本文重点阐述ＮＯＡＡ极轨气象卫星距平植被指数的处理技术及算法，以及在１９９２年干旱监测中的应用。距平植被指数是以归一化植被指数（ＮＤＶＩ）多年旬、月平均值作为背景，然后用当年旬、月的ＮＤＶＩ值减去背景值。植被指数的距平值不仅反映了植被年际间的变化，而且也指示了天气对植被的影响。用这个量监测农作物是否遭到旱灾威胁比只用ＮＤＶＩ的瞬时值优越。研究结果表明当月的距平植被指数与当月降水量距平百分率相一致。

This paper discribes a processing technique and a algorithm of ano-maly vegetation index of NOAA polar orbit meteorological Satellite,and their appli-cation to monitoring drought.Multiyear every ten-day mean and monthly mean no-rmalized difference vegetation index(NDVI)are used as the background value foranomaly vegetation index,and then the backgroud value is subtracted by currentlyyear every ten-day and monthly NDVI data to obtain anomaly value of vegetationindex. It reflects not only vegetation changes between years,but also indicates theweather impact on vegetation. The anomaly vegetation index is superior to NDVIwhen it is used for monitoring drought.It has a better relationship with monthlyprecipitation anomaly precentage.