玉米收成量對期貨交易 (commodity trading) 的影響

Elizabeth Woyke, Crystal Ball for Corn Crop Yields Will Revolutionize Commodity Trading, MIT Technology Review, August 9, 2016.

Deriving financial insights from satellite images isn’t a new idea, but TellusLabs is putting a twist on it. The Boston startup analyzes satellite imagery from NASA as well as weather data from the National Oceanic and Atmospheric Administration and seasonal, crop-growing information from the U.S. Department of Agriculture. It then uses machine-learning algorithms to generate intelligence about natural resources, such as predicting agricultural yields.
The strategy might sound similar to that of other satellite imagery analysis companies like Descartes Labs and Orbital Insight. However, TellusLabs plans to differentiate itself by applying scientific expertise in vegetation and climatology to its analysis, maintaining a narrow focus on natural resources, and quickly rolling out new products. Its goal is to be “a Bloomberg terminal for Earth signals.” “There’s a broad base of people who have to make tough decisions around natural resources, and we want to give them quality data, quickly,” says TellusLabs CEO and cofounder David Potere. 

The company’s first foray into the market is Kernel, an agricultural commodities forecast modeling tool that recently entered a publicly accessible open-beta phase. The free, beta version of Kernel has limited features, but the full-fledged product is an interactive, online dashboard that shows a map of the main corn-growing regions in the U.S.—across 18 states—and key financial indicators, such as predicted yield, harvested area, and total production. Users can view data at a state, agricultural district, or county level and look at historical yield data sourced from the USDA. The dashboard also features an indicator arrow—analogous to a stock-market ticker—that denotes the average change in corn yield estimates, week over week. TellusLabs will update the forecasts daily. 

Like a Bloomberg terminal, Kernel is designed to be a nexus for fast, reliable financial data, which people can utilize multiple ways. A commodities trader could use the information to make money off trades in the futures market. An ethanol plant operator could consult Kernel to gauge whether its contracted farmers will be able to supply enough corn to keep it running. An agribusiness company like John Deere could license the data feed and integrate it into a smart pump that automatically adjusts how much water it gives crops.