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Fire effects consist not only in direct damage to the vegetation but also in the modification of both chemical and physical soil properties. Fire can affect the alteration of soil properties in different ways depending on fire severity and soil type. The most important consequences concern changes in soil responsiveness to the water action and the subsequent increase in sediment transport and erosion. Post fire soil loss can increase in the first year by several orders of magnitude compared to pre-fire erosion. In this study a distributed model based on the Revised Universal Soil Loss Equation (RUSLE) is used to estimate potential post-fire soil loss for four different fire events occurred in Basilicata region in 2017. Geographic Information System techniques and remote sensing data have been adopted to build a prediction model of post-fire soil erosion risk. Results show that this model is not only able to quantify post-fire soil loss but also to identify the complexity of the relationships between fire severity and all the factors that influence soil susceptibility to erosion.

The analysis of 4 year In-SAR Interferometry images and a detailed geomorphological survey have been carried out to detect a large Deep-Seated Gravitational Slopes (DSGSD) affecting the urban area of the Episcopia village, in Southern Italy. The DSGSD largely develops within phyllites of the Liguride Units and, in the upper slope, within Pleistocene sand and conglomerate deposits of the Sant'Arcangelo Basin. Field survey has shown trenches at the top and an evident bulge at the base of the DSGSD, corresponding to the Talweg of the Sinni River. Geological and geomorphological field surveys allowed us to hypothesize a listric geometry of the DSGSD subsurface plane reaching about 700 m of depth. Furthermore, the multi-temporal In-SAR Interferometry analysis collected from November 2014 to May 2017 revealed that a ground deformation of +/- 30 mm was occurred, and the process is still active in the whole area.

Urban sprawl phenomenon is one of the higher threats to the preservation of soil resources. Soil consumption is strongly related to social and economic factors that characterize a territory. Several models have been developed to recreate future scenarios based on past expansion development dynamics. Among cellular automata models for urban growth simulation, SLEUTH is considered as an effective tool to support urban management. However, the model does not explicitly include demographic dynamics and socio-economic ones. This paper compares the results of two different simulations performed on the same study area through the SLEUTH model. While the first simulation is performed using the classical method of calibration of the model, the second one proposes the inclusion of some socio-economic variables within the simulation process. The results show a better match with the actual development trends of settlement by the simulation that takes into account the social and economic aspects of the analysed territory.

The increasing accessibility of Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR) data, grants the opportunity to experiment new methods to support disaster risk management. However, while SAR analyses are becoming extremely popular, thanks, in particular, to the availability of open source satellite images such as those from the Copernicus project, LiDAR analyses are still less common because of the scarce availability of this type of data over significant time frequencies. In this paper we propose an innovative procedure based on the use of SAR and LiDAR data to rapidly assess seismic damage in the early post-emergency phases. The methodology was applied to the case study of the town of Amatrice (Central Italy), which was hit by a strong earthquake swarm that started in August 2016. Specifically, SAR data is used for a large-scale analysis of terrain displacements following the seismic event, while LiDAR reliefs are used to carry out a change detection and to identify the level of damage at a building-scale in the urban settlement of Amatrice. Results will show how the proposed approach can be extremely effective both in the non-emergency phases to monitor seismic-affected areas and support emergency planning, as well as during the immediate post-earthquake phases to assess the damage it has caused and to support first aid dispositions.

Recent Italian earthquakes have been highlighted the role of the historical centers and their high vulnerability. To define effective mitigation strategies, the historical environments must be accurately investigated. The first and fundamental step is an assessment based on the knowledge of dimensional characteristics, construction techniques and materials. The seismic vulnerability evaluation depends on the quality and completeness of information available for the buildings under examination. In this paper, the characterization of an historical center and its buildings has been treated considering a new approach and existing common techniques for assessment of buildings' dimensional characteristics. Using GIS, data collected on the investigated historical center has been analyzed to obtain the typological characterization of the surveyed buildings in order to evaluate the seismic vulnerability, urban resilience, and recovery strategies for historical center. Based on comparison with an existing classical procedure, the approach seems also very promising in order to carry out a first evaluation of post seismic damage.

This article is focused on the FIRESAT methodology developed for and funded by the Protezione Civile of the Basilicata Region. The fire monitoring system is based on satellite free of charge data and developed for the dynamic estimation of vegetation fire susceptibility and fire impact in forest and non-forestry ecosystems. The purpose of this fire risk system is the timely (daily) and detailed (from 1 km down to 30 m) monitoring of the vegetation and meteorological conditions which can affect the proneness of vegetation to fire. FIRESAT provides operational monitoring tools for a systematic forest fire management from risk estimation to fire severity mapping, including the estimation of fire damage on hydro-geological risk and vegetation fire resilience.

Landscape preservation in Italy is a major issue in national cultural heritage conservation policies. Urban settlements growth is among the most threatening factors for the correct landscape preservation. Such phenomenon may result in corrupting the correct landscape-system functioning, particularly when the development occurs without precise planning prescriptions. Land-use/cover evolution dynamic is a subject widely and thoroughly investigated, especially concerning consumption of natural and other lands due to anthropogenic activities. This paper focuses on a region in southern Italy, where soil consumption is known to represent a urging matter of concern. However, although the negative impacts of soil consumption are well known, to our knowledge there are no case studies presenting a precise quantitative assessment of the intensity of such phenomenon for the region of interest. Furthermore, this study aims at forecasting the development of urban settlements through the application of the cellular automata model SLEUTH; the case study concerns the Municipality of Altamura (Apulia region, Italy). Results highlight how current landscape preservation instruments alone cannot ensure a reduction in soil consumption phenomenon and how urban areas expansion is incompatible with a correct landscape conservation in the study area.

The 2030 Agenda by United Nations highlights the necessity of undertake concrete actions to “protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss”. However, human activities on land use are strongly threatening habitat quality, causing their fragmentation and a dramatic loss of biodiversity all over the world. This paper proposes an application of the InVEST Habitat Quality model as a tool to support the definition of sustainable development policies able to favour the preservation of habitat structures while promoting their exploitation as cultural and landscape assets. The model is applied to the Basilicata Region (Southern Italy). Results show how modelling the impacts of human activities on biodiversity and ecosystem services can strongly help planning activities in distinguish those areas that should undergo to a conservation regime to preserve habitat integrity from those which are most prone to transformations, taking advantage by the social and economic benefit deriving from the human activities connected to their use.

Up to nowadays, satellite data have become increasingly available, thus offering a low cost or even free of charge unique tool, with a great potential for operational monitoring of vegetation cover, quantitative assessment of urban expansion and urban sprawl, as well as for monitoring of land use changes and soil consumption. This growing observational capacity has also highlighted the need for research efforts aimed at exploring the potential offered by data processing methods and algorithms, in order to exploit as much as possible this invaluable space-based data source. The work herein presented concerns an application study on the monitoring of vegetation cover with the use of multi-temporal (2010-2014) satellite Modis data. The selected test site is the Iguazu park highly significant, being it one of the most threatened global conservation priorities (http://whc.unesco.org/en/list/303/). In order to produce synthetic maps of the investigated areas to monitor the status of vegetation and ongoing subtle changes, satellite data were processed using Principal Component Analysis (PCA). Results from our investigations pointed out an ongoing degradation trend.

Among the objectives of the Sustainable Development Goals by United Nations, "Affordable and Clean Energy" aims at ensuring access to affordable, reliable, sustainable and modern energy for all. However, in Europe there is not a precise understanding of the unleashed potential that could be achieved through the exploitation of solar and wind resources. This study presents an application to retrieve spatial explicit estimates of Direct Normal Irradiance (DNI) through the use of data from geo-stationary satellites. The energetic demand of large metropolitan areas in Europe is then retrieved and compared with the potential production of energy for domestic use through solar panels. Results of this comparison are presented based on the assumption that only the 1 % of the built up area could be covered with solar panels, and hence devoted to energy production. Outcomes suggest that even such a little coverage, if spread systematically over urban areas can in most of the cases satisfy urban population domestic needs.

The negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective monitoring and containment measures have not been started, yet. This research proposes a methodology to map and monitor land use changes. To this end, a time series from 1985–2010, based on the multi-temporal Landsat data Thematic Mapper (TM), has been analyzed in the Vulture Alto-Bradano area, a mountain zone of the Basilicata region (Southern Italy). Results confirm a double potentiality of using these data: on the one hand, the use of multi-temporal Landsat data allows going very back in time, producing accurate datasets that provide a phenomenon trend over time; on the other hand, these data can be considered a first experience of open data in the field of spatial information. The proposed methodology provides agencies, local authorities and practitioners with a valuable tool to implement monitoring actions. This represents the first step to pursue territorial governance methods based on sustainability, limiting the land take.