New answers tagged classification
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Here is an article by the Earth Engine team that does a little explaining on morphological operations within Earth Engine
Fo your case, you may be able to get away with using image.focal_mode() (or some combination of morphological ops) for a straightforward clean up of your classes, the Earth Engine team provide a great example of how to do this for land ...
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LAS 1.2 has a classification byte, which is 8 bits. However 3 of those bits are used for the flags (withheld, synthetic, and keypoint).
With laspy, classification accesses the 5 bits that LAS 1.2 allows for the classification number. 2^5 is 32, meaning you can store 32 classes (0-31) in that 5-bit integer. It doesn't touch the flag bits.
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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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