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layout: page
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title: Python Framework for LUCC and Coastal Dynamics
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description: Developing a discrete event simulation-based framework for Land-Use and Cover Change analysis.
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title: "DisSLUCC: Discrete Spatial Simulation for LUCC"
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description: "A Python framework for Land Use and Cover Change and coastal dynamics based on discrete event simulation."
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importance: 1
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category: Leadership
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category: Research
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## 🛰️ Project Overview
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## 🛰️ Overview
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This research project proposes the development of a specialized **Python framework** for simulating Land-Use and Cover Change (**LUCC**) and **coastal dynamics**. The core technical innovation lies in the implementation of **Discrete Event Simulation (DES)**, which allows for a more granular and efficient representation of complex environmental transitions compared to traditional models.
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[span_0](start_span)[span_1](start_span)The **DisSLUCC** (Discrete Spatial Simulation for Land Use and Cover Change) project aims to develop an extensible Python framework for simulating environmental changes[span_0](end_span)[span_1](end_span). [span_2](start_span)[span_3](start_span)It is built upon the **DisSModel** engine, currently under development by the **LambdaGEO** group at UFMA[span_2](end_span)[span_3](end_span).
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The primary geographic focus is the monitoring and modeling of **mangroves**, which are critical ecosystems for coastal resilience, particularly along the coast of Maranhão, Brazil.
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[span_4](start_span)[span_5](start_span)The project addresses a critical gap: providing a modern, Python-based alternative to established but aging modeling infrastructures[span_4](end_span)[span_5](end_span).
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## 🛠️ Technical Objectives
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## 🛠️ Technological Transition
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The framework aims to integrate modern spatial data science tools to overcome the limitations of conventional modeling approaches:
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The core of DisSLUCC is a strategic mapping and evolution of two major scientific models into the Python ecosystem:
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* **Simulation Engine:** Implementing a discrete event logic to model ground-level state transitions over time.
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* **Geospatial Integration:** Heavy utilization of **GeoPandas**, **Rasterio**, and **LuccME** for high-performance vector and raster data manipulation.
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* **Mangrove Focus:** Specific modeling of gain and loss dynamics in coastal transition zones (Apicum-Mangrove).
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* **[span_6](start_span)[span_7](start_span)[span_8](start_span)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[span_6](end_span)[span_7](end_span)[span_8](end_span). [span_9](start_span)[span_10](start_span)This includes both discrete (neighborhood rules) and continuous (CLUE-S approach) allocation algorithms[span_9](end_span)[span_10](end_span).
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* **[span_11](start_span)[span_12](start_span)[span_13](start_span)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[span_11](end_span)[span_12](end_span)[span_13](end_span).
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## 🚀 Impact and SDGs
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## 🔬 Methodology & Infrastructure
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This project is directly aligned with the United Nations **Sustainable Development Goals (SDGs)**:
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[span_14](start_span)[span_15](start_span)The development follows an iterative approach across three phases[span_14](end_span)[span_15](end_span):
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1. **[span_16](start_span)[span_17](start_span)Discrete Models:** Validation of categorical land-use states[span_16](end_span)[span_17](end_span).
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2. **[span_18](start_span)[span_19](start_span)Continuous Models:** Implementation of spatial regression and iterative allocation[span_18](end_span)[span_19](end_span).
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3. **[span_20](start_span)[span_21](start_span)[span_22](start_span)Coastal Dynamics:** Real-world experiments using data from the **Maranhão coast** under IPCC climate scenarios[span_20](end_span)[span_21](end_span)[span_22](end_span).
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* **SDG 13 (Climate Action):** Through the modeling of carbon sequestration and coastal resilience.
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* **SDG 14 (Life Below Water):** Protection of marine and coastal ecosystems.
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* **SDG 15 (Life on Land):** Sustainable forest management and halting biodiversity loss.
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[span_23](start_span)[span_24](start_span)The framework leverages the **Salabim** discrete event engine and supports both vector (**GeoPandas**) and matrix (**NumPy**) substrates[span_23](end_span)[span_24](end_span).
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## 📘 Execution Details
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## 🌍 Sustainable Development Goals (SDGs)
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* **Principal Investigator:** [Prof. Sérgio Souza Costa](http://lattes.cnpq.br/2073311645132958)
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* **Execution Period:** August 2026 – September 2028
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* **Primary Software Output:** [dissmodel](https://github.com/LambdaGeo/dissmodel)
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[span_25](start_span)This research contributes directly to several United Nations SDGs[span_25](end_span):
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* **[span_26](start_span)[span_27](start_span)[span_28](start_span)SDG 4 (Quality Education):** Training students in Geographic Data Science and scientific software engineering[span_26](end_span)[span_27](end_span)[span_28](end_span).
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* **[span_29](start_span)[span_30](start_span)SDG 13 (Climate Action):** Modeling carbon sequestration and climate change impacts[span_29](end_span)[span_30](end_span).
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* **[span_31](start_span)[span_32](start_span)SDG 14 (Life Below Water):** Protecting coastal and marine ecosystems like mangroves[span_31](end_span)[span_32](end_span).
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* **[span_33](start_span)[span_34](start_span)SDG 15 (Life on Land):** Managing sustainable land use and halting biodiversity loss[span_33](end_span)[span_34](end_span).
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## 🔬 Keywords
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`modeling framework` • `LUCC` • `coastal dynamics` • `Python` • `GeoPandas` • `LuccME` • `mangroves` • `discrete event simulation`
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## 📘 Key Information
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* **Principal Investigator:** [Prof. [span_35](start_span)[span_36](start_span)Sérgio Souza Costa](http://lattes.cnpq.br/2073311645132958)[span_35](end_span)[span_36](end_span)
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* **[span_37](start_span)[span_38](start_span)Period:** August 2026 – September 2028[span_37](end_span)[span_38](end_span)
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* **[span_39](start_span)Collaborating Researcher:** Prof. Denilson da Silva Bezerra[span_39](end_span)
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* **[span_40](start_span)[span_41](start_span)[span_42](start_span)Open Science:** All results will be published as open-source code and featured in the upcoming book *Geospatial Modeling with Python*[span_40](end_span)[span_41](end_span)[span_42](end_span).
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> **Opportunities:** We are looking for motivated students and researchers in Applied Computing to join this project. [Contact us for more information](mailto:sergio.costa@ufma.br).
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> **Get Involved:** We are training four undergraduate fellows in **Geographic Data Science**. [span_43](start_span)[span_44](start_span)[span_45](start_span)Check our [GitHub repository](https://github.com/LambdaGeo) for interactive Jupyter Notebooks and framework updates[span_43](end_span)[span_44](end_span)[span_45](end_span).

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