This repository provides the complete Google Earth Engine (GEE) pipeline for mapping the annual increment, extent, age, and loss of secondary vegetation across Brazil and Amazonia at 30-meter spatial resolution for the period 1986–2024.

Land-use and land-cover maps from the MapBiomas Project (Collection 10.1) are used as input data. The algorithm identifies secondary vegetation by detecting transitions from anthropic land use back to native vegetation classes in the MapBiomas annual time series. This dataset provides critical spatially explicit information for supporting carbon emissions reduction, biodiversity, and restoration policies.

Figure 1. Conceptual diagram of the land-use dynamics underlying the secondary vegetation mapping algorithm. Old-growth forest (1985) is cleared by fire and converted to agriculture and livestock. Abandoned land undergoes early succession, developing into secondary forest. A second deforestation cycle (2018) illustrates the recurrent nature of secondary vegetation dynamics detected annually from the MapBiomas land-cover time series.

• Windows 10/11 (64-bit)
• macOS 12+
• Ubuntu 22.04 LTS

No non-standard hardware is required. All computations run on Google's cloud infrastructure.

No local installation is required. GEE runs entirely in the browser.

1. Register for a free GEE account at https://earthengine.google.com (approval typically takes 1–2 business days)
2. Open the GEE Code Editor
3. Copy and paste the contents of the desired script (see Repository Structure below)

Typical setup time: < 5 minutes (after account approval).

gee_brazil_sv/
│
├── 🌐 gee_brazil_sv_code.js                        ← Brazil mapping script (v8.1)
├── 🌐 gee_amazonia_sv_code.js                      ← Amazonia mapping script (v3)
├── 🔽 gee_brazil_sv_toolkit_download.js            ← Download toolkit by boundaries (v0.0.2)
├── 📤 Secondary_Vegetation_TIFfile_Export_Tool.js  ← Per-year GeoTIFF export tool
│
├── 📂 figures/                                     ← Repository figures
└── 📄 README.md

Maps the annual increment, extent, age, and loss of secondary vegetation across all of Brazil using MapBiomas Brazil Collection 10.1 (1986–2024). Configurable via the block at the top of the script:

var firstYear           = 1985;               // First year of the data series
var lastYear            = 2024;               // Last year of the data series
var mapbiomasCollection = 'collection10_1';   // MapBiomas collection version
var mappingVersion      = 'v8_1';             // Version of the mapping process
var assetFolder         = 'users/ybyrabr/public'; // Destination folder for exported assets

Exports four multi-band GEE assets (one band per year): secondary_forest_increment_, secondary_forest_extent_, secondary_forest_age_, and secondary_forest_loss_.

Maps secondary vegetation specifically within the Amazonia biome using MapBiomas Amazonia Collection 6 (1986–2023). Configurable similarly:

var firstYear           = 1985;          // First year of the data series
var lastYear            = 2023;          // Last year of the data series
var mapbiomasCollection = 'collection6'; // MapBiomas Amazonia collection version
var mappingVersion      = 'v3';          // Version of the mapping process
var assetFolder         = 'users/ybyrabr/public'; // Destination folder for exported assets

Exports the secondary vegetation datasets as annual GeoTIFF files to Google Drive, one file per year. Configurable via the top block:

var collection    = 'collection9'; // MapBiomas collection name
var mappingVersion = 'v71';        // Mapping version
var lastYear      = 2023;          // Last year to export
var startYear     = 1986;          // Start year (age, extent, increment)
var lossStartYear = 1987;          // Start year (loss dataset)
var type          = 3;             // Vegetation type (3 = Forest Formation)

An interactive GEE application that allows users to visualize and download secondary vegetation data by administrative boundaries (states and municipalities), watersheds, biomes, and protected areas — without writing any code.

1. Open the GEE Code Editor
2. Copy and paste gee_brazil_sv_code.js (Brazil) or gee_amazonia_sv_code.js (Amazonia)
3. Adjust the configuration block at the top if needed (e.g., lastYear, assetFolder)
4. Click Run — all export tasks appear in the Tasks panel
5. Click Run on each task to start the exports to your GEE asset folder

Expected run time: 5–60 minutes per task (cloud-based; varies with server load and region size).

If you prefer to download annual GeoTIFF rasters rather than using GEE assets:

1. Copy and paste Secondary_Vegetation_TIFfile_Export_Tool.js into the GEE Code Editor
2. Edit the configuration block to match the asset version and years you want
3. Click Run — export tasks appear in the Tasks panel
4. Click Run on each task to export to Google Drive

Output: One GeoTIFF per year per product (age, extent, increment, loss), clipped to Brazil at 30 m resolution.

For downloading data clipped to specific states, municipalities, biomes, or protected areas:

1. Copy and paste gee_brazil_sv_toolkit_download.js into the GEE Code Editor, or access it directly: https://code.earthengine.google.com/13bfcedb77ac7bac9ea1fb962b587a54?hideCode=true
2. Select the desired boundary and data type
3. Click Export images to Google Drive

Expected run time: < 5 minutes per export.

The processed datasets are publicly available as multi-band GEE assets. Each band represents one year, named classification_YYYY. To load the latest version in GEE:

var age       = ee.Image('users/ybyrabr/public/secondary_forest_age_collection10_1_v8_1');
var extent    = ee.Image('users/ybyrabr/public/secondary_forest_extent_collection10_1_v8_1');
var increment = ee.Image('users/ybyrabr/public/secondary_forest_increment_collection10_1_v8_1');
var loss      = ee.Image('users/ybyrabr/public/secondary_forest_loss_collection10_1_v8_1');

Replace {product} with age, extent, increment, or loss.

The final data layers (v2) are also available in the Zenodo repository: https://doi.org/10.5281/zenodo.3928660

The algorithm operates in four sequential steps applied annually to the MapBiomas land-cover time series:

If you use this code or data, please cite:

@article{silvajunior2020,
  author  = {Silva-Junior, Celso H. L. and Heinrich, Viola H. A. and Freire, Ana T. G.
             and Broggio, Igor S. and Rosan, Thais M. and Doblas, Juan and Anderson,
             Liana O. and Rousseau, Guillaume X. and Shimabukuro, Yosio E. and
             Silva, Carlos A. and House, Joanna I. and Aragão, Luiz E. O. C.},
  title   = {Benchmark maps of 33 years of secondary forest age for {Brazil}},
  journal = {Scientific Data},
  year    = {2020},
  doi     = {10.1038/s41597-020-00600-4}
}

• Silva-Junior, C. H. L., et al. Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data (2020). https://doi.org/10.1038/s41597-020-00600-4

• Heinrich, V. H., Dalagnol, R., et al. Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change. Nature Communications (2021). https://doi.org/10.1038/s41467-021-22050-1

• Heinrich, V. H., Sitch, S., et al. RE:Growth — A toolkit for analyzing secondary forest aboveground carbon dynamics in the Brazilian Amazon. Frontiers in Forests and Global Change (2023). https://doi.org/10.3389/ffgc.2023.1230734

• This mapping was funded by the National Council for Scientific and Technological Development — CNPq, Brazil, through the project "YBYRÁ-BR: Space-Time Quantification of CO₂ Emissions and Removals by Brazilian Forests", Process CNPq 401741/2023-0 (from v6.1)
• This mapping was supported by the Coordination for the Improvement of Higher Education Personnel — CAPES, Brazil, Finance Code 001 (v2 to v5)

This project is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

You are free to:

• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material for any purpose, even commercially

Under the following terms:

• Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made

See the LICENSE file for full details or visit https://creativecommons.org/licenses/by/4.0.