Lesson 1. Confusion and clarity.

Hi!
I have chosen to write this blog in English although my mother tongue is Swedish and I understand Finnish as well, so that it would be useful to as wide an audience as possible. 

So, this course is something I have been waiting for ever since I heard about it from a friend who had it last year. There is something about maps that have always intrigued me and the thought of interactive maps filled with data ready to be played and tinkered with made me ecstatic!

The main focus of this course is to learn how to operate the software application Q-GIS which is an application with which one can produce and interact with data driven maps. During our first lesson we went through some key things about Q-GIS with our teacher Arttu Paarlahti continuously throwing in titbits of extra information here and there. At first we learned about the general set up and UI (user interface) in Q-GIS, but then Arttu made the important remark about any data management software paraphrasing  – …it’s not very possible to learn how to use Q-GIS by just looking at it, you need to use it in practice to actually learn how to use it…

Naturally following we imported a set of data consisting of a map of northern and central Europe and the amounts of pollutive nitrogen in  the Baltic Sea for each country. First we just played around with the data; ordering around layers, changing colours, looking at data.

Then came the first actually interactive part of using Q-GIS. We were supposed to visualize the data about pollutive nitrogen in the Baltic Sea for each country by creating a choropleth map based on the available data. To achieve this we had to turn the absolute numbers into relative numbers which luckily was easy enough within Q-GIS itself. To complete the task we still needed to add a legend explaining colours and specifying numbers, add a scale bar and add an arrow pointing north. The map is shown below (Picture 1.).

Picture 1. The picture shows a map visualizing the relative amounts of pollutive nitrogen in The Baltic Sea for each country.

In my mind the map turned out quite decent and the procedure was clear enough as I just followed what Arttu did and asked questions when needed. Reading Sanna Jantunen’s blog (Jantunen 2021) lessened my like for the map as she pointed out some rather good points about her own map. She made a remark about the depth lines being redundant, only stealing attention from what is truly important. This I absolutely agree with!

For homework we got to produce a similar choropleth map on our own. This time I struggled quite hard as I had forgotten how to execute some of the actions which we used during the lesson. We were supposed to choose one section of the imported data about Finnish municipalities to visualize differences and similarities between the municipalities. This was pretty much the same exercise as we did during the lesson, but soon enough I got stuck. I tried and tried, but couldn’t find the function where you change the visuals of the map. At last I looked at the recording of the lesson and found the answer. What a relief! I really hope that these kinds of recordings don’t disappear when the distance learning is not the case anymore. What would be even better would be pre recorded theory lessons which the teacher would post on Moodle for students to look at before each live-lesson so that the live-lesson would then be as efficient and smooth as possible. This would save time for the teachers in the long run as well as demonstrating the dedication of The University of Helsinki to the wonderful possibilities that technology could add to education. 

The map which I created visualizes the geographical distribution of Swedish speaking Finns in Finland. As can be seen on the map (picture 2.) the Swedish speaking population is concentrated to the coastal areas in the south, to the region of Ostrobothnia and to the Finnish archipelago. To reflect the harsh lingual divide in Finland I chose to use a rather polarized range of red-ish colours to emphasize the differences between municipalities and different regions in Finland.

Picture 2. The Picture shows the relative amounts of Swedish speaking Finns in the municipalities of Finland.

Martta Huttunen made a similar map which she put in her blog (Huttunen 2021), but concerning the distribution of Saame speakers in Finland. Saame speakers are predominantly found in the northern parts of Finland, but interestingly  a small minority (1-4%) can also be found in Helsinki. Huttunen continues to explain the reasons behind this, a key factor being The University of Helsinki being the only university south of Oulu where one can study Saame. 

I have found the content of this first week quite motivating. Although the data we analyzed and visualized was rather dry and not highly interesting the exercises were challenging and I felt like I actually learned something new and important compared to many of the earlier courses I have had. I look forward to the weeks to come as we get to delve deeper into the world of Q-GIS and geoinformatics; failing and succeeding, struggling and overcoming, but foremost – learning and preparing us for a road to masters.

 

Alexander Engelhardt

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