I have some points and know how to extract the Landsat data at these points and build and export a training dataset to feed an external classifier. But how can I efficiently and automatically build a small patch of 2-D pixels (say 3x3 neighborhood) around each sample point to build and export a similar training dataset to feed an external convolutional classifier?
I think what you need is ee.Image.neighborhoodToArray. I give an example:
var i = ee.Image.random().addBands(ee.Image.random(1)).clip(geometry)
Map.addLayer(i)
var neig = i.neighborhoodToArray(ee.Kernel.square(1))
var training = neig.reduceRegions({
collection:points,
scale: 1000,
reducer: 'first'
})
Map.addLayer(training)
link: https://code.earthengine.google.com/a406f32c989923eae10d73af8b1871be
answered Apr 2 '19 at 2:08
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Thank you very much @Rodrigo for your kind attention and quick reply. Yes it seems to be the function that I need and I wonder why GEE tutorials are completely silent about this and some other useful functions. But I don't understand one thing in your code: Why you use ReduceRegions and what does the 'First' reducer? I don't get what it does. Why not using SampleRegions function instead? – Shahriar49 Apr 2 '19 at 21:09
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The
firstreducer takes the first value of the inputs, doesn't actually reduce them, but as it is a point feature collection, it's the same to usefirstormean(or any). If you have a polygon feature collection themeanreducer will compute the mean of all inputs, and thefirstwill take just the first (which doesn't make sense in most cases) – Rodrigo E. Principe Apr 2 '19 at 22:25 -
Thanks again @Rodrigo. I understood it and found my mistake in some of previous comments. It was all about dependency of inspector values to the zoom level! After a certain zoom level I get matching values between original image and samples. But still I have a confusion: When I add neig raster to the display, I can never get the correct neighborhood values by inspecting it (regardless of zoom level and even when the inspector shows the value of original image correctly). Why? – Shahriar49 Apr 3 '19 at 14:25
