Lundi and LiDAR!
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I’ll start with the UAV. Now known as Lundi* we have finally started flying. Our initial idea was to fly indoors however our Science Centre has some intense electromagnetic fields (who knew a mostly metal high tech structure would be filled with metal and electric??) so we ended up flying outside after a few initial tests indoors. The tests flights have been in areas we deemed low wind (plenty of building to fly into though) and minimal spectators as to not distract our pilots. Speaking of pilots, Erin and I will be the main controllers of Lundi (and possibly a sister UAV soon) and will begin practicing more and more. The rest of the team will also learn to fly them but only as time permits. The RAW digital negative images .DNG are around the size of 25MB and we can take 3 photos per second. Our next step is to explore the autopilot features of the UAV that will allow us to plot flight patterns.

Now onto LiDAR (we are now styling it as LiDAR). I built a prototype housing for the sensor that allows us to get roughly a 30º angle output. After many frustrating hours with ROS I decided to put it on the shelf for a bit and write my own code. I currently just take sample readings in an .xyz format but the ultimate goal is to pull information from Lundi to give us a full .las file which includes all sorts of useful meta data. Currently the sensor only knows how to take “slides” that are the size of the laser itself but I’m working on getting it to realise its scanning from the top down (part of what the x and y values do) and I can then import it into a point cloud viewer and we should be good to go! Currently in the .xyz format we are getting 600KB/s  which translated into 4.5MB/m. Ive also started to prototype a sort of “slider” for the LiDAR that would allow us to move smoothly across a set distance. This will then be mounted up at our 3m height and scan a patch of grass with a pencil hidden inside, the ultimate goal will be able to pick out the pencil from amongst the blades of grass.

Ill be looking into photogrammetry a bit more asap as well, its proving to be a VERY useful tool.

 

*we are under the impression that Lundi means puffin in Icelandic, if any of our Icelandic friends know differently please let us know… Id hate to be flying something called “your mothers pants”

Basic Mapping of Iceland
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I had lots of success this week with QGIS. I met with Jose and we figured out some of the georeferencing issues in ArcGIS. From there I just had to figure out what to do in QGIS to georeference jpeg files. It took a little while due to different information from different versions but eventually I was able to use the georeferencer plugin in QGIS to match the images spatial to the rest of the layers we have right now. I also took images from google earth and brought them into QGIS the same way. Right now all of the layers are in WGS1984 because that is the projection the layers were in when we received them from Oli. However the way this projection works makes it so Iceland is very skewed. I then changed the layer projection to ISN2004/Lambert2004 (EPSG:5325). This means that the individual layers are projecting on the fly which is fine for what we are doing now however before analyzing anything I will need to individually convert the layers. I am not entirely sure how necessary this is because spatial analysis should still be accurate event if it is visually skewed (we will see). Comparison below:

WGS 84 (EPSG:4326) projection of Skalanes with a close up (higher definition) Google Earth image and some of the Eider points on top. The Skalanes government coast layer is also on top.
WGS 84 (EPSG:4326) projection of Skalanes with a close up (higher definition) Google Earth image and some of the Eider points on top. The Skalanes government coast layer is also on top.
ISN2004/Lambert (EPSG: 5325 projection of Skalanes ('on the fly') with the Google Earth Image, Eider points and coastline.
ISN2004/Lambert (EPSG: 5325 projection of Skalanes (‘on the fly’) with the Google Earth Image, Eider points and coastline.
This is a pretty simple DEM map of Iceland from the National Land Survey of Iceland with the coastline layer (Skalanes layers are there as well however they are too small to see).
This is a pretty simple DEM map of Iceland from the National Land Survey of Iceland with the coastline layer (Skalanes layers are there as well however they are too small to see).

 

I have also added Google Earth satellite images of Heimaey. We finally received that maps of the Skalanes peninsula from Omnimaps. They will not have any of the others ready therefore I have looked into other sources and decided that we will stop at a map store in Reykjavik (Ferdakort- Map Shop) called Iðnú Bookstore. I did cut the map that we do have so we can tape the two halves of the peninsula together. I also was able to find a topo map of the Richmond area for use when testing (checked out from the library). Aside from this I have collected some books on sense of place and the value of the outdoors to make a reading collection for our trip (besides Island on Fire).

NIR Progress
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Stephanie and I have concluded our work making calibration standards with the FTIR. You can read about the work here: Soil_Paper.

The soil NIR platform is coming along very well. I have been taking spectra in the 900-1700nm region on the same samples we used to make FTIR standards. So far I am getting promising results.Screen Shot 2016-05-16 at 9.03.47 AM

The x-axis here is wavelength and the y-axis is absorbance. These results are exciting to me because I see a clear gradient in absorbance between samples with different percentages of organic carbon. They are puzzling because I would expect to see the trend reversed, with 0% carbon absorbing less radiation. I am not entirely sure what I am seeing here yet, but these results at least confirm the sensitivity of the IR platform to relatively small variances in organic carbon. Sensitivity will be favorable in the context of Icelandic soil because it is mostly composed of andosols, which are under 25% carbon. The next steps are to rerun these standards, run a few standards that should be 0% organic C but are of a different chemical composition, and run samples with %C between 0-25%.

I have also been working a lot on the field probe. I need to do a quick field test to determine how important it is that soil conductivity and moisture content measurements are taken in the field vs. on the bench. Right now the field platform includes an IR temperature sensor, a moisture content sensor, and a conductivity sensor. I am currently debugging the existing Arduino code for this platform to be compatible with a different sensor pinout.

This past week Charlie and I discussed the sample plan for the glacier. Using what we have learned from recently published resources on glacial chronosequencing, and troubles with the sampling location in 2014, we think we have a rough plan for how to sample on the southernmost glacier.

Field Day had some internal work done
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If you’ve read my last post, you know that Field Day got a external makeover. It also got a lot of work done internally. For the past couple of weeks, Deeksha, Charlie and I have been working on the new data model for Field Day and the PostgreSQL database on hopper (or our portable machine). We’ve finally figured out the first pass. As you know, this could change as we move forward and test our designs, but this has gone through many field practices. There’s more than one table now — there’s pretty much one for each data point we are collecting (sensor, platform, host, site, sector, etc) all of which have unique keys and all of which will be available and populated before we use it in the field. This week, I integrated that into Field Day.

We decided that we wanted Field Day to connect to a remote database and retrieve all of the table data and store it into a local database. Field Day populates sites and sector drop downs in the ‘Take a Sample’ dropdown from which the user can choose the site and sector they want at that stop. Field Day can also check whether or not the platform and sensor they are using are in the database. Currently, Field Day fails if it can’t find the platform, but I’ll be making this more robust this week. Allowing the user to retrieve external database data will prevent inconsistencies with spelling, capitalization, human error, and the like which are problems we’ve had in the past.

In the zone
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Almost all of my free cycles are thinking about Iceland now, my grading is (almost) done and now I can focus a bit more on this. May Term started on Wednesday, we’re spending the mornings working/meeting together in the lab and the afternoons concentrating on our own bits. We submitted three posters to the XSEDE conference, one based on Field Day, one on UAS + LiDAR + DNG and machine learning, and one on Mothur (the software we use to process 16S rRNA sequencer output). Nic and I have a plan for the first round of testing with the UAS, unfortunately using it in the building is difficult because of all the EMI. Kristin is cruising along with Field Day, we are very close to uploaded data to the database (using the new schema) and should be ready to start Field Day Fridays this week. Erin is chugging along on the GIS, she is creating base layers by georeferencing Google Map images for Heimaey, the two glaciers, and Skalanes. Lots of list management and lab sorting this week, this is our chance to align our waterfowl for the run-up to June 23.

New design!
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This past week has been busy! I’ve done a ton. One of the things I’ve done is make Field Day look a little prettier. I find it much easier and productive and effective to work on if the application is prettier and nice to look at. Go back to my previous posts and you can see that Field Day was ok looking, but it was really dark and boring. Now it’s quite pretty and fun. I got rid of the circles and just made it icons without a background. I also made it look like the user is in a field, hence ‘Field Day!’ There are probably some other things that I could add, but for now I think it’s pretty and much nicer to work with. You can see pictures of it below.

 

fieldday-main fieldday-sample

Ambiance and a Feather
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So, it’s been a little while since my last post. Here’s a quick update. I assembled our ambiance platform using the Adafruit feather and two sensors: Altimeter and Temperature, Humidity and Pressure. The Adafruit feather is a tiny BLE capable micro controller (like a Light Blue Bean). We decided to go with the feather because the BLE chip it uses is Nordic, like the Red Bear Labs BLE Shield. With the Nordic chip we can make our own services with UUIDs. The Bean has a built-in set of UUIDs and communicates differently than the Nordic chip.

The platform sensors currently use two different communication protocols: I2C and SPI, but we decided that probably wasn’t going to be a problem. I was able to solder on the sensors to a prototyping board and upload a sketch. I tested without the BLE first time to make sure it was working. It was, thanks to sample code from Adafruit! Adafruit has a different BLE library but it’s all the same principal. I tested the BLE code with Field Day and all works well. A picture of the ambiance platform is below.

Brief Update
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Map1EiderSo there are definitely some challenges in terms of the GIS stuff. I decided to bring all the layers into ArcGIS to see if I could do more with fixing projections in a platform I already know. It gave me the same result so then I brought a base map in which showed me that I think it is the JPEG of the Skalanes area that has the projection issues not some of the other layers (some still are nowhere). When I went to create a base map layer of that area it wasn’t really working therefore I set up a meeting with Jose and will hopefully most some more updates after that meeting.

I have also started to look at good articles regarding sense of place and other wilderness related things that would help everyone to better understand that program and in order to work things like that into this program.

Scheming…
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After a week or so of tinkering we have a new version of the database schema that supports Field Day and the visualization stack. Here is the fancy entity relationship diagram for it:

IMAG0420

Field Day will load trip, site, and sector information from Postgres (config option) and cache them on the tablet. Deeksha is committed to moving the data from Iceland13 & 14 and Nicaragua14 into this new structure.

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