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<p>Due to rising water quality-related issues, a periodic and continuous monitoring system is mandatory for inland water bodies. Water quality estimation is essential for water resource management and the sustainability of riverine ecosystems. Existing in-situ, field-based, and wet laboratory estimations, although precise and accurate, account for the lack of spatial and temporal variability and represent point sampled assessment. With a high temporal resolution and fine spatial resolved scaling, remote sensing data, including the Landsat-8,9 series, and Sentinel-2 series, consecutively provide high-spatio-temporal resolution observations for real-time analysis. The Google server and cloud-based Google Earth Engine (GEE) platform support image collections, atmospherically-radiometrically corrected imagery, and large-data processing. Taking the inland waterbodies of Delhi as the study area, this study is carried out in GEE to (i) design, inquire and pre-process all Landsat and Sentinel series observations that coincide with in situ measurements; (ii) extract the spectra to develop empirical models for water quality parameters and (iii) visualize the results graphically using geospatial distribution maps, time-series charts, and create a web-application. Water quality parametric analyses were conducted for Optically Active constituents (OAC), i.e., chlorophyll-a, suspended solids, and turbidity. Validation with an independent site location is the next area of study for estimating the predicted and observed values. Spectral characteristics show correlation and similarity with the field data and active optical constituents. Besides visualizing long-term spatial and temporal variabilities through thematic maps and time-series charts, anomalies such as eutrophication at specific sites can also identify using the models developed. An online application is in progress to allow users to explore and analyze water quality trends using the latest Landsat-9 dataset. Integrating remotely-sensed images, in situ measurements, and cloud computing can offer new opportunities to implement effective monitoring programs and understand water quality dynamics.</p>

The COVID-19 pandemic was declared by World Health Organization (WHO) on 11 March 2020 and advised countries to take immediate and concerted action. The governments of India and Himachal Pradesh carried out preventive and precautionary steps to minimize the spread of coronavirus disease. In this study, the impact of a sudden halt in human activity on air quality was investigated by looking at changes in satellite imagery using a remote sensing approach. The concentrations of the gaseous contaminants studied (CO, SO2, NO2, and C6H6) show a significant decrease during the lockdown. The average particulate matter concentrations (PM10 and PM2.5) differed significantly from gaseous emissions, meaning that particulate matter significantly affects anthropogenic activities. NO2 concentrations and NOx emission variations were tracked for rural/town areas around Himachal Pradesh and major urban cities of India. Daily top-down NOx emissions were measured using the Tropospheric Monitoring Instrument (TROPOMI), which assisted in retrieving NO2 from the steady-state continuity equation. The emissions of NOx from rural, urban, and power plants were compared before and after the lockdown. The research accounted for our studies on the levels of (NO2, Ozone (O3), and sulfur dioxide (SO2) were monitored using Sentinel-5P imagery using the GEE platform.

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Abstract. To the rampant rise in urban settlements and human population, the national parks, wildlife sanctuaries, and national tiger reserves of middle and southern India have been intruded upon by human settlements regularly. These are adjoined by paths called as ‘wildlife corridors’ especially the tiger and elephant corridors which are used as a means for migration. Bandipur and Pench-Satpuda national parks have one such essential pocket of wildlife corridors the Bandipur corridor interconnects the population of 8000 plus elephants between Mysuru and Wayanad in southern India whereas the Pench-Satpuda corridor sustains 120 plus tigers between Pench-Satpuda Tiger Reserve in middle India. To assess this it’s imperative to assess the pattern of wildlife movements, changes in the animal habitats in terms of habitat cluster zones, land-use changes, the onset of human settlements and anthropogenic activities are to be monitored. For this, land use land cover (LULC) changes for these corridors were analyzed across two decades using geospatial and remote sensing technique. The study finds a organized deprivation of dense forests and open forests respectively, thus indicating large-scale destruction. The study also found the net area changes of dense forests and open forests which were diverted for agriculture activities indicating extensive encroachment of forest land for human settlement. The classification was monitored for water bodies that have reduced, indicating shrinkage during the duration under research. The existence of substantial coal deposits in the wildlife corridor and operational coal mining in the proximity of the wildlife corridor is a matter of grave concern which has been highlighted in the research. We examine to identify long-term sustenance and protection of such corridors for preserving the natural habitat. Thus, with such suitability in wildlife monitoring, we can mark an increasing need for adaptable, tenable, and secure wildlife management as illustrated under the Sustainable Development Goals (SDG 15 mentioned under United Nations).