Implement SAR texture measures based on co-occurence matrices

[Gilberto Camara]

Describe the new API function requested
Reccent papers on deforestation alerts, as for example "How textural features can improve SAR-based tropical forest disturbance mapping" indicate that some of the Haralick texture metrics based on co-occurence matrix can improve their accuracy.

For this reason, we should consider a new function sits_sar_texture() that implements the texture measures described in Table 2 of the above paper.

Associated sits API function
sits_sar_texture(cube, measure, output_dir, multicores, memzise) where:
cube is a SAR image data cube and measure is one of grey-level co-occurence matrices (GLCM) metrics.

[Jakub Nowosad]

@gilbertocamara you may be interested in https://github.com/ailich/GLCMTextures by @ailich

[Gilberto Camara]

Hi @Nowosad many thanks for the very useful tip!

[Jakub Nowosad]

@gilbertocamara you are welcome.
I think it would be great to have one high quality and comprehensive package for GLCM textures than a few ones only having some measures...