1,721,012 research outputs found
Per un progetto di suolo alla scala di distretto urbano/ For a “land project” at the urban district scale
No full textTerrace Abandonment Hazards in a Mediterranean Cultural Landscape
No full textThe phenomenon of the abandonment of terraced landscapes compromises environmental well-being and is a preamble to hydrological instability and, consequently, the collapse of terrace retaining walls, soil erosion, and loss of agricultural lands. These problems will escalate in the coming years because of climate change (CC), especially in areas in which a rise in rainfall events is expected, such as the coastline of the Campania region, which is exposed to extreme rainfall events. This study identifies a landscape management guideline for Crapolla Fiord on the Amalfi coast (Campania region), a typical cultural landscape characterized by the presence of archaeological ruins. Potential hazards were evaluated and quantified, taking into account the flow rate and the rain intensity both at the mountainside and microbasin scale. This study shows that potential hazards have increased because of the loss of terraces and may further increase due to the abandonment of agriculture. This paper points out that supporting measures are necessary in areas in which agricultural land use is still present and that the introduction of small interventions designed to raise the infiltration capacity of the soil and/or to regenerate vegetation in areas in which terraces have been lost is a best practice
Per un "progetto di suolo" alla scala di distretto urbano = For a “land project” at the urban district scale
No full textA novel approach for detecting agricultural terraced landscapes from historical and contemporaneous photogrammetric aerial photos
No full textTerraces are the most distinctive sign of human activity on the shape of the Earth surface. Their construction has increased the soils permeability and reduced the slope gradient of mountains since those territories could be exploited both for agricultural and habitable purposes. Over the last decades, they have been the subject of a quick abandonment due to their scarce competitiveness. This has caused some environmental problems, such as soil degradation and hydrological instability. Minori in Italy is one of the most ancient municipalities in the Mediterranean area characterized by the presence of terraces. This paper intends to develop a method for automatic extraction of terraces from historical and contemporaneous aerial photos using an Object-based Image Analysis (OBIA) approach. Historic photos from 1956, acquired by the Geographical Military Institute (IGM), and a contemporaneous block of RGB and multispectral images, taken in 2017 of the study area have been processed to generate a high resolution Digital Elevation Model (DEM) and detailed orthophotos. Subsequently, the OBIA classification has been applied for producing a binary map of terraced and not terraced landscapes for both datasets. Orthophoto resolution was equal to 240 mm, 7 mm and 15 mm for the historical, RGB and multispectral pictures, respectively. DEM resolution results equal to 480 mm and 0.19 mm for the historical and RGB set of data. The R 2 between the check points and the estimated values, generated during the metric reconstructions of the two obtained DEMs, resulted equal to 0.99 for both datasets (1956 and 2017). The classification accuracy of the generated binary maps (terraced/not terraced landscapes) were equal to 93% and 98%, respectively. The developed approach looks promising for the historical and contemporaneous datasets. That outcome is essential because it allows to detect terraces position and to compare them over the years in order to analyse their evolution and geomorphological changes
Extracting Land Surface Albedo from Landsat 9 Data in GEE Platform to Support Climate Change Analysis
Full text linkLand surface albedo is a relevant variable in many climatic, environmental, and hydrological studies; its monitoring allows researchers to identify changes on the Earth’s surface. The open satellite data that is provided by the USGS/NASA Landsat mission is quite suitable for estimating this parameter through the remote sensing technique. The purpose of this paper is to evaluate the potentialities of the new Landsat 9 data for retrieving Earth’s albedo by applying da Silva et al.’s algorithm (developed in 2016 for the Landsat 8 data) using the Google Earth Engine cloud platform and R software. Two urban areas in Southern Italy with similar geomorphologic and climatic characteristics were chosen as study sites. After obtaining thematic maps of the albedos here, a statistical analysis and comparison among the Landsat 8 and Landsat 9 results was performed considering the entire study areas and each land use/land cover class that is provided by the Copernicus Urban Atlas 2018. This approach was also applied to the data after being filtered through Tukey’s test (used to detect and remove outliers). The analysis showed a very good correlation between the Landsat 8 and Landsat 9 estimations (ρ > 0.94 for both sites), with some exceptions that were related to some mis-corresponding values. Furthermore, the Landsat 8 and Landsat 9 outliers were generally overlapping. In conclusion, da Silva et al.’s approach appears to also be reasonably applicable to the Landsat 9 data despite some radiometric differences
La conoscenza dei suoli urbani per la riduzione del rischio Climate Change / Enhancing urban soils for reducing Climate Change risk
No full textIl contributo si inquadra nell'ambito della ricerca condotta per il progetto Metropolis sul tema della conoscenza dei suoli urbani. In particolare, il saggio riporta in forma critica l'excursus metodologico per la definizione e la misura di alluni indicatori chiave per il funzionamento ecologico dei suoli nell'area orientale di Napoli
A Crowd-Sensing System for Geomatics Applications
No full textRisk prevention is recognized as one of the most critical aspects of the policies of environmental monitoring. Because of the limited resources and the large amount of structures used for erosion control and slope protection, the Civil Protection and the Italian Forestry Carabinieri are not able to supervise them directly, with enough frequency. The present work is aimed to develop an innovative technique for periodically monitoring those structures, combining Mobile Crowd-Sensing (MCS) technology with photogrammetry and GIS. The experiments were performed in the Nature Reserve of Tirone (a protected natural area located inside the Vesuvius National Park in Naples) by analysing the metric reconstruction of two structures (a small weir and a log crib wall), before and after an accident, artificially generated for simulating a hydrogeological event or an act of vandalism, in order to evaluate GCPs influence. The procedure was split into four main phases: periodic acquisition of sets of photos with common smartphones and their transmission via the Internet; elaboration of the threedimensional model starting from a subset of selected pictures; comparison between the generated and the previous model; database update and programming of the subsequent monitoring. The accuracy of photogrammetric reconstructions was evaluated comparing the reconstruction with and without Ground Control Points (GCPs). The results show the models extracted without GCPs are satisfactory, since they allow to retrieve dimensional information of the examined constructions and to detect any instability. Models, generated using GCPs, are more detailed, but the processing and operational time is strongly higher. © 2019, Springer Nature Switzerland AG
Earth Observation Data for Sustainable Management of Water Resources to Inform Spatial Planning Strategies
No full textWater is a vital resource for sustaining human life, well-being, and the Earth’s biodiversity and ecosystems. However, its availability and usability are decreasing due to strong anthropogenic pressure and intense climatic stress, leading to a variety of environmental issues, including desertification. Consequently, areas exposed to these factors, such as those in Southern Italy, are highly vulnerable to desertification. To address soil deterioration, it is crucial to identify and implement appropriate land management strategies aimed at promoting sustainability and improving ecosystem services. Remote sensing techniques provide a low-cost and non-destructive tool for extracting baseline information on water bodies, land use/cover classes, and Earth morphology features. When combined with meteorological data, these techniques can help identify the most effective, efficient, and sustainable water management strategies to tackle desertification. This is made possible by the vast amount of publicly available medium-resolution satellite data, such as Landsat and Sentinel missions, as well as open-source cloud infrastructures for managing big geographic data, like Google Earth Engine (GEE). The primary goal of this study is to provide a reference framework for a comprehensive workflow that moves from available data, through their proper elaboration with models, to knowledge management aimed at informing public policies. The case study presented provides a snapshot of the current state of natural water resource availability in the Apulian environment by identifying and evaluating the key hydrological balance components provided by the BIGBANG model. The input data for the model were images from Landsat missions and climate data handled in GEE. The results from the BIGBANG model were then used to define a scenario analysis to determine the best water resource planning and management policies
Indirect field technology for detecting areas object of illegal spills harmful to human health: application of drones, photogrammetry and hydrological models
Full text linkThe accumulation of heavy metals in agricultural soils is a serious environmental problem. The Campania region in southern Italy has higher levels of cancer risk, presumably due to the accumulation of geogenic and anthropogenic soil pollutants, some of which have been incorporated into organic matter. The aim of this study was to introduce and test an innovative, field-applicable methodology to detect heavy metal accumulation using drone-based photogrammetry and microrill network modelling, specifically to generate wetlands wetlands prediction indices normally applied at large catchment scales, such as a large geographic basin. The processing of aerial photos taken using a hexacopter equipped with fifth-generation software for photogrammetry allowed the generation of a digital elevation model (DEM) with a resolution as high as 30 mm. Not only this provided a high potential for the study of micro-rill processes, but it was also useful for testing and comparing the capability of the topographic index (TI) and the clima-topographic index (CTI) to predict heavy metal sedimentation points at scales from 0.1 to 10 ha. Our results indicate that the TI and CTI indices can be used to predict points of heavy metal accumulation for small field catchments
Monitoring and modelling the role of phytoremediation to mitigate non-point source cadmium pollution and groundwater contamination at field scale
No full textThis study evaluates the effectiveness of a phytoremediation technique developed within the framework of the EU-Life+ EcoRemed project and used to remove potentially toxic elements (PTEs) from some agricultural sites of the Campania Region in southern Italy. The methods discussed here should be viewed as a proof-of-concept and their potential is shown at the “Trentola” test site contaminated by low concentrations of cadmium. Advanced monitoring equipment together with modeling tools, based on the Richards and advective-dispersive equations. Coupling field monitoring and computer modeling is employed to estimate water flow and solute transport in the soil-vegetation-atmosphere system, with specific emphasis to assess the fate of the contaminant towards the groundwater. The role exerted by the EcoRemed phytoremediation protocol is evaluated by comparing two scenarios: 1) a bare soil only condition (BS scenario), and 2) a distributed phytoextraction activity obtained by planting poplar trees (Populus nigra spp) (PP scenario). The HYDRUS-1D code is used to model water flow and contaminant transport at soil-plant scale. The results showed the importance of using cost-effective monitoring devices to calibrate the soil parameters to properly describe the movement in the rhizosphere. Sensitivity analyses enabled specific features of the phytoextraction process to be identified. Moreover, especially with the aim of transferring the gained knowledge to public bodies and stakeholders, the scenarios based on 1-D numerical simulations should be conveniently complemented with simulations carried out at the scale of the entire field area, as shown in this study using the three-dimensional HydroGeoSphere (HGS) code
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