Geospatial Data Processing in Support of MIMES

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Geospatial Data Processing in Support of MIMES

• Austin Troy
• Jarlath ONeil-Dunne
• Ernest Buford
• Sean MacFaden

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GIS Support to MIMES
Server
Database
Data Processing
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Major Challenges Dataset Specific

• SIMILIE
• Does not support open spatial data formats
• Global Datasets
• Poorly documented
• Archaic formats
• Catalogued, but hard to located (buried in FTP
  sites)
• Varying resolution
• Local Datasets
• MIMES input requirements are typically not found
  in existing GIS clearinghouses
• Data varies greatly between differ focus areas

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Successes Global Data
Atmosphere
Biosphere
Anthroposhere
Hydrosphere
Lithosphere
Biosphere
Land Use

• Obtained and pre-processed readily available key
  MIMES global datasets
• Easy to locate via NASA Global Change Master
  Directory

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Climate Preprocessing Example (VT)

• Model requirements (daily time step for 3 target
  years)
• Mean wind speed
• Temperature (mean, max min(
• Relative humidity
• Precipitation
• Existing interpolated (gridded) climate data only
  available at monthly time step
• SIMILIE requirements mean interpolated data must
  line up with other raster layers SRTM90 used
  base extent and cell size

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Processing VT Climate Data
Daily Readings
Corrected Readings
Interpolated Surface
Daily Point Data
Station Locations
7.5 min/variable

• 4 Variables
• Precipitation
• Temperature (Mean, Min, Max)
• Daily Time Step
• Three 1-year intervals

22 days of processing time
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Forging Partnerships Local Datasets

• Challenge Soil variables for climate module not
  in readily accessible soil database
• Solution Request to NRCS for statewide,
  non-standard data answered within 3 hours

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Local datasets (II)

• Have begun data collection for Puget Sound,
  Tongass N.F., Vermont
• Data stored on SAL server for modeling work
• Still seeking some data layers will use global
  data where local is unavailable
• Also looking for data from other regional case
  studies