Analyzing Joshimath's sinking: causes, consequences, and future prospects with remote sensing techniques.

The Himalayas are highly susceptible to various natural disasters, such as the tectonically induced land deformation, earthquakes, landslides, and extreme climatic events. Recently, the Joshimath town witnessed a significantly large land subsidence activity. The phenomenon resulted in the development of large cracks in roads and in over 868 civil structures, posing a significant risk to inhabitants and infrastructure of the area. This study uses a time-series synthetic aperture radar (SAR) interferometry-based PSInSAR approach to monitor land deformation utilizing multi-temporal Sentinel-1 datasets. The line of sight (LOS) land deformation velocity for the Joshimath region, calculated for the year 2022-2023 using a PSInSAR-based approach, varies from - 89.326 to + 94.46 mm/year. The + ve sign indicates the LOS velocity/displacement away from the SAR sensor, whereas - ve sign signifies the earth's movement towards the SAR sensor in the direction of LOS. In addition, the study investigates feature tracking land displacement analysis using multi-temporal high-resolution Planet datasets. The result of this analysis is consistent with the PSInSAR results. The study also estimated the land deformation for the periods 2016-2017, 2018-2019, and 2020-2021 separately. Our results show that the Joshimath region experienced the highest land deformation during the year 2022-2023. During this period, the maximum land subsidence was observed in the north-western part of the town. The maximum LOS land deformation velocity + 60.45 mm/year to + 94.46 mm/year (2022-2023), occurred around Singhdwar, whereas the north and central region of the Joshimath town experienced moderate to high subsidence of the order of + 10.45 mm/year to + 60.45 mm/year (2022-2023), whereas the south-west part experienced an expansion of the order of 84.65 mm/year to - 13.13 mm/year (2022-2023). Towards the south-east, the town experienced rapid land subsidence, - 13.13 mm/year to - 5 mm/year (2022-2023). The study analyzes the causative factors of the observed land deformation in the region. Furthermore, this work assesses the ground conditions of the Joshimath region using UAV datasets acquired in the most critically affected areas such as Singhdhaar, Hotel Mountain View, Malhari Hotel, and Manoharbagh. Finally, the study provides recommendations and future prospects for the development policies that need to be adopted in the critical Himalayan regions susceptible to land deformation. The study suggests that land deformation in the region is primarily attributed to uncontrolled anthropogenic activities, infrastructural development, along with inadequate drainage systems.

Assessment of urban sprawls, amenities, and indifferences of LST and AOD in sub-urban area: a case study of Jammu.

Urbanization, particularly in peri-urban areas, often results in critically transforming the regional land use and land cover (LULC). The increased built-up in peri-urban areas affects the regional accessibility of residents of urban clusters to requisite amenities and severely affects the regional environment, as observed in the case of Jammu district situated in the foothills of the Indian Himalayas. The present study is aimed at assessing the rise of urban sprawls in Jammu district over the past two decades and how the urbanization has affected the lag in the number of amenities corresponding to the urban growth based on qualitative parameters. Further, a parameterization scheme is developed to assess the amenities quality. A comparison is made with Indore, a planned smart city, to assess the status of urbanization and residential quality based on an amenity index. The study also investigates the indifferences observed in some of the climate variables in the urban and sub-urban settings of the Jammu district. The investigation is conducted through a multi-ring buffer analysis approach utilizing the land use land cover (LULC) products based on Landsat 8/7 satellite imagery of 2002, 2013, and 2021. The indifferences in the settings are analyzed using MODIS aerosol optical depth (AOD) and land surface temperature (LST) products. The analysis leads to determination of critical urban parameters including the urban area, density, and growth rate, revealing significant urbanization at 25-27 km from the city center. Significant indifferences are observed in urban and sub-urban areas indicating higher rise in LST and AOD, particularly in the recent decade. These investigations provide critical information to urban and climate solution authorities for planning and management, particularly in critically endangered areas.

Assessment of potential present and future glacial lake outburst flood hazard in the Hunza valley: A case study of Shisper and Mochowar glacier.

In Himalayas, new glacial lake formation and expansion of existing glacial lakes have occurred as a consequence of the increasing temperature and glacier recession. These lakes have the potential to release catastrophic volumes of water and trigger a glacial lake outburst flood (GLOF). GLOFs can cause devastating downstream impacts including loss of lives, damage to infrastructure, and economic loss. The risk associated with GLOFs is evident in the case of the Mochowar and the Shisper glaciers of the Hunza valley in the Karakoram ranges. The present study is divided in two parts: 1) investigation of the recent GLOF event from the Shisper glacier ice-dammed lake on 7th May 2022. 2) identification of an overdeepening site for future lake formation at the Mochowar glacier and its future GLOF susceptibility; We used the Himalayan Glacier Thickness Mapper (HIGTHIM) to calculate the thickness of Mochowar glacier and identify an overdeepening site at its terminus. This site could host a glacial lake of area 0.22 km2 and a mean depth of 58.97 m that can release a potential flood volume leading to cascading effects with the Shisper ice-dammed lake that further increases the GLOF susceptibility. The GLOF susceptibility of this future lake was determined to be high based on a multi-criterion decision analysis. The recent GLOF event of 7th May 2022 occurred from the Shisper glacier ice-dammed lake. We applied a 2D hydrodynamic model for investigating this GLOF episode and estimated a release volume of 6.23 × 106 m3, with a modelled peak discharge of approximately 1505 m3 s-1.

CONTROL-CORE: A Framework for Simulation and Design of Closed-Loop Peripheral Neuromodulation Control Systems.

Closed-loop Vagus Nerve Stimulation (VNS) based on physiological feedback signals is a promising approach to regulate organ functions and develop therapeutic devices. Designing closed-loop neurostimulation systems requires simulation environments and computing infrastructures that support i) modeling the physiological responses of organs under neuromodulation, also known as physiological models, and ii) the interaction between the physiological models and the neuromodulation control algorithms. However, existing simulation platforms do not support closed-loop VNS control systems modeling without extensive rewriting of computer code and manual deployment and configuration of programs. The CONTROL-CORE project aims to develop a flexible software platform for designing and implementing closed-loop VNS systems. This paper proposes the software architecture and the elements of the CONTROL-CORE platform that allow the interaction between a controller and a physiological model in feedback. CONTROL-CORE facilitates modular simulation and deployment of closed-loop peripheral neuromodulation control systems, spanning multiple organizations securely and concurrently. CONTROL-CORE allows simulations to run on different operating systems, be developed in various programming languages (such as Matlab, Python, C++, and Verilog), and be run locally, in containers, and in a distributed fashion. The CONTROL-CORE platform allows users to create tools and testbenches to facilitate sophisticated simulation experiments. We tested the CONTROL-CORE platform in the context of closed-loop control of cardiac physiological models, including pulsatile and nonpulsatile rat models. These were tested using various controllers such as Model Predictive Control and Long-Short-Term Memory based controllers. Our wide range of use cases and evaluations show the performance, flexibility, and usability of the CONTROL-CORE platform.

Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach.

Urban intensification has taken a serious toll on the groundwater reserves which is one of the primary sources of fresh water on earth. Exploitation of groundwater has exponentially increased over time, especially in urban landscapes, with ever increasing demands to cater the growing population and development processes. This emphasizes on the importance of proper monitoring of the groundwater variations, which is a difficult process for not being directly accessible for physical measurements. Therefore, it is essential to develop advanced innovative indirect methods to help long-term monitoring of groundwater reserves at a relatively higher resolution, so that local level variations and their impact could be studied in case of excessively exploited zones, like cities. Recent studies have linked land-subsidence to over-exploitation of groundwater, which can be critical for urban scenario, which requires longer duration for replenishment. Thus, this study focuses on monitoring of the groundwater variations using time-series Sentinel-1 Interferometric SAR (InSAR) datasets by retrieving land deformation by PsInSAR (Persistent Scatterer Interferometric SAR) technique; applying phase information of permanent scattering candidates. 58 and 60 images were acquired during ascending and descending passes respectively between 9/10/2014 to 2/7/2020 for the study area i.e., Lucknow city (India) and its surroundings. The field measurements of groundwater level for various seasons (pre and post monsoons) were acquired from the Central Groundwater Board, Government of India (CGWB). Besides, Landsat 5 and 8 datasets were utilized to analyze the pattern of urban growth for a 30-year period and predict the near future scenario. In-depth analysis of all the components revealed a direct relationship between land deformation, groundwater variations and urban expansion. A high correlation coefficient of 0.886 was observed between groundwater level variation and the retrieved deformation measured along the groundwater wells along the deformation zones. Therefore, the overall analysis and results indicate that PsInSAR technique has great potential for estimating the groundwater levels and surface deformation at higher resolution and could be easily applied for any other city for continuous assessment.