Estimating Land Subsidence and Gravimetric Anomaly Induced by Aquifer Overexploitation in the Chandigarh Tri-City Region, India by Coupling Remote Sensing with a Deep Learning Neural Network Model

This study utilizes surface displacement data from Persistent Scatterer SAR Interferometry (PSInSAR) of Sentinel-1 satellite and groundwater storage change data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to understand land subsidence in the Chandigarh tri-city region. The satellite datasets are used along with the groundwater level data obtained from wells over the study area. Since the GRACE data are available at a much coarser spatial resolution of 1o by 1o, challenges remain in correlating the dataset with PSInSAR displacement that has been multi-looked at 14 m by 14 m resolution. Therefore, multiple sources of data (i.e., the monthly average of GRACE data, groundwater storage change and monthly average PSInSAR displacement per pixel, and interpolated groundwater level data from wells for 2017 to 2022) have been deployed into a deep learning multi-layer perceptron (DLMLP) model to estimate the groundwater storage change at the urban level. This has an indirect downscaling method that is carried out successfully using the DLMLP model for the estimation of groundwater storage changes at the urban level, which is usually complicated by applying direct downscaling methods on the GRACE data. Thus, the DLMLP model developed here is a distinctive approach considered for estimating the changes in groundwater storage using PSInSAR displacement, groundwater data from wells, and GRACE data. The DLMLP model gives an R2-statistics value of 0.91 and 0.89 in the training and testing phases, respectively, and has a mean absolute error (MAE) of 1.23 and root mean square error (RMSE) of 0.87

InSAR as a tool for monitoring hydropower projects: A review

This paper provides a review of using Interferometric Synthetic Aperture Radar (InSAR), a microwave remote sensing technique, for deformation monitoring of hydroelectric power projects, a critical infrastructure that requires consistent and reliable monitoring. Almost all major dams around the world were built for the generation of hydropower. InSAR can enhance dam safety by providing timely settlement measurements at high spatial-resolution. This paper provides a holistic view of different InSAR deformation monitoring techniques such as Differential Synthetic Aperture Radar Interferometry (DInSAR), Ground-Based Synthetic Aperture Radar (GBInSAR), Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR), Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPSInSAR) and Small BAseline Subset (SBAS). PSInSAR, GBInSAR, MTInSAR, and DInSAR techniques were quite commonly used for deformation studies. These studies demonstrate the advantage of InSAR-based techniques over other conventional methods, which are laborious, costly, and sometimes unachievable. InSAR technology is also favoured for its capability to provide monitoring data at all times of day or night, in all-weather conditions, and particularly for wide areas with mm-scale precision. However, the method also has some disadvantages, such as the maximum deformation rate that can be monitored, and the location for monitoring cannot be dictated. Through this review, we aim to popularize InSAR technology to monitor the deformation of dams, which can also be used as an early warning method to prevent any unprecedented catastrophe. This study also discusses some case studies from southern India to demonstrate the capabilities of InSAR to indirectly monitor dam health

Groundwater Assessment and Monitoring in the Northeastern Part of Nigeria Using Microwave Remote Sensing

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAs the human population continues to grow, the availability of surface water for convenient use is becoming increasingly scarce (Yu Fang et al., 2019). The negative effects of climate change such as drought has also been a major contributor to unavailability of surface water resources in certain regions (Brandon et al., 2017). Due to these reasons and more, natural reserves such as groundwater has become a primary and the most extensively used source of water (Brandon et al., 2017). The primary source of groundwater is gotten from precipitation, with a significant amount of precipitation in the presence of porous soils and with the help of gravity it infiltrates itself into the earth to form Groundwater, this in turn forms aquifers which can and has been harnessed over and over again through the construction of wells and boreholes and has been used for various purposes, including drinking, agriculture, and other human activities for centuries. Groundwater is also a key component of the water cycle; despite its invisibility it plays a crucial role in the ecosystem and the flow of various water bodies. Monitoring and investigating its variations and availability is therefore crucial for sustainability. Traditional methods such as geophysical and geo-electrical techniques have been utilized to detect, monitor and investigate groundwater resource for decades and have no doubt shown remarkable results, but these methods are not without limitations, they are expensive, timeconsuming, and in some cases limited in spatial coverage, therefore optimization is necessary for progressiveness. New and more effective microwave-based techniques have been developed and realized in recent times, they have shown to be promising in handling complex hydrological investigations and observations, one of such technique is the Interferometric Synthetic Aperture Radar (InSAR), which utilizes Sentinel-1 satellite images to assess land surface deformation. This technique allows for mappings and investigations of groundwater variability over time in a particular region by studying the subsidence or uplift pattern which could be associated with groundwater recharge or depletion (Teije et al., 2018). Another important instrument for water management is the Gravity Recovery and Climate Experiment (GRACE) mission. GRACE measures global spatial mass changes caused by gravitational anomalies by using microwave k-band ranging sensor, accelerometers, and global positioning system receivers. GRACE is particularly important for water management as water has mass and its volume varies over time, because of this GRACE can identify and measure its variations. It is also the only satellite that can analyse Terrestrial Water Storage (TWS), which comprises of all the water storages on earth. Another technique worthy of mention is the Standardised Precipitation Evapotranspiration Index (SPEI), this index makes use of hydroclimatological parameters to estimate and investigate drought conditions in regions where it is integrated. Drought could occur due to seasonal and annual variabilities of precipitation and or temperatures which in turn can be as a result of climate change. Sentinel-1 and GRACE complement each other and have varying sensitivity to aquifer system change. This project employed data from both satellites to monitor and evaluate groundwater variability in the north eastern region of Nigeria. Also, due to unavailability of in-situ data for validations and results comparisons, I considered the hydro-climatology of this region and investigated the drought situation over the specified years to strengthen my findings

An Investigation of Volcanic Ground Deformation Using InSAR Observations at Tendürek Volcano (Turkey)

Although approximately one-tenth of the world’s population lives near volcanoes, most of the 1500 active volcanoes are not monitored by ground-based instruments because of the cost and difficulty of access. Since the development of interferometric synthetic aperture radar (InSAR) in the 1990s, recent advances have allowed the near-real-time detection of surface deformations, one of the earliest markers of volcanic activity. According to the Global Volcanism Program, Turkey’s most recent eruption (involving gas and ash) occurred in the Tendürek volcano in 1885. An explosion in the Tendürek volcano, which continues to actively output gas and steam, would be a critical issue for the life and property of the people living nearby. In this context, we processed the Sentinel-1 data collected by the European Space Agency using the Stanford Method for Persistent Scatterers, and the surface deformations of the Tendürek volcano were investigated. In addition, we applied two different atmospheric correction approaches (linear phase-based tropospheric correction and the Generic Atmospheric Correction Online Service for InSAR) to reduce atmospheric effects and found that the linear phase-based tropospheric correction model produced lower standard deviation values. Subsequently, the mean deformation velocity maps, displacement time series, and deformation components in the line-of-sight direction were calculated. The results showed that the most severe subsidence was −11 mm/yr on the upper slopes of the Tendürek volcano. Although the lower slopes of the subsidence region have a lower settlement rate, the subsidence has a peak-caldera-centered location

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

IDENTIFICATION AND MEASUREMENT OF DEFORMATION USING SENTINEL DATA AND PSINSAR TECHNIQUE IN COALMINES OF KORBA

Natural Resources extraction for production of goods increases the stress on land and on the environment. Coal Mines are the primary source for energy production. This process increases the continuous deformation on land by disturbing equilibrium beneath the surface. Interferometry techniques have a capability to detect the minute deformation with millimetre precision on the ground using microwave SAR data. The study area covers the largest open cast coal mines of Asia. In this study for minute deformation identification, Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) technique has been used. Research focuses on the application of PSInSAR technique for terrain deformation detection using 17 SAR scene of Korba, Chhattisgarh, India acquired by the Sentinel-1 satellite of European Space Agency. This technique is capable to monitor the minute deformation in the coal mines of Korba, Chhattisgarh, India. The results predicted that the area is deformed with the velocity up to 30 mm/year in the coal mines and surroundings areas. The PSInSAR technique with the Sentinel-1 data provides the proficient tool for deformation monitoring in coal mines of Korba

Integration of satellite interferometric data in civil protection strategies for landslide studies at a regional scale

Multi-Temporal Satellite Interferometry (MTInSAR) is gradually evolving from being a tool developed by the scientific community exclusively for research purposes to a real operational technique that can meet the needs of different users involved in geohazard mitigation. This work aims at showing the innovative operational use of satellite radar interferometric products in Civil Protection Authority (CPA) practices for monitoring slow-moving landslides. We present the example of the successful ongoing monitoring system in the Valle D’Aosta Region (VAR-Northern Italy). This system exploits well-combined MTInSAR products and ground-based instruments for landslide management and mitigation strategies over the whole regional territory. Due to the critical intrinsic constraints of MTInSAR data, a robust regional satellite monitoring integrated into CPA practices requires the support of both in situ measurements and remotely sensed systems to guarantee the completeness and reliability of information. The monitoring network comprises three levels of analysis: Knowledge monitoring, Control monitoring, and Emergency monitoring. At the first monitoring level, MTInSAR data are used for the preliminary evaluation of the deformation scenario at a regional scale. At the second monitoring level, MTInSAR products support the prompt detection of trend variations of radar benchmarks displacements with bi-weekly temporal frequency to identify active critical situations where follow-up studies must be carried out. In the third monitoring level, MTInSAR data integrated with ground-based data are exploited to confirm active slow-moving deformations detected by on-site instruments. At this level, MTInSAR data are also used to carry out back analysis that cannot be performed by any other tool. From the example of the Valle D’Aosta Region integrated monitoring network, which is one of the few examples of this kind around Europe, it is evident that MTInSAR provides a great opportunity to improve monitoring capabilities within CPA activities