Spatiotemporal dynamics and machine learning-based prediction of aboveground biomass in the Indus delta mangroves

This dataset provides spatially explicit estimates of mangrove aboveground biomass (AGB) and associated environmental variables for the Indus Delta mangrove ecosystem. Field-based AGB spatial data were derived from the NASA CMS Global Mangrove Distribution, Aboveground Biomass, and Canopy Height dataset and used as reference data for model development. Multisource remote sensing data, including Sentinel-1 and Sentinel-2 optical imagery, were processed to extract predictor variables such as vegetation indices and surface characteristics. Additional environmental variables, including land surface temperature and land use/land cover, were incorporated to capture ecological controls on biomass distribution.
All satellite datasets underwent standard preprocessing steps, including atmospheric correction, radiometric calibration, cloud masking, and spatial resampling. The processed variables were then integrated into machine learning models (Random Forest, Gradient Boosted Regression Tree, Sup..., , # Spatiotemporal dynamics and machine learning-based prediction of aboveground biomass in the Indus delta mangroves

Dataset DOI: [10.5061/dryad.h44j0zq1m](https://doi.org/10.5061/dryad.h44j0zq1m)

## **1.** README File Description

This dataset contains spatially explicit predictions of aboveground biomass (AGB) for coastal mangrove ecosystems under future climate scenarios (2030, 2040, and 2050). Predictions were generated using multiple machine learning algorithms, including:

* CART (Classification and Regression Trees)
* RF (Random Forest)
* SVR (Support Vector Regression)
* XGBoost

The dataset also includes shapefiles defining the study area and buffer zones used in spatial analysis.

## 2. Description of File Types

This dataset includes several file formats that serve different purposes. The `.txt` files are plain text tabular data files containing spatial prediction outputs, including coordinates and predicted aboveground biomass (AGB) values. These files can be opened using s..., ,