Download Trialling spectral imaging for measuring forests

This report investigated whether aerial and satellite remote-sensing technologies could be used to map forest composition, estimate above-ground biomass, and assess whether differences in forest condition could be detected between areas with and without possum control. The researchers first developed methods to classify forest types and estimate forest biomass at a 10-metre resolution. The study successfully distinguished broad forest groups, including beech, podocarp, a mix of mānuka and kānuka, and plantation forests. However, large uncertainties in field calibration data limited the ability to detect biomass differences attributable to possum browsing. While this study took a broader landscape-scale approach using remote-sensing data to map forest composition and biomass across large areas, the companion study applied higher-resolution sensing technologies at selected sites to detect changes in canopy condition and forest health associated with possum control.

Keywords: indigenous forest; native forest; plantation forest; ngahere; remote sensing; pest monitoring; possum monitoring; forest canopy; canopy health; forest health; forest carbon; carbon storage; forest mapping; forest classification; above-ground biomass; satellite imagery; LiDAR; Sentinel-2; aerial imagery.