Improved DMSP nighttime light monthly products over India

Abstract

ABSTRACT Monthly night-time light (NTL) data can be very useful for studying intra-year socio-economic dynamics. The Earth Observation Group at Colorado School of Mines started providing monthly NTL imagery for free since 2021; based on Defence Meteorological Satellite Program Operational Linescan System (DMSP-OLS) data. In the current study, an attempt has been made to produce an improved monthly DMSP product from 1992 to 2013. The monthly DMSP product suffers from several drawbacks such as spatial inconsistency, random fluctuations in the data for consecutive years, pixel saturation in bright cores, and blooming effect around settlements. As a result, geometric errors, background noise, and radiometric errors persist in the monthly DMSP images. This research tries to address each of these errors by applying various techniques to produce a vigorously tested and improved monthly DMSP dataset consisting of 216 images (1992–2013). Automatic intensity-based registration has been used to register the monthly images to their corresponding annual composite stable light image. Thresholding and land cover data have been used to remove the background noise. Finally, ridgeline regression is implemented considering F14 December 2003 as the reference image. Each technique has been verified by qualitative analysis of the intermediate outputs. The quantitative assessments of the improved monthly DMSP product reveal that it is a good proxy measure when split from 1992 to 2002 and 2003–2013 with an R 2 of 0.84 & 0.82 w.r.t GDP and 0.83 & 0.80 w.r.t population in contrast to the original DMSP data with R 2 of 0.70 & 0.75 w.r.t GDP and 0.73 and 0.80 w.r.t population. Transect analysis across six urban cities verifies that the improved product shows reduced saturation in urban areas and increased contrast in sub-urban regions. Finally, a consistent monthly DMSP product is delivered to the research community which will be useful for studying time-series intra-year changes in urbanization, economic growth, and other socio-economic dynamics.