Category Archives: Environmental Sensing

Big Expedition to Antarctic Glacier

At the same time that the bees are disappearing and dying out, the ice is melting—everywhere.

In recent years, there have been a number of careful studies using remote sensing data and computational simulations of ice in Greenland and Antarctica.  These studies show that Greenland is melting everywhere at an accelerating pace.  This trend has been confirmed by close up, in situ, studies of the ice and sea.

The studies of Antarctica show a more complex picture, with some areas experiencing rapid retreat of glaciers, and other areas apparently holding steady.  There have been relatively few in situ studies—Antarctica is a huge space, very far away, and very hard to visit.

This spring the US National Science Foundation and UK Natural Environment Research Council announced a joint expedition to intensely study the Thwaites Glacier in Antarctica.   The International Thwaites Glacier Collaboration (ITGC) will include measurements of the surface and interior of the ice, the ocean, and the local atmosphere.

Thwaites Glacier has been observed from space to be changing rapidly, shedding ice into the ocean, and apparently thinning.

This expedition will flesh out a much more detailed picture of what is really happening, and possibly better predictions of the future of this ice.

The BBC indicates that if this rapid change leads to a complete collapse, the melt water from Thwaites would raise the average sea level by 80cm—knee deep.  It would be nice to know if such a collapse is immanent, no?

The research activity will include a variety of studies including drilling (to study the history of the ice, rock, and sediments), measurements of the ocean (including deployment of the submersible Boaty McBoatface and sensors attached to marine species), and radar and other sensors.  Cool!

One of the key questions remains the interaction of the relatively warm ocean and the ice.  Studies have shown that in some cases the ocean is invading farther under the ice, changing the grounding line.  The expedition will collect close up measurements of the glacier, to determine what is happening under the ice.

I don’t know if this actually is the “Biggest ever Antarctic field campaign”, but it is certainly a major effort, and the biggest in recent decades.

It will be interesting to see the results from these studies in the coming years.

  1. Jonathan Amos, Thwaites Glacier: Biggest ever Antarctic field campaign, in BBC News – Science & Environment. 2018.
  2. National Science Foundation, US and UK join forces to understand how quickly a massive Antarctic glacier could collapse, in NSF News Release. 2018.


WaggleNet: IoT Sensing for Beehives

Yet more Bee research from the University of Illinois Urbana-Champaign: WaggleNet.

This spring undergraduate students report a neat project, implementing an ad hoc sensor net to measure the conditions in Bee hives [1].

The students pulled contemporary technology; low cost, low power computers, radios, and sensors, to implement an inexpensive package suitable to drop in to beehives in the field. The datastreams ping pong from one node to another until they find a router and finally reach an internet connected data repository.  The data can be analyzed to monitor the environment and other aspects of the bee environment.

The prese release notes that this is an interesting project for several reasons.  The initial idea is driven by a “customer”, a bee keeper who wants to monitor the bees over winter.  The technology requires solving the whole end-to-end problem which includes not only the electronics, packaging, and networking, but also dealing with the real world of bee hives.

This is an undergraduate project, and nicely done.  It’s fine that it isn’t exactly ground-breaking.  But let me drop some links  to other work they may want to look at.

This is a great age of sensornets and “smart farming”.

There probably have been many, many beehive sensing projects (not to mention zillions of agricultural sensing designs. I know of at least one project in Utah that is extremely similar to WaggleNet.

The team expresses a desire to make this available to beekeepers everywhere.

I certainly encourage the effort to make an open source version.  I’ll note the “open source hardware” movement as one place to publish it (e.g., see this, this, this, this, this, this, as well as things like Instructables  which has dozens of DiY bee hives and gazillons of DIY sensor projects).  Publishing the whole thing, hardware, software, instructions will take considerable work.  (Contact me if you want some help organizing all this.)

On another front, I’ll point out that if this is to be really used in the world, it wil probably need to be (re-)built with solid security.   if the data is ever to be trusted the system has to be secure.  For that matter, it is important that the sensors and network cannot be hijacked to spy on people or invade other networks.

I know that this product seems harmless and not worth hacking, but unfortunately, that’s just not good enough.  (If the team has any dreams of commercial products, then they really, really need to make things secure from A to Z.)

Again, this is a very nice piece of work.  Making a real produce and/or publishing an open source version will require even more work, and collaborations with additional experts.

  1. Heather Coit, Students Develop Beekeeping IoT for Renowned Research Lab, in Ilinois Enginering – News. 2018.

Singaporean Robot Swans

Evan Ackerman calls attention to a project at National University of Singapore, that is deploying robotic water quality sensors that are designed to look like swans.

The robots cruise surface reservoirs, monitoring the water chemistry, and storing data as it is collected into the cloud via wifi.  (Singapore has wifi everywhere!)  The robots are encased in imitation swans, which is intended ‘to be “aesthetically pleasing” in order to “promote urban livability.”’ I.e., to look nice.

This is obviously a nice bit of work, and a good start.  The fleet of autonomous robots can maneuver to cover a large area, and concentrate on hot spots when needed, all at a reasonable cost. I expect that the datasets will be amenable to data analysis machine learning, which can mean a continuous improvement in knowledge about the water quality.

As far as the plastic swan bodies…I’m not really sold.

For starters, they don’t actually look like real swans.  They are obviously artificial swans.

Whether plastic swans are actually more aesthetically pleasing than other possible configurations seems like an open question to me.  I tend to thing that a nicely designed robot might be just as pleasing or even better than a fake swan.  And it would look like a water quality monitor, which is a good thing.

Perhaps this is an opportunity to collaborate with artists and architects to develop some attractive robots that say “I’m keeping your water safe.”

  1. Evan Ackerman, Bevy of Robot Swans Explore Singaporean Reservoirs, in IEEE Spectrum – Automation. 2018.
  2. NUS Environmental Research Institute, New Smart Water Assessment Network (NUSwan), in NUS Environmental Research Institute – Research Tracks -Environmental Surveillance and Treatment 2018.


Robot Wednesday

Revised Estimates on Methane Levels in The Atmosphere

As the Earth’s atmosphere and oceans warm up, theoretical models suggest that this is due to the effects of increased levels of various gasses, including CO2 and Methane (CH4).  But where are those gasses coming from, exactly?

In the case of Methane in the atmosphere, there are many sources, including human agriculture (livestock), fossil fuel use (oil, coal, gas), natural sources such as wetlands, as well as changes in chemical sinks that absorb Methane.  Uncertainties about the sources of Methane mean that projections of future growth are imprecise.

Global levels and isotopic composition of CH4 are measured by satellites, as are other atmospheric chemicals.  Satellites also measure vegetation growth on land and sea and large fires.  Wild fires release Methane and other gasses, so increases in the frequency or duration of fires is one possible source of increased Methane.

Puruseing an accurate assessment of this question, John R. Worden and colleagues report on efforts to improve the understanding of the total amount of biomass burning and the amount of Methane contributed [2], This is a complicated problem because fires are sporadic and irregular, and the effects are not necessarily easy to measure (e.g., to estimate how much and what kind of vegetation burned).

Their excellent study uses multiple data sources.

we combine bottom-up esti- mates of fire emissions, based on burnt area measurements, with the top-down CO emissions estimates…, based on the satellite concentration data” ([2], p. 2)

This is a very tricky bit of work, which has to take into consideration the details and error ranges of the different data sources it combines.

The overall results show that emissions from burning biomass were lower than previous estimates based on burned area. This brings the estimate into agreement with measures of atmospheric gasses. The finding that the atmospheric isotope studies accurately estimate emissions from burning biomass suggests that the increases in fossil fuel emissions from those same studies are accurate as well.

Overall, the study shows that the area of burned vegetation is not necessarily a good measure of the amount of emissions.  Combining multiple satellite datasets showed that the relationship is non-linear. This makes sense: all vegetation is not the same, nor are all fires equivalent.

It is also important to note that emissions from burning biomass are not themselves particularly large, and in fact are smaller than previous estimates.  The important thing is that this study makes the data from all sources more consistent with each other, increasing confidence in the accuracy of the data and the theoretical models.

Nice work.

  1. Adam Voiland. 2018. “What is Behind Rising Levels of Methane in the Atmosphere?” NASA Earrth Observatory, January 11.
  2. John R. Worden, A. Anthony Bloom, Sudhanshu Pandey, Zhe Jiang, Helen M. Worden, Thomas W. Walker, Sander Houweling, and Thomas Röckmann. 2017. “Reduced biomass burning emissions reconcile conflicting estimates of the post-2006 atmospheric methane budget.” Nature Communications 8 (1):2227. doi: 10.1038/s41467-017-02246-0


Space Saturday

“Wearable” Sensors for Plants

I saw the headline about “wearable sensors for plants”, so I had to have a look.

Of course, the word “wearable” is kind of dumb here.

However, the technology is actually pretty cool: “a simple and versatile method for patterning and transferring graphene-based nanomaterials onto various types of tape to realize flexible microscale sensors.” [2]

Printing various patterns on tape can create sensors that measure strain, pressure, or moisture, for instance.  The sticky tape can attach to anything, including leaves of plants.  This is a cheap way to whip up and add sensors to the real world, including agricultural crops.

Pretty cool, even if plants don’t actually “wear” them.

  1. Liang Dong, Engineers make wearable sensors for plants, enabling measurements of water use in crops, in Iowa State University – News Service. 2018.
  2. Seval Oren, Halil Ceylan, Patrick S. Schnable, and Liang Dong, High-Resolution Patterning and Transferring of Graphene-Based Nanomaterials onto Tape toward Roll-to-Roll Production of Tape-Based Wearable Sensors. Advanced Materials Technologies, 2 (12):1700223-n/a, 2017.


Dusting the Ocean

One of the cool and important thing about Earth Observation from space is that it makes it possible to measure large scale events and interactions which are beyond the ability for puny humans to easily measure.

For example: dust.

In addition to silt from coasts and rivers, dust particles drift through the air from land, falling in the oceans (or distant land). While this dust is sometimes an important loss at the source (around here, we call it “soil erosion”, and we lament the loss of fertile, productive soil).  But it lands somewhere, and wherever it comes down, it is fertilizer from the sky.

For example, the vast dry lands of norther Africa are stripped of tons of dust every year, which blows across the Atlantic, where it falls to nourish the lush Amazon forests.   Wow!

This month NASA calls attention to another dust story, the annual rain of dust from Alaska out into the North Pacific.

image by Joshua Stevens, using MODIS data from LANCE/EOSDIS Rapid Response

This plume of dust is similar to the silt from a river or coast, except that it falls much farther off shore, potentially feeding plankton and other life there.

In particular, this dust contains iron, which is an important nutrient that is in short supply out in the ocean waters.

As is so often the case, the story is complex and not fully understood. It seems that this iron rich dust mainly blows out in the fall (the driest season, before the snow covers the land).  But plankton needs sunlight, too, so there isn’t much action until the next spring.  So the iron hangs around in the water over the winter somehow [2].

The research uses satellite imagery with measures from the land and sea.

This phenomenon is interesting for a second reason. Studies of paleoclimates using ice cores have found a negative correlation between atmospheric dust and carbon dioxide. There isn’t any obvious explanation for this relationship.

One possibility is that dust in the air fertilized plankton, which take up increased amounts CO2 from the air [3].

Maybe something like: glaciers grind the Earth, the dust blows out to sea, plankton blooms and eats more carbon dioxide, which reduces greenhouse effects, amplifying glaciation.

  1. Joanna E. Bullard, Matthew Baddock, Tom Bradwell, John Crusius, Eleanor Darlington, Diego Gaiero, Santiago Gassó, Gudrun Gisladottir, Richard Hodgkins, Robert McCulloch, Cheryl McKenna-Neuman, Tom Mockford, Helena Stewart, and Throstur Thorsteinsson, High-latitude dust in the Earth system. Reviews of Geophysics, 54 (2):447-485, 2016.
  2. John Crusius, Andrew W. Schroth, Joseph A. Resing, Jay Cullen, and Robert W. Campbell, Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust. Global Biogeochemical Cycles, 31 (6):942-960, 2017.
  3. Adam Voiland, Connecting the Dots Between Dust, Phytoplankton, and Ice Cores, in The Earth Observatory Image of the Day. 2017, NASA.



Space Saturday

Antarctic Surface Under the Ice

In a valuable companion to research on the heat flux under Antarctica, a team of scientist from Edinburgh published new maps of the rocks under an important area of Antarctica.

The research group assembled a higher resolution map of the rock underneath the Pine Island Glacier in West Antarctica [2]. This is, of course, critical information for understanding and predicting the flow of the ice.

This region is particularly important because the glacier has been thinning and flowing into the sea rather rapidly over the past 50 years, contributing 5-10% of global sea rise observed. Thus, the speed of this process has an important impact on projections of sea level rise.

“The retreating Pine Island Glacier (PIG), West Antarctica, presently contributes ~5–10% of global sea-level rise. PIG’s retreat rate has increased in recent decades with associated thinning migrating upstream into tributaries feeding the main glacier trunk.”

The study used ice-penetrating radar to measure the rock under more than a kilometer of ice. The radar was dragged across the ice surface, collecting data in 40 x 100 m patches.

The findings show a remarkably varied and mountainous surface under the ice. This means that there is quite a lot of friction, which will slow the ice flow in many places. These findings will provide much better parameters to computational models of this glacier.

High-resolution images of the bed across Pine Island Glacier. a Location and context. In b, the colourmap shows regional bed topography from Bedmap223, the black line is the ice divide, the white line is the grounding line51, and high-resolution survey patches are shown as black rectangles. Locations of offshore bathymetry shown in Fig. 2c, f are marked. c uses the same schema but demarcating survey patches with white rectangles, labelled by season of data acquisition (2007/08, 2010/11 and ‘iSTAR’ = 2013/14) and an end label denoting the location (where ‘tr’ = trunk; ‘it’ = intertributary and ‘t1, t5…’ denotes tributaries numbered after ref. 52. Surface ice velocities53 contoured at 100-m intervals are also shown. d–l Perspective views of the bed beneath Pine Island Glacier, together with parameters of ice flow. Vertical exaggeration in all images = 10. τ b and U b are the mean basal shear stress (kPa) and mean basal ice velocity (m a−1) from model inversion37; P r is the measured upstream propagation rate of ice thinning per ice-stream tributary from 1992 to 2015 using a thinning/non-thinning threshold of 1.0 m a−1 6 and β is the inverted basal traction coefficient equal to τ b/U b


The detailed information from this study required close up, on site measurements. Perhaps it would be possible to get similar data from aircraft or spacecraft, though I suspect it would be difficult. Of course, the topographical information from this study will be combined with long term satellite observations of the air, ice, and sea, to get a more complete picture of what is happening.

It is interesting to note that despite the high friction underneath that we now know about, this glacier has been absolutely cruising retreating at rapid pace. How fast would it be melting if it weren’t sliding over the teeth of a mountain range? Is the rugged terrain under the ice helping to preserve the ice cap as the air and sea warm up?

This detailed study covers only one small patch of the Antarctic coast. It will be interesting to see the results of similar studies on other glaciers, as are planned.

  1. Jonathan Amos, Antarctic glacier’s rough belly exposed, in BBC News – Science & Environment. 2017.
  2. Robert G. Bingham, David G. Vaughan, Edward C. King, Damon Davies, Stephen L. Cornford, Andrew M. Smith, Robert J. Arthern, Alex M. Brisbourne, Jan De Rydt, Alastair G. C. Graham, Matteo Spagnolo, Oliver J. Marsh, and David E. Shean, Diverse landscapes beneath Pine Island Glacier influence ice flow. Nature Communications, 8 (1):1618, 2017/11/20 2017.