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If I understand you correctly, you have polygon data for training and validation. Aside from common methodological technicalities in using point data I see no reason that you cannot use your polygon data. This conceptually treating your polygons as a discrete spatial process with an expected spatial homogeneity in the validation. There will most certainly be ...


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It is better to select a reference that is consistent wit the one used to create the map (points for pixel-based classification, polygons for object-based classification), otherwise it is more difficult (or even impossible) to unambiguously assign a label to the validation entity. In your case, there is clearly a gap between the classification and the ...


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Finding the center is not as simple as you think. take an example square in EPSG:4326: Transform it into World Mercator, and the center is somewhere else: In Lambert conformal conical, it is not yet a rectangle: And same for azimutal equidistant: So be careful if you think of a "simple" rectangle and its center point. The world is not a plane! My ...


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Vincenty's formula (ellipsoid based) is more accurate than haversine (sphere based). Also, lat and long are usually expressed in degree, but your coordinates are not in 0-180, therefore you could be in another system than expected.


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There is a Adafruit Ultimate GPS Breakout - 66 channel w/10 Hz, it has position accuracy of <3 meter, velocity accuracy of 0.1 meter per second and cost around 40$. For a working model with Raspberry Pi, here is a tutorial.



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