Geospatial analysis of elephant habitat suitability and movement for mapping the elephant corridor in Dalma Wildlife Sanctuary (India).

Wildlife and natural resources constitute an integral part of the ecosystem, whereas human interventions dismantled the living conditions of the wildlife. This is testified in the Dalma Wildlife Sanctuary (DWS) where the habitats of Asian elephants have changed due to human intervention and deforestation over the decades. The present study aimed to assess the elephant habitat suitability in the DWS of Jharkhand state (India) using the geospatial parameters such as forest density, degree of slope, proximity to water bodies, land use land cover, proximity to agricultural land, built-up density, and road density.

Investigation of fire regime dynamics and modeling of burn area over India for the twenty-first century.

The characteristics of the vegetation fire (VF) regime are strongly influenced by geographical variables such as regional physiographic settings, location, and climate. Understanding the VF regime is extremely important for managing and mitigating the impacts of fires on ecosystems, communities, and human activities in forest fire-prone regions. The present study thereby aimed to explore the potential effects of the confounding factors on VF in India to offer actionable and achievable solutions for mitigating this concurring environmental issue sustainably.

Assessing tea plantations biophysical and biochemical characteristics in Northeast India using satellite data.

Despite advancements in using multi-temporal satellite data to assess long-term changes in Northeast India's tea plantations, a research gap exists in understanding the intricate interplay between biophysical and biochemical characteristics. Further exploration is crucial for precise, sustainable monitoring and management. In this study, satellite-derived vegetation indices and near-proximal sensor data were deployed to deduce various physico-chemical characteristics and to evaluate the health conditions of tea plantations in northeast India.

Monitoring tea plantations during 1990-2022 using multi-temporal satellite data in Assam (India).

Background: Tea is a valuable economic plant grown extensively in several Asian countries. The accurate mapping of tea plantations is critical for the growth and development of the tea industry. In eastern India, tea plantations have a significant role in its economy.

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).

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.

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.

Impacts of partial to complete COVID-19 lockdown on NO and PM 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.

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 NO concentration and ground-station measurements of NO and PM between March-May in 2019 and 2020. Detailed analysis of the changes to atmospheric composition are carried out over six major urban areas (i.