Posts Tagged ‘map’

A Quick Map With QGIS and OSM

Posted: June 18, 2015 in GIS
Tags: , , ,

What I love about QGIS is that one is able to create a nice map quickly. The other day I was asked to make a situation map for the project we are working on to include it into presentation. Аll I had was a laptop with no relevant spatial data at all, but with QGIS installed (I even had no mouse to draw something). Though it was more than enough: I loaded OSM as a base layer and used annotation tool to add more sense to it. Voilà:

As access to the GIS and mapping is becoming easier every year the more people and companies create maps. Unfortunately often they just do not know what they are actually showing at their maps. This issue is being mentioned over and over again.

Here is the example that I discovered recently: Cyberthreat Real-Time Map by Kaspersky antivirus company. Here how it looks like:

Amongst the other info they show the Infection rank for each country… based on total threats detected…. You may have already guessed what is the fail, but I let me explain it anyway.

See, the №1 infected country is Russia, which is the home country for Kaspersky and where this antivirus is quite popular. So we can conclude that the rankings that supposed to demonstrate the severity of virus activities merely demonstrates the number of Kaspersky software installations across the globe.

Lets test this hypothesis. I don’t have the data about the number of installation of Kaspersky software per country, but it is safe to assume that this number is proportional to the population of the given country. Also it is easier to get infection rankings for countries from the map than the number of the threats detected. If I had total threats data per country I would compare it to the population. Having infection rankings it is more rational to compare it to the population rankings instead. So I picked 27 random countries and compared their infection and population rankings. The result is demonstrated at the plot below:

Infection rank vs. Population rank

The linear model is fairly close to Inrection rank = Population rank. It is clear that the phenomena that is presented as an Infection rank just reflects a total software installations per country and not the severity of the ‘cyberthreat’. In order to get the actual Infection rank the number of detected threats have to be normalised by the number of software installations.

 

Schema of the Conservation Areas in Leningradskaya Region

About a year ago I was asked to create a small (a B5 size) and simple schema of the conservation areas in Leningradskaya region. I did it using QGIS. Here you are the author version of the schema and several notes that might be helpful for a beginner map-maker.

There was a huge disproportion between areas of different objects and both polygon and point markers were needed to show them. I decided to use Centroid Fill option in polygon style to be able to use only one layer (polygon) instead of two (polygon and point). Using Centroid Fill makes points in centres of the small polygons overlap and mask these tiny polygons.

All the administrative borers were stored in one layer (and there are far more borders than one see here). They are drawn using rule-based symbology so I didn’t even need to subset this layer to get rid of the rest of the polygons in this layer.

All the names of the surrounding countries, regions, city and the water bodies are not labels derived from layers, but labels created inside the map composer. It was quicker and their position was more precise which is crucial for such a small schema.

There was a lack of space for the legend so I had to utilise every bit of canvas to place it. I had to use 3 legend items here. One of them is actually overlapping the other and setting a transparent background for the legends was helping with that.

Finally labels for the conservation areas (numbers) were outlined with white colour to be perfectly readable. Some of them were moved manually (with storing coordinates in special columns of the layer) to prevent overlapping with other labels and data.

P.S. Don’t be afraid to argue with the client about the workflow. Initially I was asked it manually digitise a 20 000 x 15 000 pixels raster map of the Leningrad region to extract the most precise borders of the conservation areas (and districts of the region). Of course I could do it and charge more money for the job, but what’s the point if some of that borders are not even to be seen at this small schema? So I convinced client to use data from OSM and saved myself a lot of time.