Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author’s group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications.

Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation.

Damage assessment from very high resolution (VHR) remote sensing imagery plays a fundamental role in the delineation of the impact caused by catastrophic events. To date internationally accepted standard guidelines on how to assess damages to building using vertical imagery have not yet been developed. This study therefore proposes a building damage scale – and related interpretation guidelines to be operationally adopted as a standard by the main stakeholders – tailored to analyses based on VHR remote sensed vertical imagery. Preliminarily, some of the damage scales used for building damage assessment by the main satellite-based emergency mapping services have been analysed and discussed. A quantitative thematic accuracy analysis based on the open accessible crisis datasets related to the earthquake occurred in Central Italy in August 2016 has been carried out. The results highlight that by using VHR remotely sensed images it is not possible to directly apply damage classification scales addressing slight structural damages (e.g. the lowest grades proposed by EMS-’98). The paper demonstrates that using different damage classes and detailing the interpretation guidelines with operational examples is essential to increase the thematic accuracy of the analysis.

Digital twins (DTs) are highly valuable tools for urban planning as they provide a virtual replica of the physical city, integrating real-time data and simulations to enhance the decision-making and management processes. The use of DTs expands the possibilities for data integration and visualization in urban contexts. This includes real-time data measurements from multiple sources, such as sensors and IoT devices, facilitating comprehensive insights. DT’s virtual representation helps authorities and planners visualize urban dynamics and improve their understanding of urban ecosystems, energy efficiency, traffic management, emergency response, and more. DT supports the simulation and modeling of different scenarios in an urban built environment, enabling the predictive analysis of transformation decisions and the anticipation of future trends and challenges. This paper highlights the assumptions and ongoing progress in the development of a DT for the city of Turin (Italy), focusing on a range of applications, such as the extraction of built and natural environment features, land use data, road network and pavement quality, and signage, along with continuous model updates over time.

In recent years, growing attention is paid to remote sensing when used for disaster management applications. This is essentially due to the large variety of remotely acquired imagery available for the extraction of geometric and thematic features in order to map, delineate and grade natural disasters impacts. Another key point is the quick availability of those images in rapid mapping procedures in order to deliver the data (reference and thematic) to concerned users. This paper briefly describes the current state-of-the-art of remote sensing techniques usage in emergency mapping, paying particular attention, in the second part, to the GIO-EMS new operational service delivered by the European Commissio