He aims to develop innovative and cost-effective ways to monitor forest damage

A modern forest inventory covers various aspects essential for sustainable forestry, including data on trees and stands as well as biodiversity and greenhouse gas balances. Sampling methods are developed to support key components of forest inventory, ensuring accurate and reliable data collection. This field provides valuable insights for practical forestry applications and environmental monitoring and assessment.

Can you tell us what you are working on?

- My research is about developing statistical methods for collecting information about forests and forest damage, known as probability sampling designs. Using modern technologies, for example drones, measurements can be carried out faster, more accurately and at a lower cost. But first we need to derive the statistical properties of the design.

- In my research, I combine theory and computer simulation. I compare different methods to find those that are accurate, cost less and work well in practice. Right now, I am looking at how flight paths for drones can be optimised to meet this.

What got you interested in this particular field?

- I like the interdisciplinary perspective of mixing statistics with remote sensing and ecology. I get to apply my mathematical background to environmental challenges and nature conservation, and I can work together with experts in different fields.

What do you want to contribute with?

- Better methods can help us improve resource allocation and ensure that we collect timely and reliable information. It can also help decision-makers to improve monitoring programmes. Accurate forest damage assessment is crucial for sustainable forest management and our work aims to provide new methods to collect data efficiently.