Despite the recognized effectiveness of LiDAR in penetrating forest canopies, its capability for archaeological prospection can be strongly limited in areas covered by dense vegetation for the detection of subtle remains scattered over morphologically complex areas. In these cases, an important contribution to improve the identification of topographic variations of archaeological interest is provided by LiDAR-derived models (LDMs) based on relief visualization techniques. In this paper, diverse LDMs were applied to the medieval site of Torre Cisterna to the north of Melfi (Southern Italy), selected for this study because it is located on a hilly area with complex topography and thick vegetation cover. These conditions are common in several places of the Apennines in Southern Italy and prevented investigations during the 20th century. Diverse LDMs were used to obtain maximum information and to compare the performance of both subjective (through visual inspections) and objective (through their automatic classification) methods. To improve the discrimination/extraction capability of archaeological micro-relief, noise filtering was applied to Digital Terrain Model (DTM) before obtaining the LDMs. The automatic procedure allowed us to extract the most significant and typical features of a fortified settlement, such as the city walls and a tower castle. Other small, subtle features attributable to possible buried buildings of a habitation area have been identified by visual inspection of LDMs. Field surveys and in-situ inspections were carried out to verify the archaeological points of interest, microtopographical features, and landforms observed from the DTM-derived models, most of them automatically extracted. As a whole, the investigations allowed (i) the rediscovery of a fortified settlement from the 11th century and (ii) the detection of an unknown urban area abandoned in the Middle Ages.

The current study aims to analyse the conservation state of the Sassi of Matera site (Southern Italy), a place inscribed on the UNESCO World Heritage List since 1993 (the Sassi and the Park of the Rupestrian Churches of Matera) and recently awarded 2019 European Capital of Culture. Furthermore, the article considers the influence of some of the causative factors controlling the Matera building conservation state, paying particular attention to the site microclimatic conditions such as the insolation and winds. We studied this subject through a new methodology that makes a combined use both of stone decay data gained from the extensive field assessments of the visible weathering forms catalogued in an ad hoc questionnaire and GIS advanced spatial analysis techniques such as Map Algebra and Kernel Density Estimation. The research puts into evidence that the Sassi of Matera shows a fair state of conservation that is conditioned by the wind/rain actions and sun exposure. Besides, just the already well known facts that the surfaces facing north seem to be most influenced by the wind/rain actions; and that, on the contrary, the decay of the walls facing south seems to be guided mainly from the sun exposure, put into evidence the importance of locating the intensities of the decays in any urban tissue or any site in order to plan conservation interventions and prioritize actions and the usefulness of the spatial analysis techniques and data processing.Project “PRO_CULT” (Advanced methodological approaches and technologies for Protection and Security of Cultural Heritage) financed by Regional Operational Programme ERDF 2007/2013.Peer reviewe

Earthquake insurance can be a useful tool to build more sustainable societies and disaster-resilient communities. However, the coverage is not common in many countries. This article aims to contribute to the literature through an empirical analysis of the online interest in earthquake insurance through Google Trends. The proposed methodology implies to move from a top-down conceptual approach to a bottom-up/data-enabled one. It allows us to explore potential triggers and dynamic patterns of online interest in earthquake insurance at daily time-scale through the lens of Big Data. In order to validate the methodology, the article considers Italy as a test area. For this country, where the coverage rate is low, we fuse multiple databases to create 16-year daily time series of public search activities about the insurance in Italy and analyse it with other data sources. As a result, the peak analysis shows a connection with the occurrences of large domestic earthquakes, overseas earthquakes, and policy decisions, which create time windows of opportunities for insurers and policymakers to boost the public’s motivation towards the coverages. The research outcomes suggest that the data-enabled approach can additionally be applied in other countries where the coverage rate is low and stakeholders are facing the challenge to strive against earthquake under-insurance.

This paper deals with a UAV LiDAR methodological approach for the identification and extraction of archaeological features under canopy in hilly Mediterranean environments, characterized by complex topography and strong erosion. The presence of trees and undergrowth makes the reconnaissance of archaeological features and remains very difficult, while the erosion, increased by slope, tends to adversely affect the microtopographical features of potential archaeological interest, thus making them hardly identifiable. For the purpose of our investigations, a UAV LiDAR survey has been carried out at Perticara (located in Basilicata southern Italy), an abandoned medieval village located in a geologically fragile area, characterized by complex topography, strong erosion, and a dense forest cover. All of these characteristics pose serious challenge issues and make this site particularly significant and attractive for the setting and testing of an optimal LiDAR-based approach to analyze hilly forested regions searching for subtle archaeological features. The LiDAR based investigations were based on three steps: (i) field data acquisition and data pre-processing, (ii) data post-processing, and (iii) semi-automatic feature extraction method based on machine learning and local statistics. The results obtained from the LiDAR based analyses (successfully confirmed by the field survey) made it possible to identify the lost medieval village that represents an emblematic case of settlement abandoned during the crisis of the late Middle Ages that affected most regions in southern Italy.

This paper demonstrates how historical research is a valuable tool for identifying past geological, geomorphological and climatic hazards and therefore critical for mitigating and reducing future risk. The authors describe the potential of a scientific field that straddles that of the geologist, geographer, historian and archivist. Historical records include a range of materials and sources of information, which can be very diverse; from written documents to cartographies, and from drawings to marble tombstones. They are all useful and convey important data, on the date of the event, the size of the phenomena, sometimes on ground effects, damage or magnitude. The authors discuss how to conduct historical research by providing a list of locations and how important historical documents can be found. Works that mention geological phenomena are listed, starting with the first occasional descriptions by individuals in letters, up to very specific publications in individual fields of interest. With this introduction, the editors of the Special Issue wish to draw attention to the importance of historical documentation, which is too often ignored or considered of low priority by the scientific community, but can contain key information on events, their impacts and social and cultural adaptations.