Night-Time Light Data and their Application on Post-Disaster Response Situation After a Winter-Storm Induced Power Outage Event

Keywords: nighttime light data, GIS, social segregation, post-disaster recovery, remote sensing, spatial analysis
Abstract Type: Virtual Paper Abstract

Abstract

Night-time Light data (NTL) has been an important source of data to analyze different types of Human-Environment interaction. This paper looks at the changes in Human Activity in a disaster-affected area to understand the post-disaster recovery efforts in the context of remote sensing, which enables the opportunity to act quickly for the authority to assist in the relief and reconstruction effort. It also investigates whether social segregation occurs in the rehabilitation effort in order to minimize it in the future. Based on the theory of the post-disaster recovery model (Haas et al, 1977) different indicators including pre-disaster development rate, recovery rate, reconstruction rate, post-disaster development rate, and relative reconstruction rate are defined by time-series data analysis. As a case study, the power outage event after the winter storm of 2021 in Texas has been chosen. For this study, the daily data of NASA's Black Marble night-time lights product suite (VNP46) from January 01 to March 30 of 2021 have been studied. Using regression analysis, the relationships are shown between the analyzed NTL and human activity, right after a natural disaster like a winter storm. As the most active response and recovery efforts take place immediately after the disaster event, daily data paints the most accurate picture of the post-disaster recovery process. This paper shows the imbalance between high-income and low-income neighborhoods in the power restoration process. This documentation also considers the scenarios where power restoration is of high priority, which will be helpful for decision-makers after any emergency.