DisSLUCC: Discrete Spatial Simulation for LUCC

A Python framework for Land Use and Cover Change and coastal dynamics based on discrete event simulation.

🛰️ Overview

The DisSLUCC (Discrete Spatial Simulation for Land Use and Cover Change) project aims to develop an extensible Python framework for simulating environmental changes. It is built upon the DisSModel engine, currently under development by the LambdaGEO group at UFMA.

The project addresses a critical gap: providing a modern, Python-based alternative to established but aging modeling infrastructures.

🛠️ Technological Transition

The core of DisSLUCC is a strategic mapping and evolution of two major scientific models into the Python ecosystem:

  • From LuccME (Lua/TerraME) to Python: We are implementing the state-of-the-art modular architecture of LuccME—originally developed by INPE in Lua—into a flexible Python environment. This includes both discrete (neighborhood rules) and continuous (CLUE-S approach) allocation algorithms.

  • Integrating BR-MANGUE: The project will incorporate the biophysical rules of the BR-MANGUE model to simulate coastal dynamics, such as sea-level rise, sediment accretion, and mangrove vegetation migration.

🔬 Methodology & Infrastructure

The development follows an iterative approach across three phases:

  1. Discrete Models: Validation of categorical land-use states.
  2. Continuous Models: Implementation of spatial regression and iterative allocation.
  3. Coastal Dynamics: Real-world experiments using data from the Maranhão coast under IPCC climate scenarios.

The framework leverages the Salabim discrete event engine and supports both vector (GeoPandas) and matrix (NumPy) substrates.

🌍 Sustainable Development Goals (SDGs)

This research contributes directly to several United Nations SDGs:

  • SDG 4 (Quality Education): Training students in Geographic Data Science and scientific software engineering.
  • SDG 13 (Climate Action): Modeling carbon sequestration and climate change impacts.
  • SDG 14 (Life Below Water): Protecting coastal and marine ecosystems like mangroves.
  • SDG 15 (Life on Land): Managing sustainable land use and halting biodiversity loss.

📘 Key Information

  • Principal Investigator: Prof. Sérgio Souza Costa
  • Period: August 2026 – September 2028
  • Collaborating Researcher: Prof. Denilson da Silva Bezerra
  • Open Science: All results will be published as open-source code and featured in the upcoming book Geospatial Modeling with Python.

Get Involved: We are training four undergraduate fellows in Geographic Data Science. Check our GitHub repository for interactive Jupyter Notebooks and framework updates.