Four-Dimensional Covid-19 Simulation in Slums Using Hologram Interferometry of Sentinel-1A—Satellite

Abstract

This study is the first work in implementing four-dimensional (4-D) hologram interferometry to simulate COVID-19 rate variations in slums using microwave remote sensing technology. The study also proposed a new mathematical formula to simulate the rate of COVID-19 from 4-D hologram interferometry; termed as Marghany’s 4-D hologram SAR interferometry. The most critical challenge of the world is pandemic COVID-19; which is spreading widely across slums. Slums are considered the main source of criminals and diseases owing to lack of perfect housing, unsanitary conditions, poor infrastructures and occupancy security. The meagre in the impenetrable urban slums are the furthermost susceptible to impurity because of (i) scarce and delimited admission to wellbeing drinking water and satisfactory extents of water for individual sanitation; (ii) the absence of elimination and handling of an excretory product; and (iii) the lack of removal of solid waste. In this view, urban slum requires the standard and accurate method to be identified automatically from remote sensing data. In this context, a remote sensing technique plays a tremendous role in monitoring land use spatial variations. The data are used that involved historical three Sentinel-1A data. The consequences present that the hologram Interferometric technique is being an admirable device for a disordered urban slum in place of it can differentiate between them from its adjacent setting. Reconstruction of a 4-D urban slum is delivered by hologram Interferometric phase unwrapping based on Particle Swarm Optimization (PSO), besides historical time variations of COVID-19 are allied with slum. Hologram interferometric reveals a countless imbrication of COVID percentage rate of 1.2% between high-class zone with the urban slum. The consequences disclose that urban slums, road networks, and infrastructures are effortlessly categorized. In conclusion, the hologram Interferometric based on Particle Swarm Optimization (PSO) is an appropriate algorithm for chaotic 4-D urban slum automatic detection in Sentinel-1A.