Land degradation neutrality (LDN) in Rajasthan, Western India: a combined approach of pressure-state-response model and MODIS data products.

Land degradation has become a key concern worldwide due to changes in meteorological variables and human-caused activities. This study primarily focuses on the rate, impact, and pattern of land degradation in western India. In this instance, we evaluated the effectiveness of land degradation neutrality (LDN) between 2000 and 2020 using an integrative approach based on a PSR (pressure-state-response) model developed by the OECD-UNEP under the UNCCD framework. Here, we mainly used MODIS products (e.g., NDVI, PET, LULC, and NPP). Also, soil organic carbon (SOC) and climatic variables (e.g. precipitation, aridity index and soil moisture) were taken into account. These indicators were analysed using the Google Earth Engine (GEE) code editor platform, and post-processing was done through Q-GIS software. The analysed parameters indicate that the NDVI and NPP values are + 0.20 to + 0.3 and 4.27 × 109 to 7.74 × 109 kg Cm-2, respectively. However, overall precipitation and soil moisture depicted a positive trend, and the aridity index adeptly followed a negative trend. Hence, the land degradation rate has increased in the north-western region besides the Aravalli range and neutrality work in the southwest part of the study area. The overall land degradation trend is negative over the last two decades. Therefore, this study anticipates the policymakers and government bodies to understand about land degradation of western India.

Analyzing the Risk to COVID-19 Infection using Remote Sensing and GIS.

Globally, the COVID-19 pandemic has become a threat to humans and to the socioeconomic systems they have developed since the industrial revolution. Hence, governments and stakeholders call for strategies to help restore normalcy while dealing with this pandemic effectively. Since till now, the disease is yet to have a cure; therefore, only risk-based decision making can help governments achieve a sustainable solution in the long term. To help the decisionmakers explore viable actions, we propose a risk-based assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water, and associated land use/land cover, are related with COVID-19 contagion and calculated them in a GIS-based multicriteria risk reduction method. The results showed disparateness in COVID-19 risk areas with a higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed prioritizing wards under higher risk zones for intelligent decision making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

Coronavirus pandemic versus temperature in the context of Indian subcontinent: a preliminary statistical analysis.

The novel coronavirus (COVID-19) has unleashed havoc across different countries and was declared a pandemic by the World Health Organization. Since certain evidences indicate a direct relationship of various viruses with the weather (temperature in particular), the same is being speculated about COVID-19; however, it is still under investigation as the pandemic is advancing the world over. In this study, we tried to analyze the spread of COVID-19 in the Indian subcontinent with respect to the local temperature regimes from March 9, 2020, to May 27, 2020. To establish the relation between COVID-19 and temperature in India, three different ecogeographical regions having significant temperature differences were taken into consideration for the analysis. We observed that except Maharashtra, Rajasthan and Kashmir showed a significantly positive correlation between the number of COVID-19 cases and the temperature during the period of study. The evidences based on the results presented in this research lead us to believe that the increasing temperature is beneficial to the COVID-19 spread, and the cases are going to rise further with the increasing temperature over India. We, therefore, conclude that the existing data, though limited, suggest that the spread of COVID-19 in India is not explained by the variation of temperature alone and is most likely driven by a host of other factors related to epidemiology, socioeconomics and other climatic factors. Based on the results, it is suggested that temperature should not be considered as a yardstick for planning intervention strategies for controlling the COVID-19 pandemic.

Water quality assessment of Majhiaon block of Garwa district in Jharkhand with special focus on fluoride analysis.

Fluoride in groundwater is known to contaminate the water sources globally. Jharkhand, one of the states in the eastern part of India, is known to have excessive fluoride content in groundwater sources. The present work involves assessment of water quality with special reference to fluoride in Majhiaon block of Garwa district in Jharkhand. Iron, nitrate and arsenic were also tested for the water samples collected from site. Eight hundred forty samples were tested for fluoride on site using colourimetry method, and one tenth of the samples were brought to laboratory for iron, nitrate, arsenic and fluoride analysis. Results show that 402 samples were having fluoride above permissible limit. Iron and nitrate were found to be beyond permissible limits in 302 and 286 water samples, respectively. More than 50% of samples collected from school had fluoride levels above permissible limits. Arsenic was well within the limits. However, few samples shown were excessive of iron and nitrate.