Algorithms for Analysis of Geolocation Error of Nightlight Satellite Data and Greenhouse Gas Data Calculated on Their Basis

This study develops an approach, algorithms and software to analyse the bias of nightlights remote sensing satellite data and corresponding bias calculated on the basis of global data on greenhouse gas emissions. We used city boundary data from Open Street Map, as well as high-resolution Open-Source Data Inventory for Anthropogenic CO2 (ODIAC) data on carbon dioxide emissions. We based the algorithms of the analysis on the iterative calculation of correction vectors for shifting emission data that provide the maximum magnitude of carbon dioxide emissions within the administrative boundaries of cities. We demonstrate the main stages of the proposed algorithm implementation for a number of cities from different continents.