Natural disasters are increasing worldwide, partly because of effects of climate changes. Ground deformation generated by catastrophic events represents a growing problem that affects hundreds of millions of people worldwide. The surface changes due to natural events, i.e. landslides, sinkholes, volcanic activities, land subsidence, etc., and can lead to structural damage of buildings and infrastructures, loss of extensive agricultural and/or natural areas, damage to tourist sites and cultural heritage, rise of salt wedges, regression of coastlines, and can have a significant economic and social impact. This negative impact can be further aggravated by climate change (e.g. sea level rise, modifications of rainfall intensity and period) in particular in low-lying coastal areas and unstable slopes. Ground deformation monitoring during and after a natural disaster plays a key role in the management of such natural hazards by providing cost-effective solutions for risk mitigation strategies.
This Research Topic is devoted to all research related to monitoring systems of ground deformations at various scales based on remote sensing techniques (in particular, but not limited to, InSAR) complemented with ground-based data (e.g. GNSS, precise leveling, Structure from Motion photogrammetry, Terrestrial Laser Scanning), including measurements from airplanes, helicopters, UAV. This Research Topic aims to collect original contributions focusing on both methodological aspects, including theoretical studies, and applications. The applications can concern every sector, from the natural environment (e.g. landslides, morphological changes of an area, etc.) to urban areas (e.g. buildings, old towns, bridges, dams, etc.), performed for various motivations (e.g. risk assessment, cultural heritage safeguard, geotourism, etc.).
Contributions in which remote sensing data are used in conjunction with data provided by other techniques to improve the quality of the results (accuracy, costs and times of survey and data processing), are welcome. Papers discussing theoretical models, results obtained from monitoring activities, evolution in space and time of ground deformation processes, are also welcome. We particularly encourage the submission of manuscripts presenting new and/or innovative applications of remote sensing techniques and/or ground based-data for the management and monitoring natural catastrophic events, including data processing and analysis methods based on deep learning or other advanced methods.
Natural disasters are increasing worldwide, partly because of effects of climate changes. Ground deformation generated by catastrophic events represents a growing problem that affects hundreds of millions of people worldwide. The surface changes due to natural events, i.e. landslides, sinkholes, volcanic activities, land subsidence, etc., and can lead to structural damage of buildings and infrastructures, loss of extensive agricultural and/or natural areas, damage to tourist sites and cultural heritage, rise of salt wedges, regression of coastlines, and can have a significant economic and social impact. This negative impact can be further aggravated by climate change (e.g. sea level rise, modifications of rainfall intensity and period) in particular in low-lying coastal areas and unstable slopes. Ground deformation monitoring during and after a natural disaster plays a key role in the management of such natural hazards by providing cost-effective solutions for risk mitigation strategies.
This Research Topic is devoted to all research related to monitoring systems of ground deformations at various scales based on remote sensing techniques (in particular, but not limited to, InSAR) complemented with ground-based data (e.g. GNSS, precise leveling, Structure from Motion photogrammetry, Terrestrial Laser Scanning), including measurements from airplanes, helicopters, UAV. This Research Topic aims to collect original contributions focusing on both methodological aspects, including theoretical studies, and applications. The applications can concern every sector, from the natural environment (e.g. landslides, morphological changes of an area, etc.) to urban areas (e.g. buildings, old towns, bridges, dams, etc.), performed for various motivations (e.g. risk assessment, cultural heritage safeguard, geotourism, etc.).
Contributions in which remote sensing data are used in conjunction with data provided by other techniques to improve the quality of the results (accuracy, costs and times of survey and data processing), are welcome. Papers discussing theoretical models, results obtained from monitoring activities, evolution in space and time of ground deformation processes, are also welcome. We particularly encourage the submission of manuscripts presenting new and/or innovative applications of remote sensing techniques and/or ground based-data for the management and monitoring natural catastrophic events, including data processing and analysis methods based on deep learning or other advanced methods.
