1 00:00:00,000 --> 00:00:04,560 all right hi everyone my name is Gigi Pavur and I'm an undergraduate senior 2 00:00:04,560 --> 00:00:09,300 at Georgia Tech majoring in Earth that Atmospheric Sciences I'm so excited to 3 00:00:09,300 --> 00:00:13,019 be here today with you all at AGU to tell you about a project I did this 4 00:00:13,020 --> 00:00:17,609 summer through NASA DEVELOP, so NASA DEVELOP is a program within the Applied 5 00:00:17,609 --> 00:00:22,940 Sciences program at NASA which is designed to increase participants like 6 00:00:22,949 --> 00:00:27,150 me. Our capacity to use NASA earth observations so we do 10-week 7 00:00:27,150 --> 00:00:32,460 feasibility projects, so with the help of my teammates Chelsey Dandridge, Robyn Kim 8 00:00:32,460 --> 00:00:37,680 and Sarah Aldama, um, we were able to use NASA earth observations to improve 9 00:00:37,680 --> 00:00:41,340 landslides situational awareness in the Dominican Republic 10 00:00:49,960 --> 00:00:52,880 okay so imagine that 11 00:00:52,890 --> 00:00:56,460 we are three thousand three hundred and eighty nine miles away from where you're 12 00:00:56,460 --> 00:01:01,170 sitting right now at AGU you'll find a small country on the island of 13 00:01:01,170 --> 00:01:06,299 Hispaniola and the Caribbean Sea the Dominican Republic so with its location 14 00:01:06,299 --> 00:01:11,280 in the hurricane belt of the tropics the Dominican Republic is frequently exposed 15 00:01:11,280 --> 00:01:15,030 to very heavy rainfall events which can trigger landslides 16 00:01:15,030 --> 00:01:19,950 so my DEVELOP team partnered with a geological service in the Dominican 17 00:01:19,950 --> 00:01:24,270 Republic to help improve their situational awareness of landslides and 18 00:01:24,270 --> 00:01:27,960 our project partners were really interested in understanding how to limit 19 00:01:27,960 --> 00:01:32,369 the loss of life and protect infrastructure for landslides and then 20 00:01:32,369 --> 00:01:36,450 also our project supported an international agreement between the NASA 21 00:01:36,450 --> 00:01:42,210 earth science division and the Central American integration system and that 22 00:01:42,210 --> 00:01:46,439 agreement was designed to increase collaborations between NASA and Central 23 00:01:46,439 --> 00:01:50,340 American countries, so I was really exciting to get to work on a project of 24 00:01:50,340 --> 00:01:55,259 this international scale and calibre and then also I'd like to point out that I 25 00:01:55,259 --> 00:02:03,210 too went bananas when I saw that fruit also has landslide risk so NASA has 26 00:02:03,210 --> 00:02:07,619 about 30 satellites that are constantly orbiting Earth and collecting 27 00:02:07,619 --> 00:02:11,250 environmental data and this data is really useful to study environmental 28 00:02:11,250 --> 00:02:15,730 challenges like landslides so for a project we use two earth 29 00:02:15,730 --> 00:02:20,620 observations the first was from the shuttle radar topography mission or SRTM 30 00:02:20,620 --> 00:02:26,650 which provides elevation data and we use that to determine slope and then we also 31 00:02:26,650 --> 00:02:30,880 used global precipitation measurement from GPM which is the satellite right 32 00:02:30,880 --> 00:02:32,220 here 33 00:02:33,860 --> 00:02:39,060 okay so landslide experts at Goddard Research Center at Space Flight Research 34 00:02:39,080 --> 00:02:44,340 Center created a model called LHASA and yes you guessed it LHASA is another 35 00:02:44,340 --> 00:02:48,610 NASA acronym so it stands for a Landslide Hazard Assessment for 36 00:02:48,610 --> 00:02:53,769 Situational Awareness so this model is publicly available online through github 37 00:02:53,769 --> 00:03:00,579 as both a Python script and an R script so my team worked to use this model and 38 00:03:00,579 --> 00:03:04,630 take it from a global scale and cater it specifically for the Dominican 39 00:03:04,630 --> 00:03:08,590 Republic and we did this by incorporating local data from our 40 00:03:08,590 --> 00:03:10,340 project partners 41 00:03:12,960 --> 00:03:16,500 so a really important component of the LHASA model is a 42 00:03:16,500 --> 00:03:21,660 susceptibility map so this shows the landslide susceptibility in the 43 00:03:21,670 --> 00:03:27,340 Dominican Republic and my team created this by using a fuzzy overlay model to 44 00:03:27,340 --> 00:03:32,519 determine the correlations between landslide factors like elevation slope 45 00:03:32,519 --> 00:03:36,519 distance to active fault lines clay percentage lithology 46 00:03:36,519 --> 00:03:42,700 and forest covered loss and so when the static map is combined in LHASA with 47 00:03:42,700 --> 00:03:52,720 precipitation measurements it will output near real-time nowcast so when 48 00:03:52,720 --> 00:03:57,819 the rainfall the historical rainfall exceeds the 95th percentile it will 49 00:03:57,819 --> 00:04:01,569 issue a high hazard nowcast if your susceptibility map says it's a 50 00:04:01,569 --> 00:04:08,049 very susceptible region to landslides so since GPM rainfall data is available 51 00:04:08,049 --> 00:04:12,220 every 30 minutes you could realistically make new outputs for this every half 52 00:04:12,220 --> 00:04:21,099 hour so you might be wondering landslides are a natural process for 53 00:04:21,099 --> 00:04:25,000 altering topography so why are they considered a natural disaster what makes 54 00:04:25,000 --> 00:04:28,220 them a natural disaster and what I learned through this project 55 00:04:28,220 --> 00:04:32,720 is that it really becomes a natural disaster when it affects people so once 56 00:04:32,720 --> 00:04:35,990 again our project partners were really interested in knowing where landslides 57 00:04:35,990 --> 00:04:40,640 impact people so we created this bivariate map on which depicts the 58 00:04:40,640 --> 00:04:48,080 intersection of landslide susceptibility and and population so the regions but 59 00:04:48,080 --> 00:04:53,840 you want to pay attention to are this deep red color up there which represent 60 00:04:53,840 --> 00:04:57,680 high population and high landslide susceptibility and now fortunately 61 00:04:57,680 --> 00:05:00,920 you'll see there aren't actually that many pixels of that color which is a 62 00:05:00,920 --> 00:05:07,130 good thing and then you can see as well but Santiago and Santo Domingo and then 63 00:05:07,130 --> 00:05:10,880 Bayer hona all have high populations because those are their main cities but 64 00:05:10,880 --> 00:05:15,980 they aren't located in susceptible regions the central area has very high 65 00:05:15,980 --> 00:05:19,280 landslide susceptibility but not a lot of people living there because it's 66 00:05:19,280 --> 00:05:24,560 actually a national park so the idea is that this bivariant map can be used fore 67 00:05:24,560 --> 00:05:29,300 quick heuristic identifications of regions on where people are at risk 68 00:05:32,620 --> 00:05:37,600 all right then lastly a big final outcome of our project was we wanted to increase 69 00:05:37,620 --> 00:05:42,440 our project partners capacity to actually use NASA the earth observations 70 00:05:42,440 --> 00:05:46,280 so we wrote a tutorial so that they could do everything that we did over the 71 00:05:46,280 --> 00:05:52,640 summer and one thing that we also showed them was how mapping landslides from 72 00:05:52,640 --> 00:05:57,080 space can help them better understand where landslides occur even if they 73 00:05:57,080 --> 00:06:01,940 don't have the budget necessarily to do ground mapping or like field research so 74 00:06:01,940 --> 00:06:07,220 the three images on the right wait left so an interesting story about a 75 00:06:07,220 --> 00:06:11,270 landslide that happened so we have a forest with the road going through it in 76 00:06:11,270 --> 00:06:18,950 2012 and then by 2014 wait 2016 all the trees are gone and then by 2018 we have 77 00:06:18,950 --> 00:06:23,420 evidence of a landslide so once again our project partners can use this to go 78 00:06:23,420 --> 00:06:27,350 back and improve their historical landslide inventory and then our 79 00:06:27,350 --> 00:06:29,780 tutorial also went through how to use LHASA 80 00:06:29,780 --> 00:06:34,520 and how to make their own susceptibility map and then lastly it was translated 81 00:06:34,520 --> 00:06:38,419 into Spanish and shared with other Central American countries so that they 82 00:06:38,420 --> 00:06:42,840 can hopefully use this as a start point to use LHASA in their country 83 00:06:45,420 --> 00:06:46,760 okay 84 00:06:47,840 --> 00:06:54,580 ,um so I'd like to end with a quote that was in the NASA calendar last year which 85 00:06:54,590 --> 00:06:58,720 judging from the line over there I'm sure you guys are all familiar with it 86 00:06:58,720 --> 00:07:03,350 but the quote I think it perfectly captures the value of applying NASA 87 00:07:03,350 --> 00:07:07,370 earth observations to combat environmental challenges so the quote is 88 00:07:07,370 --> 00:07:12,400 from Nelson Mandela and it says action without vision is only passing time 89 00:07:12,400 --> 00:07:17,600 vision with action is merely daydreaming but vision with action can change the 90 00:07:17,600 --> 00:07:20,300 world so quite literally earth observations 91 00:07:20,300 --> 00:07:24,320 give us the perspective and vision we need to take action and according to 92 00:07:24,320 --> 00:07:28,370 Nelson Mandela that's how we change the world so here we can see the night 93 00:07:28,370 --> 00:07:33,050 lights of Earth and we know that from this perspective of space. Disasters 94 00:07:33,050 --> 00:07:37,760 don't they aren't confined by country borders and from my DEVELOP project this 95 00:07:37,760 --> 00:07:42,080 summer I learned that the applications of earth observations can also transcend 96 00:07:42,080 --> 00:07:51,560 these boundaries so lastly thank you to the moon and back to all the people who 97 00:07:51,560 --> 00:07:56,180 helped me do this project including our project partners in the Dominican 98 00:07:56,180 --> 00:07:59,210 Republic our science advisors Dr. Ross and Dr. 99 00:07:59,210 --> 00:08:04,220 Dalia Kirschbaum and then of course to my wonderful team Sarah and Robin and 100 00:08:04,220 --> 00:08:08,630 Chelsea they put up with a lot of landslides jokes for me which as you 101 00:08:08,630 --> 00:08:12,850 know is a very slippery slope thank you