ABSTRACT
This chapter focuses on a national study of Coronavirus disease (COVID-19) using remote sensing (RS) indicators in Iran. Time-series analysis is performed on RS indicators (n=12) including wind speed, temperature, evaporation, carbon monoxide (CO), nitrogen dioxide (NO2), Sulphur dioxide (SO2), ozone (O3), formaldehyde (HCHO), cloud cover, precipitation, air pressure and soil moisture (SM) to identify remotely sensed products that may contribute to COVID-19 transmission. Epidemiological investigations of infectious diseases mostly concentrate on medical aspects and infection control and disregard the geographic components of the diseases. Surface pressure (SP) is an indicator that effects some respiratory diseases such as chronic obstructive pulmonary disease, therefore it is employed in this study. Soil Moisture (SM) is an environmental indicator that can be provided by RS data. Copernicus program provides some environmental parameters that can present appropriate information about diseases.
