Yao-Hua Law is an environmental journalist based in Malaysia. In 2019, he teamed up with a writer and editor SL Wong to launch Macaranga, a publication that covers the environment and sustainability in Malaysia.

The team uses a lot of data in his work, and geospatial context is crucial for telling his stories. This is why mapping has become an integral part of his reporting process. Yao-Hua Law uses a variety of tools, including Felt, QGIS, and Mapbox.

In recent months, Felt has become an indispensable part of his workflow because it helps the team to collaborate on maps while gathering all the data for the article and then, after the final version is embedded on the website, it gives readers an opportunity to explore the map on their own across different zoom levels.

Protecting Malaysian forests

Malaysia is one of the top mega-biodiversity hotspots, and it still has a lot of forest cover. Although it is a small country, it is quite well-developed, with one of the more advanced economies in the region. “We are in quite a good spot to be able to protect a lot of the forest. And we are still at a junction when we can make timely decisions about how we want to use our forest,” says Yao-Hua Law. He and his colleague asked readers to vote on the topics Macaranga should cover, and forest preservation was a leader, so he decided to investigate it.

Even though within peninsula Malaysia, 85% of the forests are forest reserves. However, logging and mining is legal in some of these reserves, and sometimes they are even used for farms or oil palm plantations. Yao-Hua Law set out on a mission to investigate the discrepancy between forest loss detected by satellites and official data released by the government. His investigation was published as a two-part series: Navigating the Multiverse of Forest Data and Projects that Replaced Natural Forests in Peninsular Malaysia, both featuring Felt maps.

Mapping deforestation data

To kick things off, Yao-Hua Law decided to compare government data about forests in the peninsula with imagery provided by satellites. He looked annual reports published by the Department of Environment (DOE) and for the satellite data, he referred to the Global Forest Watch.

After analyzing these two dataset in QGIS, Yao-Hua Law determined which years were marked by the highest rate of tree loss and which states had the most tree loss based on satellite data. He also found out which states had the biggest gap between satellite-reported data and government reported data.

Then, he added development projects within forest reserves that were approved by the government hoping that he will be able to compare and match the area of each project with the tree loss around that project. “The first thing for us to really get the hang of or to confirm is whether the method or the approach actually works,” adds Yao-Hua Law.