RS / GIS for Disaster Management. Some Important Definitions. Classifications of Natural Disasters. Disasters W/Some Human Influence

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1 RS / GIS for Disaster Management A Basic Introduction to Natural Disasters Using Remote Sensing & GIS ~~~~~~~~~~ Rev. Ronald J. Wasowski, C.S.C. Associate Professor of Environmental Science University of Portland Portland, Oregon 1 December 2015 The problem Eight-fold increase in losses over 4 decades Population growth, urbanization, encroachment One approach Before Establish baseline data During During-event monitoring & assessment After Geographic & structural extent of damage Some Important Definitions Natural disaster Nature Extreme events in Earth s system Lithosphere, hydrosphere, atmosphere, biosphere Rate How fast disasters occur Rapid Earthquakes, tsunamis, eruptions Slow Some landslides, drought Natural hazard Potentially damaging phenomenon Setting San Francisco Yucca Mountain Variations Related to Plate Tectonics Classifications of Natural Disasters Purely natural disasters Earthquakes, eruptions, hurricanes Human- made disasters Oil spills, industrial accidents, wars Human- induced disasters Urban landslides, living on volcano flanks Human- aggravated disasters Climate change Purely Natural Disasters Disasters W/Some Human Influence Earthquakes Tsunamis Volcanic eruptions Avalanches Glacial outbursts Thunderstorms Hail storms Straight-line winds Tornadoes Hurricanes Asteroid impacts Aurora borealis Floods Reduced surface permeability Pavement, building footprints Increased channel speed Storm sewers Dust storms Poor farming practices Poor construction practices Droughts Human-induced climate change

2 Mixed Natural / Human Influence Landslides Subsidence Dolines & mine sinkholes Erosion Coastal & inland Desertification Coal fires Global warming Sea-level rise Disasters W/Some Natural Influence Crop diseases Monoculture Insect infestation Wildfires Mangrove swamp decline Coral reef decline Acid deposition Rain, fog & solid Ozone depletion Purely Human Disasters Armed conflicts Landmines Major transportation accidents Air, rail & multi-vehicle Nuclear & chemical accidents Oil spills Pollution Surface water, ground water, soil & air Electric power grid failures Losses From Disasters Dollars Lives Earthquakes 35% 48% Floods 29% 8% Wind 29% 44% Others 7% U.S. Natural Disasters: Scale Issues In Disaster Management Continental scale > 1:1,000,000 Hazard-free & hazard-prone regions Regional scale > 1: 100,000 Land-use guidance Medium scale > 1: 25,000 Large engineering structures Local scale > 1: 5,000 Municipal planning

3 RS / GIS for Flood Assessment Terrain mapping Old New DTMs Topographic maps LiDaR & radar maps Historic flood mapping Historic & new imagery + field verification Flood susceptibility mapping Derivative maps from DTMs Predictive mapping Geomorphology, hydrology, land use 2005 Northern Pakistan Earthquake RS-GIS for Earthquake Assessment Scale issues Large scale Seismic macro zonation Scales ranging from 1:5,000,000 to 1:50,000 Small scale Seismic micro zonation Scales ranging from 1: 50,000 to 1:10,000 Platform issues Satellites Both small & large scale imagery > 40 cm GRC Aircraft Large scale imagery > 1 cm GRC Bands for Earthquake Assessment Visible Visual & digital identification of all lineaments Digital edge detection algorithms Reflected infrared Vegetation anomalies Water availability along fault lines Thermal infrared Thermal anomalies Radar Identify lineaments ~ to look direction RS / GIS for Volcanic Assessment Before eruptions Baseline vegetation & structural data Mount St. Helens During eruptions Visible & CIR Surface flows, ash plumes Thermal IR Active lava channels After eruptions Damage assessment Rescue & recovery Mount St. Helens: Post-Eruption

4 RS / GIS for Landslide Assessment Scale issues Large scale Regions prone to landslides Individual large landslides Many small landslides Small scale Local areas prone to landslides Monitoring of well-known landslides, road cuts Sensor issues Satellite Generally small scale imagery Aerial Desirability of stereo capability Three-dimensional viewing of landslides Methods for Landslide Assessment Landslide inventory Heuristic Experience & skill of the user Statistical hazard analysis Multi-factor analysis using GIS Landslide susceptibility Information value method Weights-of-evidence GIS modeling Bayesian GIS analyses Dempster-Shafer GIS analyses Fuzzy logic GIS analyses RS / GIS for Fire Assessment Baja Wildfire: 18 November 2005 Monitor the major contributing factors Fuel Vegetation type, biomass, water, stress Topography Slope, aspect, run length Weather Wind speed & direction, temperature, humidity Types of datasets Static Baseline & trend line datasets Dynamic Rapidly changing phenomena May 2000 Cook Ranch TX Fire Scar August 2004 Record U.S. Crops

5 Ukraine 2005 Stressed Crops Mine Fires Sensor issues Visible & CIR Smoke & vapor plumes Thermal infrared Thermal anomalies Low-temperature TIR band Platforms Aircraft Landsat TM & ETM+ TIR bands NOAA-AVHRR ERS1-ATSR RESURS-01 RS / GIS for Tornado Assessment Oklahoma City Tornado Path Before tornadic activity Baseline data Satellite & aerial imagery During tornadic activity Doppler radar After tornadic activity Visible & CIR Thermal infrared Damage assessment Rescue & recovery Northern Chandeleur Islands, LA Pre-Katrina Post-Katrina Wilma Colors the Caribbean: 2005

6 Coast of Namibia: 9 August 2005 Phytoplankton W. African Dust Storm: 4 Sep Hydrogen Sulfide Yellow Sea Dust Storm: 6 Nov Alaskan Dust Storm: 5 Nov Alaskan Dust Storm Detail Alaska Glacial Dust (30 Oct. 2009)

7 Iceberg Breaks: 4 November Arctic Sea Ice Minimum October 2007 S. California Fires Aral Sea Dust Storm Banda Aceh Tsunami Effects Wet Wadi (2007/09/19)

8 Dry Wadi (2009/09/18) China Haze (28 October 2009) Gulf of Mexico: 10 November 2009 Sivash, Ukraine Mineral Lakes Phytoplankton Bloom: 24 June 2010 Gulf Oil Slick: 26 June

9 NW Pakistan Landslide: 2 May