Great read from Michael Pocock: Linking remote sensing, citizen science data and AI could transform environmental monitoring | UK Centre for Ecology & Hydrology www.ceh.ac.uk/news-and-med...
15.07.2025 09:04 β π 1 π 0 π¬ 0 π 0@vdplasthijs.bsky.social
Post-doc (AI for monitoring ecosystems) @ AI group, WUR. Previously Oxford DPhil, The Alan Turing Institute & Peak District NP. vdplasthijs.github.io
Great read from Michael Pocock: Linking remote sensing, citizen science data and AI could transform environmental monitoring | UK Centre for Ecology & Hydrology www.ceh.ac.uk/news-and-med...
15.07.2025 09:04 β π 1 π 0 π¬ 0 π 0There is still lots of scope for further improvements; if that's of interest please don't hesitate to get in touch!
17.06.2025 09:57 β π 0 π 0 π¬ 0 π 0We combined sentinel-2 images and UKBMS butterfly occurrence records to predict butterfly species presence from satellite data. We developed a soft contrastive loss that acts as a regulariser and improves prediction accuracy.
17.06.2025 09:57 β π 0 π 0 π¬ 1 π 0Published last week at the CVPR FGVC Workshop; our paper on "Predicting butterfly species presence from satellite imagery using soft contrastive regularisation".
PDF (with links to data/code) available here:
openaccess.thecvf.com/content/CVPR...
With @david-alexander.bsky.social
20.05.2025 08:42 β π 0 π 0 π¬ 0 π 0In our latest perspective article, we outline how ML can overcome 4 current obstacles for large-scale, high-resolution monitoring of protected areas.
doi.org/10.1002/2688...
Hope this stimulates the conversation and provides a pathway of how ML research can be applied for monitoring PAs at scale.
π― How can we empower scientific discovery in millions of nature photos?
Introducing INQUIRE: A benchmark testing if AI vision-language models can help scientists find biodiversity patterns- from disease symptoms to rare behaviors- hidden in vast image collections.
Threadππ§΅
Hi, I'm using satellite data to predict species biodiversity! Could I be added please :) Thanks!
23.11.2024 10:29 β π 3 π 0 π¬ 0 π 0Using computer vision and #MapReader software, we analysed the loss of field boundaries across the #PeakDistrict Since the 1950s, the White Peak has seen a 12% reduction-551 km lost from an original 4,814 km. A stark reminder of landscape change ππΏ storymaps.arcgis.com/stories/5c89... #maps #GIS
21.11.2024 19:52 β π 23 π 9 π¬ 1 π 1