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Geospatial data and analysis is critical for conservation, from planning to implementation and measuring success. The Geospatial group focuses on all aspects of this field, from field surveys to remote sensing and data development/analysis to GIS systems.

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Vance Russell
Over 35 years of experience in biodiversity conservation worldwide, largely focused on forests, rewilding and conservation technology. I run my own business assisting nonprofits and agencies in the conservation community
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discussion

Recommended Hardware to stitch together Drone Imagery into Orthomosaics

William Rippon

25 November 2024 6:25am

Recently I've been trying to generate orthomosaic overlays from drone imagery using WebODM. Whilst my computer is fine stitching together RGB imagery of up to 140 photos at a time...

15 1
David Hill

21 December 2024 5:21am

This site may be of use for WebODM and photogrammetry using UAVs, as it focuses purely on processing that type of data and the hardware required.   It also covers Conservation and Agriculture analysis and training using open source GIS and 3D point cloud software. Follow the links below:

https://www.geowingacademy.com

Hope this helps.

Lance Legel

3 January 2025 3:41am

Hi @willrippon, I've worked with 3D reconstruction systems (software and hardware) for over 10 years now, and lately I've been really pleasantly surprised by Pix4D.

Here is a demo for a landscape survey my company just did.
Here is a 300 MB orthomosaic we just got as well.
Here is the hardware workflow described in detail.

On top of the drone imagery, we did "post-processing kinematics" (PPK) of the drone images (a very important thing to do, otherwise photogrammetry quality really suffers).  I'm happy to discuss workflow further, and plan to release open source code and services.

If nothing else, go with Pix4D.

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discussion

Photogrammetry of Coral Reef Breakwaters

Matthew Duggan

20 December 2024 1:11am

Hello WildLabs community!I was curious if anyone had any experience or helpful insight into the following project I am working on with coral reef/land mapping interfaces in the...

1 3
Sean Hill

22 December 2024 8:35am

Hi Matthew

 

Wow, what an amazing project! It is incredible how you have managed to figure out some of the complexities of combining underwater imagery with UAV imagery. I am sure that was a fascinating learning experience. 

I cannot help you with Points 1 and 3 but can suggest using Orfeo Toolbox for your segmentation process in Point 2. It integrates with QGIS and is open source. It will work with your UAV ortho maps if there is enough visible detail of the corals. You will be able to build and train your own model in order to accurately segment you reef. It takes a bit of know how to us the Machine Learning algorithms but once you get the hang of it it becomes immensely powerful. I will be building an online course on how to build your own machine learning processing algorithms in 2025 using this brilliant package. Once segmented you can save out the shapefiles and use them to segment and define your 3D point clouds in Agisoft.

Alternatively, look into using Picterra Geospatial AI. It is cloud based and much simpler to use but you may need to compress your imagery or point clouds in order to upload them given the file size you mentioned above.  (Although they probable do allow for large uploads these days, I used Picterra in the past and it was brilliant!). Also i am not sure if it works with point clouds directly but have a look

I hope this helps. Great project!

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discussion

Query Regarding ArcMap

Muzna Kashaf

15 November 2024 2:21pm

I am not able to use tools in arcmap 10.8. I mean tools are not running in my arcmap 10.8. What would be the reason and how to solve it?

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discussion

Is there relation between Economic GDP and Geospatial tools?

Sarah Maagi

12 November 2024 9:54am

Hello everyone,Is there a way to get information about Economic GDP of places using geospatial tools such as remote sensing. And if there is, can I get the website where I can...

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High-resolution sensors and deep learning models for tree resource monitoring

Elsa Carla De Grandi

25 November 2024 9:14pm

The paper looks at technology advances for vegetation cover changes monitoring. For example, computer vision methods to infer 3D parameters via contextual learning from optical images.

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Read "High-resolution sensors and deep learning models for tree resource monitoring | Nature Reviews Electrical Engineering" on Nature

High-resolution sensors and deep learning models for tree resource monitoring | Nature Reviews Electrical Engineering

Trees contribute to carbon dioxide absorption through biomass, regulate the climate, support biodiversity, enhance soil, air and water quality, and offer economic and health benefits. Traditionally, tree monitoring on continental and global scales has focused on forest cover, whereas assessing biomass and species diversity, as well as trees outside closed-canopy forests, has been challenging. A new generation of commercial and public satellites and sensors provide high-resolution spatial and temporal optical data that can be used to identify trees as objects. Technologies from the field of artificial intelligence, such as convolutional neural networks and vision transformers, can go beyond detecting these objects as two-dimensional representations, and support characterization of the three-dimensional structure of objects, such as canopy height and wood volume, via contextual learning from two-dimensional images. These advancements enable reliable characterization of trees, their structure, biomass and diversity both inside and outside forests. Furthermore, self-supervision and foundation models facilitate large-scale applications without requiring extensive amounts of labels. Here, we summarize these advances, highlighting their application towards consistent tree monitoring systems that can assess carbon stocks, attribute losses and gains to underlying drivers and, ultimately, contribute to climate change mitigation. Trees are crucial for Earth’s ecosystems, aiding in carbon absorption, climate regulation and biodiversity support. High-resolution satellite sensors and artificial intelligence enable detailed tree monitoring at national and continental levels, simplifying biomass assessment, national reporting and climate change mitigation efforts.

Nature