Editorial: Management and monitoring of natural disasters using remote sensing and ground-based data

Introduction: Intensity and frequency of the natural disasters are increasing worldwide, above all also because of human activity and related effects on climate changes. In this context, 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, coastal erosion, volcanic activities, earthquakes, land subsidence, etc., 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) and by climate change driven increased anthropogenic influence (e.g., groundwater withdrawal) in particular in low-lying coastal areas and unstable slopes. Ground deformation monitoring before (when possible), during and after a natural disaster plays a key role in the management of such natural hazards by providing cost-effective solutions for implementing risk mitigation strategies. Management and monitoring of natural events can be performed using different data: they can be acquired at various scales based on remote sensing techniques (in particular, but not limited to, InSAR–Interferometric Synthetic Aperture Radar) complemented with ground-based surveys (e.g., GNSS–Global Navigation Satellite System, precise leveling, Structure from Motion photogrammetry, Terrestrial Laser Scanning), including measurements from airplanes, helicopters, UAV (Unmanned Aerial Vehicle) as well as USVs (Unmanned Surface Vehicles) or also UUVs (Unmanned Underwater Vehicles). As each technique is characterized by advantages and disadvantages, when remote sensing data are used in conjunction with data provided by other techniques the quality of the final results improves (in terms of accuracy, costs and times of survey and data processing). In this way, the integration of data obtained from different sources play a fundamental role to improve the information that must be available for every risk mitigation activity.