The Best Practices and Debugging guides have more complex examples and provide techniques useful for overcoming errors and scaling your Earth Engine analyses to larger areas, longer time series and more data. More advanced Earth Engine concepts provide necessary background for understanding how the Earth Engine service works and writing effective code.
The remainder of the guides are intended to illustrate important concepts about data types such as:
Image, The fundamental raster data type in Earth Engine.
ImageCollection, a stack or time-series of images.
Geometry, the fundamental vector data type in Earth Engine.
Feature, or a
FeatureCollection, or a set of features.
Reducer, an object used to compute statistics or perform aggregations.
Join, or how to combine datasets (
Featurecollections) based on time, location, or an attribute property.
Array, for multi-diminsional analyses.
There are also sections for machine learning, specialized or
sensor specific algorithms (e.g. Landsat algorithms), and
Code Editor specific features such as
Earth Engine apps, and data (asset) management.