Reconstruct Tracks (GeoAnalytics Desktop)

Summary

Creates line or polygon tracks from time-enabled input data.

Illustration

Reconstruct Tracks tool
Time-enabled points that have been reconstructed into tracks are shown.

Usage

  • Reconstruct Tracks is run on point or polygon features. The input layer must be time enabled with features that represent an instant in time.

  • You can specify one or more fields to identify tracks. Tracks are represented by the unique combination of one or more track fields. For example, if the fields flightID and Destination are used as track identifiers, the features ID007, Solden and ID007, Tokyo would be in two separate tracks, since they have different Destination field values.

  • Features that have a buffer applied will result in polygonal tracks. Input point features that do not have a buffer applied will result in polyline tracks.

  • Input features will consist of time-enabled features that represent an instant in time. Results are line or area features that represent an interval in time. The start and end of the interval are determined by the time at the first and last features in a track.

    Input features with two distinct tracks (green and red) showing time type instant (left) and resulting tracks (right) or time type interval
    The input features with two distinct tracks (green and red) that have time type instant (left) and the resulting tracks (right) or time type interval are shown.

  • For linear results, only tracks that contain more than one point will be returned. If you apply a buffer, all features will be returned.

  • You can optionally apply a buffer to your input features. When you apply a buffer, the resulting tracks will be polygon features.

    Input points with a buffer applied reconstructed into tracks
    Input points with a buffer applied are reconstructed into tracks.

  • When buffering input features, each input feature is buffered. Then a convex hull is generated to create a polygon track.

    Input points (green), intermediate buffer for visualization (blue hatching), and the resulting polygonal track (blue)
    An example of input points (green), an intermediate buffer for visualization (blue hatching), and the resulting polygonal track (blue) are shown.

  • Fields used in the buffer expression must be numeric and will be applied using the units of the input's spatial reference. See Arcade expressions in the GeoAnalytics Desktop toolbox for more information. You can use track-aware equations.

  • By default, only the count of points or polygons in a track will be calculated. Additional statistics can be calculated by specifying the Summary Fields parameter value.

  • By default, tracks are created using a geodesic method. The method is applied to the following two components of the analysis:

    • Tracks crossing the international date line—When using the geodesic method, input layers that cross the international date line will have tracks that correctly cross the international date line. This is the default. Your 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.
    • Buffers—Input features can optionally be buffered. To learn more about when to apply a geodesic or planar buffer, see Create buffers.

  • You can split tracks in the following ways:

    • Time Split—Based on a time between inputs. Applying a time split breaks up any track when input data is farther apart than the specified time. For example, if you have five features with the same track identifier and the times of [01:00, 02:00, 03:30, 06:00, 06:30] and set a time split of 2 hours, any features that are measured more than 2 hours apart will be split. In this example, the result would be a track with [01:00, 02:00, 03:30] and [06:00, 06:30], because the difference between 03:30 and 6:00 is greater than 2 hours.
    • Time Boundary Split—Based on defined time intervals. Applying a time boundary split segments tracks at a defined interval. For example, if you set the time boundary to 1 day, starting at 9:00 a.m. on January 1, 1990, each track will be truncated at 9:00 a.m. every day. This split accelerates computing time, as it creates smaller tracks for analysis. If splitting by a recurring time boundary makes sense for your analysis, it is recommended for big data processing.
    • Distance Split—Based on a distance between inputs. Applying a distance split breaks up any track when input data is farther apart than the specified distance. For example, if you set a distance split of 5 kilometers, sequential features greater than 5 kilometers apart will be part of a different track.
    • Split Expression—Based on an Arcade expression. Applying a split expression splits tracks based on values, geometry or time values. For example, you can split tracks when a field value is more than double the previous value in a track. To do this, using an example field named WindSpeed, you can use the following expression: var speed = TrackFieldWindow("WindSpeed", -1, 1); 2* speed[0] < speed[1]. Tracks will split when the previous value (speed[0]) is less than two times the current value.

  • You can apply none, one, two, three, or four split options at the same time. All of the examples below use a gap split. The results, assuming you apply a time split of six hours, a time boundary of one day, and distance split of 16 kilometers, are as follows:

    Five examples of input points (green) with varying time and distance splits
    Five examples of input points (yellow) with varying time and distance splits are shown.

    Split optionDescription

    Six input points with a time and location

    Input points with the same identifier. The distance between the points is marked on top of the dotted line, and the time of each point measurement is marked below the points. There are four splits on the timeline. The red splits represent the time boundary split of one day starting at 12:00 a.m. The blue split represents the distance split when the distance between two points is greater than 16 kilometers. The purple split represents the time split when the temporal distance between two sequential points is more than six hours.

    Example with no time split and no distance split

    Example with no time split and no distance split.

    Example with a time split of 6 hours

    Example with a time split of six hours. Any features more than two hours apart are split into separate tracks.

    Example with a time boundary of 1 day

    Example with a time boundary of one day, starting at midnight. At each one-day interval starting from the specified time (here 12:00 a.m.), a track is created.

    Example with a distance split of 16 kilometers

    Example with a distance split of 16 kilometers. Any features more than 16 kilometers apart (the features at 05:00 a.m. and 06:00 a.m.) are split into separate tracks.

    Example with a time split of 6 hours and a time boundary split of 1 day at 12:00 a.m.

    Example with a time split of six hours and a time boundary of one day starting at 12:00 a.m. Any features more than six hours apart or that intersect with the time duration split at 12:00 a.m. are split into separate tracks.

    Example with a time split of 6 hours and a distance split of 16 kilometers

    Example with a time split of six hours and a distance split of 16 kilometers. Any features more than six hours apart (the features at 06:00 a.m. and 7:00 p.m.) or farther than 16 kilometers apart are split into separate tracks.

    Example with a distance split of 16 kilometers and a time boundary of 1 day starting at 12:00 a.m.

    Example with a distance split of 16 kilometers and a time boundary of one day starting at 12:00 a.m. Any features greater than 16 kilometers apart or that intersect with the time duration split at 12:00 a.m. are split into separate tracks.

    Example with a distance split of 16 kilometers, a time split of 6 hours, and a time boundary of 1 day starting at 12:00 a.m.

    Example with a distance split of 16 kilometers, a time split of six hours, and a time boundary of one day starting at 12:00 a.m. Any features farther than 16 kilometers apart, or more than six hours apart, or that intersect with the time duration split at 12:00 a.m. are split into separate tracks.

  • When you split a track using a time split, distance split, or split expression, you can decide how segments between the split will be created. You have the following options:

    • Gap—Create a gap between the two features that were split.
    • Finish After—Create a segment that ends after the split.
    • Start Before—Create a segment that ends and starts before the split.

    The following diagram shows an example of the split types:

    Three types of time splits

    Three examples of time splits on the same input points (yellow) are shown.

    Time split optionDescription

    Five input points with a time and location

    Five input points with the same identifier. The time of each point is marked below the dotted line. There is one split between 2:00 a.m. and 5:00 a.m. for all examples. Each track is split into two segments between the third and fourth points on the track. The first track is green and the second is purple. How the tracks are split is defined by the split type parameter.

    Gap Gap split

    Example with a gap between the two points that are split. This is the default.

    Finish After Finish After split

    Example in which the track finishes after the split, at the fourth point. The second track starts at the fourth point.

    Start Before Start Before split

    Example in which the track splits before the split, at the third point. The second track starts at the third point.

  • The following are examples of why it may make sense to define tracks using the split parameters and the field identifier parameter using an airline flight as an example:

    • An aircraft feature has aircraft ID, flight ID, pilot name, start time, and flight_maneuver fields. The flight_maneuver field represents whether the aircraft is on land, ascending, descending, or at a constant altitude.
      • Use the aircraft ID field as the identifier to see where each plane has traveled.
      • Use the aircraft ID and the flight ID fields as the identifiers to compare distinct routes.
      • Use the aircraft ID field and the time boundary of one year to examine the flights for each aircraft for a year at a time.
      • Use the pilot name, aircraft ID, and start time fields to view each pilot's flight.
      • Use the aircraft ID field as the identifier, and split distances farther than 1,000 kilometers, to determine new tracks, given that a 1,000-kilometer jump in measurements should not belong to the same track.
      • Use the aircraft ID field as the identifier and split using an expression when the value in the flight_maneuver field changes. For example, var flight_manuever = TrackFieldWindow("maneuver", -1, 1); flight_maneuver[0] != flight_maneuver[1] checks whether the current value in a track and the previous value match. If not, the track is split.

  • Output tracks will return the fields used as track identifiers, the count of features within a track (count), the start and end time of each track (start_date and end_date), the duration of the track in milliseconds (duration), and any other optional statistics (formatted as statisticstype_fieldname).

  • You can improve performance of the Reconstruct Tracks tool by doing one or more of the following:

    • Set the extent environment so that you only analyze data of interest.
    • Use the planar method instead of geodesic.
    • Don't apply a buffer.
    • Split your tracks using the Time Split, Time Boundary Split, Distance Split, or Split Expression parameters. The Time Boundary Split parameter will have the biggest performance gains.
    • Use data that is local to where the analysis is being run.

  • This geoprocessing tool is powered by Spark. Analysis is completed on your desktop machine using multiple cores in parallel. See Considerations for GeoAnalytics Desktop tools to learn more about running analysis.

  • When running GeoAnalytics Desktop tools, the analysis is completed on your desktop machine. For optimal performance, data should be available on your desktop. If you are using a hosted feature layer, it is recommended that you use ArcGIS GeoAnalytics Server. If your data isn't local, it will take longer to run a tool. To use your ArcGIS GeoAnalytics Server to perform analysis, see GeoAnalytics Tools.

  • Similar analysis can also be completed using the following:

Parameters

LabelExplanationData Type
Input Layer

The points or polygons to be reconstructed into tracks. The input must be a time-enabled layer that represents an instant in time.

Feature Layer
Output Feature Class

A new feature class with the resulting tracks.

Feature Class
Track Fields

One or more fields that will be used to identify unique tracks.

Field
Method

Specifies the criteria that will be used to reconstruct tracks. If a buffer is used, the Method parameter determines the type of buffer.

  • Geodesic — If the spatial reference can be panned, tracks will cross the date line when appropriate. If the spatial reference cannot be panned, tracks will be limited to the coordinate system extent and may not wrap.
  • Planar —Planar buffers will be created.
String
Buffer Type

Specifies how the buffer distance will be defined.

  • Field —A single field will be used to define the buffer distance.
  • Expression —An equation using fields and mathematical operators will be used to define the buffer distance.
String
Buffer Field
(Optional)

The field that will be used to buffer the input features. Field values are applied in the units of the spatial reference of the input unless you are using a geographic coordinate system, in which case they will be in meters.

Field
Buffer Expression
(Optional)

The expression that will be used to buffer input features. Fields must be numeric, and the expression can include [+ - * / ] operators and multiple fields. Calculated values are applied in the units of the spatial reference of the input unless you are using a geographic coordinate system, in which case they will be in meters.

Use Arcade expressions such as as_kilometers($feature.distance) * 2 + as_meters(15).

If the layer is added to the map, the Fields and Helpers filters can be used to build an expression.

Calculator Expression
Time Split
(Optional)

Features that are farther apart in time than the time-split duration will be split into separate tracks.

Time Unit
Distance Split
(Optional)

Features that are farther apart in distance than the distance split value will be split into separate tracks.

Linear Unit
Time Boundary Split
(Optional)

A time span to split the input data into for analysis. A time boundary allows you to analyze values within a defined time span. For example, if you use a time boundary of 1 day, and set the time boundary reference to January 1, 1980, tracks will be split at the beginning of every day.

Time Unit
Time Boundary Reference
(Optional)

The reference time used to split the input data into for analysis. Time boundaries will be created for the entire span of the data, and the reference time does not need to occur at the start. If no reference time is specified, January 1, 1970, is used.

Date
Summary Fields
(Optional)

The statistics that will be calculated on specified fields.

  • Count—The number of nonnull values. It can be used on numeric fields or strings. The count of [null, 0, 2] is 2.
  • Sum—The sum of numeric values in a field. The sum of [null, null, 3] is 3.
  • Mean—The mean of numeric values. The mean of [0, 2, null] is 1.
  • 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.
  • 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 null.
  • Variance—The variance of a numeric field in a track. The variance of [1] is null. The variance of [null, 1, 1, 1] is null.
  • 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.
  • Any—A sample string from a field of type string.
  • First—The first value of a specified field in a track.
  • Last—The last value of a specified field in a track.

Value Table
Split Expression
(Optional)

An expression that splits tracks based on values, geometry or time values. Expressions that validate to true will be split.

Calculator Expression
Split Type
(Optional)

Specifies how the track segment between two features is created when a track is split. The split type is applied to split expressions, distance splits, and time splits.

  • Gap —No segment is created between the two features. This is the default.
  • Finish After —A segment is created between the two features that ends after the split.
  • Start Before —A segment is created between the two features that ends before the split.
String

arcpy.gapro.ReconstructTracks(input_layer, out_feature_class, track_fields, method, buffer_type, {buffer_field}, {buffer_expression}, {time_split}, {distance_split}, {time_boundary_split}, {time_boundary_reference}, {summary_fields}, {split_expression}, {split_type})
NameExplanationData Type
input_layer

The points or polygons to be reconstructed into tracks. The input must be a time-enabled layer that represents an instant in time.

Feature Layer
out_feature_class

A new feature class with the resulting tracks.

Feature Class
track_fields
[track_fields,...]

One or more fields that will be used to identify unique tracks.

Field
method

Specifies the criteria that will be used to reconstruct tracks. If a buffer is used, the method parameter determines the type of buffer.

  • GEODESIC If the spatial reference can be panned, tracks will cross the date line when appropriate. If the spatial reference cannot be panned, tracks will be limited to the coordinate system extent and may not wrap.
  • PLANARThe tracks will not cross the date line.
String
buffer_type

Specifies how the buffer distance will be defined.

  • FIELDA single field will be used to define the buffer distance.
  • EXPRESSIONAn equation using fields and mathematical operators will be used to define the buffer distance.
String
buffer_field
(Optional)

The field that will be used to buffer the input features. Field values are applied in the units of the spatial reference of the input unless you are using a geographic coordinate system, in which case they will be in meters.

Field
buffer_expression
(Optional)

The expression that will be used to buffer input features. Fields must be numeric, and the expression can include [+ - * / ] operators and multiple fields. Calculated values are applied in the units of the spatial reference of the input unless you are using a geographic coordinate system, in which case they will be in meters.

Use Arcade expressions such as as_kilometers($feature.distance) * 2 + as_meters(15).

Calculator Expression
time_split
(Optional)

Features that are farther apart in time than the time-split duration will be split into separate tracks.

Time Unit
distance_split
(Optional)

Features that are farther apart in distance than the distance split value will be split into separate tracks.

Linear Unit
time_boundary_split
(Optional)

A time span to split the input data into for analysis. A time boundary allows you to analyze values within a defined time span. For example, if you use a time boundary of 1 day, and set the time boundary reference to January 1, 1980, tracks will be split at the beginning of every day.

Time Unit
time_boundary_reference
(Optional)

The reference time used to split the input data into for analysis. Time boundaries will be created for the entire span of the data, and the reference time does not need to occur at the start. If no reference time is specified, January 1, 1970, is used.

Date
summary_fields
[summary_fields,...]
(Optional)

The statistics that will be calculated on specified fields.

  • COUNT—The number of nonnull values. It can be used on numeric fields or strings. The count of [null, 0, 2] is 2.
  • SUM—The sum of numeric values in a field. The sum of [null, null, 3] is 3.
  • MEAN—The mean of numeric values. The mean of [0,2, null] is 1.
  • 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.
  • STDDEV—The standard deviation of a numeric field. The standard deviation of [1] is null. The standard deviation of [null, 1,1,1] is null.
  • VAR—The variance of a numeric field in a track. The variance of [1] is null. The variance of [null, 1,1,1] is null.
  • 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.
  • ANY—A sample string from a field of type string.
  • FIRST—The first value of a specified field in a track.
  • LAST—The last value of a specified field in a track.

Value Table
split_expression
(Optional)

An expression that splits tracks based on values, geometry or time values. Expressions that validate to true will be split.

Calculator Expression
split_type
(Optional)

Specifies how the track segment between two features is created when a track is split. The split type is applied to split expressions, distance splits, and time splits.

  • GAPNo segment is created between the two features. This is the default.
  • FINISH_LASTA segment is created between the two features that ends after the split.
  • START_NEXTA segment is created between the two features that ends before the split.
String

Code sample

ReconstructTracks example 1 (stand-alone script)

The following Python window script demonstrates how to use the ReconstructTracks tool.

# Name: ReconstructTracks.py
# Description: Reconstruct hurricane points into hurricane tracks, where each 
#              location is buffered by the wind speed * 100.

# Import system modules
import arcpy

# Set local variables
inFeatures = "c:/mydata/Hurricanes.shp"
trackIdentifier = "EVENTID"
out = "c:/mydata/OutputDatasets.gdb/HurricaneTracks"
bufferExpression = "WINDSPEED * 100"
statistics = [["PRESSURE", "MEAN"]]

# Execute Reconstruct Tracks
arcpy.gapro.ReconstructTracks(inFeatures, out, trackIdentifier, 
                              "GEODESIC", "EXPRESSION", None, 
                              bufferExpression, None, statistics)

Licensing information

  • Basic: No
  • Standard: No
  • Advanced: Yes

Related topics