Find Dwell Locations

Available in big data analytics.

The Find Dwell Locations tool determines dwell locations from time-sequential points in a track. Dwell locations are defined as sequential observations with little or no movement over a certain period of time. Depending on your industry, application, or use case, dwell locations can also be referred to as stay points or idle detection. Tracks are identified by the key field specified for the Track ID option. Each track can have 0, 1, or more dwell locations.

Depending on the dwell output type, the resulting layer can display the dwell location as dwell points, all points including dwells, a convex hull of the dwell locations, or a mean center point of the dwell. The output contains the count of features within a dwell location, the start and end time of the dwell, the duration of the dwell, and any additional statistics that have been calculated.

Workflow diagram

Example

The following is an example use case for the tool:

A transportation department is monitoring vehicle movement in near real time to identify dwell locations witnessed throughout the day. The Find Dwell Locations tool can be used to identify dwell locations where vehicles have not exceeded a certain speed threshold.

Usage notes

Keep the following in mind when working with the tool:

• The key field specified for the Track ID and Start Time options must be identified on the input dataset to use this tool.
• The input layer must be of a time type of instant; time type of interval is not supported.
• If you generate an output type of Dwell Features, All Features, or Mean Centers, the output is a point layer. If you choose Convex Hulls, the output is a polygon layer.
• If you're generating an output type of Mean Centers or Convex Hulls, the resulting features have an interval time that creates fields named DwellStartTime and DwellEndTime. These fields are identified as the Start Time and End Time options, respectively.
• Features that are missing the key field specified for the Track ID or Start Time option are ignored during processing.
• You can specify one or more fields to identify tracks in addition to the Track ID option. Tracks are represented by the unique combination of one or more track fields.
• By default, dwell locations are created using a Geodesic method for distance calculation. It is recommended that you use geodesic distance in the following circumstances:
  • When using the Geodesic method, input layers that cross the international date line have tracks that correctly cross the international date line. This is the default. The input layer or processing spatial reference must be set to a spatial reference that supports wrapping around the international date line, for example, a global projection such as World Cylindrical Equal Area.
  • If the input data is in a local projection, use the Planar distance method. For example, use the Planar method to examine dwell locations within a single state. The input layer or processing spatial reference must be set to a spatial reference local to the dataset.
• You can calculate additional statistics using the Summary Fields parameter. The summary fields statistics available depend on the field type you are summarizing.
  • A string attribute field can use the Any, Count, and Count distinct statistics.
  • A numeric attribute field can use the Any, Count, Count distinct, Sum, Sum of squares, Min, Max, Range, Variance, and Standard deviation statistics.
  • A date attribute field can use the Any, Count, Min, Max, and Range statistics.
• The output layer of dwell locations can be represented in one of four ways, as illustrated in the following table:

  Output type	Description	Example
  All Features	Every feature is returned. The resulting features have a time type of instant. Only the dwell observation count statistics are calculated for this output type. The count represents the number of features that belong to a single dwell. Features that are not dwells have a count of 0.
  Dwell Features	Only features that are part of a dwell are returned. The resulting features have a time type of instant. Only the dwell observation count statistics are calculated for this output type. The count represents the number of features that belong to a single dwell.
  Mean Centers	Each dwell has a single point returned representing the mean center of the dwell in distance and time. The resulting features have a time type of interval. The dwell observation count of the number of features in the dwell is always calculated. You can calculate statistics on this type of dwell feature. By default, no statistics are calculated.
  Convex Hulls	Each dwell is represented by a convex hull of the dwell features. The resulting features have a time type of interval. The dwell observation count of the number of features in the dwell is always calculated. You can calculate statistics on this type of dwell feature. By default, no statistics are calculated.

Parameters

The following are the parameters for the tool:

Parameter	Description	Data type
Input Layer	The input point layer with tracks from which to find dwells. The input layer must be a time-enabled layer with features that represent instances in time.	Features
Distance Tolerance	The maximum distance between points to be considered a single dwell location.	String
Timespan tolerance	The minimum time duration to be considered a single dwell location. Both time and distance are considered when finding dwells. The Distance Tolerance parameter specifies distance.	String
Output type	Specifies how the dwell features are returned. Dwell Features—All of the input point features that are part of a dwell are returned. Mean Centers—Points representing the mean centers of each dwell group are returned. This is the default. Convex Hulls—Polygons representing the convex hull of each dwell group are returned. All Features—All of the input point features are returned.	String
Track ID fields	Choose the field or fields to uniquely identify features that are processed. This parameter is automatically populated if the key field specified for the Track ID option has been set on the input layer.	String
Method	Specifies the distance calculation method. Geodesic Planar(Euclidean)	String
Summary Fields	Specifies the statistics that are calculated for specified fields. Different statistics are available depending on whether the field type is a string, numeric, or date field. Any—A sample string from a field of a type string. Count—Calculates the number of nonnull values. It can be used on numeric fields or strings. The count of [null, 0, 2] is 2. Count distinct—Calculates the number of distinct, nonnull values. It can be used on numeric fields or strings. The count distinct result of [null, 4, 3, 4] is 2. Sum—The sum of numeric values in a field. The sum of [null, 1, 3] is 4. Sum of square—The sum, over all observations, of the squared differences of each observation from the overall mean. The sum of squares of [null, 2.2, 3.1, 4.7] is 3.206. Min—The minimum value of a numeric field. The minimum of [0, 2, null] is 0. Max—The maximum value of a numeric field. The maximum value of [0, 2, null] is 2. Mean—The mean of numeric values. The mean of [0,2, null] is 1. Range—The range of a numeric field. This is calculated as the minimum value subtracted from the maximum value. The range of [0, null, 1] is 1. The range of [null, 4] is 0. Variance—The variance of a numeric field in a track. The variance of [1] is null. The variance of [null, 1,1,1] is 1. Standard deviation—The standard deviation of a numeric field. The standard deviation of [1] is null. The standard deviation of [null, 1,1,1] is 1.	String

Output layer

The dwell output layer contains fields based on the Output Type parameter. If an output type of Dwell Features or All Features is set, all input fields are retained and more fields representing information about the dwell are added. If an output type of Mean Centers or Convex Hulls is set, the Track ID field of the input layer is retained and more fields representing the entire dwell event are added. The tables below outline the fields that are added.

Output fields added when the Dwell Features or All Features output type is chosen

Field name	Description	Field type
All input fields are retained	All input fields from the input dataset are retained.	Any
DwellID	A sequentially numbered dwell ID value is created to uniquely identify the dwells.	String
MeanX	The mean x-value (longitude) of the points that form the dwell.	Float64
MeanY	The mean y-value (latitude) of the points that form the dwell.	Float64
DwellDuration	The duration of the dwell event in milliseconds.	Int64
MeanDistance	The mean distance traveled between each point forming the dwell event.	Float64
DwellObservationCount	The number of observations that form the dwell event.	Int32

Output fields added when the Mean Centers or Convex Hulls output type is chosen

Field name	Description	Field type
All input fields are retained	All input fields from the input dataset are retained.	Any
DwellID	A sequentially numbered ID value for the journey. The first journey for a given track is 1, the second journey is 2, and so on. These IDs are used as the basis for the values in the PreviousJourneyId and NextJourneyId fields.	String
MeanX	The mean x-value (longitude) of the points that form the dwell.	Float64
MeanY	The mean y-value (latitude) of the points that form the dwell.	Float64
DwellDuration	The duration of the dwell event in milliseconds.	Int64
MeanDistance	The mean distance traveled between each point forming the dwell event.	Float64
DwellObservationCount	The number of observations that form the dwell event.	Int32
DwellStartTime	The start time of the dwell. This field is identified in the output as the Start Time option.	Date
DwellEndTime	The end time of the dwell. This field is identified in the output as the End Time option.	Date

Considerations and limitations

Consider the following when working with the tool:

• The input layer must contain point features with time-enabled features of a type instant.
• Features that do not have time are not included in the analysis.
• When calculating a convex hull and a dwell location is completely stationary (one unique location) or composed of two unique points that are colinear, a small value based on the tolerance of the spatial reference used in an analysis is used as the width, height, or diameter to create output polygons instead of convex hulls. These polygons are used for visualization and do not represent the spatial extent of the dwell. Examples of these cases are described in the following table:

  Input case	Description	Example
  Coincident (one spatially unique point)	If the input features are stacked (coincident), the resulting convex hull is an invalid polygon. In this example, the coincident input features are represented by the red dot in the center of the yellow polygon. The yellow polygon represents the output convex hull result for coincident points. The blue polygon shows what a convex hull looks like when there are four noncoincident points in a single dwell location.
  Colinear (two spatially unique points)	If the input features are in a line (most common with two spatially unique points), the resulting convex hull is an invalid polygon. In this example, colinear points are represented by red dots within the yellow polygon. The yellow polygon represents the output convex hull result for colinear points.