G. R. Moncrieff

Continuous land cover change detection in a critically endangered shrubland ecosystem using neural networks

This paper uses neural networks to detect land cover change in Renosterveld shrublands, achieving high accuracy and operational deployment for habitat loss monitoring.

Locating and dating land cover change events in the Renosterveld, a Critically Endangered shrubland ecosystem

This study maps and dates land cover change in Renosterveld shrublands using satellite data, finding 478.6 hectares lost between 2016 and 2020 with high temporal accuracy.