Access data from the MODIS web service and perform quality filtering in Python
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Access the MODIS web service and perform quality filtering using Python

Date: May 15, 2018
Contact for ORNL DAAC:

Keywords: MODIS, web service, Python, REST


The tutorial outlined in the jupyter notebook will explore using the Python to access MODIS Land Products through the new (May 2018) REST-based web service hosted by the ORNL DAAC. For a full description and usage examples of the web service, please visit the ORNL DAAC's MODIS site:

Using the MODIS Web Service users can:

  • Retrieve MODIS subsets through command line operations
  • Download and integrate subsets directly into client-side workflows
  • Download and visualize subsets with customized code ... and much more.

This tutorial will demonstrate how to do the following in Python:

  • dates and subset request examples
  • build a time series of MOD11A2 land surface temperature from multiple web service subset requests
  • perform quality control filtering based on multiple MODIS qc criteria

The same tutorial is provided in R in another ORNL DAAC repository.

Daytime LST for North Table Mountain Ecological Preserve 2001-2003

Source Data

Input data were accessed through the MODIS Web Service hosted at the ORNL DAAC. All necessary steps for accessing the web service using Python are outlined in the jupyter notebook.

Other methods for accessing data through the web service are described at the MODIS web page;


Python 2 or 3 Libraries: requests, json, datetime, pandas, numpy, matplotlib


Access the the tutorial here: