inner_joins.py

import ee 
import geemap

# Create a map centered at (lat, lon).
Map = geemap.Map(center=[40, -100], zoom=4)

# Make a date filter to get images in this date range.
dateFilter = ee.Filter.date('2014-01-01', '2014-02-01')

# Load a MODIS collection with EVI data.
mcd43a4 = ee.ImageCollection('MODIS/MCD43A4_006_EVI') \
    .filter(dateFilter)

# Load a MODIS collection with quality data.
mcd43a2 = ee.ImageCollection('MODIS/006/MCD43A2') \
    .filter(dateFilter)

# Define an inner join.
innerJoin = ee.Join.inner()

# Specify an equals filter for image timestamps.
filterTimeEq = ee.Filter.equals(**{
  'leftField': 'system:time_start',
  'rightField': 'system:time_start'
})

# Apply the join.
innerJoinedMODIS = innerJoin.apply(mcd43a4, mcd43a2, filterTimeEq)

# Display the join result: a FeatureCollection.
print('Inner join output:', innerJoinedMODIS)

# Map a function to merge the results in the output FeatureCollection.
joinedMODIS = innerJoinedMODIS.map(lambda feature: ee.Image.cat(feature.get('primary'), feature.get('secondary')))

# Print the result of merging.
print('Inner join, merged bands:', joinedMODIS.getInfo())


# Display the map.
Map