1 00:00:02,468 --> 00:00:04,770 [KATE FICKAS]: It's really an amazing little critter 2 00:00:04,770 --> 00:00:08,474 and it's been around for over 3 billion years. 3 00:00:08,507 --> 00:00:13,012 In 2016, Utah Lake exploded in cyanobacteria blooms. 4 00:00:13,012 --> 00:00:18,251 The problem is that many cyanobacteria produce toxins. 5 00:00:18,251 --> 00:00:20,253 [NARRATOR]: You may have heard it called "blue-green algae," 6 00:00:20,253 --> 00:00:22,454 but it's really a kind of bacteria, 7 00:00:22,454 --> 00:00:26,626 taking in sunlight to drive photosynthesis, and giving off oxygen. 8 00:00:26,626 --> 00:00:30,504 [KATE]: It actually requires quite a bit of lab testing 9 00:00:30,504 --> 00:00:33,384 to know whether or not it's a harmful algal bloom. 10 00:00:33,384 --> 00:00:37,244 And what we're really worried about is people and pets 11 00:00:37,244 --> 00:00:40,044 ingesting that cyanobacteria. 12 00:00:40,044 --> 00:00:42,784 [NARRATOR]: Dr. Kate Fickas is a harmful algal blooms scientist 13 00:00:42,784 --> 00:00:44,834 at Utah State University. 14 00:00:44,834 --> 00:00:47,280 She helps the Utah Department of Environmental Quality 15 00:00:47,280 --> 00:00:50,082 track conditions in lakes and reservoirs. 16 00:00:50,082 --> 00:00:53,164 [KATE]: So Utah is the second dryest state in the nation. 17 00:00:53,164 --> 00:00:56,889 Most of our major lakes are actually man-made reservoirs. 18 00:00:56,889 --> 00:00:58,824 They're heavily used for recreation. 19 00:00:58,824 --> 00:01:01,127 They're heavily used for agriculture. 20 00:01:01,127 --> 00:01:04,734 And they're really important to the state, as a resource. 21 00:01:04,897 --> 00:01:08,868 [NARRATOR]: In 2017, harmful algal blooms returned to Utah Lake. 22 00:01:08,868 --> 00:01:13,205 This time, officials used satellite data to identify troubled locations. 23 00:01:13,205 --> 00:01:15,107 But how can instruments up in space 24 00:01:15,107 --> 00:01:18,711 tell us about microscopic organisms in a lake down on Earth? 25 00:01:18,711 --> 00:01:21,314 By measuring their blue-green color. 26 00:01:21,314 --> 00:01:24,617 Landsat collects light in visible and infrared wavelengths. 27 00:01:24,617 --> 00:01:28,287 Cyanobacteria reflect more green light than plain water does, 28 00:01:28,287 --> 00:01:31,524 allowing Landsat to identify algal blooms. 29 00:01:31,524 --> 00:01:35,027 [NIMA PAHLEVAN]: From satellite, what we see is, basically, 30 00:01:35,027 --> 00:01:37,663 that primary pigment, which is chlorophyll-a 31 00:01:37,663 --> 00:01:41,300 but the color, by itself, could be misleading 32 00:01:41,300 --> 00:01:47,673 a nice picture is not necessarily providing a set of quantitative data. 33 00:01:47,740 --> 00:01:50,314 [NARRATOR]: Algal blooms can look beautiful from space 34 00:01:50,509 --> 00:01:53,612 but the numbers behind the images are the important part. 35 00:01:53,612 --> 00:01:57,216 [NIMA]: Each measurement is highly accurate, and it's very, 36 00:01:57,216 --> 00:01:58,918 it's very much corresponding 37 00:01:58,918 --> 00:02:01,987 to the number of photons that are leaving the body of water 38 00:02:01,987 --> 00:02:04,344 which could be related to the biomass 39 00:02:04,344 --> 00:02:06,826 and the amount of phytoplankton 40 00:02:06,826 --> 00:02:09,128 [NARRATOR]: Dr. Nima Pahlevan is working with NASA 41 00:02:09,128 --> 00:02:10,529 and the US Geological Survey 42 00:02:10,529 --> 00:02:13,366 to make sure Landsat users have consistent, accurate, 43 00:02:13,366 --> 00:02:16,502 and ready-to-use data about lakes and rivers. 44 00:02:16,902 --> 00:02:19,004 Water is difficult to study from space, 45 00:02:19,004 --> 00:02:20,673 because only a fraction of the sunlight 46 00:02:20,673 --> 00:02:22,541 is reflected back to the satellite. 47 00:02:22,541 --> 00:02:24,677 But engineering improvements on Landsat 8 48 00:02:24,677 --> 00:02:26,178 have "levelled up" its ability 49 00:02:26,178 --> 00:02:29,415 to measure the small signals from water bodies. 50 00:02:29,949 --> 00:02:31,884 After Landsat collects the data, 51 00:02:31,884 --> 00:02:35,087 it gets beamed down to the USGS EROS center, 52 00:02:35,087 --> 00:02:36,455 where it is archived. 53 00:02:36,455 --> 00:02:40,358 The raw numbers pass through checkpoints to align the geography, 54 00:02:40,593 --> 00:02:42,461 correct for sun strength, 55 00:02:42,461 --> 00:02:45,431 and then compensate for the effects of the atmosphere. 56 00:02:45,598 --> 00:02:51,570 [NIMA]: you're essentially removing the atmospheric scattering and absorption 57 00:02:51,817 --> 00:02:54,173 [NARRATOR]: Let's break down what Nima means here. 58 00:02:54,173 --> 00:02:55,941 To measure the amount of cyanobacteria 59 00:02:55,941 --> 00:02:58,711 you need to know how much light reflected off the surface. 60 00:02:58,711 --> 00:03:01,847 But some of that light gets scattered by molecules in the atmosphere 61 00:03:01,847 --> 00:03:03,649 on the way to the satellite, 62 00:03:03,649 --> 00:03:05,551 lessening the signal received. 63 00:03:05,551 --> 00:03:07,686 And sometimes light that never made it to the surface 64 00:03:07,686 --> 00:03:09,688 gets scattered into the satellite, 65 00:03:09,688 --> 00:03:11,123 adding a false signal. 66 00:03:11,123 --> 00:03:13,574 Like removing the haze from a photograph, 67 00:03:13,574 --> 00:03:16,695 atmospheric corrections leave you with a quantitative measurement 68 00:03:16,695 --> 00:03:19,098 of exactly how much light left the water, 69 00:03:19,098 --> 00:03:21,300 known as aquatic reflectance. 70 00:03:21,300 --> 00:03:23,602 [NIMA]: You would want to look at the actual 71 00:03:23,602 --> 00:03:27,239 physical measurements to derive 72 00:03:27,239 --> 00:03:31,310 physically meaningful products from satellite data. 73 00:03:31,410 --> 00:03:32,711 [NARRATOR]: And that's the goal, 74 00:03:32,711 --> 00:03:35,781 to transform the raw materials into finished products, 75 00:03:35,781 --> 00:03:38,984 so that end users don't have to build it themselves. 76 00:03:38,984 --> 00:03:42,755 [NIMA]: by providing aquatic reflectance products, 77 00:03:42,755 --> 00:03:49,395 you're reducing, majorly reducing the burden on satellite users. 78 00:03:49,695 --> 00:03:51,397 [NARRATOR]: Although it is still provisional, 79 00:03:51,397 --> 00:03:53,299 Nima's Aquatic Reflectance Data Product 80 00:03:53,299 --> 00:03:56,469 is available for download from the USGS. 81 00:03:56,469 --> 00:03:57,870 Scientists like Kate Fickas 82 00:03:57,870 --> 00:04:02,241 convert the data product to maps showing the amount of chlorophyll-a, 83 00:04:02,241 --> 00:04:03,843 helping local officials pinpoint 84 00:04:03,843 --> 00:04:06,846 where to test for toxins and warn residents. 85 00:04:06,846 --> 00:04:09,482 [KATE]: I use Landsat and other remote sensing technology 86 00:04:09,482 --> 00:04:12,051 to help local health departments understand 87 00:04:12,051 --> 00:04:13,419 where there's a bloom, 88 00:04:13,419 --> 00:04:15,221 the magnitude of a bloom 89 00:04:15,221 --> 00:04:17,256 and the size of the bloom. 90 00:04:17,256 --> 00:04:21,404 [NARRATOR]: The spatial detail is another benefit of using Landsat data. 91 00:04:21,404 --> 00:04:25,698 Each pixel is only a 30-meter square, the size of a baseball diamond. 92 00:04:25,698 --> 00:04:28,968 Yet, it collects data across a broad area. 93 00:04:28,968 --> 00:04:32,905 In other words, there is a lot of data at a fairly high resolution. 94 00:04:32,905 --> 00:04:35,174 [KATE]: with Landsat, we can get into some of the marinas 95 00:04:35,174 --> 00:04:37,510 that are popular fishing and swimming spots, 96 00:04:37,510 --> 00:04:39,814 in order to inform local health departments 97 00:04:39,814 --> 00:04:42,248 about making public health decisions 98 00:04:42,681 --> 00:04:46,185 [NARRATOR]: For the 2017 outbreak, that's exactly what happened. 99 00:04:46,185 --> 00:04:49,889 Satellite data gave an early warning to local officials in Utah. 100 00:04:49,889 --> 00:04:51,524 The extra week of warning saved 101 00:04:51,524 --> 00:04:55,294 hundreds of thousands of dollars in health care costs.
 102 00:04:55,895 --> 00:04:58,697 Monitoring algal blooms from aquatic reflectance data 103 00:04:58,697 --> 00:05:02,201 is just one example of benefits from Landsat's data products: 104 00:05:02,668 --> 00:05:03,769 wildfires, 105 00:05:03,769 --> 00:05:04,937 snow cover, 106 00:05:04,937 --> 00:05:06,344 vegetation health, 107 00:05:06,344 --> 00:05:08,807 temperature and more are available, 108 00:05:08,807 --> 00:05:12,144 for every spot on Earth. 109 00:05:13,779 --> 00:05:16,382 Landsat's highly calibrated data products, 110 00:05:16,382 --> 00:05:18,350 free to download and use, 111 00:05:18,350 --> 00:05:22,421 are making detailed Earth-observation data more accessible to users 112 00:05:22,421 --> 00:05:25,090 and bringing a greater benefit to society. 113 00:05:25,261 --> 00:05:26,559 [NASA and USGS logos] 114 00:05:26,559 --> 00:05:30,262 Landsat is a joint program of NASA and USGS