1 00:00:01,167 --> 00:00:07,549 -As a tool for planetary geomorphology in the  Canadian High Arctic, take it away Chimara. 2 00:00:09,092 --> 00:00:15,890 -Thanks Jo, I'm just going to start presenting  my screen and transitioning into my presentation. 3 00:00:17,559 --> 00:00:19,310 I hope everybody can see my screen okay. 4 00:00:20,061 --> 00:00:26,109 Just give me thumbs up. Okay. Awesome. Hi,  like Jo had mentioned, my name is Chimara   5 00:00:26,860 --> 00:00:31,156 and I'm currently living in the Netherlands, but  I recently just graduated from Western University   6 00:00:31,740 --> 00:00:36,369 in the Earth Sciences Department as well as  the Institute for Earth and Space Exploration. 7 00:00:36,369 --> 00:00:42,542 So, I'm going to be showing you a lot of really  pretty pictures today. Really colorful pictures.   8 00:00:42,542 --> 00:00:47,422 So just that's just a disclaimer if  you're sensitive to colours and light. 9 00:00:48,131 --> 00:00:51,634 But I will be talking to you about the Canadian  High Arctic and a lot of features that you'll   10 00:00:51,634 --> 00:00:55,889 see where there's permafrost, so ice  that's buried underneath the ground. 11 00:00:56,431 --> 00:01:00,685 But first I want to just talk about planetary  analogues because the focus of my talk will   12 00:01:00,685 --> 00:01:06,191 be about Earth and also on Mars. So, we used  planetary analogues such as these two planets,   13 00:01:06,191 --> 00:01:10,779 because although their neighbouring  planets they have a lot of differences   14 00:01:10,779 --> 00:01:14,032 and also a lot of similarities. So,  I'm just going to leave those there,   15 00:01:14,032 --> 00:01:19,079 I'm not going to talk about them in specifically,  but mostly the similarities is what I'm interested   16 00:01:19,746 --> 00:01:25,335 because that's how they are analogous to each  other. So, there's a lot of impact craters on   17 00:01:25,335 --> 00:01:31,091 Mars and on Earth, volcanoes, gullies, which  are from the cliffsides from water erosion. 18 00:01:31,091 --> 00:01:33,426 But today I want to talk about the periglacial   19 00:01:33,426 --> 00:01:38,681 land system is what it's called, but a  fancy word for permafrost environments,   20 00:01:38,681 --> 00:01:44,062 and these permafrost environments can house a lot  of really cool shapes and features on the ground,   21 00:01:44,604 --> 00:01:49,234 and some are called pattern ground and this  is an example of a pattern on the ground. 22 00:01:49,901 --> 00:01:54,531 Polygonal networks is the name of these  little honeycomb-like shapes that you see on   23 00:01:54,531 --> 00:01:59,744 the ground on Mars and on Earth. They also have  similar scale, which begs to ask the question,   24 00:02:00,537 --> 00:02:05,083 is there ice on Mars as well? Or how much ice  is there underneath these pattern grounds? 25 00:02:05,083 --> 00:02:09,337 So that's kind of the question that I would  like to answer by just looking at the surficial   26 00:02:10,296 --> 00:02:13,174 geomorphology, which is another word for shapes   27 00:02:13,883 --> 00:02:17,011 on the ground and the forms  of these different patterns. 28 00:02:17,011 --> 00:02:23,643 So, they are very prominent in areas where there's  frost mass movement and nivation is just simply   29 00:02:23,643 --> 00:02:29,065 movement of frost underneath as well and wind  activities, and just for an example there's a   30 00:02:29,065 --> 00:02:33,820 lot of patterns other than just the polygons  that I showed. There's also stone circles,   31 00:02:33,820 --> 00:02:40,535 steps, nets, stripes, different types of patterns  depending on the slope, how cold it is, the type   32 00:02:40,535 --> 00:02:46,624 of substrate or sediment, if there's pebbles or  sand. But I've highlighted the ones that you'll   33 00:02:46,624 --> 00:02:52,463 potentially see today, and I'll be focusing  on a mapping technique that's called LIDAR,   34 00:02:52,463 --> 00:02:56,426 which stands for light detection and  ranging, and it produces these images   35 00:02:56,426 --> 00:03:01,181 that we turn into digital elevation models,  which that's what they're officially called. 36 00:03:02,223 --> 00:03:07,103 So, the two sites that I went to or had the  privilege of actually going and doing field   37 00:03:07,103 --> 00:03:13,234 work in the Canadian High Arctic in 2018 and  2019 is Axel Heiberg Island in Strand Fjord.   38 00:03:13,234 --> 00:03:17,739 So, you can see those polygons already in  this little fan like feature and then also   39 00:03:17,739 --> 00:03:24,454 a giant crater 23 kilometers in diameter, called  Haughton impact structure in Devon Island. It's   40 00:03:24,454 --> 00:03:29,709 the largest uninhabited island in the world,  and both these types, including High Arctic,   41 00:03:29,709 --> 00:03:35,798 are very ideal for Mars analogue studies because  of their dry and kind of polar desert environment. 42 00:03:36,466 --> 00:03:42,138 So, for the first study site we looked at this  massive fan, alluvial fan, that kind of came   43 00:03:42,138 --> 00:03:47,644 out of this little valley over here, and we  divided them into three little zones because   44 00:03:47,644 --> 00:03:53,399 of the different characteristics that these shapes  had. And so, all of the Canadian High Arctic has   45 00:03:53,399 --> 00:03:59,322 continuous permafrost zone, at least the very High  Arctic. So everywhere has ice, but we just don't   46 00:03:59,322 --> 00:04:06,621 know really how much. So, these three separate  zones, you can see the polygons evolve in shape   47 00:04:06,621 --> 00:04:10,917 and also in just the different sizes that they  have. So, in the middle is what we're kind of   48 00:04:10,917 --> 00:04:15,630 interested in, because you can see there's little  secondary cracks and we actually don't know what's   49 00:04:15,630 --> 00:04:23,096 causing those, whereas over here in the closest  and the farthest edge, we don’t really see that. 50 00:04:23,721 --> 00:04:29,018 So, could it be that here's a little  step under there? Is there a water basin?   51 00:04:29,018 --> 00:04:35,024 Is there ice underneath? How much ice? Maybe  there's some pooling, so that's why it's really   52 00:04:35,024 --> 00:04:40,113 important to use GIS techniques using satellite  imagery, and because we were lucky enough to have   53 00:04:40,697 --> 00:04:48,621 this backpack LIDAR, so it shoots lasers,  essentially, outside laterally side-by-side   54 00:04:48,621 --> 00:04:55,336 and it measures the distance as you walk. So,  it creates a model mapping elevation, such as   55 00:04:55,336 --> 00:05:00,216 this one, this really colourful one, showing the  highest in brown and the lowest in purple. So   56 00:05:00,842 --> 00:05:05,013 that's essentially what I've been trying to map,  and the different shapes and how they can show   57 00:05:05,638 --> 00:05:10,601 that there is ice underneath. We also did collect  samples as well as other things, but a lot of the   58 00:05:10,601 --> 00:05:16,691 mapping I really enjoyed and processing this data  is really, really fun to work with. There's a lot. 59 00:05:16,691 --> 00:05:23,406 So, we call it hyper resolution because if I were  to zoom in on this image, I could literally see a   60 00:05:23,406 --> 00:05:28,995 two-centimeter pebble on this image, because  that's how good the resolution is of this   61 00:05:28,995 --> 00:05:33,958 backpack LIDAR was and that's why we were unable  to actually map the entire thing because we had   62 00:05:33,958 --> 00:05:40,757 to walk around all day. So, this was a result of a  whole days' worth of walking. Just that one blob. 63 00:05:41,549 --> 00:05:48,306 And so, we move on to another site that we went to  inside the crater in the island lower, and we see   64 00:05:48,306 --> 00:05:53,644 all of these boring little grids over here that  you see on the side, but they're not actually as   65 00:05:53,644 --> 00:05:58,691 boring as you think. They have different patterns  and as well as different grain sizes and different   66 00:05:59,233 --> 00:06:04,280 areas where they are in the crater, so that's what  I was trying to map spatially, where they are,   67 00:06:04,280 --> 00:06:10,453 what kind of substrates, but to make it more  interesting, we mapped to the entire crater   68 00:06:10,453 --> 00:06:15,625 as well as the parts that have dots on  the map. So, these are the LIDAR grids   69 00:06:15,625 --> 00:06:22,590 collected by this other backpack LIDAR, they’re  similar models just one is developed later on   70 00:06:22,590 --> 00:06:26,594 than the other. But we created these  maps and they essentially show you   71 00:06:26,594 --> 00:06:31,974 the little hyper resolution forms that  you will never see from a satellite image.   72 00:06:31,974 --> 00:06:36,938 So, if I was to take a satellite image of the  Arctic, I would never see these forms unless   73 00:06:36,938 --> 00:06:40,942 I was actually there on the ground myself,  mapping them with this backpack LIDAR. 74 00:06:40,942 --> 00:06:46,614 So, we were lucky enough to even have that kind  of resolution. So, what I did with these shapes   75 00:06:46,614 --> 00:06:53,329 is I mapped every single one of them and drew  kind of circles and shapes and whatever there   76 00:06:53,329 --> 00:06:59,794 is I could find, and you had to map  these shapes geomorphologically and   77 00:06:59,794 --> 00:07:05,466 you have to kind of statistically prove  that they are is a pattern somewhat. 78 00:07:05,466 --> 00:07:10,346 So, what I did was I looked at the area,  perimeter, and elongation ratios as well.   79 00:07:10,346 --> 00:07:16,602 and also the compactness. So, these are the kernel  density estimation maps is what it's called,   80 00:07:16,602 --> 00:07:21,899 it's basically a heat map showing the saturation,  so the first one over here on the left side   81 00:07:21,899 --> 00:07:29,407 is showing you the elongation, how long the forms  are, so this is the LIDAR grid, and then I had to   82 00:07:29,407 --> 00:07:37,248 manually kind of map these on grids themselves,  and there's quite a few of them. And then also the   83 00:07:37,248 --> 00:07:42,044 one on the right side here at the bottom is just  mapping how compact. So, as you can see this is   84 00:07:42,044 --> 00:07:47,425 a high compactness and then the low compactness,  that's kind of the measure that I was looking for.   85 00:07:47,425 --> 00:07:55,016 And so, it's really interesting to see, because  if you, if I was able to quantify this, can I also   86 00:07:55,016 --> 00:08:01,647 prove just by looking at the GIS spatial analysis  if there is ice underneath or how the movement   87 00:08:01,647 --> 00:08:07,737 of the surface is reflected in the subsurface  somewhat. So remote sensing and GIS really plays a   88 00:08:07,737 --> 00:08:14,368 big part, especially because we can't really go to  Mars at the moment, not yet on a crewed mission.   89 00:08:14,368 --> 00:08:19,665 So, on Earth were lucky enough to even go to  these places and compare them to another planet. 90 00:08:19,665 --> 00:08:22,210 So, this is just an exaggerated version of   91 00:08:22,210 --> 00:08:26,672 these grids that I was talking about with  you and I just wanted to show a little bit   92 00:08:26,672 --> 00:08:32,762 of the slope difference. So, this is  stone stripes, but that's about it. 93 00:08:32,762 --> 00:08:37,016 But to wrap it all up, I just wanted  to ask everybody in the audience. It's   94 00:08:37,016 --> 00:08:42,271 kind of a brain teaser. So, I mentioned  that we cannot work, we can only really   95 00:08:42,271 --> 00:08:45,900 look at satellite images of Mars right  now because, we do have rovers there,   96 00:08:46,442 --> 00:08:49,737 but they can't really take high  resolution images unless we have a drone. 97 00:08:50,863 --> 00:08:54,450 So, if I were to ask you which planet  was Earth and which one was Mars,   98 00:08:54,450 --> 00:08:58,454 which would you pick? I’ll  give you maybe 10 seconds,   99 00:09:02,041 --> 00:09:05,628 and you can type it in the chat, or you  can just keep amongst yourself it’s fine,   100 00:09:06,837 --> 00:09:11,968 you can type any image, A is  Earth or Mars, B is Earth or Mars. 101 00:09:16,055 --> 00:09:29,318 They're both different planets, I can tell you  that one. Some people, you guys are actually   102 00:09:29,318 --> 00:09:34,532 very good at this, but yeah, so we actually  funnily enough we have a higher resolution   103 00:09:34,532 --> 00:09:38,828 satellite imager on Mars than we  do on Earth, so these are just   104 00:09:39,412 --> 00:09:45,626 gullies on Earth and Mars, and so if you  guessed that correctly, congratulations. 105 00:09:45,626 --> 00:09:47,420 And that's it for me. 106 00:09:47,420 --> 00:09:51,632 If you have any questions it looks answer them and  if I have time, I do have like a one-minute video,   107 00:09:52,300 --> 00:09:57,179 but that's okay. I don't have to show it,  but it's essentially the field work season   108 00:09:57,179 --> 00:10:01,225 if you'd like to see how the data is  collected, what we did, no polar bears though. 109 00:10:01,892 --> 00:10:06,063 I don't know, do I have time, if not, I  can just send put the link in the chat. 110 00:10:06,606 --> 00:10:09,817 -Yeah, put it in the chat Chimara,  that'd be great, okay? That's a great. 111 00:10:09,817 --> 00:10:10,860 -That's a super idea. 112 00:10:10,860 --> 00:10:14,363 Yeah, we're out of time I'm afraid.  So, thank you so much Chimara,   113 00:10:14,363 --> 00:10:18,117 that was really interesting. How  cool is that? Totally amazing. 114 00:10:18,117 --> 00:10:20,119 -No pun intended. 115 00:10:21,245 --> 00:10:28,419 -Very very interesting. Thank you  so much for that. That was great.