In this way, we will only need to use a POST Request node with a delay of 2,000 ms.Įlevation data visualized on Bing Map using the OSM Map View node. Now we have a JSON table with the arguments for the API POST.The nodes in this case would be: the Columns to JSON and JSON Row Combiner. Generate the JSON with the latitude and longitude data in the required format.Generate a loop to request a maximum of 1,000 points per call.Filter this data to generate the JSON that I will use as a request body in a POST call to the service.Identify points that have no elevation data or have an error.
Maps 3d gps tracks download#
By being careful with the calls, I was able to download the information for over 105,000 points that had previously wrong or missing elevation information in less than 4 minutes. To be honest, extracting just the GPS information and displaying it didn’t seem sufficient but I also didn’t want to incur the expense of an API like Google’s to get the elevation.Īfter some research, I found an API service ( ) that I could use to automate those queries and get the data. Missing elevation dataĭuring the data blending process, I realized that there were stages and caminos that did not have elevation information. In any case, I already had 398,000 GPS points to begin with. This is when a tool like KNIME helps you tremendously to blend data from different sources. Leave a comment and give me the opportunity to learn :-).ĭuring this ETL process, I noticed that some files were missing or even data within some of those files. I am sure that more advanced KNIME users will find a better way of doing this. Here is the detail of the GPX parser workflow that I implemented with KNIME. I chose GPX because I found it easier to extract the data to an intermediate JSON file.Īfter downloading each of the 1,015 individual files corresponding to all the stages of all the variants of all the Caminos, I unified them into a single database of GPS points using the open source, no-code tool for data science par excellence: KNIME Analytics Platform. Data is available in both GPX and KML formats. This information has been provided by the Federación Española de Asociaciones de Amigos del Camino de Santiago ( FEAACS). I am more interested in the technical viability than the perfection of the result.Īs I said before, the starting data is all the GPX files available on the CNIG portal ( Spanish National Center of Geographic Information). I am not an expert programmer and it is a personal project.
![maps 3d gps tracks maps 3d gps tracks](https://ak.picdn.net/shutterstock/videos/13255625/thumb/1.jpg)
The initial premise is simple: geolocalized information available to be processed with no-code tools, and an easy way to visualize it that can be integrated into a WordPress-based website.
Maps 3d gps tracks how to#
But how to approach the whole process without programming? There is more and more geopositioned information, and being able to visualize it quickly and easily while having it embedded in a web page is the best way to analyze it. Or is it easier to obtain data of this type? I have no idea.Īnyway, lately I have been exploring how to create a 3D map to visualize information from routes in GPX format. What could be the reason? Maybe my natural predisposition to travel and explore. If you have read my previous article, you know that I love visualizing and working with geolocated data.
![maps 3d gps tracks maps 3d gps tracks](https://live.staticflickr.com/8274/8706049702_eab6fb15b8_n.jpg)
Maps 3d gps tracks code#
Using no code tools to process massive geoloc data