Massimo Conforti

Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy)

The Calabria (Southern Italy) region is characterized by many geological hazards among which landslides, due to the geological, geomorphological, and climatic characteristics, constitute one of the major cause of significant and widespread damage. The present work aims to exploit a bivariate statistics-based approach for drafting a landslide susceptibility map in a specific scenario of the region (the Vitravo River catchment) to provide a useful and easy tool for future land planning. Landslides have been detected through air-photo interpretation and field surveys, by identifying both the landslide detachment zones (LDZ) and landslide bodies; a geospatial database of predisposing factors has been constructed using the ESRI ArcView 3.2 GIS. The landslide susceptibility has been assessed by computing the weighting values (Wi) for each class of the predisposing factors (lithology, proximity to fault and drainage line, land use, slope angle, aspect, plan curvature), thus evaluating the distribution of the landslide detachment zones within each class. The extracted predisposing factors maps have then been re-classified on the basis of the calculated weighting values (Wi) and by means of overlay processes. Finally, the landslide susceptibility map has been considered by five classes. It has been determined that a high percentage (61%) of the study area is characterized by a high to very high degree of susceptibility; clay and marly lithologies, and slope exceeding 20° in inclination would be much prone to landsliding. Furthermore, in order to ascertain the proposed landslide susceptibility estimate, a validation procedure has been carried out, by splitting the landslide detachment zones into two groups: a training and a validation set. By means of the training set, the susceptibility map has first been produced; then, it has been compared with the validation set. As a result, a great majority of LDZ-validation set (85%) would be located in highly and very highly susceptible areas. The predictive power of the model is considered reliable, since more than 50% of the LDZ fall into 20% of the most susceptible areas. The reliability of the susceptibility map is also suggested by computing the SCAI index, true positive and false positive rates; nevertheless, the most susceptible areas are overestimated. As a whole, the results indicate that landslide susceptibility assessment based on a bivariate statistics-based method in a GIS environment may be useful for land planning policy, especially when considering its cost/benefit ratio and the need of using an easy tool.

Landslide inventory map of north-eastern Calabria (South Italy)

Landslides are one of the most widespread natural hazards in many areas of Calabria region (Southern Italy), due to the combination of its peculiar geological, morphological, and climatic characteristics and very often to unsustainable land management. This study reports the reconnaissance and the characterization of landslides of north-eastern Calabria (south Italy). The landslide inventory map was obtained by combining field surveys with the analysis of topographic maps and multi-temporal air photos, taken in the period ranging from 1954 to 2006. This analysis has provided the spatial and temporal evolution of mass movements. The integration and elaboration of the data obtained in a GIS environment provided the inventory map of landslides on a scale 1:50,000. Landslides are widespread in the study area and play an important role in the present-day landscape evolution. A total of 1003 landslides were recognized, occupying a surface of 230.4 km2, about 30.5% of the whole study area. The landslides were mapped on the basis of the movement type, as follows: slides, flows, falls and complex landslides. Slide and complex type mass-movements are very common, and represent more than 87% of the landslides mapped. The pelitic lithologies show the highest density of landslides, mainly complex type. Multi-temporal air photo interpretation and field surveys provided data for distinguishing the state of activity of the landslides; therefore, 29% of the landslides mapped has been assessed active while the remaining 71% has been considered inactive. This kind of map is an useful tool for land planning policy. As all the data are digitized and stored in GIS database, this will provide the basic input needed to generate the landslide susceptibility assessments besides evaluate the landslide hazard and risk.

Geomorphological map of the Crotone Province (Calabria, South Italy)

Abstract Please click here to download the map associated with this article. The geomorphological map described covers an area of about 1,720 km, located on the northeastern part of Calabria (south Italy); it contributes to the understanding of both long-term landscape evolution and present-day trends of the Crotone Province. The map, at a 1:75,000 scale, integrates information coming from geomorphological analysis of relief, air photo interpretation and fieldwork. It documents the interplay between tectonic and climatic controls at different temporal and spatial scales. Several remnants of planation surfaces, developed during late Miocene-early Pliocene, result from ancient landscape fragmentation and uplift since the Late Pliocene. Marine and alluvial terraces reflect complex cycles of erosion and deposition, possibly in relation to climate and tectonism during most of the Quaternary. Finally, the present landscape is heavily affected by slope denudational processes such as mass movements, running water processes and wave action. This map may provide the basis for further analyses, representing a useful tool for land management as well as the initial step for the assessment of geomorphological hazard and risk.

Denudation processes and landforms map of the Camastra River catchment (Basilicata – South Italy)

This paper performs denudation processes and landforms characterizing the Camastra River catchment (Basilicata – South Italy), on a 1:40,000 scale map. The map, which includes gravitational processes and landforms and water erosion processes and landforms, was obtained by combining field surveys with the analysis of topographic maps and of multi-temporal aerial photos, ranging from 1954 to 2010. These latter provided information on both spatial and temporal evolution of geomorphic processes. The integration and the elaboration of the data obtained in a GIS environment provided the inventory map of denudation processes and landforms. Landslides are widespread in the study area, and play an important role in the present-day landscape evolution. A total of 953 landslides were recognized, occupying a surface of 79 km2, about 22% of the whole study area. The recognized landslides were mapped on the basis of movement type, as follows: slides, flows, falls and complex landslides. With regard to water erosion processes, the most evident and spectacular landforms in the study area are represented by badlands (the so called calanchi), due to concentration of running water on steep clayey slopes, producing narrow and knife-edge ridges. Finally, sheet, rill and gully erosion are particularly active on areas devoid of vegetation cover, as well as on cultivated fields. This kind of map is an useful tool for land planning policy. Also, these types of studies are basic and complementary to applied methods for investigation and mapping of land susceptibility to denudation processes, as landslides and water erosion.

Landslide Susceptibility Mapping Using Artificial Neural Network in the Urban Area of Senise and San Costantino Albanese (Basilicata, Southern Italy)

Landslides are significant natural hazards in many areas of the world. Mapping the areas that are susceptible to landslides is essential for a wise territorial approach and should become a standard tool to support land-use management. A landslide susceptibility map indicates landslide-prone areas by considering the predisposing factors of slope failures in the past. In the presented work, we evaluate the landslide susceptibility of the urban area of Senise and San Costantino Albanese towns (Basilicata, southern Italy) using an Artificial Neural Network (ANN). In order, this method has required the definition of appropriate thematic layers, which parameterize the area under study. To evaluate and validate landslide susceptibility, the landslides have been randomly divided into two groups, each representing the 50% of the total area subject to instability. The results of this research show that most of the investigated area is characterized by a high landslide hazard.

Mass movements inventory map of the Rubbio stream catchment (Basilicata – South Italy)

In the Basilicata region (South Italy) slope movements, caused by soft rocks, rapid tectonic uplift, earthquakes, and seasonally heavy precipitation, constitute one of the major geologic hazards. For this reason a detailed inventory map of mass movements has been created in a test area of south-eastern Basilicata. The map was compiled from field surveys and multi-temporal air photo interpretation. For each landslide, the map depicts the state of activity and dominant type of slope movement. The integration and analysis of the data obtained by using a geographic information system has produced the mass movements inventory map at a scale of 1:25,000. Mass movements are widespread and play a key role in the landscape evolution of the study area. A total of 175 landslides were recognized, occupying a surface area of 16.2 km2, about 9% of the whole basin of interest. The spatial distribution and type of mass movements are mainly related to the lithology and structural features. Field surveys coupled with interpretation of multi-temporal aerial photos allowed us to distinguish between active (20.6%) and inactive (79.4%) landslides. Mass movements, mapped on the basis of movement type, are represented by slides, flows and complex landslides. The complex and slide type movements are very common, and represent more than 86% of the landslides mapped.

Soil loss assessment in the Turbolo catchment (Calabria, Italy)

Soil loss caused by accelerated erosion is a growing problem in the Mediterranean belt in general, and in many parts of the Calabrian region (Southern Italy), in particular. It is due to the combination of peculiar geomorphological, pedological and climatic features, very often exacerbated by unsuitable land management. The aim of this study is to analyze and map soil loss by water-induced soil erosion at the catchment scale. Soil loss was quantified using the revised universal soil loss equation (RUSLE) model implemented in a geographical information system. The RUSLE is an empirical model which estimates the average annual soil loss that would generally result from splash, sheet and rill erosion. The analysis shows that total soil loss estimated in the study area is 16,470.88 t yr−1 with an average annual soil loss of 5.65 t ha−1 yr−1. Spatial variation and rates of soil erosion are mainly linked to land use, and the rate of soil erosion varies from less than 1 t ha−1 yr−1 in wooded areas to more than 40 t ha−1 yr−1 in barren land. In addition, the comparison between soil loss and slope maps shows that ∼47% of the estimated soil loss involves slopes with a gradient >20°. The map shows seven classes of soil loss, with 8% in the upper three classes and 51% in the lowest class.

Organic carbon and total nitrogen topsoil stocks, biogenetic natural reserve ‘Marchesale’ (Calabria region, southern Italy)

ABSTRACT It is essential estimating the spatial distribution of soil organic carbon (SOC) and soil total nitrogen (STN) stocks and their spatial-temporal variations to understand the role of soil in ecosystem services and in the global cycles of carbon and nitrogen. This work was aimed to quantify and map the stocks of SOC and STN in topsoils in an area of the Biogenetic Natural Reserve ‘Marchesale’ (Calabria region, southern Italy). Forest soil samples (0–20 cm depth) were collected at 231 locations and analysed in laboratory for SOC and STN. Moreover, in all samples, bulk density (BD) and soil coarse fragments (SCFs) were determined. Geostatistics was used to map all soil properties (SOC, STN, BD and SCFs) and the stocks of SOC and STN. The mean stock values were 86.3 Mg ha−1 for SOC and 5.1 Mg ha−1 for STN. The total amounts stored in the study area (33.2 ha) were 2865.2 Mg for SOC and 170.1 Mg for STN. Although only the topsoil was considered, the accompanying maps (1:4000 scale) will be useful for the sustainable management of the Biogenetic Natural Reserve ‘Marchesale’ and for undertaking appropriate conservation plans to mitigate the emissions of greenhouse gases.

Monitoring soil organic carbon content using Vis-NIR spectroscopy: A case study in southern Italy

Assessment and monitoring of soil organic carbon (SOC) quality are important for understanding SOC dynamics and developing management practices of soils. This study investigated the feasibility of visible and near infrared (Vis-NIR) spectroscopy as a fast method to determining and monitoring the SOC content in a mountains area of the Calabria region (southern Italy). In this study, a multitemporal data set including 299 topsoil samples was used: 208 soil samples were collected in 2012 whereas 91 in 2015. The soil samples were collected using a metallic core cylinder with a diameter of 7.5 cm and a height of 20 cm. The Vis-NIR reflectance of soil samples was measured in laboratory, under artificial light, using an ASD FieldSpec IV 350-2500 nm spectroradiometer (Analytical Spectral Devices Inc., Boulder, Colorado, USA), while SOC was determined using a Shimadzu TOC-analyzer with a SSM-5000A solid sample module (Shimadzu Corporation, Kyoto, Japan). In order, to develop a prediction model based on soil spectra and reference laboratory data of SOC the partial least squared regression (PLSR) analysis was applied. Therefore, prior to develop calibration model spectra pre-treatment was carried out to minimize noise and optimize calibration accuracy from the data. PLSR prediction model was developed using the soil samples collected in the 2012. The optimum number of factors to retain in the PLSR models were determined by cross validation. The model was tested using the soil data sampled in the 2015. Results revealed a high level of agreement between measured and predicted values with high coefficients of determination (R2) and low root mean square error (RMSE). These results indicate that Vis-NIR spectroscopy could a promising method for determine and monitoring the SOC content.

Interplay between land use changes and soil erosion in a small mountainous catchment in southern Italy

Land use is one of the most important factors controlling soil erosion. Moreover, erosion rates may vary through time as a response to land use changes. The aim of this work was to analyze the main land use changes in the last 60 years and to assess the relationships between them and spatial and temporal distribution of soil loss at catchment scale.The study was carried out in the Torano catchment (northern Calabria), which is representative of wide sectors of Calabria Region, where the overall soil erosion susceptibility is high. Aerial photos interpretation of different years (1954 and 2012), and field survey were used to assess and map types and variations of land use in the study area. The mean annual rate of soil erosion and the effects of land use changes on soil erosion since 1954 to 2014 were analyzed by using the revised universal soil loss equation (RUSLE) in a GIS environment.Results showed that the total soil loss estimated in the Torano catchment was 2216.76 t yr-1 in 1954, 3242.22 t yr-1 in 2014. Furthermore, the rate of mean annual soil loss increased from 4.30 t ha-1 yr-1 in 1954 to 6.29 t ha-1 yr-1 in 2014. Increasing erosion rates was mainly caused by the transformation of natural forest, scrub and pasture areas into crop fields. In addition, from 1954 to 2014 the barren land progressively increased from 0.2% to more than 2 %; in these areas and the highest soil loss values were observed. The increase of cultivated and barren lands, from 1954 to 2014, caused a 46.3 % increase soil loss. Therefore, the spatio-temporal changes of land use in the Torano catchment had an important role on soil erosion control.