Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modelling Approach
Open Access
- 6 July 2020
- journal article
- research article
- Published by MDPI AG in Sustainability
- Vol. 12 (13), 5464
- https://doi.org/10.3390/su12135464
Abstract
The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10 concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.Keywords
Funding Information
- University of Technology Sydney (Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS))
- King Saud University (Researchers Supporting Project number RSP-2020/14)
This publication has 43 references indexed in Scilit:
- Spatio‐temporal modelling and analysis of urban heat islands by using Landsat TM and ETM+ imageryInternational Journal of Remote Sensing, 2009
- Measuring the quality of life in city of Indianapolis by integration of remote sensing and census dataInternational Journal of Remote Sensing, 2007
- Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity DelhiEnvironmental Monitoring and Assessment, 2006
- Green Urban Political Ecologies: Toward a Better Understanding of Inner-City Environmental ChangeEnvironment and Planning A: Economy and Space, 2006
- Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeansRemote Sensing of Environment, 2004
- Natural Environments—Healthy Environments? An Exploratory Analysis of the Relationship between Greenspace and HealthEnvironment and Planning A: Economy and Space, 2003
- Relationships between percent vegetation cover and vegetation indicesInternational Journal of Remote Sensing, 1998
- Classification-based emissivity for land surface temperature measurement from spaceInternational Journal of Remote Sensing, 1998
- Survey of emissivity variability in thermography of urban areasRemote Sensing of Environment, 1982
- A scaling method for priorities in hierarchical structuresJournal of Mathematical Psychology, 1977