Estimating mangrove aboveground biomass in the Colombian Pacific coast: A multisensor and machine learning approach.

ABSTRACT: The Colombian Pacific Coast is renowned for its exceptional biodiversity and hosts vital mangrove ecosystems that benefit local communities and contribute to climate change mitigation. Therefore, estimating mangrove aboveground biomass (AGB) in this region is crucial for planning and managing these coastal forest covers, ensuring the long-term sustainability of the essential environmental services provided by the Colombian Pacific Coast (CPC). This study employed a spatial estimation approach to assess mangrove AGB, evaluating various parametric and non-parametric models using a multisensor combination and machine learning on the Google Earth Engine (GEE) platform within the CPC. Synthetic aperture radar (SAR) satellite imagery (ALOS-2/PALSAR-2, SRTM, NASADEM, and ALOSDSM) and optical data

SUBMITTER: Selvaraj JJ 

PROVIDER: S-EPMC10618429 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature