Assessing Land Subsidence Using Remote Sensing Data

Dear Colleagues,

Land subsidence, the gradual sinking of the Earth's surface, is a widespread phenomenon that can occur due to various natural and human-related processes, including groundwater withdrawals, underground mining, permafrost thawing, and sediment compaction. The consequences of land subsidence are of global concern, with 45 states in the US alone being affected by this phenomenon. In China, for instance, land subsidence affects an area of approximately 79,000 square kilometers, mainly in heavily populated regions where it poses a continuous threat to infrastructure, buildings, and human lives and causes substantial economic losses.

Continuous monitoring of areas affected by land subsidence is vital to develop mitigation strategies and action plans that can prevent or minimize the associated hazards. To achieve this, the integration of various monitoring technologies and techniques has become increasingly important. Among these, remote sensing technologies such as LiDAR, synthetic aperture radar (SAR), radar interferometry (InSAR), and GPS provide high-resolution data that can detect Earth's changes with great precision (from centimeters to millimeters). Similarly, algorithmic and methodological developments, such as neural networks, machine learning, and principal component analysis, can analyze large and noisy datasets and extract relevant information for hazard mapping and risk assessment.

We invite submissions for a Special Issue on "Assessing Land Subsidence Using Remote Sensing". The Special Issue aims to advance our understanding of the use of remote sensing technologies for monitoring and quantifying land subsidence and its impacts on human societies and ecosystems. We welcome original research articles, reviews, and perspectives that cover various aspects of remote sensing for land subsidence assessment, from the theoretical basis to practical applications. Topics of interest include, but are not limited to:

• Advances in remote sensing technologies for the assessment of land subsidence;
• Methodologies for processing and analyzing remote sensing data for subsidence mapping and monitoring;
• Integration of multiple remote sensing techniques for accurate and efficient subsidence assessment;
• Machine learning and other advanced data analysis techniques for subsidence detection and prediction;
• Case studies of subsidence assessment using remote sensing in various regions and contexts;
• Mitigation planning and management based on remote sensing assessments;
• Challenges and opportunities for the future of remote sensing in the assessment of land subsidence.

Dr. Emre Havazli
Dr. Talib Oliver-Cabrera
Dr. Francesca Cigna
Guest Editors

Manuscript Submission Information

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