Applications of Remote Sensing & Ecological Forecasting by s2939Sm

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									                 Ecological Forecasting for Vital Signs Monitoring



Forrest Melton
CSU Monterey Bay, Seaside, CA

Ecological Forecasting Lab
NASA Ames Research Center, Moffett Field, CA


With contributions from:

Rama Nemani, Petr Votava, Andrew Michaelis,
Christina Milesi, Hirofumi Hashimoto,
Weile Wang


Support from:

NASA Applied Sciences Program: REASoN Award,
Decision Support through Earth Science Research
Results Award




                                                  MODIS EVI, Yosemite National Park



NARSEC 2007 Workshop                                 Santa Fe, New Mexico, March 8, 2006
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                     TOPS: Common Modeling Framework




   Monitoring, modeling, and forecasting at
   multiple scales

Nemani et al., 2003, EOM                      White & Nemani, 2004, CJRS   2
       Access to a variety of remote sensing platforms




Integration across: Platforms, Sensors, Products, DAACs is non-trivial   3
Access to a variety of observing networks




  Weather network            Fluxnet




Streamflow network           Soil moisture network

                                                     4
Ability to integrate a variety of models




          Biogeochemical Cycling
          Crop growth/yield
          Pest/Disease
          Global carbon cycle


                            Prognostic/diagnostic models   5
       Ability to work across different scales of time and space

          Hours                                 Years/Decades




Days                        Weeks/Months




                        Weather/Climate Forecasts at various lead times   6
                                                          Downscaling
                                 Standard TOPS Outputs

MODIS PRODUCTS (8 days/Annual)      TOPS-NOWCASTS (daily)                 DATA PROPERTIES
       1   LAI                            17   TOPS-SNOW
                                                                          Spatial Resolution:
       2   FPAR                           18   TOPS-SOIL MOISTURE         30m to 1km
       3   GPP/NPP                        19   TOPS-ET                    Temporal Resolution:
       4   LST-TERRA/AQUA                 20   TOPS-OUTFLOW               1 to 30 days
       5   NDVI                           21   TOPS-GPP/NPP
       6   EVI                                                            Data Presentations:
                                          22   TOPS-PHENOLOGY
                                                                          Nowcast, forecast,
       7   LANDCOVER*                     23   TOPS-VEG STRESS            anomaly, cumulative,
       8   ALBEDO                                                         current average
       9   SNOW                     TOPS-FORECASTS (5 days to 180 days)
                                                                          Data Formats:
      10   FIRE                           24   BGC-LAI/PHENOLOGY          Binary, GeoTIFF, JPEG,
METEOROLOGY (Daily)                       25   BGC-SOIL MOISTURE          PNG
      11   MAX TEMPERATURE                26   BGC-OUTFLOW                Metadata:
      12   MIN TEMPERATURE                27   BGC-ET                     ESML & OGC compliant
      13   RAINFALL                       28   BGC-VEG STRESS             Delivery Mechanisms:
      14   SOLAR RADIATION                29   BGC-SNOW                   FTP, WMS, Web

      15   DEW POINT/VPD                  30   BGC-GPP/NPP

      16   DEGREE DAYS


           * Once a year



                                                                                                   7
                    Standard TOPS Outputs: Local to Global Scales

              Global NPP Anomalies                   U.S. Gross Primary Productivity
                                                                                         California Daily
                                                                                         Soil Moisture
                                                                                         Estimates




                                                                   Napa Valley
                                                                   Forecasted
                                                                   Vineyard Irrigation
   Yosemite Minimum Temperatures                                   Demands


Spatial scales from 0.5 degrees to 4m. Temporal scales from yearly to daily.                                8
TOPS Products for Yosemite




                             9
          Anomaly Detection for Resource Monitoring




Automated anomaly detection and trend analysis assist resource managers in identifying
significant events and focusing ground-based monitoring and management efforts.




                                                                                         10
                                Interpreting Anomalies




Ground-based observations key to validating and interpreting anomalies.   11
Long-Term Monitoring and Trend Analysis




                                          12
Long-Term Monitoring and Trend Analysis




                                          13
TOPS Data Fusion: Trend Analysis for Features of Interest




                                          MODIS Direct Broadcast image of a fire
                                          event in Yosemite National Park,
                                          September, 2005.




                                                                                   14
Using TOPS to Assess Long-Term Trends and Predict Future Change


 •   Key question: How will land use
     change and climate change affect
     landscape dynamics in U.S. parks?
 •   Establish baselines and identify
     trends using historical data
 •   Automated event and anomaly
     detection, trend analysis
 •   Monitoring and modeling of GPP/NPP
     and other landscape indicators
     (NDVI/EVI, LAI/FPAR, snow cover
     timing and extent, soil moisture,
     evapotranspiration, vegetation stress,
     watershed outflow)
 •   Use GCM outputs to drive TOPS to
     produce long-term simulations of park
     ecosystems under different land-use
     and climate change scenarios




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      TOPS Applications for Vital Signs Monitoring

 SNN Vital Sign                         TOPS Products
 Weather and climate                    Daily meteorology, impacts of long-
                                        term predicted change

 Surface water dynamics                 Watershed outflow, soil moisture


 Snowpack                               Snow cover extent and timing


 Landscapes dynamics, fire effects on   NDVI/EVI, LAI/FPAR, soil moisture,
 plant communities                      evapotranspiration, vegetation stress

 Phenology                              Phenology


 Net primary productivity               GPP, NPP



 Recent trends, current conditions, ecological forecasts

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