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First, your file sizes are as expected. When you go from 1000m per pixel, to 30m per pixel, you get 1111-times increase in size, which is close to what you see from 2 MB to 3.4 GB, once you also consider compression etc. The calculation is: (1000 m/ 30m)^2 = 1111.1 It is squared due to the raster being a 2d array. The whole point of STARFM, or ESTARTFM (a ...


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If you have gdal, you can try gdal_translate -outsize 3333.33% 3333.33% -r bilinear input.tif output.tif


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Including NDVI with your spectral bands is a very common practice in land cover classification and will almost certainly increase your classification accuracy. The Random Forests (RF) algorithm is fairly robust against overfitting. Leo Breiman and Adele Cutler, pioneers in Random Forests, claim that Random Forests does not overfit (reference). However, you ...


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