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The processes of land transformation related to soil erosion and land degradation are complex phenomena that require an approach as detailed and multidisciplinary as possible. In some Mediterranean inland areas, these issues seem to be very connected to the dynamics of transformation and abandonment of agricultural areas. In order to carry out this preliminary investigation for the assessment of dynamics and relationships between processes and land cover, an approach based on GIS and remote sensing has been applied. The study started with implementation of the Revised Universal Soil Loss Equation (RUSLE) model to calculate soil erosion on a monthly and annual basis. The resulting data were then processed through a Getis-Ord local autocorrelation index in order to produce a persistent erosion map. All datasets created were correlated with the cover classes that need more attention, i.e., arable land and post-cultivation vegetation area. All the techniques and methodologies, have been applied in a rural area of the Basilicata Region (South Italy) using exclusively a Free and Open Source Software (FoSS) GIS approach as it guarantees the possibility to perform a series of complex analyses in a simple and effective way so that they can be implemented in environmental monitoring actions and plans.

Fires are one of the main causes of environmental degradation as they have an impact on flora and fauna, can also strongly influence ecological and geomorphological processes and permanently compromise the functionality of the ecosystems and soils on which they impact. The severity of the fire event influences the superficial hydrological response and the consequent loss of soil. Precipitation on the basins recently affected by fires produces an increase in the outflow which commonly transports and deposits large volumes of sediment, both inside and downstream of the burned area. In the years following the fire, the loss of soil is very high and the degradation processes of the soils are much greater than in the pre-event. The aim of this study is to evaluate the potential annual loss due to post-fire erosion using remote sensing techniques, RUSLE (Revised Universal Soil Loss Equation) methodology and GIS tecniques in nine different event occurred in 2019 in the northern part of the Apulia Region (Southern Italy). Geographic Information System techniques and remote sensing data have been adopted to study the post-fire soil erosion risk. Satellite images are the most appropriate for environmental monitoring as they provide high resolution multispectral optical images, infact are able to monitor the development of vegetation by assessing the water content an changes in chlorophyll levels. This study can be useful to spatial planning authorities as a tool for assessing and monitoring eroded soil in areas affected by fires, representing a useful tool for land management.

Italy is a geologically complex and relatively young territory that is particularly vulnerable to natural disasters (i.e., earthquakes, flooding, landslides). In particular, landslide activity is considered one of the most relevant processes shaping the Italian peninsula, often closely affecting urban and industrial areas and infrastructures. Landslide activity in southern Italy strongly influenced the development of urban areas by controlling the shape and the areal extend of the urban settlements. In this paper, we propose a multidisciplinary approach capable of assessing the correlation between landslides and the spatial distribution of urban fabric. To this aim, we consider as case studies, the two municipalities of Pisticci and Corleto Perticara, in the Basilicata region in southern Italy, that strongly differ for the geological contexts and landslide types. The evolution in time of the landslide activity and the shape variations of the two considered settlement systems is described in terms of shape index from 1950 to 2006. Starting from the description of the two study areas, from both the geological and the urban point of view, the shape index will be calculated. Eventually, the results obtained will be compared with the perimeters of the urban centers defined by the respective urban planning regulations.

In this letter, we performed investigations on the potentiality of the Sentinel-1, C-band synthetic-aperture radar (SAR), for the characterization and mapping of burned areas and fire severity. To this aim, we focused on fire occurred on July 13, 2017, in Metaponto (South of Italy). Both VH and VV polarizations were considered. Radar Burn Difference (RBD) and radar burn ratio (RBR) were computed between Sentinel-1 data acquired before and after the fire using both single- and time-averaged scenes (to reduce speckle noise effects). The most marked differences between burned and unburned areas were observed in the VH polarization of both RBD and RBR. The novelty of our approach is based on the use of three steps data processing devised to identify different levels of fire severity without using fixed thresholds. The burned areas are first: 1) highlighted using the ratio between multitemporal data set acquired before and after the fire occurrence; 2) further enhanced by Getis–Ord spatial statistic; and 3) finally, categorized using ISODATA unsupervised classification. The approach herein proposed pointed out that: 1) the time-averaged ratio of VH polarization of Sentinel-1 well perform in mapping burned area and 2) the use of Getis–Ord spatial statistic coupled with ISODATA unsupervised classification suitably captures the diverse levels of burned severity as confirmed by in situ assessment.

In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoring and mitigation specifically devised for decision-makers and planning authorities. The main objectives of SERV_FORFIRE are: (i) to create a bridge between observations, model development, operational products, information translation and user uptake, and (ii) to contribute to creating an international collaborative community made up of researchers and decision-makers and planning authorities. For the purpose of this study, investigations into a fire burnt area were conducted in the south of Italy from a fire that occurred on 10 August 2017, affecting both the protected natural site of Pignola (Potenza, South of Italy) and agricultural lands. Sentinel 2 data were processed to identify and map different burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used to overcome the limits of fixed threshold values and to devise an automatic approach that is easier to re-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 random plots selected from in situ analyses performed extensively in the investigated burnt area. The field survey showed a success rate of around 95%, whereas the commission and omission errors were around 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 data allows the development of standardized burn severity maps to evaluate fire effects and address post-fire management activities that support planning, decision-making, and mitigation strategies.