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Drones / Feed

Used to pick up signals from tracking gear on the ground, collect images of wildlife and habitats from the air, gather acoustic data with specialized hydrophones, or even collect snot samples from whales' blowholes, drones are capable of collecting high-resolution data quickly, noninvasively, and at relatively low cost.

careers

Conservation Innovation Manager

David Will

27 September 2023 11:08pm

Island Conservation's Innovation Team is dedicated to developing innovative, data-driven tools to increase the scale, scope, and pace of island restorations around the world. As the Conservation Innovation Manager, you...

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Mapping seagrass with drones and AI

Ellie Warren

4 August 2023 2:00am

GeoNadir shared how drones and AI can help assess seagrass habitats at the Great Barrier Reef, as well as how satellite imagery can monitor seagrass on a wider scale.

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discussion

Project Spotlight: Monitoring tropical freshwater fish in Kakadu National Park with drones, underwater cameras and AI

Stephanie O'Donnell

12 July 2023 3:40pm

This was such a fantastic presentation in our June Variety Hour show. Andrew and his team are exploring applications of a whole range of technologies, anda are looking to share...

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Stephanie O'Donnell

12 July 2023 3:58pm

During Andrew's talk, @dmorris put out a call in the chat that might be relevant to folks catching up on the video, so I'll drop it here too: 

Re: Andrew's fish work... part of the reason I got in touch with Andrew a few weeks ago is that I'm trying to keep track of public datasets and public models for marine video that have basically this gestalt (video where fish look fishy-ish). I think we're getting close to enough public data to train a general-purpose model that will work well across ecosystems. My running list of datasets is here:

https://lila.science/otherdatasets#images-marine-fish

Let me know if folks know of others!

There are also a grand total of two public models that I'm aware of that sort of fall into this category... one is Andrew's:

https://github.com/ajansenn/KakaduFishAI

The other is:

https://github.com/warplab/megafishdetector

If folks know of other publicly-available models, let me know about those too!

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UAV-assisted counts of group size facilitate accurate population surveys of the Critically Endangered cao vit gibbon Nomascus nasutus

Diep

13 June 2023 3:51am

This paper explores the use of UAVs equipped with thermal and standard cameras to accurately count the group sizes of the Critically Endangered cao vit gibbon, highlighting how this technology can overcome the limitations of traditional ground-based methods and contribute to...

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Read "UAV-assisted counts of group size facilitate accurate population surveys of the Critically Endangered cao vit gibbon Nomascus nasutus | Oryx | Cambridge Core" on Cambridge Core

UAV-assisted counts of group size facilitate accurate population surveys of the Critically Endangered cao vit gibbon Nomascus nasutus | Oryx | Cambridge Core

UAV-assisted counts of group size facilitate accurate population surveys of the Critically Endangered cao vit gibbon Nomascus nasutus - Volume 58 Issue 2

Cambridge Core
discussion

ISO Speakers for Emerging Technologies class.

Flor Sangermano

31 May 2023 4:29pm

Hi Everyone, Apologies for posting across multiple groups.  I'm teaching a new course @ Clark University next semester on emerging technologies for conservation. The course...

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Carly Batist

31 May 2023 10:21pm

Definitely interested! I'm in the ecoacoustics/acoustic monitoring space, working at Rainforest Connection and Arbimon.

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AirSeed: Drone planting takes flight to promote reforestation in flood-affected NSW

Esther Githinji

30 May 2023 12:28pm

AirSeed has developed a unique approach to tackle climate change and restore biodiversity by combining drone technology, machine learning, and seed pod biotechnology to carry out planting that’s 25x faster than traditional hand-planting methods.

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Read "AirSeed: Drone planting takes flight to promote reforestation in flood-affected NSW | Humanitech | Australian Red Cross" on Humanitech | Australian Red Cross

AirSeed: Drone planting takes flight to promote reforestation in flood-affected NSW | Humanitech | Australian Red Cross

AirSeed has developed a unique approach to tackle climate change and restore biodiversity by combining drone technology, machine learning, and seed pod biotechnology. To validate whether this approach could be delivered in partnership with disaster-affected communities to support local regeneration efforts, AirSeed collaborated with landholders impacted by landslides in northern NSW.

Humanitech | Australian Red Cross • 19 Apr 2023
discussion

Animal tracking stories

Wildlife Drones

22 May 2023 2:19am

Do you have a wild animal tracking story that involves adventure or misadventure? Share it with us! From going around in circles for hours to discovering predators instead of your...

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Using computer vision to understand bee vision

Ellie Warren

5 May 2023 1:10am

Here's an innovative project from the Harvey Mudd College Bee Lab that could help us understand how bees view their environments, and thus better protect bee habitat. This project uses computer vision and drone imagery to replicate "bee vision" of flowers and how it differs from...

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Researchers use taxidermy bird drones to monitor wildlife

Stephanie O'Donnell

26 April 2023 2:40pm

Interesting project - “Our main goal for this is to develop a nature-friendly drone concept for wildlife monitoring,” Hassanalian said. “Traditional drones are often disruptive to ecosystems due to issues such as sound and unfamiliarity, so developing quieter, natural-looking...

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event

AI for Pelicans Challenge

Tjomme Dooper

20 April 2023 10:04am

In this Challenge, we will use AI to detect and classify pelicans in Romania's Danube Delta to evaluate the breeding population based on aerial photographs.

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ML-ready datasets for aerial/drone wildlife surveys

Dan Morris

29 March 2023 5:27pm

I got inspired to collect a list of annotated, appear-to-be-ML-ready datasets related to drone/aerial wildlife surveys:https://github.com/agentmorris/agentmorrispublic/blob/main/...

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Dan Morris

12 April 2023 5:53pm

Following up here... a few of us huddled virtually and assembled standardized metadata, standardized sample code, and sample annotated images for all the datasets on that list.  I don't know whether this exercise was useful, but it was fun!  

The URL hasn't changed, but I consider the list open for business now, let us know what we're missing:

https://github.com/agentmorris/agentmorrispublic/blob/main/drone-datasets.md

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discussion

Advice on afforable LiDAR scanners for Amazon forest surveys

Jeremy Dickens

5 April 2023 3:47pm

Dear allFirstly, what a fantastic group! I love following the discussions on this site and am a true believer in the power of the crowd so am hoping someone might have the...

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Eduardo Zanette

6 April 2023 6:21pm

Hi Jeremy, 



With a quick search I've found the paper linked below. It looks like equipments such as Livox MID are sufficient for plot-level analyses, but not for individual trees. Also, it has performed worse in dense canopies and broadleaf forest, thus I believe we won't have a technology capable of doing what you aim for this amount of money (< $1000) in a few years from now.



I hope someone give us an alternative, though. :D



Best,

 

 

https://www.mdpi.com/2072-4292/13/1/77
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discussion

Exploring storage options for mass data collection

Adam Roberts

22 March 2023 3:20am

Hi all. I'm currently exploring options for data storage en masse. With our project we will be collecting 24hr hydrophone data, drone video 6hr per day, photography &...

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Carly Batist

22 March 2023 7:36pm

Hi Adam!

I mostly live within the ecoacoustics space so I'll just speak on the hydrophone part of your request; Arbimon is a free web/cloud-based platform with unlimited storage for audio files. We've got an uploader app as well for mass-uploading lots of files. There's also a bunch of spectrogram visualization/annotation tools and analysis workflows available. It's AWS running under the hood.

I have some experience working directly with AWS & Microsoft Azure, and I've found personally that AWS was more user-friendly and intuitive for the (fairly simplistic) kinds of tasks I've done.  

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