## 3 Applied Research  
Here, we shift the focus to the practical applications and ongoing research leveraging remote sensing in the Dead Sea region. We explore how these tools are actively being used to address critical scientific, environmental, and industrial challenges, such as monitoring the Dead Sea Transform fault, detecting sinkholes, assessing shoreline changes, and mitigating risks to infrastructure and tourism. This section also highlights recent innovations, \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Parameters** & **Satellite** & **Ground-Based** & **Integrated Techniques** \\ \hline \multirow{6}{*}{1. Introduction to the Method} & Uses remote sensing technologies like SAR (sub-mm accuracy), optical imagery, and VHR imaging (30 cm resolution) for monitoring large-scale geological changes. & Employs localized techniques like ERT (depth: 100 m), seismic surveys (resolution: \(\sim\)1 m), LiDAR (vertical accuracy: 10 cm), and comprehensive geohazard monitoring. & Combines satellite SAR (\(\sim\)100 \(\times\) 100 km coverage) \\  & High spatial resolution ( Sentinel-2: 10–60 m; WorldView-3: 30 cm). Temporal resolution: revisit times of 5–16 days. & Enploys localized techniques like ERT (depth: 100 m), seismic surveys (resolution: \(\sim\)1 m), LiDAR (vertical accuracy: 10 cm), and comprehensive geohazard monitoring. & Combines satellite SAR (\(\sim\)100 \(\times\) 100 km coverage) \\  & High spatial resolution ( Sentinel-2: 10–60 m; WorldView-3: 30 cm). Temporal resolution: revisit times of 5–16 days. & Enploys localized techniques like ERT (depth: 100 m), seismic surveys (resolution: \(\sim\)1 m), LiDAR (vertical accuracy: 10 cm), and comprehensive geohazard monitoring. & Adaptable resolutions: satellite data for large-scale changes, ground-based methods for localized precision. & \\ \hline \multirow{6}{*}{3. Data Acquisition} & Freely available datasets (e.g., Sentinel, Landsat) and commercial VHR datasets (e.g., WorldView) offer global coverage with up to 30 cm spatial resolution. & Requires on-site equipment like LiDAR (point density \(>\) 20 points/m\({}^{2}\)) and ERT (2–4 h per line), conducted by skilled operators. & \multirow{6}{*}{Fuses datasets from SAR, LiDAR, and seismic methods, enabling multi-source geohazard analysis.} \\  & Processes include radiometric corrections, atmospheric corrections, and SAR phase unwrapping (e.g., Sentinel-2). & Includes subsurface imaging, inversion modeling, and integration of LiDAR DEMs with geophysical survey data. & Cloud-based data fusion and real-time recalibration improve workflow efficiency and monitoring accuracy. \\ \hline \multirow{6}{*}{5. Integration Opportunities} & Validates ground-based observations, integrates SAR data with LiDAR DEMs, and enhances precision in subsidence mapping. & Provides detailed subsurface data (e.g., voids detected at depths of 30–70 m) to validate satellite findings. & AI-enhanced integration of SAR and ground-based data achieves \(>\) 92\% sinkhole detection accuracy. \\ \hline \multirow{6}{*}{6. Applications and Case Studies} & Monitoring shoreline retreat (\(\sim\)1 m/year), sinkhole formation, and subsidence using SAR (15.5 mm deformation cycles) and Landsat data. & Mapping sinkholes (\(>\)30 cm diameter), assessing dike stability, and analyzing subsurface voids with ERT and seismic refraction. & Dynamic hazard monitoring: sinkhole volumes (300–4500 m\({}^{3}\)) and subsidence rates (\(\sim\)45 cm/year) in the Dead Sea basin. \\ \hline \end{tabular}
\end{table} 
Table 2: Systematic evaluation of satellite, ground-based, and integrated geohazard monitoring techniques, providing insights into their method, spatial and temporal resolution, data acquisition, processing frameworks, integration opportunities, and specific applications.