loc_data_2019

<p>Real data from November 2019 extracted from Google Location History files captured with an Android smartphone. Contains two weeks of human movement behavior of a single person occurring in the Netherlands. Modes include biking, walking, bus and train.</p>

datasets

Trajectory data formed by human or animal movement is often marked
by periods of movement interspersed with periods of standing still. It is
often of interest to researchers to separate geolocation trajectories of
latitude/longitude points by clustering consecutive locations to produce a
model of this behavior. This package implements the Stay Point detection
algorithm originally described in Ye (2009) <doi:10.1109/MDM.2009.11> that
uses time and distance thresholds to characterize spatial regions as
'stops'. This package also implements the concept of merging described in
Montoliu (2013) <doi:10.1007/s11042-011-0982-z> as stay point region
estimation, which allows for clustering of temporally adjacent stops for
which distance between the midpoints is less than the provided threshold.
GPS-like data from various sources can be used, but the temporal thresholds
must be considered with respect to the sampling interval, and the spatial
thresholds must be considered with respect to the measurement error.

Danielle McCool

stopdetection

Stop Detection in Timestamped Trajectory Data using
Spatiotemporal Clustering

McCool Danielle

loc_data_2019 function


<div class="section" id="loc-data-">
<h3><code>loc_data_2019</code></h3><p></p><p>
</p><p>A data frame with 21,911 rows and 3 columns:</p><dl>
<dt>latitude</dt>
<dd><p>unprojected latitude coordinate using WGS84 ellipsoid</p></dd><p></p><p><dt>longitude</dt>
<dd><p>unprojected longitude coordinate using WGS84 ellipsoid</p></dd></p><p><dt>timestamp</dt>
<dd><p>POSIXct timestamp with date and time using fractional seconds</p></dd></p><p>...</p><p></p></dl><p></p><p></p></div>


Format

Timestamped Location Data — loc_data_2019


<div class='section' id='loc-data-'>
<h3><code>loc_data_2019</code></h3>


<p>A data frame with 21,911 rows and 3 columns:</p><dl>
<dt>latitude</dt>
<dd><p>unprojected latitude coordinate using WGS84 ellipsoid</p></dd>

<dt>longitude</dt>
<dd><p>unprojected longitude coordinate using WGS84 ellipsoid</p></dd>

<dt>timestamp</dt>
<dd><p>POSIXct timestamp with date and time using fractional seconds</p></dd>

...

</dl>

</div>


loc_data_2019: Timestamped Location Data

Description

Usage

Arguments

Format

`loc_data_2019`