Author(s)

Evaldo Araújo de Oliveira¹, Augusto José Pereira Filho²

¹Department of Physics, Federal University of Sao Paulo, Diadema, Brazil.
²Department of Atmospheric Sciences, University of Sao Paulo, Sao Paulo, Brazil.

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.

Image Classification, Density Weather Maps, Statistical Texture Approach

Oliveira, E. and Filho, A. (2022) Looking at the Statistical Texture Approach Applied to Weather Radar Rainfall Fields. Journal of Geographic Information System, 14, 29-39. doi: 10.4236/jgis.2022.141002.