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How can I perform a regression analysis between image reflection and field data in Google Earth Engine platform?

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I am also doing the same thing for my PhD, at the moment I don't have a definitive answer. but this is how I am going to do it.

Method1, Google earth engine is a very powerful application and there is a Assets section where you can upload data files. but the recognized file types are limited. for further details please check Assets Help Page

Method2, run the Google Earth Engine stuff in google earth engine and transfer the out put to the Google Drive with using Export Methods of Google Earth Engine then download it and run in R or QGIS with data bases

Method3, Best Method Try to use the Google Colab where the IPython notebooks have the capacity of recognizing almost all the data bases and data types as well as it can run Google Earth Engine processors with little bit of tweaking, go to the Google Earth Engine IPython Help Page for further details. (use Pandas, Numpy, GeoPandas, and etc to read the data and, sklearn, keras, or tensorflow for analysis)

Method3 is the best possible way for execution, and it is by taking the maps from Google Earth Engine and running the regression and classification tasks under Google Colab with using IPython.

For smaller tasks the the best method is Method2 with downloading the processed Images from Google Earth Engine and open them in QGIS or R and run the data files on top of it. This method is best if you are trying to do it with very little coding

Yes, using IPython is the best option but QGIS and R have more visualization options for the data.

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