Quantifying Nighttime Light Changes in KL, Putrajaya, and Selangor from Human Activities Impact of Pandemic COVID-19

The Malaysian government has implemented extensive physical distancing measures to prevent and control virus transmission in response to the pandemic COVID-19. Particularly in the Kuala Lumpur, Putrajaya, and Selangor regions, quantitative, spatially disaggregated information about the population-scale shifts in an activity caused by these measures is extremely rare. A next-generation space-borne low-light imager called the Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS-DNB) can monitor changes in human activities. However, a cross-country examination of COVID-19 replies has not yet utilized the potential. To understand how communities have complied with COVID-19 measures in the two years since the pandemic. This study aims to quantify nighttime light (NTL) before and during COVID-19 using multi-year (2019–2021) monthly time series data derived from VIIRS nighttime light (NTL) products covering urban areas in Selangor, Putrajaya, and Kuala Lumpur. The NTL was processed in the Google Earth Engine (GEE) platform. NTL data has documented the link between curfew orders, nationwide closures, and the uneven response to control measures between and within the areas. Our findings demonstrate satellite images from VIIRS DNB can examine public opinion regarding national curfews and lockdowns, laws, and the sociocultural elements that influence their effectiveness, particularly in unstable and sparsely populated areas. Statistical T-test analysis revealed that the p-value for Kuala Lumpur was 0.01687, and less than 0.05 meant a significant difference between NTL reduction before and during COVID-19. Petaling showed a p-value of 0.0034 and less than 0.05, indicating a significant difference between NTL reduction before and during COVID-19. However, for area Putrajaya, the p-value is 0.0957, and more than 0.05 means there is no significant difference between the reduction of NTL before and during COVID-19.