Archive by Author | Meg

New Planet Four: Ridges Search

Today we have a guest blog by JPL research scientist Laura Kerber,  our lead researcher on Planet Four: Ridges. Laura studies  physical volcanology, aeolian geomorphology, wind over complex surfaces, and the ancient Martian climate.

Greetings to you in these apocalyptic times! I hope that you and your families are doing well in isolation, or wherever you find yourselves to be.

 Over the last few years, Planet Four: Ridges has ranged far and wide across the Arabia Terra, from Nili Fossae near the future landing site of the Mars 2020 Perseverance rover, all the way to the plains of Meridiani Planum, near where little Opportunity lost its life in a 2018 global dust storm after 15 beautiful years of adventure. Along the way, you all have discovered many other treasures, including polygonal fracture networks, networks of dark lines, patches of desiccation polygons (mud-cracks) and many other fascinating features, each of which could seed a study of its own.

Your polygonal ridge discoveries are now being incorporated into a journal article, which has been undergoing many iterations as we prepare it for submission.

In the meantime, thanks to hard work by Meg Schwamb and Michael Aye, a new part of Meridiani has been opened up to us to search, just to the east of where we had been looking:

Figure 1. The broad region of study. The aquamarine dots are where you found Meridiani ridges in the last campaign. The turquoise squares are the footprints of the images that we’ll be looking through this time. The orange line is the fictional traverse of Mark Watney in the novel “The Martian” by Andy Weir. The yellow star is the location of the Opportunity rover. The background is from the Mars Orbiting Laser Altimeter, which gives us topography (blue is low and red is high).

On our last foray into ridge hunting, we learned that Meridiani has two distinct kind of polygonal ridges. There are regular polygonal ridges, which have straight connectors and enclose polygonal shapes (commonly found in northern Arabia Terra near Nili Fossae), and Meridiani ridges, which are often arcuate, enclosing circles or fractions of circles, and intersecting each other like tattered lace. While individual polygonal ridges are thin, Meridiani ridges can have wide, flat tops, or can appear splintered. There is a new tutorial to explain these two ridge types.

Your mission (should you choose to accept it) is to range around our new region of Meridiani, looking at images and classifying them into those that have regular polygonal ridges, those that have Meridiani ridges, and those which have neither (of which there are many!) I encourage you to use the “Done and Chat” button, hashtags, and collections to point out strange or mysterious things that you encounter on your way. There is a link on each image at the bottom (click the tiny “i” after clicking “Done and Talk”) that can take you to the source CTX image if you are curious about the area. Also don’t be afraid to zoom around on the Mars version of Google Earth (with the CTX global image layer on) and tell us what you find that way.

During this pandemic, many of us are cooped up in our homes with nowhere to go. Luckily, despite not being able to travel the Earth as we are used to, we are all free to fly over the vast empty deserts of planet Mars.

Whether you are a long-time Planet Four Ridge Hunter or you’re just joining us now, have fun exploring Mars and happy ridge-hunting!

Planet Four Team + Science Friday Live Chat – Today (Monday April 27) at 4pm EDT/9 pm BST/1 pm PDT

The Planet Four will be participating in Live Chat/webinar with the Science Friday team today (Monday April 27) at 4pm EDT/9 pm BST/1 pm PDT . The webinar is open to the public and you can ask some of the team questions, see demos of the projects, and more. We’ll be highlighting all the Planet Four projects. You can find connection details and more here.

If you can’t make our live chat, there were will be a several others this week from other projects from around the Zooniverse as well. Also we’ll post a link to the recorded video when it’s available. And as always, the team is available on Talk, so feel free to jump in on any of the Planet Four projects Talk and ask the science team questions there too.

Introducing the Planet Four Organization

The team has been blown away by the classifications that have pouring in over the past several weeks. We know it’s a difficult time around the world right now, and we wanted to thank you for taking time out of your day to help explore and study the Red Planet. The Planet Four science team has been working from home, and currently there are two papers drafts the team is focusing on: one paper examining the Planet Four derived wind directions compared to Martian climate simulations and the other paper exploring polygonal ridge distributions including Planet Four: Ridges classification data.

Today we’re pleased to announce the launch of the Planet Four organization. Organizations are a recently added feature for research teams with multiple projects on the Zooniverse platform. Now, there’s a place with links to all the Planet Four projects, plus links to the blog and our social media accounts, all in one place. You’ll be able to quickly see the status of each project and collective statistics about all three Planet Four projects.

Check out the new Planet Four organization webpage at http://www.planetfour.space.

Launching Planet Four 2.0

Today we have a post by Candy Hansen, principal investigator (PI) of Planet Four and Planet Four: Terrains.  Candy also serves as the Deputy Principal Investigator for HiRISE (the camera providing the images of spiders, fans, and blotches seen on the original Planet Four project).  Additionally she is a  member of the science team for the Juno mission to Jupiter. She is responsible for the development and operation of  JunoCam, an outreach camera that involves the public in planning images of Jupiter.

WELCOME BACK!!

We are delighted to be back in business with Planet Four on the Zooniverse’s Project Builder platform.  Thanks to all of your previous work the science team has been busy in the hiatus. 

As you know we published our first paper.  It describes the catalog of YOUR measurements that we have compiled, and the statistical analysis applied.  We are now able to query the catalog to get the measurements of fans, directions of fans, assessment of when seasonal activity begins and how it develops, for example.  This is allowing us to address the scientific questions that we laid out when we conceived this citizen science project. 

As a result, the second paper is well underway.  Like wind socks the fans tell us the direction of the wind at the time they emerge.  We are comparing the wind directions predicted by a regional scale atmospheric model with the actual measurements of fan directions.  Sometimes the predictions agree very well (typically in early spring), and sometimes they don’t.  When the predictions don’t agree we are analyzing why – for example, is there local topography affecting the wind direction?  Or is it because it is late in the spring and some areas of ground may be frost-free?  Or, and this is the most important, is the model lacking enough sophistication to reproduce the observed winds?  Your measurements are our guide to the actual on-the-ground environment, so if the results don’t agree, we know we need to improve the model.   

Our third paper is also almost finished.  Particles in the fans land on top of the layer of seasonal dry ice.  As time goes on the dark particles warm up and sink into the ice.  We can use your measurements of fan lengths to quantify this process.   Fan lengths slowly decrease with time as particles gradually sink.

We are looking forward to being back in business with your help, to tackle the next science question on our list:  how do Mars’ dust storms affect seasonal activity?  We will be posting the latest images from Manhattan, Ithaca, Inca City and Giza first because we have the longest time history for those locations.  Then we will add other locations to fill in some of the other longitudes. 

It’s great to be back working with you!  Please know that we value your generous contribution of your time, our most valuable commodity. Check out the new and improved Planet Four at www.planetfour.org.

Ideas on the Formation of Resistive Polygonal Ridges on Planet Mars

Today we have a guest post from Planet Four: Ridges volunteer, Bill Hood (geocanuck). Bill Hood is a semi-retired Canadian geologist who has spent 40+ years in the mineral exploration business as a contractor, consultant and prospector. When not wandering around in the mosquito-infested swamps of northern Ontario or the grizzly-prone mountains of the Yukon, he can be found residing in a small town near the city of Winnipeg. A self-confessed Star Trek fan, Bill occasionally argues that it is mineral exploration that will drive human exploration of space, and is rumoured to have already started Mars Palladium Corp. Bill spotted the NASA P4R news release in early 2017, and has been addicted to Mars images/geology ever since.

It appears customary on Planet Four, that after one does a talk or presentation involving Planet Four: Ridges material, a blog is in order. On January 8, 2020, I did a talk titled “Ideas on the Formation of Resistive Polygonal Ridges on Planet Mars” at a meeting of the Manitoba Mineral Society here in Canada. The Society meets monthly in the city of Winnipeg in the local planetarium building, so there’s a slight crossover with the astronomy crowd.

My presentation comprised three main parts: 1) fun facts about Mars, 2) Planet Four: Ridges and the science arising from it, and 3) my ideas on the formation of polygonal ridges. After a brief run-through of the basic geography of Mars, locations of all the landers, and some fun images of faces, structures and items that look like they could only have been constructed by beings with opposing digits or sharp teeth, I outlined how the Zooniverse Planet Four websites functioned to generate Mars data. Next, I outlined some of the science interpretations coming from this data, including the abstract for the talk by Aditya Khuller, Laura Kerber et al, at the 2018 American Geophysical Union convention, as well as a proposed paper titled “Polygonal Ridge Networks in Arabia Terra, Nili Fossae and Nilosyrtis: Evidence for Groundwater Influence”, presently in preparation by the same authors. I then summarized the basic hypothesis of this work to date, which suggests that “Nili” type polygonal ridges on Mars have resulted from burial, compaction and faulting of shallow-basin, clastic sediments, with subsequent groundwater flow and mineral deposition along these polygonal-oriented fault/fracture systems. Subsequent erosion exposed these hard, resistive ridges on Mars. Terrestrial models from the North Sea basin and resistive ridges exposed across the Middle East seemed to be an entirely plausible analogy.

But being a person of contrary character and residing in the frozen environs of rural Canada, I explained to the members of the society that I had difficulty being convinced by the proposed ridges formation argument. When I looked at Mars images, I saw glaciers and pingos and permafrost patterned ground that looked like something out of Arctic Canada, while my on-line Zooniverse friends, most residents of warmer climates, saw a world of palm trees and torrid deserts. As I told my friends in the local Mineral Society on that cold January night, it was clear that I had not just a responsibility, but a Canadian national duty, to advocate a “permafrost hypothesis” for polygonal ridges on Mars.

From my observation, it appears that the “Nili” type polygonal ridges, named for a future type locality in the Nili Fossae region of northeast Arabia Terra on Mars, comprise a range of polygonal oriented resistive ridges, as well as irregular or semi-circular ridges which enclose the margins of ridge areas. It appears that these polygonal ridges are forming in the subsurface, within the basal clastic sediments in local craters, valleys and basins, just above the unconformity at the top of the older Noachian cratered basement rocks on Mars. The similarities to ice fracture patterns and permafrost patterned ground were fairly obvious. So I presented a couple dozen slides, both from Mars and Earth, pointing out fracture pattern similarities, with the caution that there were scale differences and the obvious sub-sediment vs. sub-aerial disparities.

I concluded my talk showing a series of hypothetical cross-sections illustrating a possible process for forming these unusual polygonal ridges in the sub-surface on Mars. The basic idea I am presenting is that a sub-surface permafrost cap may have formed a confined groundwater aquifer. Evidence of sub-surface artesian flow is rather obvious in many Mars images, but the question of what triggered this flow is important. I’m suggesting that the accumulation of aeolian sediment may have formed a thermal blanket which allowed remnant geothermal heat to erode the permafrost cap, triggering artesian flow from the aquifer into basal clastic sediments above the unconformity and into overlying ice-wedge fractures in the permafrost. Having a long residence time, these groundwaters would be at maximum total dissolved solids, so mineral deposition would be significant on evaporation/sublimation. 

So that’s my Planet Four blog. I’ll conclude with one takeaway, which is that if this ridge process consumed all the subsurface ice, the Nili ridge areas may not be the best places to send future Mars colonists. I can also advise that the members of the Mineral Society asked that Mars be added to the summer field trip schedule. 

Early Warm Wet Mars
Cooling Mars. Permafrost.
Confined Aquifer. Aeolian Deposition.
Thinning Permafrost. Artesian Flow.
Open Aquifer. Evaporation/Sublimation.
Induration/Lithification of Basal Sediments/Fractures.
Erosion. Variable Exposure. 

One Step Closer to Launching Planet Four 2.0

In May of last year, Planet Four project was paused. Since then we have been working on a new version of the project on the Zooniverse’s Project Builder Platform.  In October, we gave you a sneak peek of two potential versions of Planet Four 2.0.  Based on the feedback we received, we have made some tweaks and finalized the website design.

Before we officially launch the new website, we want your feedback.  Please go try our our latest version of Planet Four 2.0 and let us know what you think. You can take part here.

New data on Planet Four: Terrains

Planet Four: Terrains is back from hiatus. We’ve come up with a new set of images to search on the site. These CTX images will continue our trend of searching further northward and covering gaps in our coverage.

p4tmap

The figure above shows the newly uploaded CTX images on the geologic map of the Martian south polar region. The blue is the south polar layered deposits (SPLD). This is where most of the spiders are located, but we’ve already learned through Planet Four: Terrains that there are spiders also outside the SPLD, so that’s why the search region expands well beyond the SPD. The red rectangles show you the CTX images that we’ve currently uploaded to the site. The bright green rectangles are the second half of the dataset.

Our current plan is to write a summary science paper with a final catalog from the spider search over the past several years, after we get through both sets of CTX images. We’ll look at the soil thermal inertia and other properties and see if we find a links or correlations to where spiders are visible. We think this we’ll wrap up this phase of Planet Four: Terrains, but we already have some ideas where we might take the project next.

Thanks for your help! Dive in today at http://terrains.planetfour.org!

Help beta test the new Planet Four

In May, the original Planet Four project was paused. Since then the team has been working on a new version of the project utilizing the Zooniverse’s latest web tools. Great news! We’re nearly ready to launch the new and improved Planet Four on the Zooniverse’s Project Builder Platform.

Before we launch the site live, we need your help! We’re ready for you to take a sneak peek at the site and let us know what you think. We have developed two different styles for the classification interface, and the team is having trouble deciding between the two. We’d like you to try them out and let us know what you think. The team will be looking at performance of the two different classification interfaces and your feedback to figure out which design is the right one for the new Planet Four.

If you can spare a few minutes, please map fans and blotches in one or both of the workflow styles and let us know what you think. Try it out at www.zooniverse.org/projects/mschwamb/planet-four

Building the NASA Citizen Science Community Meeting

Greeting from Tucson Arizona. I’m here with Planet Four PI Candy Hansen at the Building the NASA Citizen Science Community Meeting. The aim of the workshop is to bring together researchers engaged in successful citizen science projects, citizen science experts and platforms supporting citizen science projects (including representatives from Zooniverse), the NASA Science Mission Directorate, and researchers interested in applying citizen science to their research problems.

I gave an invited talk (my slides are included below) highlighting science results and the success of Planet Four and advertising Planet Four: Terrains and Planet Four: Ridges. It’s exciting that people in the planetary and astronomical community see Planet Four as a successful project. That is in large part due to the contributions of the Planet Four volunteer community.  It was great to talk about Planet Four’s first paper and also mention the science team is working on three other publications right now based on the first fan and blotch catalog.

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Can I Lend a Hand? Co-operation between AI and Martian Scientists

Today we have a guest post from Dr Eriita Jones and Professor Mark McDonnell. Eriita is a Planetary and Space Scientist, Research Fellow at the School of IT and Mathematical Sciences, University of South Australia, and an ECR member of the National Committee for Space and Radio Science. Her primary research areas are (i) the remote detection and characterisation of subsurface water environments on Mars and Earth, and (ii) quantifying the habitability of other planetary bodies. She is particularly interested in new computational data analysis techniques and in assessing the benefits of machine learning for space science. Mark McDonnell leads the Computational Learning Systems Laboratory at University of South Australia. He has published over 100 research articles in the fields of machine learning, computational neuroscience, and statistical physics. Mark has worked extensively with industry partners to deliver applied machine learning solutions in areas such as precision agriculture, recycling, and sports analytics. His research interests lie at the intersection of machine learning and neurobiological learning.

Artificial intelligence may get some bad press, but there are of course many tasks with which AI can provide tremendous benefit to human beings. One of the tasks that AI can be utilised for is called ‘image segmentation’, which is the process of automatically dividing an image into objects or categories so that every pixel in the image receives an associated label (e.g. car, dog, tree). This is essentially what the Planet Four citizen scientists are doing when they manually outline the boundaries to fans and blotches in polar springtime imagery from Mars. Just like a human being, in order to learn a new skill a machine needs to be taught (or ‘trained’) in the task it is being asked to perform. For state-of-the-art automated image segmentation, this training requires large amounts of data in the form of images with the categories of interest clearly labelled. In 2018, researchers at the Computational Learning Systems Laboratory at the University of South Australia in Adelaide, Australia, realised that large amounts of labelled imagery was exactly what the citizen scientists on the Planet Four project were generating. That was the start of a collaboration with the Planet Four Science Team. We wondered – could we teach an algorithm to automatically detect fans and blotches in Martian imagery? How well could a machine learn these complex features? And could the algorithm provide information which would assist the scientists in their study of these Martian phenomena?

The machine learning algorithms used here are examples of deep Convolutional Neural Networks (CNN’s) which generally perform very strongly on image segmentation problems. The algorithms are fed thousands of labelled fan and blotch images produced by the Planet 4 citizen scientists. After lots of exposure to what fans and blotches look like at different locations, years, solar longitudes, and resolutions, the algorithms become able to generalize from their experiences and apply their learning to new situations – in this case, unlabelled images that they have never seen before. In order to assess how well the machine learning techniques are performing, the algorithms are given a test. They are asked to predict where the boundaries of the fans and blotches are in some labelled images – but the algorithms are not shown the labels and have never seen those images before. We can then compare the machine’s predictions with the ‘correct answers’ – the manual labels drawn by citizen scientists. We compare with another method as well– a more traditional and less complex image classifier that does not employ machine learning. The figures below shows the output on a subset of one HiRISE image.

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We are busily working on validating the output of the machine learning algorithms on a large number of images, but we can already see ways in which they can be very useful. Although the algorithms might not always find every fan or blotch in an image, they are very good at deciding whether there is at least one feature present. In other words, they do a good job at sorting out the images which have a fan or blotch, from those that have no fans or blotches at all. This is a very useful way of streamlining the presentation of images to the Planet Four Zooniverse platform – for example, instead of having to click through ‘featureless’ images the Planet FourTeam in future may wish to make sure that every image that appears will have a fan or blotch in it for labelling. Additionally, by automatically predicting the presence of fans and blotches in new images the algorithms provide early information on feature number and density that can allow the Planet Four team to be more selective in which images have the highest priority for manual labelling.

Could machine learning one day put citizen scientists out of a job? We don’t think this is very likely. The algorithms may eventually learn to perform very well on new images if those images are similar enough to ones they have seen before. But if they are shown an image that is very different (e.g with unusual lighting conditions, strange background terrain, or uncharacteristic fans and blotches), it is likely that the machine won’t be quite as good at segmentation as a well-trained human eye. So don’t worry citizen scientists, AI is just here to lend a hand – thanks for all the fabulous data, and stay turned for an exciting update in a few months!