Analysis of ocean parameters (Sea surface temperature - SST, sea water temperature - SWT, sea water salinity - SWS, chlorophyll-a - Chl-a concentration and surface latent heat flux - SLHF), shows characteristic behaviors associated with the Morocco Mw 6.8 earthquake occurred on 8 September 2023. From late August to early September, pronounced negative SST anomaly has been observed within the epicentral areas. Changes in Chl-a concentration and SWS are observed which could be attributed to the upwelling prior to the earthquake. The contrastive analysis in SWT and SWS from an Argo station located close to the epicenter, reveals anomalous changes in the seawater prior to the earthquake, this could be associated with the mixing of underground ocean water due to the build of stress within the epicentral region.

Despite numerous studies on dwindling groundwater resources in northern India, the linkage between Groundwater Storage (GWS) and hydroclimatic variability in the Indo-Gangetic Plain (IGP) has not been widely studied. In this regard, an attempt has been made to assimilate the satellite-based observations of hydroclimatic variables (predictors) (Precipitation- P, Evapotranspiration- ET, Soil Moisture-SM, and Runoff- RO) to predict GWS using multi-regression machine learning models (Random Forest; R2=0.81). Predicted estimates of the GWS show that northern and NW parts of the IGP are highly affected, and large residual estimates in the eastern parts are due to the uncertainty in the observed P and ET. Despite the performance of the models, spatial biases have been recognized between the observed and predicted estimates of the GWS, suggesting no significant variations among the predictors (hydroclimatic variables) in the major parts of the study area.

The eco-hydrology of the Himalayan catchments depends on their glacial and snow coverages as well as associated dynamics. These components of the Himalayan cryosphere can be seen as tracers of climate variability. In this study, MOD10A2 products have been used along with Landsat-5/8 datasets to capture the spatiotemporal fluctuations in the intra-annual snow cover of Arunachal Pradesh and its Tawang basin. Snow cover has been mapped for the past 21 years 2000-2021, for both the ablation and accumulation period using MOD10A2 products and normalized difference snow index (NDSI) (threshold: 0.4). The accumulation and ablation period snow cover shows decreasing and increasing trend respectively for the entire Arunachal Pradesh. However, for the Tawang basin, the accumulation and ablation period snow cover trend seems to be stable at 450 Km2and 100 Km2,, respectively. The contaminated snow cover of the Tawang region on 16 February 2022 (Landsat-8) has been identified as 564.42 Km2(53.7%). ALOS PALSAR digital elevation model (DEM) has been used to identify glacial lakes (slope <4°) within the Tawang basin.

Earthquakes associated with strong ground vibration are a significant factor in infrastructural damage. Since earthquake impact is observed over a large area, satellite remote sensing can be effectively used to perform seismic impact assessment. The present study attempts to investigate the damage around the Lawar Mandi region due to the Mw6.0 Afghanistan earthquake (21 June 2022) triggered at a hypocenter depth of 4 Km. The damage assessment is performed with the help of radar interferometry in conjunction with optical remote sensing techniques. The vertical seismic deformation as obtained from Sentinel-1, shows ground subsidence that reaches a maximum value of 179 mm near the epicenter. A co-seismic surface break along the northeast-southwest direction is also observed. Some of the locations around infrastructures of the Lawar Mandi region show reduced co-seismic coherence with increased tasseled cap transformation (TCT)-wetness difference and temporal difference liquefaction index (TDLI) using Landsat-8 OLI, indicating the possibility of liquefaction/cyclic mobility.

Crop residue burning (CRB) has been a serious issue since 1986 in northwestern and northern India due to health threats and weather impacts. This study utilizes satellite and ground based data to assess the variations in the crop harvesting and burning periods, including their effects on the atmospheric conditions and air quality of Rajasthan during post-monsoon periods of 2002-2021. The normalized difference vegetation index (NDVI) values are found to show a shift (low values) from October to November until recent years. The increased fire counts in November indicate the change in harvesting and burning time. The crop residue burning in Punjab and Haryana is likely to influence the air quality of adjacent parts, as inferred from the higher AOD and AE values over source regions, leading to a rise in AOD and AE over Rajasthan in recent years. The higher AOD values during post-monsoon months are shown to be associated with high dust loading and the presence of biomass-burning aerosol. Pronounced changes are also observed in methane (CH4), Carbon monoxide (CO), Total Column Ozone (TCO), and Total column water (TCW) during post-monsoon. The HYSPILT trajectories show the airmass transport from the source regions of Punjab and Haryana towards Rajasthan, affecting the air quality to cause adverse impacts on human health and climate.

Over the past three decades, thermal anomalies from satellite infrared data have been widely discussed and associated with earthquakes. Besides infrared satellite data, the recent use of passive microwave satellite data has emerged as an important dataset to detect the potential thermal anomalies prior to earthquakes in all weather conditions due to its capability to monitor the earth in cloudy and foggy conditions and has been applied to the numerous strong earthquake events around the world. On 5 September 2022, an Mw 6.6 earthquake occurred in Luding county, nearby Mt. Gongga, China, with heavy cloud coverage over the epicenter and its surrounding region before and after the event. In the present study, the microwave brightness temperature (MWBT) and clear-sky outgoing longwave radiation (ClrOLR) data were used together to identify the potential seismic thermal anomalies. Prominent anomalous signals were detected around the epicenter, appearing within 2 months preceding the earthquake. Further analysis was conducted through the combination of other parameters from satellite and ground observations, including precipitation, cloud fraction, and soil moisture, in order to verify and better understand the detected anomalous signals. Our results suggest that the combination of MWBT and ClrOLR can be used as an effective tool to detect thermal anomalies associated with earthquake events in cloudy conditions over the epicenter.

Groundwater depletion is one of the serious geo-environmental issues causing ground subsidence, which damage buildings, infrastructures and causes loss of life. The quantitative and qualitative evaluation of groundwater variability requires multiple approaches to measure hydraulic head level and geodetic deformation. In this study, we have made efforts to integrate multiple hierarchical space-borne data, including Gravity Recovery and Climate Experiment (GRACE), Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR), geological and hydrological data, to quantify subsidence in Chandigarh city and its surroundings. First, we conducted New-Small BAseline Subsets (NSBAS) and pointwise persistent scatterer (PS) InSAR techniques in parallel, using three-years Sentinel-1 data showing a vertical subsidence up to 120 mm/year around fluvial sediment deposits. Further, correlation analysis of hydraulic/climatic measurements clearly shows the subsidence associated with the groundwater depletion. The pattern of PS points shows the instability of structures associated with the ground subsidence over the central city areas. The monumental architectures designed by Le Corbusier in the northern sectors are outside of the main subsidence area. In the target area, the magnitude of subsidence and surface deformation due to groundwater depletion depending on the subsurface geophysical environment and the anthropogenic activities within the region and surroundings. The results provided a case of monitoring scheme using multi-resolution satellite data about the subsidence and associated consequences due to groundwater depletion.

The Indo-Gangetic plains (IGP) suffers from poor air quality and high atmospheric pollution over the years. Various natural and anthropogenic sources are the causes of the poor air quality, affecting the population in the IGP and surrounding areas. The local and long-range transport of dust affects the air quality of the IGP region and sometimes depending upon the favorable meteorological conditions dust reaches the Himalayan foothills. region. We have carried out the analysis of aerosol properties and air quality using a Microtop Sun photometer and low-cost air quality sensors at the IIT Mandi campus (high altitude site) and Dhampur (rural site). The observed$\text{PM}_{2.5}$and aerosol optical depth (AOD) at IIT Mandi show a strong influence of dust, however, the$\text{PM}_{2.5}$and AOD are found to be lower compared to the values observed at Dhampur (located 200 km northeast of Delhi). Local industries, dust, and crop residue burning are the main sources of pollution in the rural areas of the northern parts of India. The low-cost sensors provide good quality data from IIT Mandi and Dhampur, our results show the need for a dense network in rural places to understand the dynamics of pollutants, especially in the IGP, one of the polluted regions in India.

The main agricultural crop in Vietnam is rice. After crop harvesting, the residue is burned by the farmers in the south and north of Vietnam to prepare for the next crop. In this paper, we have analyzed satellite and ground data to study the influence of crop residue burning on aerosol parameters and air quality. Our results show pronounced changes in aerosol properties and air quality, which have adverse impacts on human health and long-term impacts on climate.

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.

On May 21, 2021 (UTC), an Mw 7.3 earthquake occurred in Madoi County of Qinghai Province (China). There was no damage to buildings or loss of life; however, surface manifestation was observed in the epicentral areas. The analysis of synthetic aperture radar (SAR) and ground observation data shows changes in the section of the Yellow River and some lakes within the epicentral region associated with this strong earthquake. The changes in radar backscattering coefficient (BC) in water bodies are observed attributed to turbidity from the intense shaking of the earthquake. The liquefaction locations observed in the field within the epicentral region, which is also supported by the changes in the BC derived from Sentinel-1 data.

The multi-parameter at different pressure levels prior and after the Yutian earthquake (M 6.3) in China observed by AIRS (the Atmospheric Infrared Sounder) aboard EOS (the Earth Observing System) Aqua satellite have been analyzed based on the Index of Anomaly (IA) and deviation (STD) threshold method. Complementary variations in the different parameters (carbon monoxide, ozone, air temperature, skin temperature and outgoing longwave radiation) along the main active faults on 1–2 days prior to the event are observed showing existence of coupling between lithosphere and atmosphere. Our results show that the sudden variations in these parameters could be attributed to the tectonic and seismic activities.

In the last three last decades air pollution level has been increased significantly especially in the northern parts of India with Delhi being the most polluted city. Population growth, energy demand, industrial growth, increased crop burning, increased traffic density and coal burning have affected the air quality of Delhi and surrounding areas upto a great extent. In the present paper, we have used MODIS Terra and Aqua data to study the annual and seasonal variations of Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) and also tried to identify the sources of pollution based on AOD and AE. A wide variation in AOD, (range 0.07 to 3.49) and AE, (range 0-1.8) is observed during 2000-2019 over Delhi and surrounding regions. This shows very poor air quality and highly polluted atmospheric. Different aerosol types are found to be season dependent based on the detailed analysis of AOD and AE retrieved from satellite data during the period 2000-2019. The present analysis shows dominance of anthropogenic aerosols (AA) during winter whereas biomass burning (BB) during post monsoon seasons. During pre monsoon season pollutant continental (PC) and mostly dust (MD) were observed for many days as air mass travel from Thar Desert, Middle East and Arabia with the westerly winds. In the recent decade, clean days in Delhi are reduced significantly.

Obvious increased microwave brightness temperature has been observed around the epicenters before strong earthquakes. It can be looked as a potential signal for thermal anomalies related to earthquake activities. However, passive microwave observation can be affected by many environmental factors, such as soil moisture, vegetation cover, surface properties (surface temperature, soils and surface texture) and atmospheric parameters (water vapor, air temperature, etc.) Four different types of land cover regions - desert, vegetation, ocean and glacier have been considered in the present paper to study the sensitivity of different environmental parameters on passive microwave brightness temperature. Our results show that the main factors affecting the MWBT depend on the surface covers. The characteristics of the underlying surface over the seismogenic region should be considered in the further research of seismic microwave anomalous signals detection.

The Pacific Ocean is about 12.3 km far away from the epicenter of La Habra M5.1 earthquake in 2014.Chl-a concentration, buoys ocean water temperature, upwelling index and surface latent heat flux data over the regions have been analyzed based on ground and satellite observation in the present paper. Our results show obvious increased Chl-a concentration, upwelling index, ocean water temperature and SLHF before the earthquake event. The blooming Chl-a concentration before earthquake could be attributed to the upwelling of nutrient-rich water brought by the redistribution of thermal structure of ocean water due to the increased ocean water temperature caused by the enhancement of stress over Seismogenic zone. Chl-a concentration could provide potential warning signal for impending coastal earthquakes.

Drought occurrence is a gradual process with long-lasting effects and satellite remote sensing data help in the monitoring and severity of drought conditions. This paper analyzes MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data to study the vegetation stress associated with drought conditions over India. Dynamics of monthly Normalized Difference Vegetation Index (NDVI) and its association with climate conditions over 10 years period have been studied. We have considered satellite data for the period 2006-2015 from three highly stressed NDVI regions based on seasonal NDVI difference from 2015-2016. The drought conditions correspond to the pronounced changes in weather parameters (land surface temperature, air temperature, and relative humidity) and adjacent sea surface temperature. The detailed analysis of these parameters shows a close relation with reduction upto 13% in NDVI values in 2016 associated with a pronounced reduction in precipitation and increase in surface temperature.

Punjab state (located in north-west part) is known as food basket of India. Every year, after the crops are harvested during post monsoon (Oct.-Nov.) and summer (April-May) seasons, crop residues are burnt. The plumes of the burning during post monsoon season are transported over the Indo-Gangetic basin (IGB), upto far distances over the IGB and also over the central parts of India based on the favorable meteorological conditions. The plume greatly impacts the air quality affecting health of 900 million people living in the IGB. During 2016, crop residue burning coincided with the Diwali festival, as a result, dense haze, fog and smog were persisted for long time that affected day to day life of people. We have used satellite data to study the changes in atmospheric and meteorological parameters associated with the crop residue burning.

Satellite sensors are now capable of monitoring various total atmospheric gas concentrations and meteorological parameters at different pressure levels. These sensors provide information at spatial and temporal resolutions, which can be used to alert people about possible exposure to hazardous gases, if the concentrations of these gases are found to exceed normal concentrations. Aliso Canyon is a ground storage facility located in California, where there was blow out of a well and intense gas release in the atmosphere that was first detected on 23 October 2015. In this paper, we have used satellite data to monitor methane (CH4) and carbon monoxide (CO) along with other relevant meteorological parameters. Our results show enhancement of CO and CH4 concentrations around Aliso Canyon associated with the gas leaks with the blow out.

The paper discusses the use of remote sensing, digital elevation model and topographic slope angle in evaluating the seismic site-conditions in Damascus region. Thirty meter pixel resolution DEM, derived from the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER), was the basis for the slope angle-velocity model and subsequent map products. The predominant period (T0), amplification factors (Fa and Fv) and microzonation maps have produced for Damascus region. The estimated results have been compared with the earlier results. The estimated results using proposed new approach have shown a good agreement to seismic array results. Suggested slope angle-velocity relationship shows a better estimation of site-conditions and microzonation maps compared to the Wald-Allen method.

Increasing anthropogenic activities have direct connections to global warming and climatic change. The land and ocean temperature show an increasing trend throughout the globe. In this paper, we have analyzed satellite derived ocean temperature data to study the impacts of climate change on the fish catch along the west coast of California during years 2005–2014. We have considered monthly fish landing data of five different species from three different coastal California cities: Eureka, San Francisco, and Los Angeles. The different populations of fish landing were compared with the ocean temperature and other controlling parameters. The detailed analysis of these parameters show a close relation with the different species of fish landing. The increasing ocean surface temperature shows positive and negative correlations with the different species of fish catch, and some fish species seem to decline with the increasing ocean surface temperature.

Diwali festival in India is popularly known as the “festival of illumination”, celebrated between mid-October and mid-November of each year depending upon Hindu calendar. During this festival, people light their houses with candles and oil lamps and play with crackers and have fireworks one or two days prior to Diwali day especially in urban areas. The air quality is found to degrade on the Diwali day and this continues for few days after Diwali. The atmospheric aerosol loading is found to increase abruptly after Diwali. In the present paper, we discuss changes in black carbon concentration and total ozone column associated with Diwali festival.