Download - WE1.L10 - IMPLEMENTATION OF THE LAND, ATMOSPHERE NEAR-REAL-TIME CAPABILITY FOR EOS (LANCE)
Land Atmosphere Near real-time Capability for EOSDIS (LANCE)
Karen Michael, Kevin Murphy, Dawn Lowe, Jeanne Behnke - ESDIS Project, GSFC Martha Maiden, NASA HQ Chris Justice (UMd), Michael Goodman (NASA HQ) UWG Co-Chairs
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lance.nasa.gov
The Land, Atmosphere Near-real-time Capability for EOS(LANCE)
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• Building on existing EOSDIS elements LANCE provides data from MODIS, OMI, AIRS, MLS, and AMSR-E instruments in near real-time (< 3 hours from observation)
• Utilizes algorithms used for Standard Science Products, but relaxes requirements for slower ancillary data inputs
• High operational availability • Applications of LANCE data
include:
– Numerical weather & climate prediction/forecasting
– Monitoring of Natural Hazards
– Drought Early Warning
– Disaster Relief
– Agricultural Monitoring
– Air Quality
– Homeland Security
• A stand alone system Ocean Color Web has been developed for NRT applications
lance.nasa.gov
LANCE System Architecture
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lance.nasa.govLeverages existing EOS processing and distribution capabilities at multiple locations, collocated with science expertise.Provides users with a ‘one-stop-shop’ for EOS near real-time products through the LANCE web portal.Primary driver of latency is in the spacecraft to ground transmission. New approaches and capabilities are being evaluated to effect latency improvements.
TERRA
AQUA / AURA
lance.nasa.gov
High Operational Availability withMeasurable Latency
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LANCE vs. Standard Product Latency – MODIS Example
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Standard Processing LANCE Processing(typical)
Product Category Terra(hrs) Aqua(hrs) Terra/Aqua (hrs)
L1/Cloud Mask 8 25 1.7
L2 Snow 8 25 1.8
L2 Sea Ice 8 25 2.0
L2 Fire 8 25 1.9
L2 Clouds 32 32 2.2
L2 Aerosol 32 32 2.2
L2 LSR 40 41 2.1
lance.nasa.gov
Near Real-Time vs. Science Quality Products – MODIS Example
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Science Product Near Real-Time Product
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Near Real-Time vs. Science Quality Products – MODIS Example
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Short Name
Science Data Match
(% Global)
#pixel
(%Global)
Omission Error
#pixel (%)
Commission Error
#pixel (%)
MOD09 LSR-B1 98.94 N/A N/A N/A
MOD09 LSR-B2 99.12 N/A N/A N/A
MOD09 LSR-B3 99.32 N/A N/A N/A
MOD09 LSR-B4 99.16 N/A N/A N/A
MOD10 L2 Snow 99.97 31831094 (2.1%) 39751 (0.13%) 44255 (0.14%)
MOD29 L2 Sea Ice 99.95 14471848 (5.5%) 8383 (0.06%) 14812 (0.1%)
MOD14 L2 Fire 99.97 3207 (0%) 2 (0.06%) 3 (0.09%)
• For LSR the Match is the percentage of NRT data with <1% error margin when compared to the operational Collection 5 codes
• For Snow, Sea Ice, and Fire, the Match is the exact pixel to pixel match between NRT and operational Collection 5 codes
• Omission and Commission errors are computed as a percentage of the snow, sea ice, fire in the operational Collection 5 products
lance.nasa.gov
Brokerage and Direct Access
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LANCE focuses on providing data to brokers who perform value added processing and services for downstream users.
LANCE provides limited services that enable brokers to quickly create products for hazard, forecasting and disaster response
All requests for LANCE enhancements are reviewed by the user working group to ensure enhancements are coordinated with LANCE capabilities and resources
ApplicationBrokers
ApplicationBrokers
ApplicationBrokers
ApplicationBrokers
Direct Access
lance.nasa.gov
AIRS/MLS Products
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LANCE-AIRS-Aqua Icelandic Volcano Ash Plume
Eyjafjallajokull April 15, 2010LANCE AIRS/MLS
AIRS L1B channel subsets are available in BUFRAIRS L2 quality improved using NOAA/NCEP Global Forecast SystemAIRS is availble in the following formats PNG, GeoTIFF, and KMZ formats using the Open Geospatial Consortium (OGC) Web Map Service (WMS)
Instrument Product Categories Average Latency
AIRS Radiances, Temperature and Moisture Profiles, Clouds and Trace Gases
75 – 140 minutes
MLS Ozone, Temperature 75 – 140 minutes
Visible 3km SO2 10km
Processing Lead: Bruce Vollmer
lance.nasa.gov
AMSR-E Products
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LANCE-AMSR-E-AquaHurricane Alex, July 1, 2010,08:26
UTCAMSR-ECurrently implementing Baseline Near Real-time processing at the AMSR-E SIPSEnhancements will include development of an L2A algorithm specialized for near-real time processing and rapid deployment of updated L2B and L3 algorithms operating at the SIPS.
Instrument Product Categories Average Latency
AMSR-E Brightness Temperatures, Soil Moisture, Rain Rate, Ocean Products
80 - 135 minutes
Processing Lead: Helen Conover
lance.nasa.gov
OMI Products
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LANCE-OMI-AuraIcelandic Volcano Eyjafjallajokull April 15, 2010, 11:58-12:04 UTC
LANCE OMIOMI NRT products are available through LANCE to registered users including OMTO3 (Total Column Ozone), OMSO2 (Sulphur Dioxide) and OMAERUV (Aerosol).
Instrument Product Categories Average Latency
OMI Ozone, Sulfur Dioxide, Aerosols
100 – 165 minutesLatency excludes L3
Processing Lead: Curt Tilmes
lance.nasa.gov
MODIS Products
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LANCE-MODIS-TerraOil Spill in Gulf of Mexico May 24, 2010 16:50 UTCLANCE MODIS
Currently implementing geographic, parameter and band subsetting in addition to pan sharpening, reprojection, mosaicing, sub-sampling, flood mapping and Geo Tiff format conversion.Future developments include integration of the MODIS Rapid Response, Web Coverage and Mapping along with the Fire Information for Resource Management System
Instrument Product Categories Average Latency
MODIS Radiances, Cloud/Aerosols, Water Vapor, Fire, Snow Cover, Sea Ice, Land Surface Reflectance, Land Surface Temperature
90 – 145 minutesLatency excludes L2G and L3
Processing Lead: Edward Masuoka
lance.nasa.gov
MODIS Global Time FiresLast 10 days
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lance.nasa.gov
Fire Information for Resource Management
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• FIRMS provides the MODIS fire information in small, easy to use formats through the internet and fire email alerts.
• Capabilities• Interactive Web GIS• Email alerts (sent to over 100 countries) • Subsets of MODIS images• Active fire data downloads (KML, Shape, Text files and plug-ins for Google Earth and
NASA World-Wind)
• FIRMS provides the MODIS fire information in small, easy to use formats through the internet and fire email alerts.
• Capabilities• Interactive Web GIS• Email alerts (sent to over 100 countries) • Subsets of MODIS images• Active fire data downloads (KML, Shape, Text files and plug-ins for Google Earth and
NASA World-Wind)
FIRMSFire Information for Resource Management
University of Maryland, NASA GSFC, Sigma Space, UN FAO
lance.nasa.gov
Active Fire Mapping
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Source: http://activefiremaps.fs.fed.us/index.phpUSDA/USFS
lance.nasa.gov
Flood Mapping
16Dartmouth Flood Observatory
lance.nasa.gov
Sea - Ice Monitoring
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Source: http://www.ec.gc.ca/glaces-ice/default.asp?lang=En&n=D32C361E-1
Canadian Ice Service
lance.nasa.gov
Dust Detection Over Land
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The Approach:Use multi-spectral MODIS data to identify dust via color, thermal, spectral (11/12) contrast, and 1.38 cirrus filtering.
())Vis/NIR IndexVis/NIR IndexTemperature Temperature
Cirrus FlagCirrus FlagSplit WindowSplit Window
dust
The Application: Depicting dust storms over the bright deserts through enhanced imagery.
DoD Context:Mission planning, aircraft routing/launch/recovery, weapons selection.
Source: Jeff Hawkins
Naval Research Laboratory Monterey
Dec 3-18, 2007Dec 19-Jan1, 2008Jan 1-Jan 16, 2008Jan 17 – Feb 1, 2008Feb 2 – Feb 17, 2008Feb 18 – March 4, 2008March 5- March 20, 2008March 21- Apr 5, 2008
Drought Monitoring
April 6- Apr 21, 2008
Source: NASA MODIS NDVI
Vegetation Index Time Series for Cropped Areas in Iraq
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Current Season (2007-2008)
Mean (2000-2007)Source: NASA MODIS NDVI
Mean Vegetation
Index
Mean Vegetation
Index
Drought Impacted Vegetation Index (2007-08)
Drought Impacted Vegetation Index (2007-08)
averageaverage
average USDA FAS / UMD / GSFC
lance.nasa.gov
GEO Agricultural Monitoring Community of Practice
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• Several global/regional scale systems in place – many use MODIS data• Data latency is critical for all of these programs
lance.nasa.gov
Way Forward
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• Initial System Review and User Forum Held (Dec 2009) • Decisions on LANCE Registration• Need for a User Working Group recognized to guide system development and prioritize activities
• Weekly Project Telecons to coordinate common issues across processing systems – web portal, metrics, reducing latency, algorithm succession, outreach • LANCE User Working Group being formed (Fall Meeting Planned, DC Area) – topics include:
- Prioritization of development activities - Further Latency improvements being worked- Access improvements- NASA Near Real Time Symposium Planned for Spring 2011
• Join us at the Fall 2010 AGU
• IN07: Current Capabilities and Future Needs of Near Real-Time Data: Perspectives from Users and Producers