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Header image: Laura Kloepper, Ph.D.

discussion

Piloting a QGIS Course for Conservation Staff – Seeking Interest & Input

Hi everyone,I’m developing a QGIS training course specifically for conservation practitioners working with patrol data (e.g. SMART) and other field-based spatial datasets. The...

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Hi Emma, I would definitely be interested in this course too. Sign me up!

Hi Robynne - I'm really glad you're interested.  I'm running a cohort at the moment but have so far only covered some QGIS basics so you would be welcome to jump on from next Monday if that would work?

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The RCoE Geoportal

The RCoE Geoportal provides comprehensive forest datasets that can help governments, researchers, and conservationists make informed decisions. From deforestation trends to forest cover analysis, these datasets offer valuable insights for managing our natural resources.

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Trase and ClientEarth provide guidance on using geospatial data to enforce and comply with the EUDR

There are a number of publicly available ‘open’ datasets and products from government sources, research and civil society initiatives, as well as closed offerings from commercial service providers. Find out more if & how these datasets align with EUDR in the report.

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GIS and AI on deforestation and Climate Change

I'm working on establishing relevant and insightful relationship between deforestation and rainfall amount and durability in North-Eastern part of Nigeria. By leveraging GIS and...

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Hi Sebastine! Thanks for sharing this. What are you looking for from the WILDLABS community? (Collaborators, advice, networking, etc.) 

Would be interested to learn more! What data, software and tools are you using to build your models?

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discussion

What metadata is used from trail camera images?

So, this week I have started looking into adding new and more fine-grained details and methods to the result page og Animal Detect. Including the CameraTrapDP format (coming soon...

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Hi Hugo, it's great that you are thinking about adding metadata features to Animal Detect! I'll share what I think would be useful from my perspective, but I think there is a lot of variation in how folks handle their image organization. 

Time and date are probably the most important features. I rename my image files using the camtrapR package, which uses Exiftool to read file metadata and append date and time to the filename. I find this method to be very robust because of the ability to change datetimes if needed -- for example, if the camera was programmed incorrectly, you can apply a timeshift to ensure they are correct in the filenames. Are you considering adding Exif capability directly to Animal Detect? Otherwise, I think that having a tool to parse filenames would be very helpful, where users could specify which parts of the filename correspond to camera site, date, time, etc., so that this information is included in downstream processing tasks.

I have found it frustrating that information such as camera name and temperature are not included in file metadata by many camera manufacturers. I have used OCR to extract the information in these cases, but it requires a bit of manual review, and I wouldn't say this is a regular part of my workflow.

Camera brand and model can be useful for analysis, and image dimensions and burst sequence can be helpful for computer vision tasks. 

Hope this helps!

Cara

Thank you for your reply! 

It surely helps, we have use exif for a while to read metadata from images, when there is information available. Could be nice to maybe see if we could “write” some of the data into the metadata of the image, instead of just reading. Really good idea with the filename changes and structure. I will add it to a list of possible improvements and see if/how we could implement it. 

Again, thanks for the feedback 😊 

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discussion

3D Maps for conservation

Our opensource plateform EcoTeka is now allowing to view trees in 3D.Ecoteka - The Application for Urban Renaturalization — Natural solutionsWe did a prototype for viewing...

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Hi Olivier! I'm Alex from the WILDLABS community team. Thank you for sharing EcoTeka! I made a page for it on The Inventory, our wiki-style database of conservation technology tools, R&D projects, and organizations. The Inventory is an essential resource for people in the community to learn about what tools are available for their work.

As an owner of Ecoteka, I encourage you to edit this page to make it as accurate as possible! You can also become a "key contact" for EcoTeka so the WILDLABS community knows who to contact with any questions! To learn more about how to edit a page and become a key contact, read our user guide here. Reach out to myself or @JakeBurton for any troubleshooting needs!

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discussion

SwarmGuard: low-cost autonomous mesh system to detect poaching threats and protect wildlife

Hello WILDLABS Community!I’d like to share an open-source, non-commercial concept that could be useful for conservation teams, rangers, or students working with wildlife...

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Hi Aleksey, thanks for sharing this! We'd love to see you add SwarmGuard to The Inventory, our wiki-style database of conservation tech products, R&D projects, and organizations.  To learn about how to add SwarmGuard to The Inventory, read the user guide my colleague @JakeBurton  created. Reach out to either one of us with questions!

Good morning Aleksey,

Your idea is very similar to an idea I had -- I guess we are experiencing some convergent evolution.   I'd be very interested in understanding your project more.   I'd be curious to know if you've done much testing with Lora and dense foliage.  I'm just curious to know if you've hit any real limitations.  Reading your description, it sounds like perhaps you are using some mesh networking.   Anyway -- it's nice to meet you and see we had similar ideas.

Chris

Hi Chris Great to meet you — and I love that you called it convergent evolution! That’s exactly how it feels when two people independently reach a similar idea because the need is real. You're right — SwarmGuard uses basic LoRa mesh logic (peer-to-peer hopping), though I haven’t fully implemented dynamic routing yet. In tests, range can vary wildly depending on terrain: Open field: up to 2–5 km Dense foliage / rainforest-like conditions: sometimes as low as 300–500 m That’s why I’m planning hybrid setups: "Relay-only nodes" with no sensors, just LoRa pass-through Strategic placement of “intelligent nodes” with mic/cam/TinyML Possibly lightweight aerial relays (e.g., helium balloons or drones in standby) Most technical parts are working — deep sleep, wake-on-sound, basic classification (gunshot vs voice vs ambient), solar recharging, and LoRa alerts. My biggest blocker is simply funding and field access. Right now it’s a passion project — but I’d love to turn it into something deployable. If you’ve already done LoRa experiments in dense forest, I’d love to compare notes. Maybe we can even test interoperability or swap firmware tricks. Let me know if you’d like access to the repo or schematics — open-source all the way. Thanks again for reaching out! – Aleksey
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Google AI model mines trillions of images to create maps of Earth ‘at any place and time’

AlphaEarth Foundations

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Championing Decentralized Energy for Sustainable Growth & Regenerative Financele here

Mr. Tumi – Chief Visionary Officer, Ena PlusChampioning Decentralized Energy for Sustainable Growth & Regenerative FinanceAs the Chief Visionary...

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Thank you for bringing our attention to regenerative finance, Mr. Tumi. I appreciate it very much, and would like to learn more about this. Could you please refer to online sources describing that financial philosophy and the mini-grid systems?

Hi Yusuf! Thanks for sharing this. What are you looking for from the WILDLABS community? (Collaborators, advice, networking, etc.) 

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