Selection of texture features for crop discrimination using SAR imagery

Joao Vianei Soares; Camilo Daleles Renno

doi:10.1117/12.264265

17 January 1997 Selection of texture features for crop discrimination using SAR imagery

Joao Vianei Soares, Camilo Daleles Renno

Proceedings Volume 2959, Remote Sensing of Vegetation and Sea; (1997) https://doi.org/10.1117/12.264265
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

Abstract

This paper presents a methodology for selecting texture measures to maximize the discrimination of agricultural land use classes in SAR images. The images were acquired during the first flight of the Shuttle Imaging Radar-C experiment, in April 1994. L and C band SAR data at HH, HV and VV polarizations, both in ground range and slant range and in two different passes were analyzed. The kappa statistic was used to identify meaningful texture measures to discriminate seven classes. The results show that the classifications of land use based only on tonal averages produced a kappa coefficient only slightly higher than 0.50. A kappa threshold of 0.90 was reached with the simultaneous inclusion of 15 texture measures for the six images.

Citation Download Citation

Joao Vianei Soares and Camilo Daleles Renno "Selection of texture features for crop discrimination using SAR imagery", Proc. SPIE 2959, Remote Sensing of Vegetation and Sea, (17 January 1997); https://doi.org/10.1117/12.264265

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