Now that we have frozen development of the clustering algorithms for both blotches and fans and reviewed the stage of combining the different types of clusters together, we are working on the next issue. This is dealing with markings from the overlap regions of Planet Four subject images. For most Planet Four subject images, there is 100 pixel overlap with a neighboring subject image. So in our current catalog we have duplicates possibly of seasonal fans and blotches that appeared in more than one Planet Four subject image.
We’ve started to look into what’s the best wave to deal with this. The main reason we have the overlapping regions between adjacent Planet Four subject images is to make sure we identify seasonal fans that would get cut off between the two subject images if there was no overlap. The overlap should ensure at least one of the subject images has full view of the source, so we don’t miss anything.
Here’s an example of four adjacent subject images combined and the clustered markings drawn on.
You can see that in the current catalog we get two overlapping blotches with slightly different orientations and centers generated from combining the volunteer classifications. If you look at what is in our catalog for each subject image that makes up the ensemble, you see that for one of the subject images the blotch is only partially on the image. The resulting blotch marker from the combined classifications is also partially on the image, it extends beyond. We might be able to use this fact that people extended the drawing markings to fit the shape if the source went over the edge, to identify those seasonal fans and sources that extend beyond the extend of the subject image and when that happens use the catalog entry from the overlapping subject images where the source was fully in the subject image. We’re testing this hypothesis by performing a manual review in the next week or so of the catalog output of a sample of overlap regions.
We’ve been reviewing the output coming from the full Planet Four data reduction pipeline now that we’ve frozen development on the fan and blotch clustering codes. Once we have the fan markings and blotch markings clustered individually, we then have a stage that combines the individual clusters to decide it a source marked by Planet Four volunteers is really a blotch or fan by find clusters where there centers on top of each other and then depending on how many fan markings went into the fan cluster and how many markings went into the blotch cluster we decide it’s a fan or a blotch for the final catalog. What we found in the catalog review that there are nice cases where there are sources that aren’t quite a fan only or not just a blotch. With a citizen science approach we’re able to capture that fuzziness which is fantastic. We highlight a few examples below selected by Michael Aye, who has been hard at work developing this pipeline over the past several years.
In all three figures: the top left is the Planet Four subject image, top middle is all the individual volunteer fan markings, top right is all the individual volunteer blotch markings, the bottom right is the blotch clusters after clustering, the middle bottom is the fan clusters after clustering, and the bottom left is the final sources after combining the fans and blotches (the dots in this panel show the center position of the final fan or blotch in our catalog).
As you can see from above, we’re making great progress on the Planet Four data reduction pipeline. Next steps including handing the fact that the edges of most of our Planet Four subject images overlap with neighboring subject images, and ensuring that we merge overlapping volunteer markings covering the same spot on two different subject images.
The science team is making great progress towards freezing developing of the Planet Four clustering algorithm. I reviewed some of the output from the pipeline Michael Aye has been writing. Basically the task was to check on the few issues we were working on addressing by having a two size regime clustering for blotches drawn by volunteeers and pick the parameters that seemed to work best for the data.The good news is we see an improvement.
I thought I’d share some of then plots so you so you can see how close we are to finalizing the pipeline. These plots are at the stage of clustering all the blotch markings alone and then clustering all the fan markings alone. We combine the fans and blotch markings into one later on in the process. For now we’ve just run the first part of the clustering pipeline and outputted the results to these figures. As you can see we’re doing pretty well at picking up all the fans and blotches marked by the majority of the classifiers who made a marking on the subject image.
We’ve got one or two more tweaks we brainstormed in the last science team call last week, and once we review those I think we’ll be freezing development on this part of the Planet Four analysis pipeline until after the first paper is submitted.
We wanted to give a quick update on the original Planet Four. Michael Aye has been leading the development of the data analysis pipeline. As previously mentioned, we’ve hit a major milestone with completing the fan clustering algorithm for combining your classifications together. We think we’ve now hit that point for finalizing the blotch clustering algorithm.
We think we’ve now got a decent solution for addressing how to cluster very large blotches that take up half the image and very small blotches that are the default blotch circle size. Currently how we’re tackling this is clustering with one linking radius for the center of the blotch markings, and then we run the analysis again using a much larger linking radius. Here’s an example output:
This blotch clustering strategy seems to be a good compromise for our science goals and needs. We’re going to review several more test cases and if all goes well with this step, we will freeze development on the clustering pipeline. That’s one of the last hurdles to applying the pipeline to all of your classifications and dive into what the shapes and sizes and directions of the fans and blotches tell us about the seasonal carbon dioxide jet process and the surface winds in the Martian South Polar region.
We wanted to give a quick update on Planet Four. Our main focus has been to get a data reduction pipeline that robustly clusters all the volunteer drawn markings of each subject image together to identify the seasonal fans and blotches and based on the majority shape select decide if the feature is a fan or a blotch. Michael Aye has been leading this effort. We’re pleased to say that that the main fan identification portion of the analysis pipeline is complete. We still have a few more things Michael has been working on for the blotch identification part. We think we’ve come up with a decent solution for identifying small and very large blotches. We hope to have this part of the analysis pipeline finalized soon. Then we will be able to apply the pipeline to all of your classifications and dive into what the shapes and sizes and directions of the fans and blotches tell us about the seasonal carbon dioxide jet process and the surface winds in the Martian South Polar region.
I would like to share with you our new paper that just got published in January volume of Icarus journal.
The most exciting part of this paper is that HiRISE detected some new troughs in Martian polar areas. The troughs were not visible when the HiRISE observed those locations for the first time in Martian Years (MY) 28 and 29. But when we have commanded HiRISE to take repeated observations in MY 30 and 32, we were rewarded with images of new features that you can see in the animated image below.
The troughs are really small: the whole image is less than 200 m across, while the new troughs are only up to 1 m wide. The total length of them reaches 582 m thanks to their multiple branches.
The new troughs, large enough for HiRISE to detect, are created under the current climate condition – and this is really a big deal. They do look much like spiders: they have different tributaries and resemble the dendritic nature of the large spiders. And they are developing. In turn this means that the large spiders might be developing right now as well. We are still waiting to see topographical changes on the large and fully developed spiders, but we know now that the process is able to erode away quite some ground material. For example, the volume of the material that was moved to create the troughs in the image above is 24 m², they were created over 3 MY, meaning, the process moved 8 m² yearly only in this one example.
The erosion rates like this lets us evaluate the age of the large spiders. They take amazing 1.3 thousands Martian years! It is a long time for a human being, but it is really just a blink of an eye for a geological feature.
We are continuing to monitor these locations to check if these troughs will not be erased in the next years. It well may happen because the new spiders are located very close to the dune fields, and moving sand is capable to cover or sand-blast these small topographical features barely in a year.
I’ve been learning to use JMARS (Java Mission-planning and Analysis for Remote Sensing) to plot the coverage of the CTX images for Planet Four: Terrains. JMARS is a really nice tool for overlaying observation footprints and different maps and datasets on top of each other for Mars and other planets.
I decided to take a look at what the HiRISE Season 2 and Season 3 observations, that the science team is currently working on writing up, look like on a map of the South Pole when you plot their physical coverage on the pole . You can really see the overlap and what a small area that HiRISE covers compared to CTX.
Here’s the footprint HiRISE observations for Seasons 2 and 3 outlined in red on the elevation and topography map of the Martian south pole (latitude and longitude lines are in 10 degree intervals).
Here’s a zoom in on one of our favorite regions, Inca City. You can really see the repeat coverage outlined in white in this case.
Here’s another zoom in of a different area, where you can see multiple seasonal targets outlined in red:
For comparison here’s the footprints of the first set CTX images (latitude and longitude lines are in 10 degree intervals). The colors represent geologic units, but for this comparison we’re focusing on spatial distribution and coverage.
WeMartians is a brand new podcast aimed to engage the public in the exploration of Mars. The latest episode is about citizen science on Mars with Michael talking about Planet Four and Planet Four: Terrains. Listen to Michael (and cameos of other familiar Zooniverse voices) below or on the WeMartians website.
One of the key goals of Planet Four: Terrains is to identify new areas of interest to observe with HiRISE during the seasonal processes campaign so that we better learn about the carbon dioxide geyser process and about how and were spiders and related channels form. You can read more about the particular goals of Planet Four: Terrains here. Over the months we’ve read the discussions and comments on Talk and been making a list of regions to consider from your observations. We’re really intrigued by many of the things you’ve all spotted. Which is fantastic news! Talk has been a huge asset for this work, but we’re also using the classifications from the classification interface as well. I’ve spent the past three weeks putting together a software pipeline to take the multiple classifications per CTX subframe (typically 20 people review each subject image) to identify spiders, baby spiders, channel networks, craters, and the Swiss Cheese Terrain.
Now that the machinery is all together combined with the interesting gems on Talk we’re ready to make our list of proposed new HiRISE monitoring targets. By April 20th I aim t provide the rest of the Planet Four: Terrains science team a compiled list of locations for them to review. Then Anya will input these into the HiRISE planning system where they will be considered with the HiRSE team’s science goals and eventually Candy who wears many hats including Deputy Director of the HiRISE camera and lead of the seasonal processes campaign will prioritize these new areas with the already existing targets in the seasonal processes observing program. We aim to be ready for HiRISE’s first attempt to image the South Pole which is coming up in about 60 days or so.
This is where you come in. We have new images of different areas on the site now. There have already been some interesting images from this set I’ve forwarded to the rest of the team after seeing discussions on Talk. Let’s make a push to classify as much of the new data set as possible before the 18th of April. The more subjects reviewed the greater chance to include those areas at the start of the monitoring campaign. Not to worry though, we’ll also have a few chances to include additional targets later in the Spring Season to the HiRISE monitoring campaign if need be or to the next one.
If you have a free moment, classify an image or two at http://terrains.planetfour.org
I want to talk why we created the new project Planet Four: Terrains if we have Planet Four already.
The very high resolution images of HiRISE camera are really impressive and one might think that there is no reason to use a camera with lower resolution anymore. Wrong!
First, high resolution of HiRISE image means large data volume. To store on-board and to download large data from MRO spacecraft to Earth is slow (and expensive) and this means we are always limited in the number of images HiRISE can take. We will never cover the whole surface of Mars with the best HiRISE images. Sadly. so we use different cameras for it. Some – with very rough resolution and some – intermediate, like context camera (CTX). We can use CTX, for example, to gain statistics on how often one or the other terrain type appears in the polar areas. This is one point why Planet Four: Terrains is important.
Second, because HiRISE is used for targeted observations, we need to know where to point it! And we better find interesting locations to study. We can not say “let’s just image every location in the polar regions!” not only for the reason 1 above, but also because we work in a team of scientists and each of them has own interests and surely would like his/her targets to be imaged as well. We should be able to prove to our colleagues that the locations we choose are truly interesting. To show a low-resolution image and point to an unresolved interesting terrain is one of the best ways to do that. And then, when we get to see more details we will see if it is an active area and if we need to monitor it during different seasons.
Help us classify terrains visible in CTX images with Planet Four: Terrains at http://terrains.planetfour.org