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Meeting Every Challenge We have enough confidence in the value of our proprietary products and unique datasets, that we gladly meet every challenge to prove it. In studies sponsored by the National Oceanic and Atmospheric Administration (NOAA), World Bank, Yale University and others, our products have consistently out-performed in situ (weather station) observations, EarthSat’s Cropcast system and additional computer-generated models and/or satellite derived products to assess growing conditions around the world.

Our Value Over In Situ Measurements

Using the Special Sensor Microwave Imager to Monitor Surface Wetness, Journal of Applied Meteorology

The frequencies flown on the Special Sensor Microwave Imager (SSM/I) are used to dynamically derive the amount of liquid water near the surface. These data are averaged at 1° resolution throughout the globe for each month during the period of 1992-97. The 6-yr monthly means and the monthly anomalies of the wetness index are computed from this base period. To quantify the relationship between precipitation and surface wetness, these anomalies are compared with precipitation anomalies derived from the Global Precipitation Climate Program. The analysis was performed for six agricultural regions across six continents. Results indicate that the wetness index has a strong correspondence to the upper layer of soil moisture in many cultivated areas of the world.

Our Value Over NDVI Satellite Products

In a rigorous study funded by the World Bank and sponsored by the USDA, our proprietary products and datasets are compared against the Normalized Difference Vegetation Index (NDVI) and in situ data (more…). The study used each data set to predict the spatial variability in yields for winter wheat and oil seeds across India. Results demonstrate that our wetness product provides superior insight, since it detects irrigation supplies and soil moisture availability. These findings led the World Bank to purchase our product over other data for studies in Africa, Middle East and south and central America.

Our Value Over Computer-Generated Models

Using the United Sates Department of Agriculture’s data as independent validation, we compared Commodity Hedgers’ data and value to Earth Satellite Corporation’s computer-generated models of future yields in soybean, corn and winter wheat across North America, South America, Europe and the Former Soviet Union. These comparisons clearly demonstrate the value of our actual observations versus model solutions that are derived from limited point measurements. Furthermore, they demonstrate that our near-real time measurements see events as they occur in context, while computer-generated models can only guess at the growing conditions.

Using the Special Sensor Microwave/Imager to Monitor Land Surface Temperatures, Wetness, and Snow Cover

By: Alan Basist, Norman Grody, Thomas Peterson, Claude Williams

A method has been developed to calculate land-surface temperatures using measurements from the Special Sensor Microwave/Imager (SSM/I). To accomplish this, the authors identify numerous surface types and make dynamic adjustments for variations in emissivity. Training datasets were used to define the relationship between the seven SSM/I channels and the near-surface temperature. The U.S. networks of first-order and cooperative stations (quality controlled by the National Weather Service) serve as validation data. The correlation between satellite-derived and in situ temperatures during the independent case ("Blizzard of 1996") was greater than 0.95. The authors also present SSM/I-derived snow cover and wetness maps from this 2-week period of the blizzard.