How we use analytics data to improve Global Forest Watch
It’s been nearly two years since I started working at vizzuality. In that time there hasn’t been a week where I haven’t been thinking about or looking at the analytics for Global Forest Watch (GFW). Every piece of analysis helps frame decisions about new features, things to refine and new ways to communicate forest data. I want to show you some of the things we’re learning about who uses GFW and how they use it. Who knows, maybe it will help you communicate the data as well…
In this first blog, I want to investigate which forest areas people are most interested in. I’ll be looking at how people interrogate different parts of the world using the interactive map, country pages, and embedded maps.
I’ll start with the big picture: on the main GFW map, where are people looking? As you can see in the map below, there are a few key places people gravitate to. There are peaks of attention on the three main areas of tropical rainforest in the world — South and Central America, Central Africa and Southeast Asia — as well as a hotspot in Eastern Europe (near Romania) and the Northeast and Northwest coasts of America.
The keen eyed among you will spot that these observations are very similar to an analysis we did last year, so it looks like people keep returning to the same places. From this we can deduce that, in general, people have pretty stable interests in forests. So if we want to use GFW to shed light on forest change in new areas, it will need to be curated in some way to bring it to the fore of people’s minds. That could be blogs, or new features on the map that guide people to look at interesting areas across the world.
Quite often the next step someone takes is to visit a country page. Once there, they can follow up on their findings with a closer look at the context of a particular country and the trends in forest change over the last 15 years. Seeing which country pages receive most attention is therefore another way to identify which areas people care about most.
Indonesia and Brazil are the top two country pages. Nearly 20% of all time spent on country pages is on these two. Other countries that are receiving longer amounts of time on their country page, compared to most countries, include Canada, Malaysia, China, the USA, Argentina and Russia. Conversely, there are 83 countries where less than five hours of time has been spent on their page.
On deeper analysis, we’ve seen two key traits in core parts of the audience for a country page. First, they are likely to be people from that country looking at their own country page. Second, they are more likely to be a returning visitor. What this tells us is that, for some people, visiting their own country page is a key reason to return to the site. We’re using this to inform some improvements to the country page, so it can be more useful for this kind of user.
Instead of going to a country page, users might decide to perform an analysis on the map. In recent months there have been around 5,000 analyses a week, many of which involve a protected area, a concession area or a whole country. We can view the places where people are analysing data as another indicator of the places that people care about.
Southeast Asia and South America is the focus of over 45% of the analyses we can attribute to an area, led respectively by Indonesia, Brazil and Peru. African countries are also analysed quite regularly, notably the Democratic Republic of Congo, Gabon and Kenya. People are coming to analyse logging areas in the Democratic Republic of Congo, whereas protected areas are of greater interest in Kenya and Gabon. Central American countries, led by Honduras and the Dominican Republic, and their protected areas are also a focus of attention. Over the coming months we hope to analyse the coordinates of user-drawn polygons, which are used more frequently to define the boundary for an analysis.
What’s notable here is the difference in the spread of time on country pages. There seems to be more analysis happening in Southeast Asian, South American and African countries, and far less in Europe and North America. Whilst both the country pages and map offer a way to dive deeper into the data for a particular area, it would seem that people are mostly using the analysis tool to find out about area of notable forest cover.
Finally, we can look at the places that people are looking at through embedded content, to see which places people want to raise awareness about using GFW data. The areas with most embed views roughly follow the trends for the map overall, with Southeast Asia, South America and Central Africa being a major focus. It’s interesting to see the very bright red hotspots in Brazil and the Republic of Congo, indicating a few, well viewed embedded graphs, possibly around key deforestation sites. While in Southeast Asia there are many more points but with less intensity, suggesting the attention is split over a wider area of forest change.
You can also see some localised hotspots where particular embedded maps have received strong attention, including South Africa and Ethiopia and some areas of North and Central America. However it looks like the focus on Eastern Europe picked up in previous parts of this analysis is not found here; either people aren’t sharing this data outside GFW as an embedded map or it’s not getting picked up by the public.
These findings are mainly useful from a communications perspective, as it helps us see the places where messages are resonating most strongly outside GFW. It’ll help us tailor our campaigns to be more engaging, reaching people with messages they care about or surprising them with new things they might not have heard.
So when you bring it all together, you start to see a picture of the forests that people care about. A theme running through this whole analysis has been the pre-eminence of Brazil and Indonesia in particular, and the regions of South America, Southeast Asia and Central Africa. But you can also see how the different ways we package the data are helping meet different needs. The country pages are serving a wider, recurring need for stats at the country level, while the analysis tools are helping people find deforestation in the different protected areas and concessions.
Thanks for reading! I hope you learned something new! If you did, please recommend it so other people like you can find this article! Any comments or questions? Fire away.
If you want more content like this, why not sign up to our newsletter?
