Is there an accuracy assessment for Google Earth?
– Geographic Information Systems Stack Exchange Accuracy assessment using Google Earth Engine? I’m using Google Earth Engine for Land Cover change detection, I would like to know whether we can generate Error Matrix (Accuracy Assessment) for a classified image in Earth Engine or not? Yes, you can.
How is a random forest classifier used in Google Earth?
This example uses a random forest ( Breiman 2001 ) classifier with 10 trees to downscale MODIS data to Landsat resolution. The sample () method generates two random samples from the MODIS data: one for training and one for validation. The training sample is used to train the classifier.
How is classification done in Google Earth Engine?
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. Instantiate a classifier. Set its parameters if necessary. Train the classifier using the training data. Classify an image or feature collection.
Where do I get validation data for Earth Engine?
Training and/or validation data can come from a variety of sources. To collect training data interactively in Earth Engine, you can use the geometry drawing tools (see the geometry tools section of the Code Editor page ).
How to collect training data in Earth Engine?
To collect training data interactively in Earth Engine, you can use the geometry drawing tools (see the geometry tools section of the Code Editor page ). Alternatively, you can import predefined training data from an Earth Engine table asset (see the Importing Table Data page for details).
How to get confusion matrix in Google Earth?
Call errorMatrix () on the classified FeatureCollection to get a confusion matrix representing validation (expected) accuracy. Inspect the output to see that the overall accuracy estimated from the training data is much higher than the validation data.