Since December 2019, the world has witnessed the stringent effect of an unprecedented global pandemic, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of January 29,2021, there have been 100,819,363 confirmed cases and 2,176,159 deaths reported. Among the countries affected severely by COVID-19, the United States tops the list.
View Article and Find Full Text PDFCoronavirus disease, a novel severe acute respiratory syndrome (SARS COVID-19), has become a global health concern due to its unpredictable nature and lack of adequate medicines. Machine Learning (ML) models could be effective in identifying the most critical factors which are responsible for the overall fatalities caused by COVID-19. The functional capabilities of ML models in epidemiological research, especially for COVID-19, are not substantially explored.
View Article and Find Full Text PDFEcosystem Services (ESs) are bundles of natural processes and functions that are essential for human well-being, subsistence, and livelihoods. The 'Green Revolution' (GR) has substantial impact on the agricultural landscape and ESs in India. However, the effects of GR on ESs have not been adequately documented and analyzed.
View Article and Find Full Text PDFDemarcation of conservation priority zones (CPZs) using spatially explicit models is the new challenge in ecosystem services (ESs) research. This study identifies the CPZs of the Indian Sundarbans by integrating 2 different approaches, that is, ESs and ecosystem health (EH). Five successive steps were followed to conduct the analysis: First, the ESs were estimated using biophysical and economic methods and a hybrid method (that combines biophysical and economic methods); second, the vigor-organization-resilience (VOR) model was used for estimating EH; third, the risk characterization value (RCV) of ESs was measured using the function of EH and ESs; fourth, Pearson correlation test was performed to analyze the interaction between ESs and EH components; and fifth, the CPZs were defined by considering 7 relevant components: ecosystem vigor, ecosystem organization, ecosystem resilience, RCV, EH, ESs, and the correlation between EH and ESs.
View Article and Find Full Text PDFRemote sensing techniques are effectively used for measuring the overall loss of terrestrial ecosystem productivity and biodiversity due to forest fires. The current research focuses on assessing the impacts of forest fires on terrestrial ecosystem productivity in India during 2003-2017. Spatiotemporal changes of satellite remote sensing derived burn indices were estimated for both fire and normal years to analyze the association between forest fires and ecosystem productivity.
View Article and Find Full Text PDFMost of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India.
View Article and Find Full Text PDFEcosystem Services (ESs) refer to the direct and indirect contributions of ecosystems to human well-being and subsistence. Ecosystem valuation is an approach to assign monetary values to an ecosystem and its key ecosystem goods and services, generally referred to as Ecosystem Service Value (ESV). We have measured spatiotemporal ESV of 17 key ESs of Sundarbans Biosphere Reserve (SBR) in India using temporal remote sensing (RS) data (for years 1973, 1988, 2003, 2013, and 2018).
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