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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.

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.

Soil erosion in fired areas is one of the main environmental problem involves degrading the quality of the soil and reducing the productivity of the affected lands. The aim of this work is to implement a procedure that analyzes the change detection of the potential soil eroded in a burned area, and discriminate the amount of potential soil loss. As part of the MESARIP project (in agreement with the Regional Civil Protection) in order to implement the analyses of soil erosion pre and post fire event, using Sentinel 2 data and with the RUSLE (Revised Universal Soil Loss Equation) method in a GIS open source environment, a graphical model has been developed. The application of the RUSLE requires a series of consequential spatial analysis elaborations and, according to this scheme, the model has been developed with the Graphical Modeler. QGIS contains in a single environment a multiplicity of tools and algorithms native to other open source GIS software, such as, for example, SAGA GIS and GRASS GIS. The user interface is very simple and requires basic and thematic input data such as DEM, MASK areas or vegetation indices etc. The advantages in the construction of the model can be identified in the standardization of map algebra operations and also in the speed of execution of the steps. Currently the model has been tested in some burned areas in 2019 located in the northern part of the Apulia Region and will be tested in operational mode during the 2020 summer season.

The use of plastic materials in agriculture involves several benefits but it results in huge quantities of agricultural plastic waste to be disposed of. Input and output data on the use of plastics in agriculture are often difficult to obtain and poor waste management schemes have been developed. The present research aims to estimate and map agricultural plastic waste by using satellite images. Waste was evaluated by means of the indexes relating waste production to crop type and plastic application as defined by the land use map realized by classifying the Landsat 8 image. The image classification was carried out using Support Vector Machines (SVMs), and the accuracy assessment showed that the overall accuracy was 94.54% and the kappa coefficient equal to 0.934. Data on the plastic waste obtained by the satellite land use map were compared with the data obtained by using the institutional land use map; a difference of 1.74% was identified on the overall quantity of waste.

Soil consumption represent an important indicator of soil management, in last few years the European States have been promoted the use and installation of renewable energy sources, with a consequent soil consumption increase. The aim of this work is to implement a procedure that analyzes the change detection of the soil consumption and discriminate those related to soil consumption due to installation of renewable energy sources from that due to built-up areas. The select test site is the Municipality of Melfi (Southern Italy) because is highly significant because is characterized by fragmented and various environments. The increase of urbanization is due to the growth of built-up areas and the exponential development of renewable sources installation. The work herein presented concerns an application study on these processes with the images of Sentinel-2 satellite. In order to produce a synthetic map of soil consumption, the Sentinel-2 images were classified using a supervised classification. A first map of soil consumption was obtained divided the area characterized by urbanization from the area with the presence of the renewable energy sources. Eolic class have been subdivided and reclassified, divided the relevant street from the turbine pad. Eolic class have been reclassified discriminate the relevant street from the turbine pad and subdivided into other subclasses referred to the power wind turbines, in order to quantify the soil consumption related to each one. All processes have been processes developed integrating Remote Sensing and Geographic Information System (GIS), using open source software.

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.

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.

A limited sector of the left side Sinni River, including Episcopia village, has been investigated matching geological and geomorphological data to In-SAR Interferometry analysis. A large Deep-Seated Gravitational Slopes (DSGSD), affecting the Episcopia slope, has been documented for the first time. The DSGSD largely develops within phyllites belonging to the Liguride Units and, in the upper portion of the slope, within the sandy and conglomerate deposits of the Sant’Arcangelo Basin. Field survey has shown typical DSGSD features as well as trenches at the top and an evident bulge at the base corresponding to the Sinni River. These data allow us to hypothesize a listric geometry of the DSGSD plane reaching a depth of about 700 m.

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 spread of new satellite and LiDAR data is recently leading to the development of effective methodologies to support the monitoring and management of disaster risks, assessing the level of damages in the very early post-event phase. The increasing availability of SAR images and the diffusion of LiDAR data due to technologies such as solutions such as drones offers the opportunity to experiment new techniques for monitoring the territory. The paper will examine the case study of Amatrice (Central Italy), the Municipality most affected by the seismic swarm started in August 2016, and discuss the results obtained with the technique of interferometric differentiation and detection of change.

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 investigations conducted previously on the Nasca puquios, with particular reference to those systematically performed by Schreiber and Lancho Rojas (1995), Schreiber and Lancho Rojas (Los puquios de Nasca: un sistema de galerias filtrantes. Editorial Los Pinos, Lima, 1998), Schreiber and Lancho Rojas (Aguas en el Desierto. Los puquios de Nasca. Fondo Editorial, Lima, Peru, 2006), have had the merit of placing the theme of Nasca water management in the center of debate on the ancient Nasca world. Water has become the crossroads of all the other research lines focused on the influence of environment and climate on the Nasca culture, as well as on the geoglyphs, ceremonial architecture, and settlements. In this cultural framework, some studies based on multitemporal, multiscale, and multisensor analyses have been performed in the Rio Grande de Nasca drainage in order to investigate the interaction between the puquios and environmental conditions, as well as to improve knowledge of the local environmental settings. Herein we present and discuss the investigations, based on the integration of remote sensing, GIS -based analyses, and geophysical prospecting, in the framework of the ITACA mission of the Italian CNR. Outputs from satellite-based investigations, along with all the information already available from previous studies, were the input data used in the statistical spatial analyses and geophysical prospecting. The main findings provided information useful to: (i) improve the current knowledge on the puquios at both intra-site and inter-site levels and their relationship with environmental and human settings, (ii) identify unknown puquios, (iii) and support planning for subsequent archaeological excavations. As a whole, the investigations based on the adopted integrated approach provided new insights into this hyper-arid area which has been the homeland for numerous civilizations, despite the extreme physical environment that presents serious obstacles to human occupation.

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.