ntl_linear_fit.py

import ee 
from ee_plugin import Map 

# Compute the trend of nighttime lights from DMSP.

# Add a band containing image date as years since 1990.
def createTimeBand(img):
  year = img.date().difference(ee.Date('1990-01-01'), 'year')
  return ee.Image(year).float().addBands(img)

# function createTimeBand(img) {
#   year = img.date().difference(ee.Date('1990-01-01'), 'year')
#   return ee.Image(year).float().addBands(img)
# }

# Fit a linear trend to the nighttime lights collection.
collection = ee.ImageCollection('NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4') \
    .select('avg_vis') \
    .map(createTimeBand)
fit = collection.reduce(ee.Reducer.linearFit())

# Display a single image
Map.addLayer(ee.Image(collection.select('avg_vis').first()),
         {'min': 0, 'max': 63},
         'stable lights first asset')

# Display trend in red/blue, brightness in green.
Map.setCenter(30, 45, 4)
Map.addLayer(fit,
         {'min': 0, 'max': [0.18, 20, -0.18], 'bands': ['scale', 'offset', 'scale']},
         'stable lights trend')