Replication code and data for the paper 'Satellite observations reveal inequalities in the progress and effectiveness of recent electrification in sub-Saharan Africa'
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Updated
Mar 18, 2020 - JavaScript
Replication code and data for the paper 'Satellite observations reveal inequalities in the progress and effectiveness of recent electrification in sub-Saharan Africa'
This code snippet demonstrates the geospatial analysis and visualization of Equatorial Guinea using Google Earth Engine. It includes layers for slope analysis, gross primary productivity (GPP), normalized burn ratio thermal (NBRT), and normalized difference vegetation index (NDVI)
This script aims to determine the most suitable threshold for surface water extraction from Sentinel-1 image and provide a fully automatic processing chain for detecting, monitoring surface water and mapping water dynamics.
📖 🌎 Scripts written during DEVELOP training in Google Earth Engine based on modules from Colorado State University.
Code for generating satellite imagery optimised for marine environment using Google Earth Engine
Common Codes for Google Earth Engine.
Based on my research work
Once you have successfully configured the project in Google Earth Engine, you can utilize the link I have provided below. Simply by pressing the "run" button, you can execute the command or script that I have prepared.
Extract the sea surface temperature from a polygon using google earth
Visualising Australian census data on Google Maps. Various cloud services and ReactJS used.
Greater Mekong Subregion - Malaria Vector Risk Assessment
Repositório de códigos utilizando a API Google Earth Engine
Google Earth Engine code for rapid point spectral signature selection on BCET-normalised scenes
Precipitation dataset comparison in GEE. Supplementary material (code and data) for the article submitted for IGARSS 2024, entitled Evaluation of precipitation datasets available in Google Earth Engine on a daily basis for Czechia.
Sample GEE scripts for the vscode EE tasks extension
Harness the power of Google Earth Engine to effortlessly generate detailed flood susceptibility maps and images. Empowering researchers and responders to assess and mitigate flood risks with precision. Your go-to resource for informed decision-making in flood-prone areas
Collection of introductory scripts and exercises for Google Earth Engine.
Supplementary material for the article "Automatic classification of forests using Sentinel-2 multispectral satellite data and machine learning methods in Google Earth Engine"
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