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The Yellow River Estuary became an important plague region of locusts because of its special geographic location. Many years' survey data showed that the environment was the chief factor that influenced locust pest occurring. In the recent years, because the amount of water from the Yellow River and precipitation reduced and distributed asymmetrically, and soil salinization became serious much more, and many farmlands went out of cultivation, which improved the habitats for locusts, the plague of locusts happened frequently under condign climate. The field survey data from 1991 to 2000 showed that the plague of locust became more aggravating year after year. Therefore, it is important to monitor and control the plague of locusts. According to many years' investigation data analysis, got the condign habitat conditions for Locusta Migratoria Manilensis (Meyen) in the Yellow River Estuary. So the breeding areas of locusts monitoring with remote sensing imagery was to identify those regions according to the condign habitat conditions. Landsat ETM+ imagery (2000-05-02) data was chosen to identify the breeding areas of locusts in the Yellow River Estuary. Firstly classified Landsat TM imagery (2000-5-2) and extract reed lands and lawn lands and slightly salinized soils. Secondly made mask images through transforming these three raster classes into vector layers, then calculated a anti-atmospheric visible light vegetation index VARIg = (B2-B3)/(B2+B3-B1). According to field investigation data of vegetation fractional cover in 2000, got the relationship between vegetation fractional cover and VARIg values, 70% to 3.0, 50% to 2.3. As a result, the infrequent areas were where VARIg values were great than 3.0, and the moderate areas were where VARIg values were between 2.3 and 3.0, and frequent areas were where VARIg values were under 2.3. According to statistical analysis, the infrequent areas were percent 10 of the lands that have the condign soil salt content for locust growth, and the moderate areas of locusts were percent 40, and the frequent areas were percent 50. Because of the low spatial resolution of ETM+ imagery not enough to identify vegetation structure and components, and the quick spatial and temporal change of soil water content, this research only discussed vegetation fractional cover and soil salt content, and quantitative assessment of the identification results and a detailed research need more high spatial and temporal resolution remote sensing data and surface data supports in the future.
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