How to calculate Multivariate Image Texture in Google earth engine or any other software?
I am trying to classify urban areas using Landsat TM data, I have tried to get the image texture using GLCM and the result is somehow good, but I have seen many other literatures which exploited Multivariate Image texture and had better result compare to GLCM method.
GLCM: uses one band as input data
Multivariate Img text: uses multi-band as input data
In my case GEE shows the usual point feature size exceeding error but also the error: "Error generating chart: Property 'Grass_Mask' of feature '0' is missing." Since for this script you can only calculate probability with 2 classes I transformed my 12 classes of a LULC_Class property to a binary property column that is called grass mask (with only values of 1 for grassland and 2 for all other classes).
Im happy to hear about your thoughts and experiences with calculating the feature importance in the GEE environment. I could also do it in R but then I have to download my very large dataset.
It is in principle impossible to capture three-dimensional information from a monocular image. However, if something is known about the scene, a monocular image or multiple monocular images (viewed from the same position) may often provide information on three-dimensional surface orientations, though not complete range information. The shape of obj...