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e-sensing / sits

Satellite image time series in R
https://e-sensing.github.io/sitsbook/
GNU General Public License v2.0
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Implement SAR texture measures based on co-occurence matrices #1116

Open gilbertocamara opened 2 months ago

gilbertocamara commented 2 months ago

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.

Nowosad commented 1 month ago

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

gilbertocamara commented 1 month ago

Hi @Nowosad many thanks for the very useful tip!

Nowosad commented 1 month ago

@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...