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SUMMARY:Geospatial foundation models enable efficient tree species mapping
  in heterogeneous montane forests - James Ball\, University of Cambridge
DTSTART:20260130T130000Z
DTEND:20260130T140000Z
UID:TALK241930@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:*Abstract*\n\nAccurate tree species mapping in heterogeneous m
 ontane forests is hindered by sharp environmental gradients\, illumination
  variability\, species diversity\, mixed stands\, and limited high-quality
  training data. We evaluated two geospatial foundation-model embeddings\, 
 AlphaEarth and Tessera\, for species classification in the mountainous Tre
 ntino region\, comparing them to conventional Sentinel-1/2 multispectral+S
 AR composites using parcel-level forest inventories covering 17 species an
 d groups. Here we applied parcel-aware training/validation and label-disti
 llation techniques\, demonstrating that foundation-model embeddings substa
 ntially outperform satellite baselines\, achieving higher accuracy with fe
 wer labels and preserving ecologically meaningful taxonomic and functional
  structure. Performance gains stem from embedding quality rather than clas
 sifier complexity\, with robustness to moderate label impurity. However\, 
 temporal transfer across years revealed notable performance degradation\, 
 especially for rare species. These findings suggest foundation models shif
 t species mapping challenges towards the availability and temporal alignme
 nt of ecological reference data\, offering promising avenues for scalable 
 biodiversity monitoring and ecological change analysis in complex mountain
  ecosystems.\n\n*Bio*\n\nJames Ball is a Postdoc with David Coomes\, speci
 alizing in forest ecology\, remote sensing\, and AI for tropical forest mo
 nitoring\, using technologies like drone lidar and satellite imagery to st
 udy tree phenology\, deforestation\, and climate change impacts\, holding 
 a PhD from Cambridge and degrees from Oxford and Imperial College London. 
 He's also involved with the Cambridgeshire Cultural Exchange Centre and fo
 unded forestmap.ai\, applying his expertise in AI for forest insights. \n\
 n
LOCATION:Room GS15 at the William Gates Building and on Zoom: https://cl-c
 am-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=ad
 don 
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