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在回顾主成分分析方法应用的基础上,为有效地从陆地卫星数字磁带中提取各种农作物的信息,首次将该法应用在三时相的TM资料中。研究小区选在瑞典南方,根据当地作物的生长特点,分别选用三天不同时像的TM CCT磁带,对该法进行了验证,经与常规方法比较,证实了主成分分析方法用于多时相资料,可省去对各种影响因素的订正,能有效地提取各种动态变化信息,保持较高精度。一引言主成分分析(简称PCA)方法是一种数据转换技术。
On the basis of reviewing the application of principal component analysis, for the first time, this method was applied to TM data of three phases in order to effectively extract information of various crops from terrestrial satellite digital magnetic tapes. The study area was selected in southern Sweden. According to the growth characteristics of the local crops, TM CCT tapes of different time were selected for three days respectively. The method was verified by comparison with the conventional method, and the principal component analysis method was proved to be suitable for multi-phase data , Which can eliminate the correction of various influencing factors, effectively extract various dynamic change information and maintain high accuracy. An Introduction The principal component analysis (PCA) method is a data conversion technique.