In our new paper we report on some novel tech that uses the sensor in a smartphone for ultraviolet spectroscopy. It is low cost and based entirely on off-the-shelf components plus a 3-D printed case. The system was designed with volcanology in mind – specifically the detection of atmospheric sulphur dioxide, but may also have applications for supraglacial spectroscopy. As far as we know this is the first nanometer resolution UV spectrometer based on smartphone sensor technology and the framework can be easily adapted to cover other wavelengths.
This follows on from a Raspberry-Pi based UV camera reported in Sensors last year which was recently adapted to sense in the visible and near-infra-red wavelengths for use on ice. The plan now is to compare the images from the Pi-cam system to those made using an off-the-shelf multispectral imaging camera that detects the same wavelengths. A report of testing this camera system for detecting volcanic gases is available at Tom Pering’s blog here.
Raspberry-Pi and smartphone based spectroscopy could make obtaining high-spectral resolution data a real possibility for hobbyists and scientists lacking sufficient funds to purchase an expensive field spectrometer. The system is also small and light and therefore more convenient for some field applications than the heavy and cumbersome field specs available commercially and can easily be mounted to a UAV.
A new paper, led by Johnny Ryan, shows that a consumer grade digital camera mounted to a drone can be used to estimate the albedo of ice surfaces with an accuracy of +/- 5%. This is important because albedo measurements are fundamental to predicting melt, but satellite albedo data is limited in its spatial and temporal resolution and ground measurements can only be for small areas. Methods employing UAV technology can therefore bridge the gap between these two scales of measurement. The work demonstrates that this is achievable using a relatively simple workflow and low cost equipment.
The full workflow is detailed in the paper, involving processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. The method was applied on the SW Greenland Ice Sheet, providing albedo maps over 280 km2 at a ground resolution of 20 cm.
This study shows that albedo mapping from UAVs can provide useful data and as drone technology advances it will likely provide a low cost, convenient method for distinguishing surface contaminants and informing energy balance models.
After testing the UAV performance in Svalbard in March, I realised the original ‘tripod’ landing assembly was not going to cut it for work in the Arctic. To prevent damage from landing in cryoconite holes and to spread the drone’s weight when landing on snow, I have added some ski’s modified from off-the-shelf landing gear for RC helicopters. This also has the added advantage that if one attachment point fails, the UAV is still landable, which is not the case for the tripod design.
As well as the ski’s, I have now added the Red-Edge camera’s down-welling light sensor to the top of the casing. This will automatically correct the images for changes in the ambient light field in each wavelength.
In recent decades there has been a significant increase in snow melt on the Antarctic Peninsula and therefore more ‘wet snow’ containing liquid water. This wet snow is a microbial habitat In our new paper, we show that distance from the sea controls microbial abundance and diversity. Near the coast, rock debris and marine fauna fertilize the snow with nutrients allowing striking algal blooms of red and green to develop, which alter the absorption of visible light in the snowpack. This happens to a lesser extent further inland where there is less fertilization.
A particularly interesting finding is that the absorption of visible light by carotenoid pigments has greatest influence at the surface of the snow pack whereas chlorophyll is most influential beneath the surface. Higher concentrations of dissolved inorganic carbon and carbon dioxde were measured in interstitial air near the coast compared to inland and a close association was found between chlorophyll and dissolved organic carbon. These observations suggest in situ production of carbon that can support more diverse microbial life, including species originating in nearby terrestrial and marine habitats.
These observations will help to predict microbial processes including carbon exchange between snow, atmosphere, ocean and soils occurring in the fastest-warming part of the Antarctic, where snowmelt has already doubled since the mid-twentieth century and is expected to double again by 2050.
Our new discussion paper, led by Black and Bloom PDRA Andrew Tedstone, examines in detail why there is a stripe of dark, fast-melting ice on the Greenland Ice Sheet, particularly in the south-west. This ‘dark zone’ is clearly visible in satellite imagery of the Greenland Ice Sheet and is important because darker ice melts faster. It is crucial to understand what causes the ice to be dark there because if it grows or darkens in a warming climate then we can expect the deglaciation of Greenland to accelerate more than is currently predicted. There are two main competing hypotheses that could explain the presence of the dark zone: 1) dust melting out from ancient ice is darkening the ice; 2) algae are growing on the ice sheet and changing its colour.
The paper shows that the dark zone changes its shape, size and duration each year. This appears to be most strongly controlled by the sensible heat flux (air temperature) between June and August, number of days with air temperatures above zero, and timing of the snow-line retreat.
These findings provide some insights into which surface processes are most likely to explain the dynamics of the dark zone. The spatial distribution of the dark ice is best explained by the melting out of dust particles from ancient ice, although these particles are not dark enough to explain the colour change of the dark zone. However, these dusts may be crucial nutrients and substrates for ice algae, suggesting that the dusts control where the dark zone is, and the algae determine how dark it gets. Our other recent TCD paper showed how algae can darken ice and snow; however, there are also meteorological conditions required for algal growth including sufficient sunlight and liquid water. We suggest in the paper that the most likely hypothesis is that dust melts out from ancient ice and stimulates the growth of algae when meteorology allows it. Algae need the dust to grow, and the dust is not dark without the algae.
Having made successful UAV test flights at home in the Peak District, we have relocated to Svalbard for a week to test the equipment in the most challenging possible conditions. We are flying in temperatures as low as -10 C, in gusty wind and after pulling the UAV to the field site in its flight case on a sled behind a snow scooter. It is taking off and landing on platforms of compacted snow.
Nevertheless, so far it has performed magnificently. There has been no damage even to the delicate props during transport, suggesting the flight case is sufficient, and the autopilot seems to be deftly dealing with the gusty wind. It interfaces quickly with the laptop and it is easy to load a preprogrammed flight, even in these very cold conditions. It was quite difficult to take of and land in ‘stabilize’ mode with the wind though.
A few modifications I’d still like to make include a new landing gear design. The three legs are OK for flat, hard ground, but for ice and snow I think it would be much better to have something with skids, or possibly a circular base, as this would protect it from landing with a leg in a cryoconite hole and prevent the camera touching the snow if the legs sink. Also, at the moment any problem with a single leg compromises the UAV’s ability to land, whereas a unit that joins to the UAV in more than one place would give more redundancy.
The battery life is also significantly reduced in these temperatures. That’s to be expected, but I’m wondering if there are more mods we can make to extend the flight time for surveying big areas in Greenland.
This performance gives me hope for a successful mapping mission in Greenland, where the UAV will be used to map the ice surface in much less demanding conditions than we are experiencing here, but will be worked on more ambitious missions (higher, further, more frequent). We are continuing to test the UAV protocol in the field for a few more days, but will now focus on our methodology for pairing UAV flights with ground sampling rather than flight tech and UAV control.
As a bonus, we were treated to a spectacular aurora on the way in…
The past few weeks have been spent working down in the robotics department at the University of Sheffield building a UAV (unmanned aerial vehicle, a.k.a drone). Ultimately, it will be used to make measurements of spectral reflectance of the ice surface in Greenland. It’s been great fun working in robotics – entering the lab is like walking onto the set of Robot Wars! UAV expert Owen McAree has been a huge help in developing the hardware and software for the drone – affectionately known as ‘albedrone’ in recognition of the albedo work it will enable – and we have now made successful test flights.
It began as an off-the-peg Steadidrone Mavrik quadcopter. However, we have made several modifications. We added a new brushless gimbal powered from the autopilot, machined a new mount that allowed us to better balance the camera and minimize the power being drawn by the gimbal, and added a GPS that can be used to trigger the image capture. We have also invested significant time into tuning the flight parameters and making it as stable and easy to fly as possible.
Flying can still be quite challenging, so I also invested in flight simulator software that interfaces with the real UAV controller, meaning I have been able to get the hang of flying safely without endangering the UAV. Significant time and effort has also gone in to writing a flight manual and logbooks for the batteries, build modifications and flight records.
We have been flight-testing the UAV at the University of Sheffield’s High Bradfield site and have now successfully made a pre-programmed flight and captured overlapping images in five spectral bands. Some examples are shown below. These are interesting as they were captured over an area with a thick cover of green vegetation, perfect for NDVI analysis. Next jobs are to a) keep modifying the UAV to extend the flight time and perhaps add some additional sensors, and b) test the software that will stitch the images and analyse the spectral information…