Assessing the response of phenology (using EVI as proxy) to changes in temperature and precipitation along an altitudinal gradient from 2001 to 2022. One of the ways I am trying to achieve this is by using a multiple linear regression analysis with EVI as the dependent variable, precipitation and land surface temperature as the predictor variables and elevation as constant. I am using the following image collections:

  1. MOD13Q1.061 Terra Vegetation Indices 16-Day Global 250m

  2. MOD11A1.061 Terra Land Surface Temperature and Emissivity Daily Global 1km

  3. CHIRPS Daily: Climate Hazards Group InfraRed Precipitation With Station Data (Version 2.0 Final)

  4. NASA SRTM Digital Elevation 30m

The MODIS collections (EVI and LST) have been parsed for QA. All daily composites have been converted into 16-day composites and all images have been clipped to the area.

I haven't found a suitable method to perform a multiple regression analysis. Please, I need help running the regression analysis, mapping the results, and generating the coefficients and slope. IS IT EVEN POSSIBLE TO DO THIS ON GEE? The code can be found here:



There are some missing data due to poor pixel quality in the area.

Secondly, the image collections have different resolutions. See images below.

EVI LST Precipitation

  • developers.google.com/earth-engine/guides/… Commented Feb 20, 2023 at 13:42
  • Thank you. Tried to modify the suggested code example but I am still struggling with the syntax. I have been able to add elevation as a constant but it generates .addBands is not a function when I try to add other variables. I've tried creating a function to add or add directly to no avail. Please, see code code.earthengine.google.com/4d39b8a5720406b39c3c8d630e8a61b0
    – Geo_CJ
    Commented Feb 20, 2023 at 15:49
  • PLEASE, CAN THIS BE DONE IN GEE? I've only used GEE for a few months and would appreciate it if someone could confirm. Thank you
    – Geo_CJ
    Commented Feb 26, 2023 at 23:55


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