1 00:00:07,173 --> 00:00:12,278 This is a site that's a kilometer long and half a kilometer wide, 2 00:00:12,512 --> 00:00:15,415 and it was constructed on a coral reef flat, 3 00:00:15,415 --> 00:00:18,852 and it has a 100 really complex 4 00:00:19,119 --> 00:00:23,390 stone structures made of basalt, something called columnar basalt. 5 00:00:24,190 --> 00:00:27,961 The whole island, including the site, is just is covered 6 00:00:27,961 --> 00:00:33,633 with some of the densest vegetation on Earth actually. 7 00:00:33,633 --> 00:00:35,635 It's one of the wettest places on Earth. 8 00:00:36,336 --> 00:00:39,305 There's a really great variety of vegetation. 9 00:00:39,305 --> 00:00:42,575 There are vines there that grow a few feet every day. 10 00:00:43,777 --> 00:00:46,079 We just couldn't believe the complexity 11 00:00:46,079 --> 00:00:49,549 of what we were seeing, and nobody knew it was there 12 00:00:50,216 --> 00:00:53,386 because the dynasty that built Nan 13 00:00:53,386 --> 00:01:00,493 Madol collapsed 4 or 500 years ago, and without constant 14 00:01:00,493 --> 00:01:03,496 maintenance of vegetative clearance, 15 00:01:03,930 --> 00:01:06,399 the vegetation just covered everything. 16 00:01:07,534 --> 00:01:10,503 We got a NASA grant 17 00:01:10,503 --> 00:01:15,608 to utilize airborne lidar to scan the rest of the island, 18 00:01:15,608 --> 00:01:20,580 which is probably 100 times larger than just Nan Madol 19 00:01:20,580 --> 00:01:23,283 and the close environs that we did before. 20 00:01:23,283 --> 00:01:26,886 And then we found that the whole island was covered 21 00:01:26,886 --> 00:01:29,589 was the landscape that radically transformed. 22 00:01:29,589 --> 00:01:31,991 And again, nobody, nobody knew. 23 00:01:32,525 --> 00:01:35,528 This is not going to be feasible in many places on Earth. 24 00:01:35,695 --> 00:01:39,232 So what about--what about satellite lidar? 25 00:01:39,599 --> 00:01:43,570 The ICESat-2 data, you know, if you if you analyze the data properly, 26 00:01:44,037 --> 00:01:49,476 it's really giving you this very precise elevations for water, for sea level. 27 00:01:49,809 --> 00:01:51,177 We're looking into using 28 00:01:51,177 --> 00:01:53,213 ICESat-2 for that shallow water bathymetry 29 00:01:53,213 --> 00:01:55,448 because a lot of the, you know, the coastal environment on Pohnpei 30 00:01:55,448 --> 00:01:56,449 is really interesting to us. 31 00:01:56,449 --> 00:01:59,519 In areas where the vegetation isn't so bad, 32 00:01:59,752 --> 00:02:01,621 I think there's a lot of promise, 33 00:02:01,621 --> 00:02:04,224 especially for like monitoring archaeological-- 34 00:02:04,224 --> 00:02:07,594 like the the state of not just archeological sites, but other things. 35 00:02:07,594 --> 00:02:11,297 Just like monitoring the kind of the structural integrity of stuff. 36 00:02:11,698 --> 00:02:12,665 For example, we just like 37 00:02:12,665 --> 00:02:16,169 tested out in the Sacred Valley of Peru, where is another place where we work. 38 00:02:16,636 --> 00:02:19,606 You can see some of these terraces that, you know, people are still using. 39 00:02:19,606 --> 00:02:20,807 I mean, it shows up beautifully 40 00:02:20,807 --> 00:02:24,244 in these ICESat-2 transects because they don't have vegetation on them. 41 00:02:24,978 --> 00:02:27,881 The application of this 42 00:02:27,881 --> 00:02:30,884 ICESat-2 data to monitoring 43 00:02:30,884 --> 00:02:35,255 sea level at some of these islands. People know that sea level rise 44 00:02:35,255 --> 00:02:39,125 is going to endanger these islands. 45 00:02:39,559 --> 00:02:42,162 And I'm thinking about the human impact. 46 00:02:42,162 --> 00:02:47,100 I'm also thinking about the cultural impact of losing that culture diversity. 47 00:02:47,433 --> 00:02:50,436 You have thousands of these islands that are occupied by these 48 00:02:50,470 --> 00:02:55,642 very different groups, and each of them has developed a really interesting 49 00:02:55,642 --> 00:02:59,212 and special culture, and if we lose that, what are we actually losing? 50 00:02:59,512 --> 00:03:00,313 Think about that. 51 00:04:39,646 --> 00:04:43,249 And I'm thinking about the human impact. 52 00:04:43,249 --> 00:04:46,252 I'm also thinking about the cultural impact of losing 53 00:04:46,686 --> 00:04:49,622 that culture diversity. 54 00:04:49,622 --> 00:04:51,190 That's probably 55 00:04:51,190 --> 00:04:54,193 not like any other place on Earth. 56 00:04:57,397 --> 00:05:00,300 it can also get, as we found out when we were working 57 00:05:00,300 --> 00:05:05,038 with the data in Peru, if there's not much vegetation, we can get 58 00:05:05,638 --> 00:05:10,176 very nice elevations from land as well from, you know, terrestrial, 59 00:05:10,410 --> 00:05:14,747 you know, from the land surface itself. 60 00:05:16,182 --> 00:05:20,086 I mean, this would be, I think, worth a program. 61 00:05:20,219 --> 00:05:23,122 I'm just suggesting this for, I said to just 62 00:05:23,122 --> 00:05:26,192 maybe get some serious thought to deploy. 63 00:05:26,225 --> 00:05:30,063 And I said to over a handful or select, 64 00:05:30,296 --> 00:05:34,200 randomly selected or carefully selected, collection 65 00:05:34,200 --> 00:05:37,203 of of islands in the Marshalls and, 66 00:05:46,979 --> 00:05:49,682 it's because it was the opportunity 67 00:05:49,682 --> 00:05:52,685 to communicate with other users 68 00:05:53,353 --> 00:05:57,390 where we are struggling with these applications. 69 00:05:57,390 --> 00:06:03,463 And of course, being part of a network of applied users increases the probability 70 00:06:03,463 --> 00:06:07,200 that we're going to be able to answer some of the questions 71 00:06:07,200 --> 00:06:10,570 that we'd like to answer with these data, because somebody else has done, done 72 00:06:11,070 --> 00:06:14,474 already done it, or they've done something similar, or 73 00:06:15,041 --> 00:06:17,543 by having conversations with them, 74 00:06:17,543 --> 00:06:20,713 we can come up with a a new approach that we haven't thought of yet. 75 00:06:20,713 --> 00:06:25,284 I think it's, you know, I mean, the idea that people come up with 76 00:06:25,885 --> 00:06:29,422 scientific breakthroughs all on their own, you know, is genius often. 77 00:06:29,422 --> 00:06:32,058 And that's, that's not the way science works. 78 00:06:32,058 --> 00:06:34,627 It really it's a it's a community effort. 79 00:06:34,627 --> 00:06:36,195 It's always a team effort. 80 00:06:36,195 --> 00:06:39,198 And, you know, when you're talking with people, 81 00:06:39,699 --> 00:06:42,402 you come up with these ideas that I don't think one 82 00:08:25,071 --> 00:08:25,338 And it 83 00:08:25,338 --> 00:08:28,341 could even give us something of the symmetry. 84 00:08:28,407 --> 00:08:31,711 So that's going to be very, very important going forward 85 00:08:31,711 --> 00:08:36,382 because we're going to take that data and we're going to take it to data 86 00:08:36,382 --> 00:08:39,418 that are recorded by a buoy there. 87 00:08:39,952 --> 00:08:44,757 And we're going to see, you know, how how the water 88 00:08:44,757 --> 00:08:48,694 elevations vary at different sides of, of the island. 89 00:08:49,529 --> 00:08:53,132 we think that this is a real strong possibility and that there's 90 00:08:53,132 --> 00:08:58,671 a really big need for this because of, you know, rising sea levels. 91 00:08:59,272 --> 00:09:03,276 We'd like to be able to track that, And he was the one I think he 92 00:09:03,342 --> 00:09:06,712 that he's like quoted as I can remember I read this. 93 00:09:06,712 --> 00:09:09,916 But anyway Adrian was the one who like, 94 00:09:09,916 --> 00:09:12,985 you know, he's interviewed somewhere and he's like, oh, you know, we we 95 00:09:13,953 --> 00:09:16,656 we found out that like sort of after the fact, after, 96 00:09:16,656 --> 00:09:19,759 after the engine was already operational, all that you can get the there's 97 00:09:19,759 --> 00:09:23,729 some penetration, there's some water penetration, there's ice at two photons. 98 00:09:23,729 --> 00:09:25,898 So you can get like shallow water bathymetry. 99 00:09:25,898 --> 00:09:28,234 There are all kinds of things that you can do. 100 00:09:28,234 --> 00:09:31,170 I mean, for the world in 101 00:09:31,170 --> 00:09:34,974 so the places where we're working with, with lidar 102 00:09:35,641 --> 00:09:38,311 are actually really difficult places to work with lidar, 103 00:09:38,311 --> 00:09:42,715 that's something that we didn't even I didn't really fully grasp, you know, 104 00:09:42,715 --> 00:09:46,552 until really getting into it, 105 00:09:46,552 --> 00:09:50,156 the, the vegetation on Pohnpei, as my father has mentioned, is really thick. 106 00:09:50,156 --> 00:09:50,890 It's not you know, 107 00:09:50,890 --> 00:09:53,159 there are a lot of places in the world where vegetation is thick. 108 00:09:53,159 --> 00:09:54,860 You know, people deal with it in Central America 109 00:09:54,860 --> 00:09:57,863 all the time, for instance, in the archeological world. 110 00:09:57,863 --> 00:10:02,268 But I think it's increasingly clear that Pompei is like really, really hard. 111 00:10:02,268 --> 00:10:05,538 The vegetation is really thinking that low vegetation too, which makes it okay. 112 00:10:11,611 --> 00:10:14,914 again, our products and services, sometimes it's research, 113 00:10:14,914 --> 00:10:19,452 sometimes it's purely research, sometimes it's finding archeological sites. 114 00:10:20,052 --> 00:10:24,323 Sometimes it's tracking environmental changes 115 00:10:24,323 --> 00:10:26,759 that are going to impact those archeological sites. 116 00:10:26,759 --> 00:10:31,764 Sometimes it's interpreting the relationship between, 117 00:10:32,264 --> 00:10:35,301 the archeological sites and how they were formed 118 00:10:35,301 --> 00:10:39,138 and why they were formed and how there's this dialectic that happens. 119 00:10:39,305 --> 00:10:40,172 Okay. 120 00:10:40,172 --> 00:10:43,709 I mean, you take a snapshot of an archeological site. 121 00:10:43,709 --> 00:10:44,844 That's that's, that