Lmst

It's been a while since the writing energy has hit. So today has been all about punching through a writeup of doing something useful with imperfect data

You have some drone images over a transect and want to get the approximate area covered [1]

Use #DroneDB CLI (https://docs.dronedb.app/docs/cli) to generate image footprints:

ddb info ./jpg/*.JPG -f geojson --geometry polygon -o footprints.geojson

Drop the footprint geojson into QGIS [2]. Dissolve them (Vector -> Geoprocessing Tools -> Dissolve) [3].

Reproject the result to a CRS in metres (eg UTM) and label with $area [4]

Done!

#droneMapping #FOSS4G #gischat

[1] Drone images in a transect. The images must have GPS metadata - position and also orientation

[2] Image footprints from DroneDB CLI as black outlines. You will need to adjust the styling for this effect

[3] Dissolved image footprint polygons as a single purple polygon

[4] Dissolved footprints, reprojected to a CRS expressed in metres and labelled with the $area. The label field reads:

to_string(round($area,2)) || ' square metres'

...which rounds the $area attribute to 2 decimal places, converts it to a string, then concatenates it with the context string contaning units.

Today we are really excited to announce support for multi-band Raster Tiles and Cloud Optimised Geotiffs (COGs) in Geobase! (only in private beta ATM hit us up if you want early access)

more at 👉 https://geobase.app

#gischat #cloudnativegeospatial #satelliteimagery #dronemapping

Drone mapping unlocks secrets of 3,000-year-old ‘mega fortress’ in the South Caucasus

A recent study using drone mapping has revealed that Dmanisis Gora, a 3,000-year-old mountainside fortress in the Caucasus Mountains, is far bigger than previously thought. The discoveries also prompted a reassessment of settlement dynamics during the Late Bronze and Early Iron Ages.

More information: https://archaeologymag.com/2025/01/drone-mapping-unlocks-secrets-of-mega-fortress/

Follow @archaeology

#archaeology #DroneMapping #dmanisisgora #bronzeage #ironage

Drone mapping unlocks secrets of 3,000-year-old ‘mega fortress’ in the South Caucasus

A recent study using drone mapping has revealed that Dmanisis Gora, a 3,000-year-old mountainside fortress in the Caucasus Mountains, is far bigger than previously thought. The discoveries also prompted a reassessment of settlement dynamics during the Late Bronze and Early Iron Ages.

The research, which was recently published in the journal Antiquity, was co-led by Dr. Nathaniel Erb-Satullo, a Senior Lecturer at Cranfield University’s Forensic Institute, and Dimitri Jachvliani of the Georgian National Museum. Their work — which has been ongoing since 2018 — showed that Dmanisis Gora had emerged not just as a centerpiece for archaeological research on the South Caucasus, but a crucial case study for investigating ancient urbanism and population dynamics

here's an #arctic example. Sea ice dtm from imagery flown with an #ANAFIUSA launched off the ice near #FFKronprinsHaakon at 81.5 north, processed in @OpenDroneMap

Colours are deformed bits. Not *quite* right yet but really close.

Part of this underlines the importance of #fieldwork. How do I know when it is "right"? It matches the consensus of people *who were there* seeing with through multiple lenses for multiple goals

#seaice #arctic #geomorphology #dronemapping

A sea ice digital terrain model derived from drone images. Parts considered 'level ice' are gray/white, colours identify ridges and deformed regions.

I've got a couple of essays / analytical pieces in the works on beautifully imperfect data.

Here's a sneak peek - using point cloud structural analysis to segment ridges in sea ice. I talked about parts of this at ESA's #LPS22, the idea goes way back to 2007 or so - patchy / lack of ongoing work in research makes progress... slow. More soon!

#arctic #seaice #polarResearch #dronemapping #landscapeAnalysis

A 3D model of sea ice made from drone photography. Parts are coloured beige and green, these are regions identified as ridges using 3D structure analysis of the data used to make the model. The beige region uses a slightly tighter threshold to say 'this is a ridge'.

#sotm2024 #lightningtalks III showcasing #mapswipe for web launch, @youthmappers chapter in Makerere University #uganda, #machinelearning project involving #dronemapping in #mozambique and #surveyresults regarding what prevents women participating more in #openstreetmap comparing men and women answers (that differ!)

...continuing a little - finding trees in drone data, no AI needed.

Because we have OK-ish representation of what is below canopy, it's possible to try and count things like trees.

A whole bunch of things later, here's a visualisation showing an orange dot for almost every tree.

What's going on with the obvious tree that wasn't picked? Just filtering decisions - if you expect research level rigor from a shakedown flight, #hireme.

#droneMapping #macroEcology #boxIronBark

Hmm. still a few bushes - however the old mine remains show up wonderfully! I should mention I'm using a cloth sampling filter - reading the original paper to tune it for these data. #researchlyfe

It's so close. The key message is - if you're doing drone things over natural surfaces, *always* check your ground segmentation assumptions, as well as knowing if you're using grass elevation or actual ground ;)

#dronemapping #photogrammetry

Arrived from hosing trains to a best-yet ground segmentation for Box Ironbark with ground disturbance (old mining features).

The compromise here is some false-negative ground results, in exchange for not identifying as many bushes and plants as ground... I hope...

Ground segmentation is a nontrivial problem for photogrammetric models. There's no cheating with last/only returns, it is all about iterating toward a useable surface morphology.

#dronemapping #photogrammetry

...a bit of box ironbark. It's not bad - next weather window I'll repeat with double (or more) the imagery. I was after the ground features / mining disturbance under-canopy, and in this forest, it's a fine application for photogrammetry. There's a little work to do on ground segmentation - every zone and target use case has its own tuning quirks!

#BoxIronbark #droneMapping #photogrammetry

photogrammetric point cloud over Box Ironbark woodland. Rust coloured points are labeled as ground, grey points are labeled 'not ground'.

Spent a little time touching grass - or drone controls - yesterday. Out in Box Ironbark woodland, heavily modified by goldrush mining.

It was a little late in the day for mapping - however, there's a result! I'll add to this thread later.

If you're in the goldfields region and you're after some low carbon aerial imagery / mapping, get in touch! Jobs far from Bendigo might need a little extra planning :D 🚲 🚁 🗺️ 📷

#Djandak #Goldfields #Bendigo #CentralVictoria #dronemapping #dronephotography

Recovering Box Ironbark woodland on Djandak (Dja Dja Wurrung country) near Bendigo

Working toward part 3 of a series on drone mapping things, I went looking for vegetation indices in @qgis . I didn't find any so I made some models to compute a few indices:

https://gitlab.com/adamsteer/qgis-things

Hope they help. Feedback welcome - if it means anything other than error correction, send a letter of engagement / purchase order ;). This work is funded by approximately $0 per year at the minute.

#FOSS4G #dronemapping #vegetation

overhead view of some structures and vegetation showing low ExGR values in blue, higher in red, overland on and blended with a true colour orthophoto. Land elevation contours are also visible.

A long awaited update to a project first started in 2020 - microhydrology using small drones, @opendronemap, @pointcloudpipe and @qgis

https://www.spatialised.net/mapping-a-small-farm-part-2-microhydrology/

#foss4G #dronemapping #hydrology #terrainanalysis #gischat

In case you're spending time hunting out how to compute plant health indices from imagery, the @OpenDroneMap
codebase has this wonderful nugget - listing calculations for many established methods (and you can make pull requests to add more!):

https://github.com/OpenDroneMap/WebODM/blob/master/app/api/formulas.py

#FOSS4G4Research #dronemapping

@sarahdalgulls maybe estimate your average image footprint from camera params and height above ground, then rule-of-thumb it. Say your image is 50m along track, you flew at 2m/sec, your images are 5s apart. You're flying 50m every 25 seconds so in a sequence of images 0-5 you can drop image 1, 2,3 and 4 (this is off the top of my head, image 4 might be needed)

Similar for between lines assuming you flew a grid. Estimate across-track footprint, see what lines can be skipped.

#dronemapping

This is one of the worst #DroneMaps I've ever made, and is also incredibly valuable because it is data that will never be captured again, plus it really helps get another dataset - the electromagnetic induction ridge survey line - into context.

It was about -12C, with 12m/s winds, 82 degrees north (in this map, north is to the right). I launched the drone with a snow shovel as a windshield against blowing /saltating snow at ground level, and at the first launch the aircraft promptly blew away and crashed in the snow.

On recovery the drone was undamaged, so we made sure it was on 'full power mode' and took off. Control was nuts - trying to keep to sane speeds for photography and flying hard into the wind then being blown back. Turning was a mission. I was done after not too long, just mentally cooked from flying.

The heroes in this story are the tools which let us undertake such audacious ideas and know that we'll get something useable. Even in the worst conditions, we had a drone that could handle it (#ANAFIUSA), software which made sense of scrappy data (#OpenDroneMap) and tools to visualise it effectively alongside other data - which makes it all worthwhile (#QGIS).

There's another story about how we map on drifting ice, that's in the works.

I was working on / funded by the Norwegian Nansen Legacy Project when this map was made, in mid-2021. My co-conspirators on this voyage were Polona Itkin and Tristan Petit. And this same drone lived to fly many more successful missions!

#Arctic #SeaIce #DroneMapping #ResearchStories #FOSS4G