1,720,974 research outputs found
Geo-Lehrpfad. Bletterbach. Geologischer Wanderführer durch den Bletterbach Aldein/Radein.
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Integration of remotely sensed soil sealing data in landslide susceptibility mapping
Full text linkSoil sealing is the destruction or covering of natural soils by totally or partially impermeable artificial material. ISPRA (Italian Institute for Environmental Protection Research) uses different remote sensing techniques to monitor this process and updates yearly a national-scale soil sealing map of Italy. In this work, for the first time, we tried to combine soil sealing indicators as additional parameters within a landslide susceptibility assessment. Four new parameters were derived from the raw soil sealing map: Soil sealing aggregation (percentage of sealed soil within each mapping unit), soil sealing (categorical variable expressing if a mapping unit is mainly natural or sealed), urbanization (categorical variable subdividing each unit into natural, semi-urbanized, or urbanized), and roads (expressing the road network disturbance). These parameters were integrated with a set of well-established explanatory variables in a random forest landslide susceptibility model and different configurations were tested: Without the proposed soil-sealing-derived variables, with all of them contemporarily, and with each of them separately. Results were compared in terms of AUC(area under receiver operating characteristics curve, expressing the overall effectiveness of each configuration) and out-of-bag-error (estimating the relative importance of each variable). We found that the parameter "soil sealing aggregation" significantly enhanced the model performances. The results highlight the potential relevance of using soil sealing maps on landslide hazard assessment procedures
Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization
Full text linkThe literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been established. This point is crucial, especially when working on wide and complex areas, in which a detailed geological map needs to be reclassified according to more general criteria. In a study area in Italy, we tested different configurations of a random forest–based landslide susceptibility model, accounting for geological information with the use of lithologic, chronologic, structural, paleogeographic, and genetic units. Different susceptibility maps were obtained, and a validation procedure based on AUC (area under receiver-operator characteristic curve) and OOBE (out of bag error) allowed us to get to some conclusions that could be of help for in future landslide susceptibility assessments. Different parameters can be derived from a detailed geological map by aggregating the mapped elements into broader units, and the results of the susceptibility assessment are very sensitive to these geology-derived parameters; thus, it is of paramount importance to understand properly the nature and the meaning of the information provided by geology-related maps before using them in susceptibility assessment. Regarding the model configurations making use of only one parameter, the best results were obtained using the genetic approach, while lithology, which is commonly used in the current literature, was ranked only second. However, in our case study, the best prediction was obtained when all the geological parameters were used together. Geological maps provide a very complex and multifaceted information; in wide and complex area, this information cannot be represented by a single parameter: more geology-based parameters can perform better than one, because each of them can account for specific features connected to landslide predisposition
Forme di urbanizzazione e tipologia insediativa
Full text linkLa conoscenza delle diverse forme di urbanizzazione e della tipologia insediativa è un elemento fondamentale della sostenibilità e della resilienza urbana. I processi di diffusione, dispersione urbana e di frammentazione continuano a produrre un effetto di “città diffusa” con conseguente perdita di limiti tra territorio urbano e rurale (Indovina, 1990, 2009; Simon, 2008). Il consumo di risorse e la sottrazione di qualità al territorio si presenta attraverso la creazione di centri urbani di dimensione medio-piccola all’esterno dei principali poli metropolitani, la crescita di zone di margine con insediamenti dispersi intorno ai centri, la saldatura di zone di insediamento a bassa densità in un continuum che annulla i limiti tra territorio urbano e rurale, la frammentazione del paesaggio e la mancanza di identità dei nuclei urbanizzati sparsi e senza coesione. Gli effetti ambientali e sociali dei fenomeni di espansione delle città a bassa densità e dello sprawl urbano sono rilevanti in termini di qualità ambientale, di integrità del paesaggio e di consumo di risorse naturali. L’entità di tali effetti dipende fortemente dalla modalità con la quale si realizza la trasformazione. In Europa e in Italia, l’espansione delle superfici impermeabilizzate, si manifesta nella frangia urbana e peri-urbana di molte importanti città come commistione di tipologie di uso del suolo diversificate e come aumento più marcato del consumo di suolo proprio nelle aree di margine e nei paesaggi suburbani (EEA, 2006; ISPRA, 2015). A questi fenomeni di espansione diffusa si associano, inoltre, costi pubblici e privati associati alla mobilità e alla fornitura e alla gestione delle opere di urbanizzazione primaria e secondaria. La frammentazione produce, infine, una forte riduzione della qualità della biodiversità complessiva nelle aree interessate, sia in termini di capacità residua di connessione degli ecosistemi sia di disponibilità dei servizi ecosistemici nelle unità territoriali.The knowledge of the different forms of urbanization and type of settlements are key element of sustainability and urban resilience. The processes of diffusion, urban sprawl and fragmentation continue to produce a consequent loss of boundaries between urban and rural land (Guess, 1990, 2009; Simon, 2008). Consumption of natural resources and threatening of land quality take place through the creation of small-medium sized urban centers outside of the major metropolitan, through the growth of dispersed settlements in marginal areas around the centers, through low-density settlement in a continuum that cancels the boundaries between urban and rural land, through landscape fragmentation and the lack of identity of the settlements scattered and without cohesion. The environmental and social effects of those phenomena are relevant in terms of environmental quality, integrity of the landscape and the consumption of natural resources. The magnitude of these effects depends strongly on how transformation is realized. In Europe and in Italy, the majority of expansion of the sealed areas is in urban and peri-urban fringe of many major cities, as a mixture of different types of land use, driving to the greater increase in the land take in this fringe areas and suburban landscapes (EEA, 2006; ISPRA, 2015). Is known that dispersed and fragmented urbanization is associated with widespread expansion of public and private costs associated with mobility and costs of primary and secondary urbanization. Fragmentation produces, finally, a strong reduction in the quality of the overall biodiversity, in terms of residual capacity of connection of ecosystems and the availability of ecosystem services in the territorial units
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispersione urbana in Europa
No full textL’indice di dispersione, definito come il rapporto tra aree a bassa densità e aree urbanizzate, può essere impiegato per un primo confronto tra le diverse aree urbane a livello europeo. Nel merito dei dati, sebbene in ambito nazionale l’indice di dispersione della città di Roma non risulti particolarmente elevato, e rientri tra i valori medi dei principali comuni italiani, in un contesto europeo tale valore diventa tra i più alti fra le città considerate, evidenziando la maggiore tendenza alla dispersione e alla diffusione insediativa della nostra Capitale rispetto alle altre citta
Satellite open data to monitor forest damage caused by extreme climate-induced events: A case study of the Vaia storm in Northern Italy
No full textThe frequency of extreme storm events has significantly increased in the past decades, causing significant damage to European forests. To mitigate the impacts of extreme events, a rapid assessment of forest damage is crucial, and satellite data are an optimal candidate for this task. The integration of satellite data in the operational phase of monitoring forest damage can exploit the complementarity of optical and Synthetic Aperture Radar (SAR) open datasets from the Copernicus programme. This study illustrates the testing of Sentinel 1 and Sentinel 2 data for the detection of areas impacted by the Vaia storm in Northern Italy. The use of multispectral Sentinel 2 provided the best performance, with classification overall accuracy (OA) values up to 86 percent; however, optical data use is seriously hampered by cloud cover that can persist for months after the event and in most cases cannot be considered an appropriate tool if a fast response is required. The results obtained using SAR Sentinel 1 were slightly less accurate (OA up to 68 percent), but the method was able to provide valuable information rapidly, mainly because the acquisition of this dataset is weather independent. Overall, for a fast assessment Sentinel 1 is the better of the two methods where multispectral and ground data are able to further refine the initial SAR-based assessment
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