Working with paths and heatmaps in Lampyre

We often emphasize that Lampyre app is not only a versatile OSINT solution, but also a very powerful analytical tool that allows you to manage data arrays of any type and size in a quick and easy manner. In our previous articles we promised you to show some extra ways for working with data on the map. So, let’s talk about paths: they can be useful in many scenarios.

Let’s imagine that you are a data analyst in a local courier company. Your goal is to optimize the couriers’ routes and plan the delivery schedule as efficiently as possible. One of your couriers works within a particular neighborhood, and you have a list of deliveries he ran yesterday. The data from the list includes delivery times and delivery addresses with their GPS coordinates. That’s what we are going to focus on first, because if you have date/time, latitude and longitude in your dataset, you will be able not only to show it on the map but also to create a path and analyze it.

So, the first thing you would do is upload a dataset in Excel, .csv or .txt format. Once imported, double-click the file in Lampyre to see it as a table and ensure everything has been imported correctly.

The next thing you need to do is to map the data from your file, so that Lampyre could build a path based on it. Add a new creation template and set a name for it (in our example we simply copied the name of our spreadsheet). Then add a new object, add the attributes and map the corresponding columns from the table to these attributes. As per screenshot below, we created a new object named Delivery with the following attributes: Name for Courier ID, Date and time and Geo point for latitude and longitude — that’s basically all you need to place your data on the map:

Once you’re done setting up your dataset, it’s time to draw it on the map! Go back to Import window, select your dataset and apply the creation template you just made by choosing it under GIS map’s drop-down menu:

You will see a map with your data placed as points. To switch to Path view, go to Explorer window, find your map and enable Path view for it:

Now, this is what you’ve got at the moment. All delivery addresses for the day connected by a very long path. Not quite clear what’s going on here, is it?

Let’s fix it by playing around with the settings. Open Properties window, then select an item on the map — either a point or a path — and change the view settings for it the way you feel it is convenient. In our example, we changed the paths’ color to light blue, as well as indicated the coordinates as blue triangles:

Now we will show you a little trick. Bring GIS Map and Table windows on top, so that you see them both. If you select a row on the table, the corresponding point will be highlighted on the map. It also works vice versa: click on a point on the table, and you will see the row for that point.

Let’s suppose that you, as data analyst, need to do find areas for optimization — and a Timeline tool will help you with this! Let’s open a Timeline window and select an interval here, for example, between 5 and 6 PM. The data in the table was filtered automatically, so now we see that there were three deliveries during this time. Now let’s look at the map: the three deliveries and the path between them are highlighted in red.

So how could we improve the courier’s efficiency? We see that there is a gray point along the path (circled in a screenshot below). What we see is that our courier made two deliveries there: number 2 below the grey triangle indicates that. However, both were outside the interval we selected, as well as visited twice and separately during the day: there are two arrows leading to the gray point, and the other two leading away from it:

Accordingly, based on this, you can see that this route part can be planned to include two more addresses. Covering more addresses along the route would help to increase the number of deliveries: for courier business, less distance means savings of time and money!

Last but not least, there is one more feature: you can enable path animation in Properties window. It will draw the path between points step-by-step, so that way you can see how a courier travelled between the delivery addresses during the day:

Now let’s see what heatmaps look like. We are going to take a bigger file, which includes deliveries done by three couriers during the day. Then import it and do the initial placing of our data on GIS map — the steps are same as described above. To enable Heatmap view, go to Explorer window, find your GIS map and enable Heatmap view for it. In our example with deliveries, the heatmap below shows all areas where deliveries took place, with red color representing the area which had the most deliveries during the day:

Similar to paths, you can focus on specific items from your data array with the help of a timeline and a table. For example, you want to look at deliveries made between 9 and 10 AM. You pick this interval using a timeline, as a result Lampyre shows only relevant rows in the table. Then you go to the table and select these rows. As a result, Lampyre draws a polygon based on the coordinates from your selection:

Such visualization is very helpful in all areas that require analysis of geolocation-based data. This is just one of many possible use cases for Lampyre app, so give it a try, this might be a perfect fit for your case too!