WEBVTT FILE 1 00:00:00.000 --> 00:00:02.770 Deadly landslides can happen in the space of minutes, 2 00:00:02.790 --> 00:00:06.310 but factors that cause landslides can be detected ahead of time 3 00:00:06.330 --> 00:00:08.410 and from space. 4 00:00:08.430 --> 00:00:11.560 With satellites, NASA scientists have developed a new model 5 00:00:11.580 --> 00:00:17.670 to estimate where and when landslides may strike around the world using real-time information. 6 00:00:17.690 --> 00:00:21.940 The model, known as Landslide Hazard Assessment for Situational Awareness, 7 00:00:21.960 --> 00:00:26.840 estimates which regions have a moderate or high chance of landslides every 30 minutes. 8 00:00:26.860 --> 00:00:30.920 For the first time, potential landslide activity can be seen globally. 9 00:00:30.940 --> 00:00:34.580 These regions are identified by several factors. 10 00:00:34.600 --> 00:00:39.100 First, the model uses the Global Precipitation Measurement Mission to track rainfall 11 00:00:39.120 --> 00:00:43.000 - the most widespread and frequent trigger of landslides worldwide. 12 00:00:43.020 --> 00:00:46.330 Then the model evaluates which areas with high rainfall 13 00:00:46.350 --> 00:00:49.860 are also prone to landslides using a susceptibility map. 14 00:00:49.880 --> 00:00:53.370 The regions highlighted in this map may have a combination of 15 00:00:53.390 --> 00:00:57.230 steep slopes, deforestation, a weak bedrock, road construction 16 00:00:57.250 --> 00:00:59.680 or are near Earthquake fault zones 17 00:00:59.700 --> 00:01:03.530 - factors that make land more prone to landslides in heavy rains. 18 00:01:03.550 --> 00:01:06.250 Scientists ran the model looking back 15 years 19 00:01:06.270 --> 00:01:11.120 to determine when and where potential landslide activity tends to happen around the world, 20 00:01:11.140 --> 00:01:14.750 or in essence when landslide season exists in different regions. 21 00:01:14.770 --> 00:01:18.760 When this model is compared to NASA’s database of landslide reports 22 00:01:18.780 --> 00:01:20.740 dating back to 2007, 23 00:01:20.760 --> 00:01:23.370 similar patterns emerge. 24 00:01:23.390 --> 00:01:28.530 For example, potential landslide activity peaks from February to April in Peru. 25 00:01:28.550 --> 00:01:33.340 Whereas in Taiwan the peak occurs in May and June. 26 00:01:33.360 --> 00:01:36.280 But not every landslide is seen or reported. 27 00:01:36.300 --> 00:01:43.110 The model also reveals landslide-prone regions that currently don’t have any reported fatalities in the database. 28 00:01:43.130 --> 00:01:46.650 Scientists will use the NASA model in combination with landslide reports 29 00:01:46.670 --> 00:01:50.490 to improve our understanding of where and when landslides may occur. 30 00:01:50.510 --> 00:01:55.940 Creating a global picture on this pervasive hazard will not only help vulnerable populations, 31 00:01:55.960 --> 00:02:00.540 but better inform disaster response and mitigation. 32 00:02:00.560 --> 00:02:07.641