring eagle, the distance up a tree from the ground (height), and the distance from the top of a vertical core sample to a diatom sample found in that core.
The reference point for the measurement of a distance above surface can vary depending on the context. For surface terrestrial locations, the reference point should be the [elevation] at ground level. For water bodies ({marine}ocean, sea, lake, river, etc.), the reference point for aerial locations should be the elevation of the air-water interface, while the reference point for {marine}sub-surface benthic locations should be the bottom of the water body at that [location]. Locations within the water body should use water [depth] and should not use any other distance above a surface.
We recommend that distance above surface always be measured in the same sense, that is, as distances above the reference surface. Distances above a reference point should be expressed as positive numbers, while those below should be negative. This is analogous to elevation, which is positive when expressing a distance above [mean-sea-level] and negative below that reference point. The maximum distance above surface will always be a number greater than or equal to the minimum distance above that surface for a given [location] (see Examples of use of depth, elevation and distance above surface, for A: terrestrial locations, B: caves, and C: aquatic locations. a signifies elevation, either of a land surface or of an air/water interface; b = distance above surface, marked positive (+) or negative (−); c signifies depth (always positive).).
For the special case of recording locations within a {caves}cave system or in an underground mine, see Caves.
{caves}Collecting in caves, underground mines and tunnels presents a number of challenges not encountered elsewhere.
In {caves}cave systems and underground mines, determining the geographic position on the surface (known as [ground zero]) can be done with radiolocation or Electromagnetic Cave-to-Surface (ECMS) Mapping System (Sogade et al. 2004), which uses electromagnetic wave technology. This requires a levelled radio loop in the [location] within the cave and a receiver above ground to determine the location underground. The surface location can then be determined using a GPS/[GNSS] receiver, as usual. With a levelled antenna, an experienced operator can determine a ground zero with an [accuracy] of one meter for a 50 m depth (2%) (Gibson 1996, {gibson_radiolocation}[Gibson 2002^]), however, more recent radiolocation beacons have increased the horizontal [accuracy] to about 0.5 to 1 per cent (Goldsheider & Drew 2014, Buecher 2016). Fortunately, many caves and mines have already been extensively mapped, so where maps are available, these may be used to determine locations.
A second method, using the cave mouth, is probably more commonly used, is easier to determine, but is less accurate and has a much greater [uncertainty]. The cave mouth, tunnel opening, mine shaft entrance, etc., are the most obvious locations to begin with. These locations can easily be obtained using a GPS unit, but be aware of the likely reduced [accuracy] of the GPS unit if the cave entrance is within a deep valley where good [GNSS] reception may be reduced. It is documenting the location of the [event] from that position that is much more difficult, especially where detailed cave maps don’t exist. At its crudest level, one may estimate the cave [extent] and determine the [corrected center] of that extent. From there you can determine a [geographic radial] as noted elsewhere in this document (see Polygons). Just recording the location of the cave entrance, and using a large radius for the uncertainty is not ideal but may be a last resort. If doing this however, make sure that your [locality] description includes as much additional information as possible – such as estimated distance from the cave entrance, [direction], and if possible, a ‘depth’. For georeferencing in Caves, see {gqg}#feature-cave[Feature – Cave^] in {gqg}[Georeferencing Quick Reference Guide (Zermoglio et al. 2020)^].
Traditionally, cavers have recorded the depth in a {caves}cave as the depth below the surface, however, in this document and for the purposes of recording biological observations, we use [elevation] (above [mean-sea-level] or [geoid]) for a position at the floor of the cave.
The distance below [ground zero] can be determined using the same radiolocation equipment as for determining the ground zero itself (see above). The [accuracy] of the distance below ground zero, calculated using these methods is around 5-10 per cent (Gibson 1996, {gibson_radiolocation}[Gibson 2002^]) for depths up to about 50 meters. As above, however, recent beacons have improved the accuracy to about 10 per cent for depths of up to 300 meters below the surface (NOT Engineers 2019). Uneven surface terrain can add to the uncertainties by up to a further 3 per cent and in very deep caves, mines, etc. where there are heavy ore bodies present, and where there are fault lines, this method is far less reliable for determining depth with errors increasing up to 20 per cent. In those conditions radiolocation may not be suitable for determining the distance below the surface.
From these figures, it is possible to determine the [elevation] of the floor of the cave by taking the elevation at ground zero and deducting the calculated distance below that point (see Specifying the vertical position of a location in a cave using an elevation e and a distance above surface X. The location a is at a vertical distance X directly above the floor of the cave, which is at elevation e. The elevation of e is determined within the cave by surveying from a known elevation on the cave floor e1, which is calculated using an estimated distance below the surface elevation at ground zero GZ.). Note that when determining elevation in a cave, the accuracy mentioned above is additional to the elevation uncertainty determined for the elevation at ground zero.
Using detailed cave maps may provide a better (and cheaper) alternative to other methods, and you should choose the best method for your purpose, but be sure to document how the elevation was determined. Cave maps can usually be obtained by contacting local speleological or cave clubs.
The water [depth] within a subterranean water body (lake, river, sinkhole, etc.) is recorded as for other water bodies and is measured from the surface of the water body (see Examples of use of depth, elevation and distance above surface, for A: terrestrial locations, B: caves, and C: aquatic locations. a signifies elevation, either of a land surface or of an air/water interface; b = distance above surface, marked positive (+) or negative (−); c signifies depth (always positive).B). The [elevation] of the surface of the water body is determined as for the floor of the cave in Specifying the vertical position of a location in a cave using an elevation e and a distance above surface X. The location a is at a vertical distance X directly above the floor of the cave, which is at elevation e. The elevation of e is determined within the cave by surveying from a known elevation on the cave floor e1, which is calculated using an estimated distance below the surface elevation at ground zero GZ..
Determining the distance above (and below) a surface (as documented elsewhere) is treated the same within a {caves}cave system (see Examples of use of depth, elevation and distance above surface, for A: terrestrial locations, B: caves, and C: aquatic locations. a signifies elevation, either of a land surface or of an air/water interface; b = distance above surface, marked positive (+) or negative (−); c signifies depth (always positive).B, Specifying the vertical position of a location in a cave using an elevation e and a distance above surface X. The location a is at a vertical distance X directly above the floor of the cave, which is at elevation e. The elevation of e is determined within the cave by surveying from a known elevation on the cave floor e1, which is calculated using an estimated distance below the surface elevation at ground zero GZ.). As above, the [elevation] of the cave floor has been determined, so a troglobiont (e.g. an animal) on the roof of the cave is given as meters above the floor of the cave whose elevation has been determined as above ("X" in Specifying the vertical position of a location in a cave using an elevation e and a distance above surface X. The location a is at a vertical distance X directly above the floor of the cave, which is at elevation e. The elevation of e is determined within the cave by surveying from a known elevation on the cave floor e1, which is calculated using an estimated distance below the surface elevation at ground zero GZ.).
Records of non-natural occurrences such as cultivated plants and captive animals, and records resulting from {marine}beach drift or having been washed ashore (such as shells on a beach that do not contain live animals) should have their "non-natural" or "non-wild" provenance recorded. There may be many valuable uses for these records even if the locations do not correspond to natural occurrences of the organisms. We recommend that the location be recorded and georeferenced, along with the nature of the provenance (cultivated, captive, washed ashore, etc.).
An ‘absence’ is when a particular detection protocol, implemented at a particular location and time, does not result in a detection. True absence occurs in areas where the environmental conditions are unsuitable for a species’ survival. Recording of absences has always been contentious. This is partly because it is very much a result of subjective interpretation and it cannot be vouchered. There are three important and overlapping factors – [location], time and methodology. An annual plant, for example, may not be present as an individual at the time of an observation, but may be present at a different time of the year. The location needs to be bounded and is closely linked to the methodology. Uncertainty of the location applies as elsewhere in this document. However, it may have additional implications. Though an observation may record that species x was not detected at a particular location at a particular time using a particular methodology, that location has an uncertainty. The uncertainty is saying that the area within which the observation (non-detection) was made is somewhere within the radius or [shape] defined by that uncertainty. It does NOT mean that the absence can be ascribed to the totality of the area described by that uncertainty.
There are many methodologies by which an observer may ascribe an absence. Each of these methodologies will have an additional methodological uncertainty associated with it, which is important to record, as it may determine the fitness of that non-detection for a particular use. For example, if you took observations every 10 meters along a [transect], and the species was not detected at any of those locations, to what extent can you ascribe an absence to the area covered by the transect? Another methodology may be related to the expertise of the observer. If an expert was intensely searching an area for a species, but at the same time noticed that they hadn’t seen any records of a closely related species, which they would have noticed if it was present – what level of certainty can be given to the surmised observation that the second species is absent from the area?
It is thus important to document:
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The location as discussed elsewhere in this document
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The area covered by the non-detection
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The time, duration, and date
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The methodology used
{ecological}Counts of animals or plants may be made remotely – for example using an aircraft utilizing direct counts by individuals or using camera or video equipment that is then analyzed back in the laboratory. Examples include aerial counts of kangaroos, counts of whales at sea, etc. It may also include the capture of information from {marine}trawls, whereby one or more ships catch marine organisms along one or more paths over a given period (for example, a day) and then the catch is analyzed back on shore. Another example is the use of tracking instruments on birds or turtles, etc. that may give either periodic or intermittent reports of [location]. Other examples are the use of satellites to remotely image penguins in the Antarctic and then use either individual researchers or machines to count the individual penguins from the satellite image and counts of caribou in the arctic using aerial photography.
In many of these examples, the count of the number of individuals within an area is the aim, rather than the location of individual organisms. This may be recorded as a [grid], a polygon, a [path], or a line. Record the location, its [extent], and the [geographic radial] for the [uncertainty] as described for these same geometries in the preceding subsections.
An issue that often arises with insect collections is the challenge of recording [locality] information on small labels. This should not be as big an issue as previously, because new technologies allow for linking information on the label to a database (through barcodes, or QR codes, etc.) with the recording of only basic information on the label. See Wheeler et al. 2001 on guidelines for preparing labels for terrestrial arthropods, but bear in mind the principles laid out in this document when preparing data for insect labels, especially the recording of [datum], [coordinate reference system] or [EPSG] codes, etc., which are not covered by Wheeler et al. 2001.
Record the sources of all measurements. Minimally, include map name and scale, the [datum] or [coordinate reference system], the source for [elevation] data, the [accuracy] reported by the GPS receiver, the UTM Zone if using UTM [coordinates], the [extent] and [radial] of the [location], the method used to record the [depth], etc.