Gis Based Spatial Analysis and Prediction of Covid-19 Cases

Abstract

COVID-19 has come out to be a threat that has far-reaching repercussions in all parts of human existence; as a result, it is the most pressing concern facing countries around the world. This paper is centred on using a geographic information system to map COVID-19 instances across India, followed by COVID-19 case projections in various areas of India. A geographic information system (GIS) is a computer system that verifies, records, stores and displays data about places on the Earth’s surface, with India as the primary emphasis. Because the COVID-19 has had a distinct influence on different parts of India, the research we conducted provides a correct connection between past, current, and future instances in India employing prediction by using the SARIMA(Seasonal Autoregressive Integrated Moving Average) model to forecast time series. Python is used to implement the project. Several databases, including global databases like Natural Earth, UNEP Environmental Data Explorer, GRUMP, and national databases like Open Data Archive and ISRO’s Geo-Platform, are utilised to collect data for mapping and displaying instances across the country. These databases are combined to get the required output that is to be plotted and displayed. The prediction of coronavirus cases has also been done using the SARIMA model with an accuracy of 95.37percent.