home Anil Madhavapeddy, Professor of Planetary Computing  

ESA's first BioSpace conference seems a huge success / Apr 2025

The European Space Agency organised the first conference on Biodiversity Insights from Space (BioSpace) in February this year, and it seems like it was a huge success. The conference itself sold out within days, and the program was so packed that the organisers had to split it into multiple chunks during the week to cope with everyone. I've only just gotten around to fully browsing the schedule, and it's incredible to see so much variety of work happening in biodiversity and remote sensing. Here's hoping that ESA makes this an annual event in Italy!   […793 words]

# 16th Apr 2025   iconnotes biodiversity forests

Cooperative Sensor Networks for Long-Term Biodiversity Monitoring / Apr 2025

# 15th Apr 2025   icontalks iconvideos biodiversity embedded esp32 sensors

2nd Programming for the Planet workshop CFP out / Apr 2025

Dominic Orchard and I had a blast running the first PROPL workshop a couple of years ago, with a full room and engaged audience in POPL in London. Last year, our sister conference LOCO took over, and it's our turn again this year! PROPL will return for a second outing in October, co-located with ICFP/SPLASH in Singapore in October. Read the call for papers here (deadline 3rd July 2025).   […565 words]

# 3rd Apr 2025   iconnotes biodiversity climate conference conservation functional service

Autoscaling geospatial computation with Python and Yirgacheffe / Apr 2025

This is an idea proposed as a good starter project, and is available for being worked on. It may be co-supervised with Michael Dales.

Python is a popular tool for geospatial data-science, but it, along with the GDAL library, handle resource management poorly. Python does not deal with parallelism well and GDAL can be a memory hog when parallelised. Geo-spatial workloads -- working on global maps at metre-level resolutions -- can easily exceed the resources available on a given host when run using conventional schedulers.

To that end, we've been building Yirgacheffe, a geospatial library for Python that attempts to both hide the tedious parts of geospatial work (aligning different data sources for instance), but also tackling the resource management issues so that ecologists don't have to also become computer scientists to scale their work. Yirgacheffe can:

Yirgacheffe has been deployed in multiple geospatial pipelines, underpinning work like Mapping LIFE on Earth, as well as an implementation of the IUCN STAR metric, and a methodology for assessing tropical forest interventions.   […453 words]

# 1st Apr 2025   iconideas biodiversity idea-available idea-beginner python spatial systems urop

An access library for the world crop, food production and consumption datasets / Apr 2025

This is an idea proposed as a good starter project, and is available for being worked on. It may be co-supervised with Alison Eyres and Thomas Ball.

Agricultural habitat degradation is a leading threat to global biodiversity. To make informed decisions, it's crucial to understand the biodiversity impacts of various foods, their origins, and potential mitigation strategies. Insights can drive actions from national policies to individual dietary choices. Key factors include knowing where crops are grown, their yields, and food sourcing by country.

The FAOSTAT trade data offers comprehensive import and export records since 1986, but its raw form is complex, including double counting, hindering the link between production and consumption.   […372 words]

# 1st Apr 2025   iconideas biodiversity conservation food idea-available idea-beginner urop

New preprint on benchmarking ultra-low power neural accelerators / Mar 2025

Josh Millar just released our latest preprint on how to make sense of the growing number of dedicated, ultra-low-power 'neural network accelerators' that are found in many modern embedded chipsets. My interest in this derives from wanting to decouple from the cloud when it comes to low-latency local environments, and this needs fast tensor operations in hardware. Josh found a huge number of interesting NPUs in modern low-cost chips, ranging from ESP32-based boards over to ARM ones. All of these have quite a variety of tradeoffs, from the operations supported (which affects which models can be run on them) to the amount of memory and CPU power.

# 1st Mar 2025   iconpapers biodiversity conservation embedded esp32 preprint sensing

LIFE becomes an Official Statistic of the UK government / Mar 2025

Our recently published LIFE biodiversity metric has just been integrated into a newly recognised Official Statistic from the UK government! This integrates the core LIFE biodiversity metric with food provenance data to track the environmental impacts of our consumption habits.   […629 words]

# 21st Mar 2025   iconnotes biodiversity conservation evidence life policy sensing

A trio of papers I read on biodiversity and forests this week / Feb 2025

This week I've been reading three really nice pieces of work by my colleagues, in the form of a review paper on biodiversity and AI, a benchmark for 3D forest reconstruction using laser scanners and a mobile app for measuring the width of tree trunks. A real bonanza for forest lovers!   […793 words]

# 20th Feb 2025   iconnotes ai biodiversity conservation forests llms sensing

Updated preprint on quantifying biodiversity cost of food consumption / Feb 2025

We've uploaded a revised preprint on our ongoing work on quantifying the biodiversity cost of global food consumption, lead by Thomas Ball. This is based on the recently published LIFE metric, combined with supply chain data and provenance modeling. […196 words]

# 1st Feb 2025   iconpapers agriculture biodiversity climate conservation consumption extinctions food land-use preprint sensing supplychains

Affordable digitisation of insect collections using photogrammetry / Feb 2025

This is an idea proposed as a Cambridge Computer Science Part III or MPhil project, and is currently being worked on by Beatrice Spence and Arissa-Elena Rotunjanu. It is co-supervised with Tiffany Ki and Edgar Turner.

Insects dominate animal biodiversity and are sometimes called "the little things that run the world". They play a disproportionate role in ecosystem functioning, are highly sensitive to environmental change and often considered to be early indicators of responses in other taxa. There is widespread concern about global insect declines[^1] yet the evidence behind such declines is highly biassed towards the Global North and much is drawn from short-term biodiversity datasets[^2] [^3].

The Insect Collection at the University Museum of Zoology, Cambridge holds over 1.2 million specimens. These include specimens collected from the early 19th century to the present day. Most specimens remain undocumented and unavailable for analysis. However, they contain data that are critical to understanding long-term species and community responses to anthropogenic change, and vital to evaluating whether short-term declines are representative of longer-term trends[^4] [^5]. As such, unlocking these insect collections is of paramount importance, and the large-scale nature of these collections necessitates the development of an efficient and effective digitisation process.

The 3D digitisation of specimens using current methods is either highly time-intensive or expensive, rendering it impossible to achieve across the collection in a reasonable time-frame. Yet, 3D models of specimens have huge potential for investigating species morphological responses to anthropogenic changes over time and identification of trade-offs in morphological responses within a 3D morphospace.   […540 words]

# 1st Feb 2025   iconideas 3d biodiversity conservation idea-hard idea-ongoing insects urop

Updated preprint on LLMs for evidence-based decision support / Jan 2025

We have just updated our preprint on using LLMs for evidence decision support with more evaluation results and corrections from peer review.

Our findings suggest that, with careful domain-specific design, LLMs could potentially be powerful tools for enabling expert-level use of evidence syntheses and databases. However, general LLMs used "out-of-the-box" are likely to perform poorly and misinform decision-makers. By establishing that LLMs exhibit comparable performance with human synthesis experts on providing restricted responses to queries of evidence syntheses and databases, future work can build on our approach to quantify LLM performance in providing open-ended responses.

See also the fantastic EEG seminar talk that the student group who worked on this over the summer gave towards the end of last year.

# 1st Jan 2025   iconpapers ai biodiversity conservation evidence llms preprint

LIFE metric published in Royal Society Phil Trans B / Jan 2025

After some years of hard work, our Mapping LIFE on Earth biodiversity metric was published today in a special issue of the Royal Society Philosophical Transactions B! The idea behind LIFE is that although human-driven habitat loss is known to be the greatest cause of the biodiversity crisis, we do not yet have robust spatially explicit metrics that quantify the relative impacts of human actions on species extinctions. And that's what LIFE provides: a way to compare the relative impacts of some landuse anywhere in the world, in a manner that is globally applicable. […409 words]

# 1st Jan 2025   iconpapers aoh biodiversity conservation economics journal nature sdms sensing spatial

Horizon scan on AI and conservation published / Dec 2024

Back in July 2024, a large group of conservation and computer scientists got together in the CCI to prioritise the storm of AI-related projects that have been kicking off around the world. Our key goal was to harness AI to accelerate the positive impact of conservation efforts, while minimising harm caused through either the direct or indirect use of AI technologies.

The first horizon scan resulting from this has just been published in Trends in Ecology and Evolution. If you're looking for a gentle introduction to some of the terms in AI from a non-experts perspective, the first section does a good job of defining a glossary as well. […118 words]

# 1st Dec 2024   iconpapers ai biodiversity cci conservation evidence horizon journal

Cooperative Sensor Networks for Long-Term Biodiversity Monitoring / Dec 2024

Josh Millar and I have been having great fun designing embedded systems for cooperative biodiversity monitoring. Josh presented our work over at LOCO 2024 with an abstract on the Terracorder project. Read more if you enjoy a combination of machine learning and ESP32 hacking.

# 1st Dec 2024   iconpapers abstract ai biodiversity embedded loco qlearning sensing terracorder

Presented poster at Sensys on low-power biodiversity monitoring / Nov 2024

Josh Millar presented our work on biodiversity sensing over at ACM Sensys 2024 in China. The full set of papers and demos has a range of impressive work on sensor networks, and some that stood out to me follow. […140 words]

# 1st Nov 2024   iconpapers abstract biodiversity sensing sensys terracorder

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