文章基本信息

标题：Looking at the Statistical Texture Approach Applied to Weather Radar Rainfall Fields
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作者：Evaldo Araújo de Oliveira ; Augusto José Pereira Filho
期刊名称：Journal of Geographic Information System
印刷版ISSN：2151-1950
电子版ISSN：2151-1969
出版年度：2022
卷号：14
期号：1
页码：29-39
DOI：10.4236/jgis.2022.141002
语种：English
出版社：Scientific Research Publishing
摘要：Texture analysis methods have been used in a variety of applications, for instance in remote sensing. Though widely used in electrical engineering, its application in atmospheric sciences is still limited. This paper reviews some concepts of digital texture and statistical texture approach, applying them to a set of specific maps to analyze the correlation between texture measurements used in most papers. It is also proposed an improvement of the method by setting free a distance parameter and the use of a new texture measurement based on the Kullback-Leibler divergence. Eight statistical measurements were used: mean, contrast, standard deviation, cluster shade, cluster prominence, angular second moment, local homogeneity and Shannon entropy. The above statistical measurements were applied to simple maps and a set of rainfall fields measured with weather radar. The results indicate some high correlations, e.g. between the mean and the contrast or between the angular second moment, local homogeneity and the Shannon entropy, besides the potentiality of the method to discriminate maps.
关键词：Image ClassificationDensity Weather MapsStatistical Texture Approach