基于光谱指数的高温目标识别方法

目前,高温目标遥感识别研究所采用的波段或光谱指数大多局限于定性分析,缺乏定量评价指标与筛选方法。为建立具有普适性的波段筛选原则及评判指标筛选方法,实现高温目标的有效识别,根据方差分析思想,构建可分性度量指标对高温目标与各类常温地物分别进行特征波段筛选,确定高温目标识别的若干有效波段,结合地物波谱特性构建并筛选高温目标最优识别指数。研究表明,经定量筛选综合确定的最优光谱指数能有效将高温目标与绝大多数常温地物区分开;在此基础上,再利用区分高温目标与易与其混淆的彩钢地物的最优识别指数进行二次识别,可进一步提高识别精度,高温目标2次识别精度分别为95. 4%和97. 6%。     

BOREAL SUMMER CLIMATOLOGY AND STANDARD DEVIATION IN GLOBAL LOW-FREQUENCY STREAMFUNCTION FIELDS AT 200 hPa

Based on NCEP/NCAR DOE daily reanalysis dataset during 1980-2015, this study investigates the boreal summer climatology and standard deviation of streamfunction in different low frequency periods (including 10-30 days, 30-60 days and more than 60 days) at 200 hPa. Distinctions in the characteristics in different periods are emphasized. It is found that the distribution of streamfunction on the timescale longer than 60 days is mainly zonal symmetric, accompanied by strong variability in the Northern Hemisphere subtropical jet streams. For the 10-30-day timescale, it reflects the zonal fluctuating structure in the middle and high latitudes and large variability in the Southern Hemisphere. Tropical quadrupole structure is observed on the 30-60-day timescale in climatology. Besides, a relative weak standard deviation is also found in this period. This work provides basic knowledge on climatology and variability in low-frequency streamfunction, which has not been fully illustrated in previous studies.