Can anyone recommend free/open source alternatives to NVivo? We’re after a tool for qualitative coding and thematic analysis of textual data, including organising and coding material, developing themes, and comparing findings across a substantial body of qualitative evidence.

Notes from ML4EO 2026 🌍 A short blog post summarizing my talk and workshop from the ML4EO conference on spatial machine learning validation. https://jakubnowosad.com/posts/2026-07-03-ml4eo/ #rspatial #EarthObservation #MachineLearning #RemoteSensing #GeoSpatial

➡️ I’ll be at ML4EO 2026 in Exeter, UK (22–24 June) Machine Learning for Earth Observation brings together work on ML, remote sensing, and geospatial data science. I look forward to good talks and meeting people. https://ml4eo.org/ #ML4EO #EarthObservation #MachineLearning #GIS

ML4EO

Machine Learning for Earth Observation

ml4eo.org

🌱 Fully Funded PhD Opportunity @ University of Exeter! 🌱 Study how NEOM’s regreening is shaping productivity in arid landscapes. Join TESS Lab using Earth Observation, ML, and field data to understand what effective regreening looks like.

Call for abstracts: ML4EO 2026 Machine learning for Earth observation 📅 22–24 Jun 2026, Exeter, UK 📝 Abstract deadline: 31 Mar 2026 🔗 https://ml4eo.org/call-for-abstracts/ #ML4EO #EarthObservation #MachineLearning #RemoteSensing #OpenScience

Want to make your research more transparent, reusable, and impactful? I’ve written a practical Open Research primer with clear guidance, especially for geospatial ecology & geography — but useful across disciplines. tess-lab.org/resources/op... I'm passionate about open research throughout my work

Submission deadline approaching for "Coding Earth – open-source solutions in Physical Geography" We look forward to submissions on open-source methods and tools in geography. ⏳ Deadline: 1 Mar 2026 🔗 https://journals.sagepub.com/home/ppg #OpenSource #RStats #Python #Julia

Fully Funded Geospatial Ecology PhD Opportunity: Evaluating the influence of NEOM regreening approaches on terrestrial productivity. Deliver new insights into plant productivity over space & time in response to dryland management, based in the supportive TESS Lab tess-lab.org,

Terrestrial Ecosystem Science & Services

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tess-lab.org

PhD Studentship Opportunity: "Quantifying Forest Plantation Damage After Cyclones Using Earth Observation" This funded project at the University of Exeter tackles a real and urgent global challenge: rapidly assessing storm damage in forest plantations. Full description on tinyurl.com/4tdw3yw6.

🌍Exploring Sentinel-2 with the Copernicus Data Space Ecosystem (CDSE)? Hugh Graham’s guide with vrtility in #rstats. Includes authentication & query of imagery and building cloud-free composites […] [Original post on fosstodon.org]

Chapter 1: Introduction to Geocomputation 🌍📊 What is geocomputation? Why use R for spatial analysis? 📌 This chapter traces its history, connects it to FOSS4G, and explores R’s power for geospatial work. Learn about R-spatial’s evolution! 🚀 🔗 […] [Original post on fosstodon.org]

🔍 Interested in spatial machine learning with R?🌍 We compare caret, tidymodels, and mlr3 for spatial tasks — and show how their workflows differ. Read it here: https://geocompx.org/post/2025/sml-bp1/ #MachineLearning #SpatialAnalysis #RStats #rspatial

These are the last few days to register for the Machine Learning for Earth Observation (ml4eo.org) conference happening on June 18-20. The event includes training workshops and over 50 contributions from academia and industry. Bursaries are available for students who don’t otherwise have funding.

ml4eo 2025

18-20 June 2025 University of Exeter Register for the conference Register for the conference workshops

ml4eo.org

Bri Pickstone@bpickstone.bsky.social · 2y ago

Join us at #ML4EO 2025, a conference on Machine Learning for Earth Observation @exeter.ac.uk! Whether you’re from academia, the public sector, or industry, ML4EO is an opportunity to reflect on RS and identify the most promising directions for future innovation. Registration is now open: ml4eo.org

Join us at #ML4EO 2025, a conference on Machine Learning for Earth Observation @exeter.ac.uk! Whether you’re from academia, the public sector, or industry, ML4EO is an opportunity to reflect on RS and identify the most promising directions for future innovation. Registration is now open: ml4eo.org

It's fantastic to see this new paper led by @bpickstone.bsky.social from her MSc project with @tess-lab.org. Her findings that 10 m grain Sentinel-2 data & relatively simple random forest models are more useful than finer spatial grain & complex CNN models are useful for applied forest monitoring.

Terrestrial Ecosystem Science & Services

Visit the post for more.

tess-lab.org

Bri Pickstone@bpickstone.bsky.social · 2y ago

New Paper! We found Sentinel-2 + Random Forest can match PlanetScope and deep learning methods for canopy height predictions in tropical forests - making monitoring more accessible! Thanks to my co-authors Andy Cunliffe (@tess-lab.org) & Hugh Graham. Read here: www.tandfonline.com/doi/full/10....

Job opportunity for a Postdoctoral Research Fellow to join our PREDICT: Predicting Resilience and Early Detection of Impending Climate Transitions project, esp. focussing on remote sensing of permafrost. The application deadline is the 5th of Feb though so be quick! www.jobs.ac.uk/job/DLN726/p...

Postdoctoral Research Fellow at University of Exeter

An opportunity for an academic position as a Postdoctoral Research Fellow is available, as advertised on jobs.ac.uk. Apply now and explore other academic job openings.

jobs.ac.uk

"Canopy heights reconstructed with drone photogrammetry are sensitive to wind speed but relatively insensitive to illumination conditions." Critical insight for anyone working with these approaches from PhD student Glenn Slade's recent paper in @ijremotesensing.bsky.social doi.org/10.1080/0143...

Repeated drone photogrammetry surveys demonstrate that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions

Unoccupied aerial vehicle (UAV) based structure-from-motion (SfM) photogrammetry surveys are becoming a standard tool for ecologists to measure plant structure and biomass in non-forest ecosystems....

doi.org

Re-celebrating this recent paper led by talented @tess-lab.org PhD student Guy Lomax on "Untangling the environmental drivers of gross primary productivity in African rangelands" published in @commsearth.bsky.social h.bsky.social www.nature.com/articles/s43...

Untangling the environmental drivers of gross primary productivity in African rangelands - Communications Earth & Environment

Total precipitation, temperature and soil nitrogen are the main drivers of gross primary productivity in dry rangelands in sub-Saharan Africa, with more variable rainfall having a small but negative i...

nature.com

I'm delighted to see our new paper "Browning events in Arctic ecosystems: diverse causes with common consequences" out in PLOS Climate. Thanks to Gareth Phoenix's leadership, this should become a benchmark study! doi.org/10.1371/jour...

Browning events in Arctic ecosystems: Diverse causes with common consequences

Arctic ecosystems are experiencing extreme climatic, biotic and physical disturbance events that can cause substantial loss of plant biomass and productivity, sometimes at scales of >1000 km2. Collect...

doi.org

For anyone seeking funding to engage with the learning or research communities at the University of Exeter, please check out this Funding Finder we've developed exeter.shinyapps.io/funding_find..., signposting hundreds of funding awards for every nationality and level.

We work closely with many partners, including those from academia and non-academic settings to progress an applied research agenda to develop and share insights into sustainable ecosystem function across scales, in socially just ways. For more information visit tess-lab.org

Terrestrial Ecosystem Science & Services

Visit the post for more.

tess-lab.org

Intro: I'm Andy Cunliffe, leading the Terrestrial Ecosystem Science and Services Lab at the University of Exeter. We aim to improve understanding of how landscapes function & can be managed for sustainable social & ecological benefit, using geospatial tools alongside spatial ecology & social science

We are undergoing a second data call! Here, we are focusing on tree species and the annotated RGB imagery. @COSTprogramme @isprs #drones #trees #deeplearning PS: All data calls within @3DForEcoTech are available here: https://t.co/Tf5m1eZ7Ub 👇👇👇 https://t.co/jZcTQkpBZO

📢 Data Call Alert! We’re building an international database for tree species classification! Share aerial RGB/RGBI imagery & manual tree species annotations by 30 Nov 2024. Contributors will join as co-authors! Here: https://bit.ly/3As0v17 #RemoteSensing #OpenData