Contents
How to perform time series classification on Google Earth?
The goal want to achieved is to perform time series classification on Google Earth Engine (GEE). So far, I have only seen per image classification in the documents. I also found that you can fit a regression with image collection from Time Series Analysis in Earth Engine By Google Earth.
What are the classifiers in Google Earth Engine?
These classifiers include CART, RandomForest, NaiveBayes and SVM. The general workflow for classification is: Collect training data. Assemble features which have a property that stores the known class label and properties storing numeric values for the predictors.
How does supervised classification work in Earth Engine?
The Classifier package handles supervised classification by traditional ML algorithms running in Earth Engine. These classifiers include CART, RandomForest, NaiveBayes and SVM. The general workflow for classification is: Collect training data.
Is there a way to perform time series supervised classification on Gee?
If using image based classification alone, it lose the phonological pattern which can indicate plants signature overtime. Is there a way to perform time series supervised classification on GEE?
Why is correlation important in time series analysis?
The concepts of covariance and correlation are very important in time series analysis. In particular, we can examine the correlation structure of the original data or random errors from a decomposition model to help us identify possible form (s) of (non)stationary model (s) for the stochastic process.
How to do linear regression in Google Earth Engine?
The same analysis from the previous linearFit section is applied here, except this time the ee.Reducer.linearRegression function is used. Note that a regression image is constructed from three separate images: a constant image and images representing SWIR1 and SWIR2 bands from the same Landsat 8 image.
How does the ndsi work in Google Earth?
The chart uses the lat/long selected by the user and builds a time series for NDSI at that point. It takes the average NDSI at that point, extracts it, and then adds it to the time series. This series is then plotting as a chart.