Forest Fire Characterization Using Landsat-8 Satellite Data in Dalma Wildlife Sanctuary.

A forest fire has caused a loss of biodiversity and forest heterogeneity and resulted in forest degradation and fragmentation. Remote sensing techniques have been widely used for locating and delineating forest fires. The present study has employed Landsat-8 satellite data during 2014-2020 for spatiotemporal analysis of forest fire in Dalma Wildlife Sanctuary (DWS). Normalized burn ratio (NBR) has been used to delineate forest fire-affected locations along with visual interpretation techniques. The results showed that an extensive area was burnt and deforested due to forest fire in DWS during 2014-2020. The burned areas due to forest fires within the notified forest boundary in DWS were 12.11 km2, 25.5 km2, 22.45 km2, 9.11 km2, 24.44 km2, 10.09 km2, and 1 km2 during 2014, 2015, 2016, 2017, 2018, 2019, and 2020, respectively, whereas burned areas outside notified boundary were 2.24 km2, 4.15 km2, 1.48 km2, 3.29 km2, 3.31 km2, 1.9 km2, and 0.1 km2. According to visual image interpretation, the highest burned area was found in 2015 (25.5 km2), whilst the least affected was found in 2020 (1 km2), and fires were mainly seen in the degraded forests and open forest regions. The present study revealed that forest fire is more dominant in Asanbani, Pardih, Bhelaipahari, Gobargushi, Bamri, Andharjhor, Somadih, Koira, Tetla, Bochkamkocha, Sah, Rbera, and Jamdih locations/beats in DWS. Thereby, these forest beats need attention from forest managers to control fire-mediated forest degradation for the conservation and restoration of forests in DWS.

Extreme rainfall-induced urban flood monitoring and damage assessment in Wuhan (China) and Kumamoto (Japan) cities using Google Earth Engine.

Floods in urban areas result in a detrimental impact on the natural environment and human health and pose major risks to assets and communication systems. In cities with high population density, the magnitude of flood damage largely depends upon flood inundation as well as floodwater depths. The present study compared recent flood inundation extent, damages caused, and possible floodwater depth in two highly developed metropolises of China and Japan, i.e., Wuhan and Kumamoto cities, for the year 2020. Sentinel-1 satellite data-driven change detection algorithm in Google Earth Engine (GEE) was applied to identify potentially flooded regions. Major land use land cover classes such as urban areas and croplands affected by the flood were mapped in conjunction with the exposed population. ALOS PALSAR digital elevation model (DEM) was used to study the inundation depth. The study revealed that 322 km2 of the area has been inundated by floodwater in Wuhan city with 230 km2 and 140 km2 areas under damaged croplands and urban regions. Around 817,095 people were exposed to this natural catastrophe in Wuhan. The city Kumamoto has witnessed an inundation area of about 505 km2 with damaged cropland of 350 km2 and an urban area of 83 km2.

Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America.

The outbreak of SARS CoV-2 (COVID-19) has posed a serious threat to human beings, society, and economic activities all over the world. Worldwide rigorous containment measures for limiting the spread of the virus have several beneficial environmental implications due to decreased anthropogenic emissions and air pollutants, which provide a unique opportunity to understand and quantify the human impact on atmospheric environment. In the present study, the associated changes in Land Surface Temperature (LST), aerosol, and atmospheric water vapor content were investigated over highly COVID-19 impacted areas, namely, Europe and North America. The key findings revealed a large-scale negative standardized LST anomaly during nighttime across Europe (-0.11 °C to -2.6 °C), USA (-0.70 °C) and Canada (-0.27 °C) in March-May of the pandemic year 2020 compared to the mean of 2015-2019, which can be partly ascribed to the lockdown effect. The reduced LST was corroborated with the negative anomaly of air temperature measured at meteorological stations (i.e. -0.46 °C to -0.96 °C). A larger decrease in nighttime LST was also seen in urban areas (by ∼1-2 °C) compared to rural landscapes, which suggests a weakness of the urban heat island effect during the lockdown period due to large decrease in absorbing aerosols and air pollutants. On the contrary, daytime LST increased over most parts of Europe due to less attenuation of solar radiation by atmospheric aerosols. Synoptic meteorological variability and several surface-related factors may mask these changes and significantly affect the variations in LST, aerosols and water vapor content. The changes in LST may be a temporary phenomenon during the lockdown but provides an excellent opportunity to investigate the effects of various forcing controlling factors in urban microclimate and a strong evidence base for potential environmental benefits through urban planning and policy implementation.

Impacts of partial to complete COVID-19 lockdown on NO2 and PM2.5 levels in major urban cities of Europe and USA.

SARS CoV-2 (COVID-19) coronavirus has been causing enormous suffering, death, and economic losses worldwide. There are rigorous containment measures on industries, non-essential business, transportation, and citizen mobility to check the spread. The lockdowns may have an advantageous impact on reducing the atmospheric pollutants. This study has analyzed the change in atmospheric pollutants, based on the Sentinel-5Ps and ground-station observed data during partial to complete lockdown period in 2020. Results revealed that the mean tropospheric NO2 concentration substantially dropped in 2020 due to lockdown against the same period in 2019 by 18-40% over the major urban areas located in Europe (i.e. Madrid, Milan, Paris) and the USA (i.e. New York, Boston, and Springfield). Conversely, urban areas with partial to no lockdown measures (i.e. Warsaw, Pierre, Bismarck, and Lincoln) exhibited a relatively lower dropdown in mean NO2 concentration (3 to 7.5%). The role of meteorological variability was found to be negligible. Nevertheless, the reduced levels of atmospheric pollutants were primarily attributed to the shutdown of vehicles, power plants, and industrial emissions. Improvement in air quality during COVID-19 may be temporary, but regulatory bodies should learn to reduce air pollution on a long-term basis concerning the trade-offs between the environment, society, and economic growth. The intersection of urban design, health, and environment should be addressed by policy-makers to protect public health and sustainable urban policies could be adopted to build urban resilience against any future emergencies.

Improvement in air quality and its impact on land surface temperature in major urban areas across India during the first lockdown of the pandemic.

The SARS CoV-2 (COVID-19) pandemic and the enforced lockdown have reduced the use of surface and air transportation. This study investigates the impact of the lockdown restrictions in India on atmospheric composition, using Sentinel-5Ps retrievals of tropospheric NO2 concentration and ground-station measurements of NO2 and PM2.5 between March-May in 2019 and 2020. Detailed analysis of the changes to atmospheric composition are carried out over six major urban areas (i.e. Delhi, Mumbai, Kolkata, Chennai, Bangalore, and Hyderabad) by comparing Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and land surface temperature (LST) measurements in the lockdown year 2020 and pre-lockdown (2015-2019). Satellite-based data showed that NO2 concentration reduced by 18% (Kolkata), 29% (Hyderabad), 32-34% (Chennai, Mumbai, and Bangalore), and 43% (Delhi). Surface-based concentrations of NO2, PM2.5, and AOD also substantially dropped by 32-74%, 10-42%, and 8-34%, respectively over these major cities during the lockdown period and co-located with the intensity of anthropogenic activity. Only a smaller fraction of the reduction of pollutants was associated with meteorological variability. A substantial negative anomaly was found for LST both in the day (-0.16 °C to -1 °C) and night (-0.63 °C to -2.1 °C) across select all cities, which was also consistent with air temperature measurements. The decreases in LST could be associated with a reduction in pollutants, greenhouse gases and water vapor content. Improvement in air quality with lower urban temperatures due to lockdown may be a temporary effect, but it provides a crucial connection among human activities, air pollution, aerosols, radiative flux, and temperature. The lockdown for a shorter-period showed a significant improvement in environmental quality and provides a strong evidence base for larger scale policy implementation to improve air quality.