Editor’s note: this article is the second part of The Fix’s series of guides on environmental journalism. Make sure you’re subscribed to our weekly newsletter so you don’t miss the next instalments.

Sometimes, you can find numerous open sources for environmental-related data when digging.

For example, while working on landslides and floods in Italy, I found an impressive work by Italian environmental protection and researh agency ISPRA called IdroGEO. It’s a platform that allows the consultation, download, and sharing of data, maps, reports, and documents of the Italian Landslide Inventory – IFFI, the national landslide and flood hazard maps, and risk indicators.

Browsing the app, you can see context data, the number of people living in at-risk areas, buildings, industries, and cultural heritage in the same situation.

You can zoom into the map, choose an area and see the numbers and data of that particular scenario.

You can also download open data.

It’s easy to understand why this kind of data is essential from a journalistic perspective: it’s because having access to this knowledge allows you to put a journalistic job at the service of the audience in the true sense of the word. People deserve to know if they live at risk, in which sense, what kind of prevention measures local and national institutions are taking.

Sometimes, things take work. For example, despite its effort, IdroGEO is not up-to-date, according to the open data page. Knowing this could help pressure the local and national governments to keep these kinds of databases open, available, and updated.

When you know the tools exist, everything seems more manageable.

For this reason, in this second part of our series about environmental journalism, we will focus on a specific tool that allows us to familiarise ourselves with several concepts and techniques.

The tool is the Global Forest Watch Map.

Global Forest Watch and the needed approach

The first thing to do whenever someone presents us with a tool – even if you find it in a piece from a source you trust, like in this case –is to understand who is behind it.

Knowing who finances an instrument gives us information and is essential in creating the context for ourselves. We will probably not use this information for an article – unless we find something strange or questionable – but we can still use it to understand if the tool is transparent, if its data is reliable, and so on.

When dealing with a transparent tool, this kind of information is generally available in the website footer and in a specific about section, like in this case.

The World Resources Institute (WRI) established the Global Forest Watch in 1997 as part of the Forest Frontiers Initiative. “It started”, says the timeline of the official website, “as a network of NGOs producing up-to-date reports about the state of forests in four pilot countries: Cameroon, Canada, Gabon, and Indonesia”.

Year by year, thanks to several institutional, public, and private partners, it evolved into a worldwide project, collecting different data from different sources and making them available for free. The platform is user friendly and relatively simple to use.

The look of the tool is a map, just like the IdroGEO. Maps are a typical way to show environmental data: they are quick to understand and meaningful. Therefore, the more familiar you are with this interface, the easier it is for you to manage this and other tools.

Let’s start with a completely white map.

When you browse into the left menu, you can see that you can turn on or off different switches that correspond to different types of indicators.

Once you turn on a switch, the map shows you the different levels of the specific indicator you chose, with different degrees of colours or pins or numbers, explained by the legend.

Let’s see for example the Global Air Quality Index, to understand how many different data types are collected into this map, and how to deal with them.

First, make sure to properly understand the data.

Each switch has got its own “i” for “information”. The mouse over label contains a very short description of the indicator you are dealing with.

Don’t forget to read the handbook

By clicking on that “i”, a pop-up window opens: it’s very important to read and understand, because it contains everything you need to properly use the map and its data.

The pop-up shows

function: it show you what kind of information you can have
resolution (if applicable). For example, if you use the Fire Alerts (VIIRS), you’ll find that the maximum resolution is 375×375 metres. This means that if the fire is smaller, you’ll probably not get any result
geographic coverage (in this case, for example, it says “Global”, but the Index is not available in every country)
sources: it shows you the primary source of the data
frequency of updates: it shows you how many times the indicator is updated
date of content: the last available update
cautions — probably one of the most important elements of this tab; not because the other ones are not relevant, but because it gives you the idea that you have to use data with care, and you can’t be sure that everything is ok without at least a double check. In this case, for example, you have to notice that “Air Quality data are published unvalidated, and so may be amended for quality assurance purposes”. It is true that they “verify in real-time data consistency with neighboring stations in order to automatically detect defective monitoring stations”, but it’s better to deal with consolidated data and to clearly point out these cautions for your readers if you work with real time data.

It’s also important to deeply understand the overview and the legend. It’s highly recommended to visit the official source, too, which is generally available by clicking on the “Learn More” button.

Global Air Quality Index, for example, comes from Aqicn.org, where you will find a lot of other data, like Air Quality Forecast, PM_2.5, PM₁₀, NO₂, and CO concentrations.

Once you get familiar with Global Forest Watch and its sources, it’s time to explore all the functions.

For some indicators, you can even see animations showing the change in time.

For example, let’s display tree cover loss with > 30% canopy density from 2001 to 2021 (keeping in mind that cover loss is not necessarily deforestation).

You can’t simply use this tool for creating a story from scratch, as usual, but it’s perfect for story discovery, support for reports with data, or story visualisation.

Let’s see, for example, how to visualise the unusual fires in the Pyrenees, due to drought, in February 2023.

There is a switch called Fire Alerts (VIIRS), source: NASA.

You can zoom into the map, select a time window and see what happens by clicking on play in the timeline on the left.

You can also select or draw an area by clicking Analysis, as I did with a specific location across the Pyrenees.

Once you have created the area, you can save it into your account and set up an almost-in-real-time alert about fires and forest change or a monthly summary.

The behaviours are similar, but each indicator has peculiar characteristics you must explore once you decide on the topic you want to cover.

Global Forest Watch is a powerful tool for its interesting functions and because it allows you to set solid bases to deal with environmental journalism.

It comes with a good help section with tutorials, examples of coverage, ready-to-use data and analysis, country by country.

Let’s see the Germany dashboard, for example.

For each country, you can browse the summary, land cover, forest change, land use, fires, climate indicators, and charts.

You can go back to the map, download data and re-use it for your own visualisations.

You can also explore different topics, like biodiversity, for example.

Practising with the Global Forest Watch and connecting with the community this tool aggregates is an excellent way to build environmental reporting skills and coverage.

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