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Google Earth Engine and R Scripts for LULC Classification and Environmental Correlation Analysis: Abijata–Shalla Lakes National Park, Ethiopia

Domain:

geospatialenvironment and energy

Record type:

softwaredataset
Creator:
Dad
Publisher:
Zenodo
Host:avatar

This repository contains the data processing and analysis scripts used in the study of land use/land cover (LULC) dynamics and environmental variable relationships in Abijata–Shalla Lakes National Park, Ethiopia.

The code supports two main components of the research:

1. LULC classification using Google Earth Engine (GEE)

A supervised classification workflow based on Landsat 8 imagery (2024) using the CART (Classification and Regression Tree) algorithm. The script includes cloud masking, image compositing, training data integration, land cover classification, and accuracy assessment, including Overall Accuracy, Kappa coefficient, Producer’s Accuracy, and User’s Accuracy. The final classified map is exported as GeoTIFF, and accuracy metrics are exported as CSV files.

2. Correlation analysis of environmental variables using R

An R-based workflow for computing and visualizing correlation matrices of bioclimatic and topographic variables. The script generates a publication-quality heatmap using the ggcorrplot package and exports a high-resolution figure suitable for journal publication.

Contents of this repository

  • Google Earth Engine script for LULC classification (LULC_Classification_GEE.js)
  • R script for correlation matrix visualization (Correlation_Matrix_R.R)
  • README file with instructions for reproducibility
  • List of required R packages (requirements.txt)

Visit

doi.org

Tasks

computer visionimage classification

Languages

Ndasa

Tags

LULC, Google Earth Engine, Landsat 8, CART, R, correlation matrix, Ethiopia, remote sensing, Abijata-Shalla

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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