Programming code for: Supporting ecological restoration: leveraging satellite data and machine learning to map invasive alien tree biomass

Programming code for: Supporting ecological restoration: leveraging satellite data and machine learning to map invasive alien tree biomass

This repository hosts the code for the processing of raw biomass and satellite-derived datasets to develop an invasive alien tree biomass model.

Summary
In this study we aim to test the performance of multi-source remote sensing-derived datasets for the estimation of biomass of invasive alien trees in South Africa.

LiDAR and field-measured invasive alien tree metrics were used to develop a regional biomass model for an alien infested region of the Aguhlas Plain, in the Cape Florisitc Region of South Africa. This study leveraged satellite-derived datasets (Sentinel-1, Sentinel-2, SRTM, GEDI-L2A, and Global Canopy Height) and machine learning to develop a regional-scale model for estimating invasive alien tree biomass at a 25m resolution. Performance of the models were assessed using the coeffiecent of determination (R-squared), Spearman correlation coeffiecent (rs), PBias, and RMSE. Predictor variable importance were also tested for. Once the models were developed, they were validated with an independant alien infested ground truth site. Additionally, the most effective model was applied to ecologically distinct catchments to test model transferability and to demonstrate how the model could be used in a practical management scenario.

• Note: 'Invasive alien trees' refer to taxa such as Pinus, Eucalyptus, Neltuma, and Acacia spp that are non-native to South Africa that can displace native vegetation and cause environmental and economic harm.

Repository Components
The components of this repository include five primary phases each including a set of method workflow notes and code scripts
The five phases include the following:

(1) Develop a target variable dataset

(2) Develop a predictor variable dataset containing different data types

(3) Model Validation

(4) Ground-truthing

(5) Model application

 

Google Earth Engine App

The invasive alien tree biomass maps for each catchment can be found here:

• Tugela: ee-lscogill4.projects.earth…
• Luvuvhu: ee-lscogill4.projects.earth…
• Olifants-Doring: ee-lscogill4.projects.earth…