fujingyao2023-cell/Electrification-status-across-Africa-at-10-m-resolution-derived-from-SDGSAT-1-nighttime-lights

Electrification status across Africa at 10 m resolution derived from SDGSAT-1 nighttime lights # SDGSAT-1 Building Electrification Processing Code This repository contains scripts used to process SDGSAT-1 nighttime light rasters and building-related raster products for building electrification mapping. ## Workflow 1. Projection and coordinate harmonization to World Mollweide. 2. Radiometric calibration of the SDGSAT-1 PL band. 3. Noise removal using ESA WorldCover land-cover classes. 4. Binary classification of nighttime light and building rasters. 5. Maximum Value Composite (MVC) synthesis for annual nighttime light products. 6. Combination of classified nighttime light rasters with a building mask raster. Large input, intermediate, and output raster data are not stored in this GitHub repository. They should be archived separately, for example on Zenodo, and cited in the paper and in this README. ## Software Requirements - ArcGIS Pro 3.x - ArcPy - ArcGIS Spatial Analyst extension - Python environment included with ArcGIS Pro These scripts use ArcPy, so they are not fully open-source Python workflows. This is acceptable for a data paper if the manuscript and repository clearly state the ArcGIS Pro dependency and document the workflow. A full Python rewrite is only necessary if the target journal requires an entirely open-source reproducible workflow or if the project aims to remove commercial software dependencies. ## Repository Structure ```text code/ 01_projection_mollweide.py 02_radiometric_calibration.py 03_data_binary.py 04_multiply_building.py config/ config_example.json docs/ ArcGIS_processing_workflow.md requirements.txt ``` ## Example Commands Run these commands from the repository root in the ArcGIS Pro Python environment. ```powershell python code/01_projection_mollweide.py ` --input-dir data/raw_sdgsat ` --output-dir data/processed/01_projected_mollweide ` --spatial-reference 54009 ` --cell-size 10 ` --resampling-type NEAREST ``` ```powershell python code/02_radiometric_calibration.py ` --input-dir data/processed/01_projected_mollweid …