extractClustersBuffer: Identifies clusters of points of GPS tracks.

In henningte/herdersTA: Extracting Movement Characteristics from GPS Trajectories of Nomadic Households

Description

extractClustersBuffer identifies clusters of points in GPS tracks based on their spatial proximity. This is done by applying density based clustering on all points within a specific daily time interval (e.g. during night). Daytime data values are assigned to the respective location id (1) if the next value after and prior the daytime values (i.e. the last value of the previous night and the first value of the following night) are identical (i.e. are defined as gaps if both values are gaps or to a location id otherwise), then (2) if the next value of the previous night is not a gap to the respective location, and then (3) if the next value of the following night is not a gap to the respective location. Therefore, results reflect a daily resolution with respect to different locations.

Usage

extractClustersBuffer(currenttrack, radius = 800)

Arguments

currenttrack	An object of class Track. currenttrack must have a logical variable gap as created by reorganizeTracks and an attribute night as created by classifyNightTrack.
radius	A numerical value representing the radius of the buffers computed around each point [m] which are used for clustering values to locations. Default is radius = 200 [m].

Value

An integer vector with the same length as the number of points in currenttrack indicating to which cluster each point is assigned. Cluster indices are not ordered, however points of trsSP representing gaps (as indicated by currenttrack$gap) get the cluster index 0.

Examples

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henningte/herdersTA documentation built on Jan. 22, 2020, 5:16 a.m.