Research and Applications using Realtime Direct Broadcast Imagery, Weather Radar, and LiDAR in Disaster Response and Preparedness

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1 Research and Applications using Realtime Direct Broadcast Imagery, Weather Radar, and LiDAR in Disaster Response and Preparedness Richard P. Watson, Ph.D. University of New Mexico Earth Data Analysis Center (EDAC) & Center for Rapid Environmental Assessment and Terrain Evaluation (CREATE) Workshop on Application of Remote Sensing Technologies for Disaster Response Sept. 12, Irvine, CA

2 Basic R/S Data Needs for Disaster Response Spatial/Spectral resolution sufficient to identify features of interest Temporal resolution sufficient to provide timely data both before and following the disaster

3 Space & Time in Disaster Response What are the features that need to be identified and characterized? Buildings, Bridges, Utility Infrastructure, etc. What aspects of these features need to be assessed? What spatial/spectral resolution is needed to: Identify features Characterize features What temporal frequency is needed for feature assessment? Answers to these questions should be driven by the product needs of the disaster management & response teams.

4 Direct Broadcast Satellites as a Source of High Temporal Frequency Imagery Center for Rapid Environmental Assessment and Terrain Evaluation (CREATE)

5 CREATE: Purpose Acquire and process real-time and near realtime remotely sensed data from environmental satellites and ground-based sensors. Integration of sensor data with environmental models for decision support. Web-based delivery of data and analytic products to end users.

6 CREATE: Implementation Satellite Ground Station for NASA and Commercial Satellites. Algorithm and Product Development for Scientific Research and End User Applications. Integration of Science-Based Models and Products in Support of Environmental Policy Development and Implementation.

7 Mississippi River Delta and Gulf Coast Bands 1, 4, 3 Terra/Aqua DB - MODIS MODerate resolution Imaging Spectrometer

Primary Use Band GSD (m) Bandwidth 1 Spectral Radiance 2 Required SNR 3 Land/Cloud Boundaries 1 250 620-670 21.8 128 2 841-876 24.7 201 Land/Cloud Properties 3 500 459-479 35.3 243 4 545-565 29.

8 Primary Use Band GSD (m) Bandwidth 1 Spectral Radiance 2 Required SNR 3 Land/Cloud Boundaries Land/Cloud Properties Ocean Color Phytoplankton Biogeochemistry Atmospheric Water Vapor Primary Use Band GSD (m) Bandwidth 1 Spectral Radiance 2 Required NE T(K) 4 Surface/Cloud Temperature Atmospheric Temperature Cirrus Clouds Water Vapor Ozone Surface/Cloud Temperature Cloud Top Altitude MODIS Bands - Primary Uses 1 Bands 1 to 19 are in nm; Bands 20 to 36 are in µm 2 Spectral Radiance values are (W/m2 -µm-sr) 3 SNR = Signal-to-noise ratio 4 NE T = Noise-equivalent temperature difference Note: Performance goal is 30-40% better than required. Table last revised Apr. 27, 1998.

9 42 MODIS Products Level 1 4 MOD 01 - Level-1A Radiance Counts MOD 02 - Level-1B Calibrated, Geolocated Radiances MOD 03 - Geolocation Data Set MOD 04 - Aerosol Product MOD 05 - Total Precipitable Water MOD 06 - Cloud Product MOD 07 - Atmospheric Profiles MOD 08 - Gridded Atmospheric Product MOD 09 - Surface Reflectance; Atmospheric Correction Algorithm Products (a/k/a Spectral Reflectance) MOD 10 - Snow Cover MOD 11 - Land Surface Temperatures (LST) and Emissivity MOD 12 - Land Cover/Land Cover Change MOD 13 - Vegetation Indices: The Normalized Difference Vegetation Index (NDVI) and an Enhanced, Modified Vegetation Index (MVI) MOD 14 - Thermal Anomalies - Fires MOD 15 - Leaf Area Index (LAI) & Fraction of Photosynthetically Active Radiation (FPAR) MOD 16 - Evapotranspiration MOD 17 - Vegetation Production and Net Primary Productivity (NPP) MOD 18 - Normalized Water-Leaving Radiance MOD 19 - Pigment Concentration MOD 20 - Chlorophyll Fluorescence MOD 21 - Chlorophyll-a Pigment Concentration MOD 22 - PAR (Photosynthetically Active Radiation) MOD 23 - Suspended-Solids Concentration MOD 24 - Organic Matter Concentration MOD 25 - Coccolith Concentration MOD 26 - Ocean Water Attenuation Coefficient MOD 27 - Ocean Primary Productivity MOD 28 - Sea Surface Temperature (SST) MOD 29 - Sea Ice Cover MOD 31 - Phycoerythrin Concentration MOD 32 - Processing Framework and Match-up Database MOD 33 - Snow Cover MOD 34 - Gridded Vegetation Indices: The Maximum Value Composited NDVI and the BRDF-Adjusted MOD 35 - Cloud Mask MOD 36 - Total Absorption Coefficient MOD 37 - Ocean Aerosol Properties MOD 39 - Clear-Water Epsilon MOD 40 - Gridded Thermal Anomalies (Burn Scars) MOD 42 - Sea Ice Cover MOD 43 - Surface Reflectance, BRDF/Albedo Parameter MOD 44 - Vegetation Cover Conversion MODISALB - Snow and Sea Ice Albedo

10 Terra & Aqua Satellites Orbit 705 km sun-synchronous, polar 98.2 deg inclination 10:30 am ± 15 minutes descending node (AM-1) or 13:30 ascending node (PM-1) period = 100 min. 16 orbits / day 233 orbit repeat cycle (approx 2 wk) Launched 12/1999 & 5/2002 Design Life: 6 years

11 Terra Satellite X-band Downlink Data format: CCSDS (Consultative Committee for Space Data Systems) Direct Playback (DP) mode: TDRSS Ku-band downlink for science data EPGS (EOS Polar Ground Station) X-band backup GHz Wallops Flight Facility (WFF) EOS Polar Ground Network Svalbard Alaska D/L 5 deg above local mask S/C antenna provides approx. constant power density ± 63.8 deg about S/C earth-pointing axis (2363 km ground radius about S/C nadir) Real-time Direct Broadcast (DB) and Direct Downlink (DDL) Direct Access System (DAS) operational duty cycle is from 0% to 100% at all times.

12 Downlink Range, DB Mode 3, 5, 10 deg Horizon Mask 10 deg 5 deg 3 deg Equidistant Cylindrical Projection 2330 km swath

13 WRRHAMS Weather-Related Road Hazards Assessment & Monitoring System Online road maintenance decision support system for weather-related hazards on rural roads in McKinley County, NM

14 WRRHAMS Goals Develop a web-based environment for identifying and visualizing transportation infrastructure locations in danger of having been damaged by precipitation events Requirements Develop methods for accessing and processing near-realtime NEXRAD precipitation data Integrate these date into hydrologic models that provide estimated surface flow based upon watershed characteristics including: Soil Characteristics Vegetation Physiography: Slope, Aspect, Flow Direction, Flow Accumulation

15 WRRHAMS Accomplishments NEXRAD acquisition and processing procedures have been developed, tested, and are now generating products and usable data on a nightly basis 24-hour total precipitation shapefiles have been generated for both New Mexico and the Olympic Peninsula for each day since February 1, Hourly precipitation values for all grid points overlapping New Mexico and the Olympic Peninsula have been compiled into a database for input into the hydrologic model. Physiographic data been imported into the modeling environment (GRASS GIS) Implementation of alternative hydrologic models (TOPMODEL and ANSWERS) is ongoing. Initial map service configuration has been completed, with integration of hydrologic analysis results planned upon completion of model implementation.

16 Elevation Data Road Networks Boundaries Analysis Area Boundaries Olympia Peninsula, WA 24-hour Precipitation Totals for Feb. 18, 2003 McKinley County, NM

17 Thank You

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