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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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You can map a function that operates on an image over an entire imageCollection before reducing. For example, I use snippets from your code above to generate a cloud-free composite of Ghana by defining the masking functions first, then applying them to the imageCollection. Note that I expanded the date range because it looks like 2013 may have some ...
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I recommend resampling your raster data to match the higher resolution dataset (i.e. smaller pixel dimensions) using gdal.
First run the gdalinfo utility on both files to determine the resolution
gdalinfo *path\to\file1.tiff*
gdalinfo *path\to\file2.tif*
then choose the smaller set of values (call these xres and yres) of the two and use gdalwarp to ...
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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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The SR product is provided as a 16-bit GeoTIFF image with reflectance values scaled by 10,000.
There is also a tutorial tutorial to convert MS radiance to reflectance.
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