Uneven urban resilience across economic sectors revealed by satellite nighttime lights

This repository contains the processed data and source data used in the study. The repository contains two main folders: cities source_data_for_main_figs. cities This folder contains one subfolder for each study city. Each city folder contains two subfolders: clipped_lc and lu. The clipped_lc folder contains the downscaled nighttime-light data after application of the stable land-cover mask. The lu folder contains the land-use data. Depending on the city, it includes one, two, or three sector-specific subfolders: commercial, industrial, and retail. Each sector-specific land-use folder contains the stable land-use mask used to extract nighttime-light values for the corresponding sector. Acronyms for city names: abu = Abu Dhabi ba = Buenos Aires cape = Cape Town hk = Hong Kong la = Los Angeles mexico = Mexico City ny = New York rio = Rio de Janeiro sp = Sao Paulo wash = Washington DC source_data_for_main_figs This folder contains three CSV files: commercial_midpoint.csv industrial_midpoint.csv retail_midpoint.csv Each file contains city-level nighttime-light midpoint values for the pre-lockdown, lockdown, and post-lockdown periods, together with the corresponding recovery-archetype classification and business-type information. These files provide the source data for Fig. 2d–f, which show gross impact, recovery, and net impact across recovery archetypes, and for Fig. 3, which presents the Multiple Correspondence Analysis of recovery archetypes, sector type, and essentiality. The four primary recovery archetypes are Chronic Decline, Partial Recovery, Full Recovery, and Resilient. Where present, the Other category represents trajectories that did not meet the classification criteria for the four primary archetypes.