Giacomo Falchetta's Projects
Replication code and data for: Aging in a warming world: global projections of cumulative and acute heat exposure of older adults
blackmaRble: retrieve, wrangle and plot VIIRS Black Marble nighttimelight data in R
Code and data to replicate the analysis of the paper titled 'Role of residential air circulation and cooling for universal household electrification'
scripts and snippets for Google Earth Engine
Script and data from: "A Gridded Dataset to Assess Electrification in Sub-Saharan Africa" by Giacomo Falchetta, Shonali Pachauri, Simon Parkinson, and Ed Byers
"Comparing transit in seven major African cities: an accessibility and network analysis" code and data
This repository hosts code and data to reproduce the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.
Generates input data for energy models on renewable energy in arbitrary world regions using public datasets. Written in Julia 1.x.
R script to convert a GTFS feed into an igraph object for network analysis in R
Monitoring hydropower reliability in Malawi with satellite data and machine learning
Replication code and data for the paper 'Satellite observations reveal inequalities in the progress and effectiveness of recent electrification in sub-Saharan Africa'
Repository of M-LED, the Multisectoral Latent Electricity Demand assessment platform.
Environmental and energy implications of meat consumption pathways in sub-Saharan Africa
PyPSA meets Africa: An Open Source Optimisation Model of the African Energy System. Our website: https://pypsa-meets-africa.github.io/
Documentation for the LEAP-RE RE4AFAGRI platform
Main code for the paper "Solar irrigation in sub-Saharan Africa: economic feasibility and development potential", by Giacomo Falchetta, Francesco Semeria, Marta Tuninetti, Vittorio Giordano, Shonali Pachauri, and Edward Byers
An open-data, open-source model to estimate urban green space and its temporal evolution globaly
Scripts used to compile the paper 'Interannual variation in Night-Time Light Radiance predicts changes in National Electricity Consumption conditional on Income-Level and Region' by Giacomo Falchetta and Michel Noussan