When global food prices spiked dramatically in late 2007 and into 2008, with the costs of many basic dietary staples doubling or even tripling, protests and riots upset much of the developing world. Following the price spike, world leaders gathered to figure out how to foresee and avert such market instabilities in the future, and a major product of those meetings was the Group on Earth Observations’ Global Agricultural Monitoring (GEOGLAM) initiative, carried out by a partnership of governments and international organizations in the G20 nations. The initiative relies primarily on satellite Earth-imaging data to improve projections of crop production and weather forecasting.
Applied GeoSolutions, based in Newmarket, NH, has been researching various applications for Earth-imaging satellite data for more than a decade. As far as crop projections, the company decided it would leverage its ongoing work on rice, which is the world’s most difficult major dietary staple to predict.
Meanwhile, parts of the two biggest rice-producing regions in the US are running out of water. In the Sacramento Valley area of California, which is home to about half a million acres of rice fields, drought has become the new normal. And in eastern Arkansas, where about a million and a half acres are dedicated to rice production, areas like the Grand Prairie region sit on aquifers that have been pumped nearly dry. One solution is to use satellite data to plan water use more efficiently.
Among the satellites most popularly used for Earth-imaging data are the Landsat series and the Terra and Aqua satellites, equipped with the Moderate-Resolution Imaging Spectrometer (MODIS) instrument. Although NASA built the satellites, the U.S. Geological Survey operates each Landsat once it’s in orbit. In addition to moisture and temperature observations, the imagers can detect the greenness, biomass vigor, and leaf moisture of rice plants, and the presence and depth of surface water, all useful for assessing crop health and predicting crop outcomes. By using the satellite imagery, Applied GeoSolutions can assess large areas at far less cost than traditional field visits.
The company approached NASA with a plan to design Web-based software that would use current and archived data from Landsat, MODIS, and other satellites, incorporating measures of rice fields, yield modeling, and weather forecasts to generate information in real time about rice coverage, growth stages, deviation from normal, and expected yield around the globe, as well as calculate the statistical certainty of that information to address risks.
Stennis Space Center granted the company Small Business Innovation Research (SBIR) contracts to create a Rice Decision Support System (RDSS) that would inform rice-related decisions ranging from how to invest in rice futures, to how to irrigate fields, where and when production risk exists, how to validate conservation practices, and when to buy, sell, or hold. The system went into operation around the start of 2014.
In the US, Applied GeoSolutions predominantly uses Landsat and MODIS data, while in Southeast Asia, it relies primarily on synthetic aperture radar (SAR) satellite data made available by governments and the Japan Aerospace Exploration Agency. The company’s system now supports the GEOGLAM initiative, helping it to supply producers, buyers, and investors around the world with more comprehensive information and projections about what was, as of 2012, the second-most produced crop in the world.
In the US, a primary RDSS application is water management. In northern California, most rice fields are flooded prior to seeding, a process called wet seeding, but as water availability continues to decline, there’s been increased need for conservation. Using satellite images, the company can determine whether a field needs to be watered, how much water it needs, and whether wet seeding is even necessary.