Mapping Tree Species Alpha Diversity in an Ecuadorian Seasonally Dry Forest 

  • 2 February 2023
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A recent study conducted in a natural reserve in the Tumbes-Chocó-Magdalena biodiversity hotspot in Ecuador has highlighted the importance of using satellites to estimate tropical forest diversity. 

In the study called “Ensemble Machine Learning for Mapping Tree Species Alpha-Diversity Using Multi-Source Satellite Data in an Ecuadorian Seasonally Dry Forest”, researchers used LiDAR models of the forest canopy from the GEDI mission, combined with RapidEye, Sentinel 2 images, topographic models and field data (tree species, stem diameter and height).

This study informs the relationship between SDTF tree diversity and remotely sensed data in southwestern Ecuador using mixed sensor types and ML. It offers opportunities for replication in other regions with similar conditions.

These initiatives support informed decision making on forest management in the tropics. 

We think this is a relevant example for NICFI users that might be applicable for their research.


Check out this link to read the full article.

Tags: NICFI, NICFI User Stories, Ecuador, machine learning

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