Argos data filters

Filters for Argos Doppler data provide flexible, automated and repeatable methods for filtering your Argos data. Data Managers can currently apply two types of Argos filters to their study data in Movebank: a Simple Argos Filter and the Douglas Filter. If the Argos data are being imported to Movebank via a live feed, these filters can be set up to automatically filter incoming data. If the Argos data are already in Movebank, Data Managers can apply the filters using the Event Editor. Note that these filters require both location estimates provided by Argos as well as the LC (Argos location class) attribute. In addition, the Best of Day filter in the Douglas Filter requires the Argos IQ and Nb mes attributes, and you will need these attributes in your dataset for the filter to run. Argos IQ values without leading 0s, such as provided by Argos WebService, will give the same results as 2-digit values (for example, a value of "06" will be processed the same way as a value of "6").

In addition to applying the filters as described below, as a first step of filtering, Movebank runs an algorithm to identify Argos "mirror" (Solution 2) locations that are very likely to be the better of the two Argos location estimates, and in these cases will store the Solution 2 coordinates as the Movebank latitude and longitude attributes—this happens in about 3% of cases. The algorithm chooses between the Solution 1 and Solution 2 locations along an animal’s track by determining the set of points that results in the shortest path through all combinations of both sets of locations, ignoring class Z locations. The algorithm then makes a second pass to fill in either the primary or alternate class Z locations. Distances are calculated as great circle routes (orthodromes) using the World Geodetic System 1984 reference ellipsoid. The LC and Douglas filters are then run on this improved set of locations. See Douglas et al. 2012 for details. Both sets of coordinates remain stored in your dataset. These changes will not be reverted if you later clear your Argos filter settings. You can also manually select which solution to use as the "correct" location in Movebank using "Argos valid location manual".

To apply filters to your Argos data,

  • Select the study (or an individual animal or tag) from the Studies page.
  • Select Data > Edit from the Studies menu.
  • If asked to select a sensor type, select Argos Doppler Shift.
  • After the data have loaded in the Event Editor, select Filter Data (located above the sensor type and study name).
  • From the dropdown list that appears, select Simple Argos Filter or Douglas Filter.
  • See the instructions below for choosing filter parameter settings.
  • Once you have chosen parameter settings, select Run to run the filter.
  • You may re-run filters as many times as you like, or clear all filtering by selecting Filter Data > Undo Filtering.
  • Select Save (located below the table) to save the dataset with the applied filter settings.

Applying these filters will mark some locations in your dataset with a “true” value in an Algorithm Marked Outlier attribute. It will not delete or modify any other part of the dataset. Points marked as outliers will show up as crosses on the map in the Event Editor and will no longer appear on the Tracking Data Map page.

These filters will work with Argos Doppler locations calculated using both the least squares analysis and Kalman filter methods. See here for more information.

Simple Argos filter

The Simple Argos Filter is based on location classes defined by Argos that indicate the accuracy of each location obtained by Argos Doppler Shift sensors. The Argos LC attribute contains the class values.

To create the filter, choose the least accurate location class that you want to be included in the filtered data. For example, if you only want to exclude locations Argos indicates as failed (location class Z), select B (the location class with the least accurate locations not considered failed). Points with the location class B and all more accurate classes will be retained, and only class Z points will be marked as outliers. The location classes are listed in order of increasing accuracy (i.e., Z being the least accurate and G being the most accurate).

Douglas Argos-Filter Algorithm

The Douglas Argos-Filter Algorithm (Douglas Filter) allows you to filter Argos data by flagging locations that exceed thresholds for distance between consecutive locations and velocity and bearing between consecutive movement vectors, as defined by the Data Manager. It was originally developed by David Douglas from the U.S. Geological Survey in Alaska and has been re-implemented for Movebank with David’s help (Thank you a lot, David!). In order to use it, you will have to set several parameters, described below. For more information, see the following resources:

Filter methods

  • MRD: Retains subsequent points which are closer than maxredun together.
  • DAR: Retains points which correspond to a realistic rate of movement and which do not form tight angles.
  • Best Hybrid: Combines the results of MRD and DAR filters for migratory species.

Parameters required by all filters

  • keep_lc: Points with an location class (LC) better or equal to this are always retained.
  • maxredun: Radius in km within which 2 points are considered self-confirming.

Duplicate record treatment

This parameter is unique to the implementation of the Douglas Filter in Movebank. Occasionally, two Argos location records will have identical timestamps. This situation can arise when two satellites pass over an animal at the same time, increasing the chances that the two location estimates could have identical timestamps. If this occurs in your dataset, Movebank can treat the records with duplicate timestamps in two ways:

  • offset by one sec: Temporarily offset duplicate timestamps by 1 second (recommended). To allow the Douglas Filter to judge the plausibility of both location estimates, this option temporarily offsets one timestamp by one second while running the filter algorithm. The original timestamps are unchanged. This can result in a filtered dataset in which two records with duplicate timestamps are retained but will ensure that both records are tested using the filter parameters you have set.
  • filter: Flag records with duplicate timestamps as outliers, while retaining one of the records if it meets the filter requirements. If both records with duplicate timestamps are identical, the last imported record is retained. If both records are not identical, the record with the better LC is retained; if the LC is the same, then the record with the better nb_mes is retained.

MRD filter advanced parameters

  • keeplast: Retain the last location for each animal.
  • skiploc: Consider 5 consecutive locations, and call them A, B, C, D, and E. The MRD filter considers consecutive triplets of locations; the first triplet would then be A, B, and C. Three distances are calculated: AB, BC, and AC. If any of the 3 distances are less than maxredun, the two respective end-point locations are retained by the filter. In the case location ‘B’ is rejected: if skiploc=0, then location ‘B’ is considered, and the next triplet would be B, C, D; and the 3 distances BC, CD, AND BD would be evaluated. If skiploc=1, then location ‘B’ is not considered (it is skipped), and the next triplet would be C, D, E; and the 3 distances CD, DE, and CE would be evaluated. Most past feedback to DAF indicates users prefer skiploc=0.

DAR filter parameters

  • minrate: Maximum realistic rate of movement in km/h.
  • ratecoef: Determines the minimum accepted turning angle among 3 subsequent points as a logarithmic function of the distance moved. Overall, tighter angles are accepted with smaller movement distances. ratecoef serves to tune that relationship. Larger values for ratecoef will be less tolerant of acute turning angles, resulting in a more directional movement path. Smaller values of ratecoef will be more tolerant of acute turning angles. ratecoef values between 10 and 25 have been most commonly prescribed.
  • r_only: Skip the angle test, filter only based on the rate of movement.

Best hybrid filter parameters

The parameters xmigrate and xoverrun determine if a sequence of points is considered a migration event.

  • xmigrate: Determines the minimum distance of a migration event.
  • xoverrun: Determines how much of a detour is accepted for a migration event. The following parameters determine if a point which is part of migration event is considered realistic.
  • xdirect: A limit for the deviation from a straight line.
  • xangle: A limit for the deviation from a straight line.
  • xpercent: A limit for the deviation from a straight line.
  • testp_a: Number of limits which need to be met if location class (LC) is better or equal than A.
  • testp_bz: Number of limits which need to be met if location class (LC) is equal or worse than B.

Best of Day filter parameters

The Best of Day filter selects one position ("Best of Day") per day or duty cycle. It is applied after the regular filtering procedure.

  • pickday: Choose "Best of Day" per GMT day, otherwise it is selected per duty cycle.
  • minoffh: Maximum time lag between 2 subsequent measurements in a duty cycle. Only relevant if pickDay = false.
  • rankmeth: Determines which criteria are used in which order to pick the best point within a duty cycle.
    • Option 1: Use LC, IQX, IQY, NBMES
    • Option 2: Use LC, IQX, NBMES, IQY
    • Option 3: Use LC, NBMES

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