Adaptive cluster sampling is a probabilistic design tailored to populations that exhibit rare or spatially clustered features, such as endangered species, epidemic cases or hidden cultural artefacts.

Accurate forest volume estimation is crucial for sustainable forest management, but the most commonly used methods often rely on models that may not always be applicable across different tree species ...