MOLUSCE – quick and convenient analysis of land cover changes

Important: MOLUSCE is 2.x only, we no longer offer support for MOLUSCE. Stay tuned for updates.

Together with Asia Air Survey we’ve developed MOLUSCE (Modules for Land Use Change Simulations) – a new tool based on QGIS that allows to perform quick and convenient analysis of land cover changes.

A researcher who analyses changes in landscape through time often deals with questions like:

  • What are the changes and where did they happen?
  • Which factors can explain the changes and strong is their explanatory power?
  • What changes are expected in future and where?

The answer for the first question can be obtained by visual estimation, but to answer other questions one will need to set hypothises, verify them, derive conclusions and see how they meet the reality.

MOLUSCE is a toolbox to partially automate the process of answering such questions.


Briefly, the workflow consists of the following steps:

  1. Obtain landcover map for few time slices and  a set of potential explanatory variables;
  2. Calculate probabilities of transitions from class to class;
  3. Build a model using ANN, logistic regression, Weights of evidence or Multi-criteria evaluation to describe transitions based on factor variables;
  4. Use this model for forecasting;
  5. Validate the result with real data.

Find more information in GIS-Lab article (Russian, autotranslated).

111 responses to “MOLUSCE – quick and convenient analysis of land cover changes”

  1. kimara says:

    Hi when I am uploading my inputs into MOLUSCE it is giving me memory error “Memory error occurred. Perhaps the system is low on memory” . Please advise how I may go about resolving this issue.Thanks

  2. ASHIK MAHMUD says:


  3. Warren says:

    Hi there. Thanks for all the information on MOLUSCE thus far. I am busy preparing all my layers and was wondering where I could find a tutorial for preparing my spatial variables, i.e., how each input spatial variable should be classed. Any help would be greatly appreciated 🙂

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