October 7, 2018
Fig. 1: Tele-seismic data used in real-event calculation, black denotes observations and red means synthetic values. Fig. 2: Two tsunami source energies were derived: Potential Energy (PE) due to seafloor uplift and Kinetic Energy (KE) due to horizontal seafloor displacement.
October 4, 2018
NASA’s G-III aircraft staged operations from Gainesville, Florida. The UAVSAR pod is located at the bottom of the aircraft’s fuselage. Credits: NASA/Samuel Choi In the aftermath of Hurricane Florence, which struck the Carolinas on Sept. 14 causing widespread damage, NASA quickly deployed a sophisticated airborne radar to give disaster response agencies a much-needed view of floodwaters that continued to threaten the region. In response to the event, the feature, "NASA Airborne Team Surveys Flooding from Hurricane Florence," was published on NASA.gov on October 4, 2018.
October 4, 2018
The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and Caltech in Pasadena, CA created a Damage Proxy Map (DPM) version 0.7 depicting areas in Central Sulawesi, Indonesia, including the city of Palu that are damaged. The damaged areas are depicted as red and yellow pixels. Damage occurred as a result of the magnitude 7.5 earthquake on September 28, 2018. The map is derived from synthetic aperture radar (SAR) images from the ALOS-2 satellite, operated by Japan Aerospace Exploration Agency (JAXA). The map covers an area of 67 by 70 kilometers, shown by the large red polygon. Each pixel measures about 30 meters across. The color variation from yellow to red indicates increasingly significant ground surface change. Preliminary validation was completed through collaboration with the Earth Observatory of Singapore comparing local media information and photos. Damage proxy maps are used as a guide to identify damaged areas; however, the maps may be less reliable over vegetated areas. For example, the scattered single colored pixels over vegetated areas may be false positives, and the lack of colored pixels over vegetated areas does mean that damage has not occurred. The DPM was created by the NASA-JPL / Caltech ARIA team, and the ALOS-2 data was provided by JAXA. The Earth Observatory of Singapore coordinated with the Sentinel Asia to timely task the ALOS-2 satellite. The algorithm development was carried out at JPL under a contract with NASA. For more information about ARIA, visit: http://aria.jpl.nasa.gov
October 3, 2018
This map was created from the Moderate Resolution Imaging Spectroradiometer (MODIS) Near Real-Time Global (NRT) Flood Mapping product. This image shows the 3-day composite flood (new/anomalous) water in red on top of the surface (known/existing) water in yellow. According to several news media outlets, many coastal buildings and streets were already flooded on September 28, 2018, indicating that an initial wave had already hit the coast in Palu, Indonesia. (Source: The New York Times, https://www.nytimes.com/2018/09/28/world/asia/tsunami-palu-indonesia-ear...). The MODIS Near Real-Time (NRT) Global Flood Mapping Project produces global daily surface and flood water maps at approximately 250 m spatial resolution. NASA Land, Atmosphere Near real-time Capability for EOS (LANCE) provides data to the NRT Global MODIS Flood Mapping initiative. This project was developed in collaboration with Bob Brakenridge at the Dartmouth Flood Observatory (DFO): http://floodobservatory.colorado.eduUsing MODIS Near Real-Time Data to Detect Flooding in Indonesia
October 3, 2018
Credit: USGS, Robert Brakenridge (Dartmouth Flood Observatory at the University of Colorado) and Albert Kettner (Dartmouth Flood Observatory at the University of Colorado). This image shows the maximum observed flooding areas using Landsat 8 and Copernicus / ESA Sentinel SAR data for Tropical Storm Florence. Landsat 8 is jointly managed by NASA and the United States Geological Survey (USGS). Copernicus is supported by the European Commission.
October 3, 2018
Ball Aerospace & Technologies Corporation Operational Land Imager (OLI) on the United States Geological Survey and NASA’s Landsat 8 satellite captured a natural-color image of Palu, Indonesia on October 2, 2018. The second image shows the same area before the earthquake and tsunami. The false-color (bands 6-5-2) images make it easier to distinguish between urban areas (purple-gray), vegetation (green), and upturned soil (brown and tan).
September 26, 2018
Landsat 8 colored dissolved organic matter (CDOM) imagery acquired 9/19/18. USGS's Landsat 8 satellite has captured colored dissolved organic matter (CDOM) imagery after Hurricane Florence’s destruction. NASA scientists use this imagery to help inform state and local agencies on water quality post-Hurricane Florence. The image reveals how soils, sediments, decaying leaves, pollution, and other debris have discolored the waters in the swollen rivers, bays, estuaries, and the nearshore ocean. These debris are an important measure of water quality and has important implications for drinking water, aquatic ecosystems and metal transport. CDOM was seen in high concentrations, even in the ocean around North Carolina’s Cape Lookout.
September 26, 2018
Landsat 8 OLI image prior to flooding on 7/14/17. Landsat 8 OLI image after flooding from Hurricane Florence, acquired 9/19/18. USGS's Operational Land Imager (OLI) on the Landsat 8 satellite has captured optical imagery of devastating flooding in the Carolinas from Hurricane Florence. NASA scientiets are using this imagery to help state and local agencies be better informed for recovery. Before and after Hurricane Florence swept through the Carolinas, the OLI on the Landsat 8 satellite observed several residential areas and major rivers. Post-Hurricane Florence images reveal devastating flooding from the Trent River in North Carolina. The Trent River reached an all-time high of 29 feet on September 17, more than twice the flood stage (the height at which the river will overflow and cause damage). Water levels decreased to 24 feet by September 20, but many homes, public buildings, and roads leading to the town of Trenton, NC are full of standing water.
September 25, 2018
The same storm captured by RainCube is seen here in infrared from a single, large weather satellite, NOAA's GOES (Geoweather Operational Environmental Satellite). Image Credit: NOAA The RainCube (Radar in a CubeSat) uses experimental technology to see storms by detecting rain and snow with very small instruments. The people behind the miniature mission celebrated after RainCube sent back its first images of a storm over Mexico in a technology demonstration in August. Its second wave of images in September caught the first rainfall of Hurricane Florence. The small satellite is a prototype for a possible fleet of RainCubes that could one day help monitor severe storms, lead to improving the accuracy of weather forecasts and track climate change over time.
September 24, 2018
This image was taken by TEMPEST-D (Temporal Experiment for Storms and Tropical Systems Demonstration) as it flew over Hurricane Florence on Sept. 11, 2018. The colors reveal the eye of the storm, surrounded by towering, intense rain bands. The green areas highlight the extent of the rain being produced by the storm, with the most intense rain shown in the yellow and red areas. The black and white image underneath is a visual image of the storm's clouds, taken by NOAA's GOES (Geoweather Operational Environmental Satellite). Credits: NASA/NOAA/Naval Research Laboratory Monterey/JPL-Caltech A new experimental weather satellite no bigger than a cereal box got an inside look at Hurricane Florence in a test of technology that could influence the future of storm monitoring from space. The satellite took its first images of Hurricane Florence on Tuesday, Sept. 11, just hours after its instrument was turned on. TEMPEST-D, which deployed into low-Earth orbit from the International Space Station in July, carries a state-of-the-art miniaturized microwave radiometer, an instrument that sees through the thick clouds to reveal the hidden interior of storms, just like a security scanner can see inside luggage at the airport.