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Every day, mapping and spatial analysis are aiding conservation decisions, protected areas designation, habitat management on reserves and monitoring of wildlife populations, to name but a few examples. If you are excited by the ways in which GIS is used in conservation, this is the group for you!

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Data Scientist (Geospatial), Global Fishing Watch

Global Fishing Watch
Global Fishing Watch are looking for a data scientist to join the Research and Innovation team. Help us tackle geospatial data fusion problems to produce the most complete picture of human activity at sea.

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Advice on afforable LiDAR scanners for Amazon forest surveys

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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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,

 

 

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discussion

Who's going to ESA in Portland this year?

So who is going to be at the Ecological Society of America meeting this year in Portland, August 6-11th?It will be my first time at the conference, so I won't know many people...

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Indeed, I'll be there too!  I like to meet new conservation friends with morning runs, so I will likely organize a couple of runs, maybe one right near the conference, and one somewhere in a nearby park where we can look for wildlife.  The latter would probably be at an obscenely early hour, so we can drive somewhere, ideally see elk (there are elk within 25 minutes of Portland!), and still get back in time for the morning sessions.

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Exploring storage options for mass data collection

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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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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article

Python for Geographers (video)

This technical workshop was recorded at the Esri Developer Summit 2021. Presenters use packages to make GIS workflows reproducible through code, work with spatial data and make relevant maps using open source packages...

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discussion

Monitoring airborne biomass

We are producing hard- and software for small scale research  radars to monitor airborne biomass automatically. We can distinguish birds, bats and insects through day and...

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Looks like you want to have a read of this thread: 

Our project in very short is, setting up a sensor network for monitoring airborne biomass, mainly insects, birds and bats in near realtime, and to develop a forecast model to be used for mitigation with respect various types of human-wildlife conflicts (e.g. wind power, pesticide application, aviation). Our expertise is mainly in radar monitoring, but we aim on add insect camera information to be merged with the quantitative biomass measeurments by radar.

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discussion

Google Earth Engine vs Microsoft's Planetary Computer: Which do I use? 

It was an utter delight to have Dr. Gilberto Câmara along to our Variety Hour show last week, he was an incredibly engaging and knowledgeable presenter and ended up staying back...

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Dear @Frank_van_der_Most and @StephODonnell , thanks for the comments. Regarding the importance of local knowledge in EO data classification, some thoughts follow:

1. Consider two AI applications: large language models (LLM) and object recognition in images.  LLMs such as ChatGPT use words to predict the next word. Since language is its own meta-language, LLMs rely on the fact that our understanding of written text is direct. There are no intermediaries between humans and the printed page. 

2. Object recognition in images (e.g., face recognition) is another kind of AI application where there is an implicit assumption: there are objects (faces, cars, etc) in the image and the role of the algorithm is to distinguish them from the background (considered as unwanted noise).

3. Classification and interpretation of Earth observation data, by contrast, uses a different paradigm. In principle, all of the data is informative. Unlike face recognition, there is no background. Every pixel counts. Pixel values are not words, but  measures of reflections, emissions or echoes of the Earth's surface. 

4. We use words to describe the reality external to us. The variety of nature is such that we have to use simplifications and taxonomies to describe our landscapes. Take the word "forest". As Chazdon et al. question in their 2016 paper, "when is a forest a forest?" The answer is: it depends on who is asking the question. 

5. There have been many attempts to join pixel values with landscape descriptions. e.g, "pixels with NDVI > 0.75 are forests". Do they? What about dry forests that only have high NDVI values in the wet season? So far, all attempts to use direct links between pixel values and landscapes have failed the test of rigour. 

6. Another example is the algorithm used by Global Forest Watch to measure tree cover gain and loss. As explained in the link below, "Not all tree cover is a forest". As GFW acknowledges, their algorithm has problems distinguishing forest from oil-palm plantation and to identify trees in dry forests (see more at  https://research.wri.org/gfr/data-methods?utm_campaign=treecoverloss2021&Limitations#limitations). 

7. Some of you may know the attempt made by FAO to standardize land use and land cover classification using the LCCS ontology. LCCS describes land properties based only on land cover types, disregarding land use. For example, LCCS does not distinguish ‘pasture’ from ‘natural grasslands’; it labels both as herbaceous land cover types. Classification in LCCS has no temporal reference. For a more detailed criticism, see Camara (2020). 

8.  There is no shortage of global land cover and land use maps. While these maps provide a general sense of the global picture, very few (if any) have local significance. As those in the WILDLABS community know, local context matters. My favourite example is the Brazilian Cerrado, an endangered biodiversity hotspot. In the last decades, many areas of natural vegetation in the Cerrado have been converted to pasture for cattle raising. However, global maps inevitably label both pastures and natural Cerrado vegetation as "grasslands". Clearly, such data is hardly usable for supporting studies and public policies in the Cerrado.

9. What is the alternative for mapping areas such as the Cerrado? The only way I see is gathering experts who understand the uniqueness of each ecosystem and try to relate each landscape to signals measured by EO satellites. This is hard and painstaking work, which many iterations. 

10. The recent availability of open big EO data is a blessing and a curse. Using time series, experts can use the temporal evolution of the pixel values to improve the discriminatory power of EO data. Take the distinction between herbaceous pasture and natural Cerrado vegetation. All savannas of the planet (including the Cerrado) have evolved to be resilient to the dry season and to fire. Therefore, while in the wet season it is sometimes difficult to distinguish between herbaceous pasture and natural Cerrado, such distinction increases in the dry season. This is a case of where time series and big data improve the classification results.

11. Big EO data is also a curse, since it requires experts to rethink how to use EO data for land classification. Selecting training samples by looking at a single image is too simplistic when we are classifying time series. Linking the values of a time series to the temporal evolution of the landscapes requires relearning what EO data is. 

Long story short: using Earth observation for conservation studies and public policy making is hard. It requires the combination of big EO data, good algorithms, and lots of expertise to understand the information inherent in the data. A nice challenge to all!

References cited:

Chazdon et al., "When is a forest a forest? Forest concepts and definitions in the era of forest and landscape restoration". Ambio, 45, p 538–550 (2016).

Camara, "On the semantics of big Earth observation data for land classification". Journal of Spatial Information Science, 20 (2020). 

 

 

Dear @gcamara , thank you so much for your elaborate reply. I am afraid, I am still overlooking something. Do I understand correctly, that the relationship between EO and local expertise is that one needs the local expertise to inform the interpretation of the EO data? But then every area that is different from its neighbors ( easier said than established ) needs a representative. That means that one needs a huge number of representatives to cover the entire earth. If that is organized, then the knowledge is collected through these people. How are the images then still useful? For the precision and the quantification? 

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GIS for a Sustainable World

The ESRI GIS for a Sustainable World Conference will be hosted 2-4th May, 2023 in Geneva, Switzerland. Learn how the humanitarian community and organizations are using GIS to maximize their impact and achieve a more...

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The WILDLABS Variety Hour: February 2023 - YouTube

Last week's Variety Hour is now up on youtube. It was a great session - we covered Moveapps, an awesome community project building marine biologgers, chatgpt and google earth engine vs microsoft's planetary computer. Thanks everyone who came along!

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discussion

Drones for GIS - Best Practice

I thought I would share our best pratice document we created as part of the Drones for GIS project we we are running at the RSPB. The aim of the document is to provide insight...

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We've just created a new version. General updates throughout

 

version notes

 

General refresh and update based on knowledge acquired over the last couple of years

Checked links

Updated CAA regulations, drone model advice including Yuneec, sensor advice (including thermal), classification advice, hydrological modelling advice, and nest survey info

This thread continues to be one of the most useful, evergreen resources - even 5+ years later! Who would have thought? 

I was speaking to a colleague from another conservation ngo last week - and it came out that she was having to start from scratch developing some consistent internal guidance to support staff members using drones. I've poiinted her here and it's already been super useful, but I'm curious if anyone has newer guidance they've developed to support drone use their organisation that they'd be able to share? If you've updated your guidance, what have you changed or found to be most important? 

Reinvigorating this thread might turn out to be super useful for lots of folk and save a lot of time in developing supporting documentation - I appreciate anyone who is able to share! 

Thanks 

Steph 

Hi all,

I've been quickly developing in-house drone services in the UK for Providence Ecological and have found some useful information for building a workflow with Rich Charpentier's YouTube channel. There are loads of good resources on YouTube but Rich's channel seems to be more useful with regard to budget/free software etc. 

It has occurred to me that there may not be very good "Best Practice" guidance for drone pilots with regard to wildlife disturbance so when considering employing a drone pilot, please bear this in mind. It is useful to talk through their experience of avoiding/mitigating disturbance to wildlife during drone operations asnd provide guidance where you feel it is required. 

Hopefully this is helpful!

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article

Download Now: A Best Practice Guide to Satellite Technologies for Tracking Wildlife

Zoological Society of London
The Zoological Society of London, with the support of WILDLABS and the UK Space Agency, are proud to publish this new guide to satellite technologies for tracking wildlife.

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Very nice! Looking forward to checking it out!
We had this comment come in to our team from @Redfoxmeek so I'm passing along the helpful resource: Hi Folks- Thanks for the manual, can I also draw your attention to...
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discussion

Recommendations about online courses on GPS wildlife tracking?

Hi! I'm looking into online courses to learn about different techniques to monitor wildlife using telemetry, GPS... Does anyone know about online courses in which I could...

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Hi Silvesru, 

We're hosting a tutorial tomorrow about how to use GPS satellite tages to monitor giraffe - this could be a good starting point! If you check out our youtube channel we have a lot of other talks about selecting and using tags on different species. See the links below

Steph 

https://www.youtube.com/@user-ku1bu3wn3q

 

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