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Improve Pasture Mapping in the Cerrado Biome

Institutional repository containing data, high-performance analytical pipelines (DuckDB / Python), and an interactive web platform developed under the agreement between WRI Brasil and FUNAPE, with technical execution by LAPIG/UFG in cooperation with Embrapa Cenargen (Project GR000153-73077-CARGILL-BRAZIL).

Deliverable: Product 1 — Detailed Sampling Plan and Sampling Improvement Strategies (August 17, 2026).


📊 Summary of Datasets & Sample Series

The platform integrates 62,009 candidate samples (in 2025) across a multi-year historical series (2020 to 2025), matched via 64-dimensional L2-renormalized cosine similarity against Embrapa's 701 in situ reference polygons (~1 ha; 608 classified across 7 pasture condition categories + 93 unlabeled):

Sample Series Description & Stratification Samples / Year (2025) Provenance & Nature
50k Series Stratified random sampling from persistent pasture (2020–2025) 50,000 Proportional to 2025 vigor strata: Low (~35%), Medium (~44%), High (~21%)
12k Series MapBiomas Col. 4 S2 (5,453) + MapBiomas 85k Landsat validation (6,556) 12,009 Visual inspection pasture samples & interpreted validation subset
Total Candidates Inclusive universe before similarity, SOM, and CBERS-4A filters 62,009 Scenarios: Inclusive (62,009) vs. Agreement with Col. 11 (56,952)
Embrapa Reference In situ field reference polygons (~1 ha) 701 608 classified across 7 categories + 93 unclassified

Annual Breakdown of the 12k Series:

  • 2019: 12,483 points
  • 2020: 12,386 points
  • 2021: 12,281 points
  • 2022: 12,149 points
  • 2023: 12,080 points
  • 2024: 12,034 points
  • 2025: 12,009 points

🌐 Interactive Web Platform (docs/)

Built upon a lightweight, modular static architecture (compatible with Jekyll and GitHub Pages Source: /docs) featuring browser GPU acceleration via Leaflet Canvas Markers and dynamic charts via Chart.js:

  • Home Page (/): Institutional overview, objectives, key figures, and section navigation.
  • Md3 Analysis (/analise-top3/):
    • Unified Filter Panel: Instant switching between the 50k Series and the 12k Series, year selection (2019 to 2025), pasture vigor filtering (CVP 1, 2, 3), Md3 similarity thresholds (0.00 to 0.95), full-text search, and typology checkboxes.
    • Spatial Bounding Box Selection: Tool to interactively select any custom geographic bounding box across the Cerrado, automatically updating counters, charts, and sample inspection tables.
    • Synchronized Dual Charts: Chart 1 (Dynamic MapBiomas sample distribution in the active view) and Chart 2 (Fixed distribution of Embrapa's 701 ground-truth points).
    • Detailed Table: Inspection of Top-3 dot products, reference FIDs, target coordinates, and assigned typologies.
    • Static Deliverables: Direct downloads of technical Reports, Presentation decks, GEE Assets, Python scripts, and Open Data tables in Parquet, CSV, and JSON formats.
    • SOM (Self-Organizing Maps): Section dedicated to unsupervised topological neural network clustering.

📁 Repository Directory Structure

lapig-wribrasil/
│
├── 🌐 docs/                          # Web Platform (Jekyll / GitHub Pages: /docs)
│   ├── _config.yml                  # Central Jekyll configuration (baseurl: "/lapig-wribrasil")
│   ├── _layouts/                    # Base layouts (default.html, page.html)
│   ├── _includes/                   # Modular HTML includes (map_viz, Produtos_Estaticos, etc.)
│   ├── assets/                      # Stylesheets, JavaScript engine, and JSON/CSV datasets
│   ├── material_suplementar/        # Technical Report (PDF) & Presentation (PDF)
│   ├── analise-top3/                # Md3 Analysis & Deliverables page
│   ├── comparacao/                  # Scenario comparison page
│   └── index.html                   # Homepage
│
├── 📊 dados/                         # Data Pipelines & Processing Engine
│   ├── arquivos_base/               # Raw Sentinel-2 embeddings, Embrapa points, MapBiomas inputs
│   ├── arquivos_saida/              # Processed Top-3 Parquets (50k & 12k Series · 2019–2025)
│   └── scripts/                     # Python / DuckDB processing pipelines
│
├── 📁 documentos/                    # Reports, Slide Decks, QGIS Styles & Maintenance Guides
│   ├── Report_Product_1_*.pdf       # Technical Report PDF
│   ├── Scaling_Ground_Truth_*.pdf   # Executive Presentation PDF
│   ├── campo_md3.pptx               # Field Presentation Deck
│   ├── qgis_cores.qml               # QGIS layer styling palette
│   └── procedimentos_manutencao/    # Maintenance & configuration documentation
│
├── 🛠️ servidor_local.py              # Local testing server (serves docs/ in real time)
├── 📄 LICENSE                       # Creative Commons Attribution 4.0 (CC BY 4.0)
└── 📘 README.md                      # Repository presentation and documentation

🚀 How to Run the Local Server

To preview the web platform locally in real time:

python servidor_local.py

Open in your browser: http://localhost:8000 or http://localhost:8000/analise-top3/.


🛠️ Reproducing Data Pipelines

1. Generate Top-3 Tables for the 50k Series (2019–2025)

python dados/scripts/gerar_top3_pivotada_50k.py --year all

2. Generate Top-3 Tables for the 12k Series (2019–2025)

python dados/scripts/gerar_top3_pivotada_11k.py --year all

3. Update Embrapa Reference Dataset (701 Points)

python dados/scripts/exportar_referencia_embrapa.py

🌿 Canonical Pasture Typologies (Embrapa)

Ground-truth samples and spectral similarity predictions are categorized into 7 primary classes:

  1. Productive Pasture (#faea40): Well-managed pasture with high forage biomass.
  2. Pasture with Weeds (#d8ff6c): Infestation of herbaceous/ruderal invasive plants.
  3. Pasture with Shrubs / Woody Species (#66c600): Significant presence of shrub and tree canopy layers.
  4. Intermediate Pasture (#f4b346): Moderate vegetative vigor with mixed grass and soil coverage.
  5. Biological Degradation (#813209): Severe degradation with prominent bare soil.
  6. Natural Regeneration (#0e5f0e): Areas undergoing natural recovery of native Cerrado vegetation.
  7. Miscellaneous (#ec2b10): Atypical, transitional, or mixed land-use features.

🤝 Partner Institutions

  • LAPIG / UFG — Image Processing and Geoprocessing Laboratory (Federal University of Goiás)
  • WRI Brasil — World Resources Institute Brasil
  • Embrapa — Brazilian Agricultural Research Corporation

📄 License

This work, including all code, datasets, documentation, and web assets, is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

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