As part of this investigation, we obtained high-resolution LiDAR digital elevation data which allowed us to investigate claims the state-run timber company VicForests was conducting widespread and systemic illegal logging in vital water catchments. The logging company was prohibited from logging slopes steeper than 30 degrees and experts had long suspected they had been breaching this law. Using the data, the team was able to show large areas of forest had been logged in breach of the law. The data was also used to show how the regulator, tasked with overseeing the logging company, had failed to investigate these claims.
By creating a 3D model of the digital elevation data, we were able to break down and guide our audience through our complex investigation into allegations of illegal logging. We created a high-resolution model as well as interactive elements to highlight the most egregious examples of potential illegal logging.
This investigation revealed hundreds of hectares of areas over the slope limit had been logged in water catchments which supply drinking water to Melbourne, a city of more than 4 million people. The trees on the steep slopes are crucial for the quality of Melbourne’s water supply, as they help in the filtration of the water. Water experts told us it would be disastrous for the city if this process of natural filtration was undermined by illegal logging
As a result of our investigation into VicForests, the Victorian government announced it would be enforcing tougher regulation of the logging company and they would face greater oversight by the regulator. The accusations revealed in the story were also referred to the state’s corruption watchdog.
The researchers, who we worked with, used the terrain data to calculate a slope for every pixel in the digital elevation model. Using the open-source software QGIS, we analysed, styled and prepared this slope data. We then exported all of our geospatial data, (slope rasters, digital elevation model, vector boundary data) to create a 3D model of one of the worst affected regions in our investigation.
The model was created in Blender using an add-on called BlenderGIS which allowed us to work with georeferenced rasters and vectors in a 3D animation project. We used Blender to build a sequence that stepped our audience through the research and investigation. This tricky process involved overlaying satellite and vector data onto a highly detailed mesh of the terrain. We created an animation that tied in with the text of the story.
The result was an immersive, mobile-friendly story that helped break down a complex investigation.
What was the hardest part of this project?
The work firstly relied on comparing several data sets. Obtaining those data sets took more than a year, some of which were obtained through Freedom of Information Laws.
From a technical perspective, the toughest part of the project was merging geospatial data with 3D animation software. This required an in-depth understanding of Blender and how the add-on BlenderGIS worked. Even simple tasks like displaying boundaries of shapefiles or introducing opacity, required a significant learning curve to achieve nice results. More complex tasks like draping shapefiles over an intricate 3D mesh required significant amounts of trial and error using processing tools in QGIS and Blender render settings.
What can others learn from this project?
I think there are three main takeaways for other journalists:
That you can take complex, geospatial data and turn it into compelling investigations. While in this particular story the data was only uncovered because we used Freedom of Information laws, often these types of geospatial datasets are made public by governments. We have shown that this data can help hold powerful organisations to account.
Visual journalistic investigations like ours show how powerful well-thought out graphics can be in conveying the substance of a story. For us, the core of this story was the data so we put lots of time and effort into how we could present our findings in a way that would have the most impact. In this case the visuals helped make a complex data story more palatable for readers.
All of the software we used to create this project are open source, meaning anyone with the know-how could reproduce something similar to this project with little to no budget.