Remote version release of vegetation disease and insect pest remote sensing and prediction system

Xinhua News Agency, Beijing, August 27th (Reporter Zhang Quan) At the 27th of the China Academy of Sciences The Institute of Everbright Information Innovation Research, at the 37th, the remote sensing of vegetation, pests and pests remote sensing monitoring and forecasting system upgrades can be achieved. , Timely monitoring and early predictions of large -scale vegetation diseases and insect pests.

The upgraded version of vegetation and diseased remote sensing monitoring and forecasting system uses analysis methods such as remote sensing, geographical information systems, plant protection, agricultural meteorological and other analysis methods to achieve the time -order monitoring of the major pest breeding area of ​​agriculture and forestry grass pests, key hazardous areas, and the spread of diseases and insect pests. The dynamic prediction of potentially harmful areas can provide pest monitoring and predictive space information products for regions of different standards.

"Multi -scale, long -term sequence, and large -scale, that is, as small as a small farm to 10,000 acres of farmland, we can always monitor the occurrence of the pests and insect pests at all times, and make predictions in a timely manner." Wenjiang said.

The system released this time is an upgraded version of the existing vegetation, diseases and insects remote sensing monitoring and forecasting systems of the Chinese Academy of Sciences. As of now, the Chinese Academy of Sciences has released more than 120 periods of global grain producing areas and typical areas of the Sino -British bilingual "Vegetated diseases and insects remote sensing monitoring and prediction reports" and a number of special reports through the system. Continuously adopted.

The 3rd vegetation and diseases and insect pests remote sensing conferences are hosted by the Chinese Academy of Sciences. They are committed to promoting the in -depth application of remote sensing technology in the theory of remote sensing and industry application of vegetation and diseases and insect pests.

【Edit: Bian Liqun】

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