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S22 | Dig Watch: Knights Hospitaller Preceptory: Site Map (GNVDI) (Patreon)

Published:
2022-10-01 19:28:52
Edited:
2022-10-04 20:36:35
Imported:
2026-06
Tags:

Content

Here's the third layer of data to add to our site map.

If you cast your mind back to the Site Walkabout on Day One, our aerial surveyor Adam Stanford discussed some of the newer survey techniques that we now have at our disposal. GNVDI is one such example, which stands for 'green normalised vegetation difference index'.

Put simply, it measures the greenness (or 'health') of vegetation, and the technique has a range of applications, not least in agricultural and environmental studies. However, in our case, GNVDI might be useful to indicate evidence of underlying archaeology.

More info on the broader technique can be found in this external article here: https://up42.com/blog/tech/5-things-to-know-about-ndvi 

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Comments

Dig For Barton, BLCHS.ORG (edited)

Comment edits

2026-09-08 22:00 Is there there a UK database of NIR images like that of LiDar or is the GNVDi conceived from the tiled drone images then through software?... if so what is the software called?
2022-10-01 20:01

James D Speckart

This is cool--I'm not sure if I see much in it myself, but it looks like a wall in the bottom right of the site, and more interestingly, maybe a faint set of paths that meet/split symmetrically leaving the site in the upper left. Thanks for sharing this kind of scan with us!

Jenna Leigh-Thompson

Also how can GNVDI equate plant health to species.. accuracy in large scale ( say a field of barley) would be more predictable than an arboretum.

Robert Boudreau

The advances in technology in just the past few years is mind-blowing.

Robin Goodfellow

Thank you - I was wondering about that particular map at the time, as so little was explained about it in that site walkabout

Graham Dombkins

I see an opportunity to put the power of AI image searching to use here. If there are large swaths of these images I wonder if some of this grunt work looking for interesting anomalies, possibly as yet undiscovered, could be undertaken.

Terry Cox

Would love some form of active Q&A session where we could learn to interpret these images better. Then we could help by getting a lot of eyes on the data during a dig. There are some faint ring shapes, for example, and it would be useful to know if these are archeology, or just the ghosts of trees long gone.

Don Cook

As always: Awesome post...great to see things like this!!!!

Anne

Great idea Terry - I reckon there will be a number of Patreons who would appreciate the opportunity for a more active involvement. There's work in setting up a viable citizen science project but there are models out there. Check out this BBC, Inside Science, item on Citizen science projects old and new (https://www.bbc.co.uk/sounds/play/m000hpdl). And take a look at Zooniverse an online platform for citizen science projects (https://www.zooniverse.org).

Eelco Kruidenier

Too bad this map is so small just like all the others so far. The key is hardly readable.

Katelijn Van Oosterwijck

If you're watching on your phone, tap on the map and then you can zoom in (recently figured this out as well haha) 😁

Peter Spencer

Hi Jenna, Whilst several government agencies and associated NGO's do utilise multispectral imagery there is currently no publicly accessible national dataset as there is with the DEFRA LiDAR data. In part this is because such data is often collected via targeting of individual sites rather than large landscape swathes and the resulting datasets are of considerable size. An exception to this is the European Space Agency's SENTINEL satellite data series which captures medium resolution (10m+) multispectral imagery globally. Whilst this resolution is perfect for evaluating large landscape scale features and trends it is unfortunately too coarse to identify most archaeological features.

Peter Spencer

Graham, you are indeed correct, the use of AI to rapidly characterise and sort remote-sensing data has become a field of huge interest in heritage studies recently. In particular the work currently being undertaken by Dr. Iris Kramer and the team at ArchAI exploring the automation of LiDAR assessment within an archaeological context may be of interest to you.