I've done a bit of work on this in GeoTools/GeoServer by extending the Heatmap Rendering Transformation to support geometries other than points.
It's not finished yet, but you can get the feature branch from my repository on GitHub.
The screenshot is of GPS tracks from when I worked as a pizza delivery driver.
I couldn't stop thinking about this... I was able to come up with a Stored Procedure to do the loop counting. The example path contains 109 loops!
Here are the flight points shown with the loop centroids in red:
Basically, it runs through the points in the order they were captured and builds a line as it iterates through the points. When the line we are ...
As @Loxodromes said above, I too am not sure that an open source library exists to do this. But it's simple enough to do in Python if you're happy enough with the scripting. For example, if you have access to numpy and scipy you can use a KDTree to easily calculate points from trail A that are within some tolerance of points from trail B.
With a bit of work ...
PDAL has an SBET reader (and a writer too) that you could use to convert the file into text and then on to most other formats.
pdal translate myfile.sbet output.txt
It is a very simple format though. See the PDAL source code for more detail on what's in there.
here is my simple approach:
create a new map in umap: http://umap.openstreetmap.fr/en
click Import Data a select all the gpx files you have and upload them into map (you can import all of them at once)
enter Edit map settings > Default properties, choose opacity 0.25, weight 10.
The three steps above will take 5 minutes and here is the result:
GPS track logs for vessels can be accessed using AIS.
Ships broadcast information such as GPS position, heading, and speed. Updates are sent over radio at periods of between 2 and 30 secs for a moving ship.
Data can be accessed on sites such as aprs.fi who provide an api, although not in GPX format. Many commercial sources also exist that can provide ...
About different geometry types:
From your description it looks like you should absolutely store your trajectories as linestrings. If you store them as points or multipoints you will have to build linestrings in runtime if you don't only want to do the calculations on the points defining the trajectories but also what is between the points.
an Example (in ...
I don't think this question can actually be answered definitively as there are many, many ways of approaching this ..
However, these thoughts may be relevant:
The data storage is relatively unimportant. Whatever mechanism you use, Database, JSON, KML, etc, it is still "flat storage".
What is important is the software you use and how you represent the ...
Yes, it is possible but not as straightforward as the question may indicate. Points are only one of many items needed. For example, you have the points but do you have the names, start and end point of a road distinguished, z-level information (one road may cross another but not have an intersection), one-way information, and so on? If you have points then ...
The SBET and SOL files have identical very different file structures. I use a python script to parse both SBET and SOL files. The script I use was modified from original NERC-ARF Tools.
EDIT: I didn't dig enough before answering. You are correct about the file size of 184 bytes, which follows with the NERC-ARF file structure. Each record has a 'header' ...
Your question has an active research area and many papers are dedicated to extract the geometrical properies of street network from moving objects (vehicles etc).
For example see
Constructing street networks from GPS trajectories (PDF)
A comparison and evaluation of map construction algorithms using vehicle tracking data
Apart from street names which ...
I noticed that the gpx file has time stamp which could be exploited.
Perhaps the below approach could work.
Make a linesegement with Vi,Vi+1
Make it Polyline
Proceed to Vi+2,Vi+3 check intersection with Polyline
if it intersects
find the point of intersection-Designate this as start/end point of the loop
Make this intersection point as Vi and ...
GPSBabel has a function for this. To take a GPX input file and interpolate points so that each is 30 seconds apart:
gpsbabel -i gpx -f INPUT.gpx -x interpolate,time=30 -o gpx -F OUTPUT.gpx
-i gpx: input file type is GPX
-f INPUT.gpx: filename is INPUT.gpx
-x interpolate,time=30: apply a filter (x), using interpolation, interpolating any points >...
I think your research is consistent with what I saw the one type I needed to read this format in Python. It's relatively simple to parse as a binary file and there are code examples of how to do so, but it's not part of any commonly used library you'll be able to grab with setup tools.
I think stuff like this:
Here is my approach on QGIS. This was for a set of bus routes, and I wanted to identify which roads had the most density of bus routes passing by.
Used the Qchainage plugin to convert my lines into points. Tested different scenarios until I produced a lot of points per line (1,500 per line, and lines were about 9kms).
Applied the heatmap symbology rendering ...
I think you might be best off considering whether you should use a range of metrics. Some users may consider the average spatialite error to be of concern, but a bigger concern is "how bad does it get". You are presumably looking at this in at least some respect (e.g. temporal vs spatial), I'm just suggesting looking very widely.
I don't have all the ...
ggplot2 and dplyr should be enough for this. They're general, not specialised packages, but once you get used to them, they're very versatile.
x <- x %>% filter(Code!=90) ##Just cleaning to remove those 'NA' rows
##Label start and end points
x <- x %>% group_by(CycloneNo) %>% mutate(state=case_when(StepNo=...
If I'm understanding correctly, a quick solution might be to just snap each track point to a grid, then do a boolean AND of the snapped version of each layer. A quick way to snap might be to just round the numbers to whatever accuracy you need:
rounding to the nearest unit,
I finally found the answer to my question:
What I needed to do was to reproject from EPSG:32632 to 4326. This is done by defining a "declared layer" to 4326 and setting the option "reproject native to declare". This is not however the end of the story. You still need to recompute the associated BBox. On the geoserver GUI, this is done by clicking on "...
The best solution up till now implements everything in SQL with postgres. It uses moving averages (windowing function) to smoothen out the trajectory plus some simplification of the computed path. Here's the SQL code:
The python module Machine Learning Python (mlpy) has an LCS method including an LCS for real series:
Perhaps you could also adapt the LCS algorithm for strings and test your own implementation against mlpy.
A quick google search results in the folloing Wikipedia page:
I think dwell time and trajectory are more appropriate words for this. See "Estimating the most likely space–time paths, dwell times and path uncertainties from vehicle trajectory data: A time geographic method".
-- Tang J, Song Y, Miller HJ, Zhou X (2015)
The part that you are missing is a map server. A map server has the job of taking raw map data and (ordinarily) serving it up as a styled bitmap image with the colors and format based on some pre-defined styling rules.
The servers then make those bitmaps available via a web accessible API that front end libraries like Leaflet or OpenLayers know how to ...
I realize this is quite an old post, however, I came across it doing similar research. I developed a pretty simple model/work flow that can accomplish just this in ArcGIS (possibly QGIS, but I've not yet implemented it there).
If you have a GPX or TCX file specifically (any point file works though), it can simply be opened up in Excel, then converted to a ...
So it is not a simple arithmetic mean of two vertices, but the mean of the altitude along the line segment, right?
It can be done in two steps:
Explode lines - breaks your line into segments (QGIS Processing Toolbox | Vector geometry)
Add raster values to features - calculates mean of all cell values along each segment (QGIS Processing Toolbox | SAGA | ...
As a backend for your maps you can use NextGIS Web (or http://nextgis.com free account). Nice QGIS or Mapserver styles are supported. Shapefiles can be styled in QGIS and upload to NextGIS Web with styles using NextGIS Connect plug-in.
Convex hull approach?
Take 1st 4 points and create 2 polygons, 1st being simple polygon connecting points in original order, close it to 1st point.
Calculate convex hull of points and compare the areas of 2 polygons.
If areas are different this is 'wrong' shape.
Proceed with point 1..4, etc. Count how many times each point participate in wrong polygon. ...
I realize this question has been answered, but I have a slightly different take on it that I figure is worth sharing.
I expect this isn't language or platform specific.
Turn both tracks into linestrings,
Buffer one of the resultant linestrings by your expected/acceptable error margin (may require projecting to an alternate coordinate system), this ...