Case Studies and Insights

Remote sensing scientists from the NSW Department of Climate Change, Energy, the Environment and Water (NSW DCCEEW) Science and Insights Division have developed a new approach to mapping the...

Using a combination of high-resolution satellite imagery and machine learning, remote sensing scientists at DCCEEW routinely map the severity of fires in NSW, aiding partners in conservation...

Machine learning methods will be developed that utilize dense time-series of C-band SAR (Sentinel-1) and optical (Sentinel-2) data to map the evolving burn scar as the wildfire progresses...

Satellite based active hotspot products are numerous and freely available in Australia. While multiple theoretical and actual measures of performance exist, understanding the relative...

Prediction modelling of fire spread are a critical component of operational fire management and strategic risk planning.

This webinar aims to give Planet users the tools they need to integrate Planet data in QGIS.