The University of Southampton
University of Southampton Institutional Repository

Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data

Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data
Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data
The Severe Acute Respiratory Syndrome-COronaVIrus Diseases 2019 (SARS-COVID-19) has sternly affected the entire world in terms of human health, loss of lives, and huge economic losses. However, pandemic-triggered lockdown (LD) events (as a preventive measure) have compelled to stop or reduce major economic activities, exerting positive impacts on the terrestrial environment. We deployed a variety of satellite products (i.e., normalized difference vegetation index (NDVI), solar-induced chlorophyll fluorescence (SIF), and aerosol optical depth (AOD)) along with gridded climatic dataset (temperature (TEMP), precipitation (PREC), and net radiation (NR)) to quantify the changes in vegetation activity (greenness and productivity) during the LD period over the Indian biogeographic provinces (BGPs) as compared to the average conditions over the previous three years (2017-2019). The analysis of the NDVI and SIF data revealed that vegetation greenness and productivity significantly enhanced during LD periods (by up to 37 to 55%, respectively). The influence of climatic drivers (PREC, TEMP, and NR) on vegetation activity was also investigated. We found that the enhancement in the vegetation activity (over BGPs) during the LD period was not entirely driven by the climatic parameters, and was therefore inferred to be also influenced by the LD events. Moreover, vegetation activity around the mining clusters were largely improved during the LD period (by up to 78%) over the coal mining, followed by iron ore mining (up to 63%), and stone mining (up to 41%) clusters) regions. In a nutshell, it can be deliberated that COVID-triggered preventive measures (i.e., country-level LD, travel bans, industry ban, curtail in mining capacity, among others) likely enhanced vegetation health and productivity. Thereby, regulatory measures can be seen as a viable option for improving the terrestrial environmental conditions in the context of climate change in the near future.
Aerosol optical depth, Mining, NDVI, Pandemic, Solar-induced chlorophyll fluorescence
1010-6049
Ranjan, Avinash Kumar
6fe28711-022d-418a-885f-091a2391e33b
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Xiao, Jingfeng
71ebaa81-0af4-40c0-a799-bdd4d8ac9f38
Gorai, Amit Kumar
4a98fbf8-bfcc-45ef-aab0-70408cc06e3e
Ranjan, Avinash Kumar
6fe28711-022d-418a-885f-091a2391e33b
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Xiao, Jingfeng
71ebaa81-0af4-40c0-a799-bdd4d8ac9f38
Gorai, Amit Kumar
4a98fbf8-bfcc-45ef-aab0-70408cc06e3e

Ranjan, Avinash Kumar, Dash, Jadunandan, Xiao, Jingfeng and Gorai, Amit Kumar (2022) Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data. Geocarto International. (doi:10.1080/10106049.2022.2071469).

Record type: Article

Abstract

The Severe Acute Respiratory Syndrome-COronaVIrus Diseases 2019 (SARS-COVID-19) has sternly affected the entire world in terms of human health, loss of lives, and huge economic losses. However, pandemic-triggered lockdown (LD) events (as a preventive measure) have compelled to stop or reduce major economic activities, exerting positive impacts on the terrestrial environment. We deployed a variety of satellite products (i.e., normalized difference vegetation index (NDVI), solar-induced chlorophyll fluorescence (SIF), and aerosol optical depth (AOD)) along with gridded climatic dataset (temperature (TEMP), precipitation (PREC), and net radiation (NR)) to quantify the changes in vegetation activity (greenness and productivity) during the LD period over the Indian biogeographic provinces (BGPs) as compared to the average conditions over the previous three years (2017-2019). The analysis of the NDVI and SIF data revealed that vegetation greenness and productivity significantly enhanced during LD periods (by up to 37 to 55%, respectively). The influence of climatic drivers (PREC, TEMP, and NR) on vegetation activity was also investigated. We found that the enhancement in the vegetation activity (over BGPs) during the LD period was not entirely driven by the climatic parameters, and was therefore inferred to be also influenced by the LD events. Moreover, vegetation activity around the mining clusters were largely improved during the LD period (by up to 78%) over the coal mining, followed by iron ore mining (up to 63%), and stone mining (up to 41%) clusters) regions. In a nutshell, it can be deliberated that COVID-triggered preventive measures (i.e., country-level LD, travel bans, industry ban, curtail in mining capacity, among others) likely enhanced vegetation health and productivity. Thereby, regulatory measures can be seen as a viable option for improving the terrestrial environmental conditions in the context of climate change in the near future.

Text
Manuscript__Rev2_author_Details_Xiao - Accepted Manuscript
Download (3MB)

More information

Submitted date: 10 August 2021
Accepted/In Press date: 23 April 2022
e-pub ahead of print date: 8 May 2022
Published date: 8 May 2022
Additional Information: Publisher Copyright: © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Keywords: Aerosol optical depth, Mining, NDVI, Pandemic, Solar-induced chlorophyll fluorescence

Identifiers

Local EPrints ID: 457153
URI: http://eprints.soton.ac.uk/id/eprint/457153
ISSN: 1010-6049
PURE UUID: 81742ede-4f0f-4d70-87b5-136b95185100
ORCID for Jadunandan Dash: ORCID iD orcid.org/0000-0002-5444-2109

Catalogue record

Date deposited: 25 May 2022 16:30
Last modified: 17 Mar 2024 07:17

Export record

Altmetrics

Contributors

Author: Avinash Kumar Ranjan
Author: Jadunandan Dash ORCID iD
Author: Jingfeng Xiao
Author: Amit Kumar Gorai

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×