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    Hikes in grocery prices often arise from factors outside of governments' control, whether it's bird flu driving up egg costs or heavy rain in California drowning crops. But farmers can gain more control over the availability of certain foods by using satellite data, finds a new study led by researchers from University of Maryland. 

    Remote sensing has long been used to track and make predictions about crop harvests. But governments have been hesitant to heavily invest in the technology for crop monitoring and planting because they lacked evidence of the ability to produce quantifiable economic benefits-until now. 

    "The models we created show that remote sensing forecasting can reduce food prices in import-dependent countries by 1.1%~12.5%," said Laixiang Sun, a professor in the Department of Geographical Sciences. "By using remote sensing to predict a poor harvest in the Northern Hemisphere(半球), the Southern Hemisphere can plant more to avoid a shortage. If the Northern Hemisphere has a good harvest, the Southern Hemisphere can plant less to avoid an oversupply. This will keep prices stable."

    The researchers first created models to predict how much warning farmers in the opposite hemisphere could have of potential shortages or surpluses. To do so, the researchers used remote-sensing data before a 2008 poor wheat harvest in, Russia, a 2012 good wheat harvest in Ukraine, and 2012's poor soybean harvest in Brazil. The wheat-forecasting models accurately predicted production in 2008 and 2012 two months before the harvests.

    The researchers also developed economic models to show how predictions of upcoming shortages and surpluses could prevent food price changes. With data from 2007 and 2011, the years immediately before the wheat and soybean harvests, the models showed that consumers in import-dependent countries could save some money if farmers could see and respond to the predicted harvests in the opposite hemisphere. 

    Sun said the findings justify continued monitoring of crop growth from space—and not a moment too soon, either. "This is important, as global food security is increasingly threatened by regional human conflicts and extreme weather events from climate change," he said.

    1. (1) What kept governments from investing in satellite data for crop monitoring?
      A . Lack of economic proof. B . Difficulty in interpreting data. C . Insufficient satellite technology. D . Farmers' resistance to new methods.
    2. (2) According to Sun, how can remote sensing forecasting impact prices?
      A . By causing a global price movement. B . By stabilizing importing countries' food prices. C . By reducing food prices in areas with poor harvests. D . By predicting food prices of a year with good harvests.
    3. (3) Why does the author mention "economic models" in paragraph 5?
      A . To clarify the accuracy of crop forecasting models. B . To show how remote sensing can reduce food prices. C . To prove the economic profits of using satellite data. D . To explain the impact of climate change' on food security.
    4. (4) Why does Sun consider continued space-based crop monitoring crucial?
      A . It resolves human conflicts worldwide. B . It relieves threats to global food security. C . It enhances farmers' awareness of climate change. D . It helps prevent extreme weather events from happening.

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