Giulia Sofia

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards

Soil water erosion is a serious problem, especially in agricultural lands. Among these, vineyards deserve attention, because they constitute for the Mediterranean areas a type of land use affected by high soil losses. A significant problem related to the study of soil water erosion in these areas consists in the lack of a standardized procedure of collecting data and reporting results, mainly due to a variability among the measurement methods applied. Given this issue and the seriousness of soil water erosion in Mediterranean vineyards, this works aims to quantify the soil losses caused by simulated rainstorms, and compare them with each other depending on two different methodologies: (i) rainfall simulation and (ii) surface elevation change-based, relying on high-resolution Digital Elevation Models (DEMs) derived from a photogrammetric technique (Structure-from-Motion or SfM). The experiments were carried out in a typical Mediterranean vineyard, located in eastern Spain, at very fine scales. SfM data were obtained from one reflex camera and a smartphone built-in camera. An index of sediment connectivity was also applied to evaluate the potential effect of connectivity within the plots. DEMs derived from the smartphone and the reflex camera were comparable with each other in terms of accuracy and capability of estimating soil loss. Furthermore, soil loss estimated with the surface elevation change-based method resulted to be of the same order of magnitude of that one obtained with rainfall simulation, as long as the sediment connectivity within the plot was considered. High-resolution topography derived from SfM revealed to be essential in the sediment connectivity analysis and, therefore, in the estimation of eroded materials, when comparing them to those derived from the rainfall simulation methodology. The fact that smartphones built-in cameras could produce as much satisfying results as those derived from reflex cameras is a high value added for using SfM.

Open-pit mining geomorphic feature characterisation

Abstract Among the anthropogenic topographic signatures on Earth, open-pit mines are of great importance. Mining is of interest to geomorphologists and environmental researchers because of its implication in geomorphic hazards and processes. In addition, open-pit mines and quarries are considered the most dangerous industrial sector, with injuries and accidents occurring in numerous countries. Their fast, accurate and low-cost investigation, therefore, represents a challenge for the Earth science community. The purpose of this work is to characterise the open-pit mining features using high-resolution topography and a recently published landscape metric, the Slope Local Length of Auto-Correlation (SLLAC) ( Sofia et al., 2014 ). As novel steps, aside from the correlation length, the terrace’s orientation is also calculated, and a simple empirical model to derive the percentage of artificial surfaces is tested. The research focuses on two main case studies of iron mines, both located in the Beijing district (P.R. China). The main topographic information (Digital Surface Models, DSMs) was derived using an Unmanned Aerial Vehicle (UAV) and the Structure from Motion (SfM) photogrammetric technique. The results underline the effectiveness of the adopted methodologies and survey techniques in the characterisation of the main mine’s geomorphic features. Thanks to the SLLAC, the terraced area given by open-cast/open-pit mining for iron extraction is automatically depicted, thus, allowing researchers to quickly estimate the surface covered by the open-pit. This information could be used as a starting point for future research (i) given the availability of multi-temporal surveys to track the changes in the extent of the mine; (ii) to relate the extent of the mines to the amount of processes in the area (e.g. pollution, erosion, etc.), and to (iii) combine the two points, and analyse the effects of the change related to changes in erosion. The analysis of the correlation length orientation also allows researchers to identify the terrace’s orientation and to understand the shape of the open-pit area. The tectonic environment and history, or inheritance, of a given slope can determine if and how it fails, and the orientation of the topographic surface or excavation face, with respect to geologic features, is of major significance. Therefore, the proposed approach can provide a basis for a large-scale and low-cost topographic survey for sustainable environmental planning and, for example, for the mitigation of environmental anthropogenic impacts due to mining.

Flood dynamics in urbanised landscapes: 100 years of climate and humans’ interaction

Raising interest in the interaction between humans and climate drivers to understand the past and current development of floods in urbanised landscapes is of great importance. This study presents a regional screening of land-use, rainfall regime and flood dynamics in north-eastern Italy, covering the timeframe 1900–2010. This analysis suggests that, statistically, both climate and land-use have been contributing to a significant increase of the contribution of short duration floods to the increase in the number of flooded locations. The analysis also suggests that interaction arises, determining land-use dynamics to couple with climatic changes influencing the flood aggressiveness simultaneously. Given that it is not possible to control the climatic trend, an effective disaster management clearly needs an integrated approach to land planning and supervision. This research shows that land management and planning should include the investigation of the location of the past and future social and economic drivers for development, as well as past and current climatic trends.

Comparison of Pleiades and LiDAR Digital Elevation Models for Terraces Detection in Farmlands

Among the most evident anthropogenic modifications of the landscape, terraces related to agricultural activities are ubiquitous structures that constitute important investments worldwide, and they recently acquired a new relevance to modern concerns about land-use management and erosion control. Conservation agriculture and terraces management are an application with great potentialities for Satellite Earth observation and the derived high-resolution topography. Due to its high agility, the Pleiades satellite constellation provides new, high-resolution digital elevation models (DEMs) with a submetric resolution that could be potentially useful for this task, and their application in a farmland context is nowadays an open research line. This work provides a first analysis, performing an automatic terrace mapping from DEMs obtained from Pleiades images, as compared to LiDAR DEMs. Two existing methods are considered: 1) the fast line segment detector (LSD) algorithm and 2) a geomorphometric method based on surface curvature. Despite the lower performances of Pleiades DEMs with respect to that of the LiDAR models, the results indicate that the Pleiades models can be used to automatically detect terrace slopes greater than 2 m with a detection rate of more than 80% of the total length of the terraces. In addition, the results showed that when using noisy DEMs, the geomorphometric method is more robust, and it slightly outperforms the LSD algorithm. These results provide a first analysis on how effective Pleiades DEMs can be as an alternative to LiDAR DEMs, also highlighting the future challenges for monitoring large extents in a farmland context.

Prospects for crowdsourced information on the geomorphic ‘engineering’ by the invasive Coypu (Myocastor coypus)

ABSTRACT: Among the most invasive species, the Coypu (Myocastor coypus) best exemplifies the widespread effect of alien species on ecosystems. Among the impacts, the induced erosion in riverbanks has an increasing economic and social importance. Despite its significance, this type of erosion is rarely quantified, and the available information is limited to local knowledge, grey literature, and maintenance reports. This research shows the potential of freely and instantly available Structure‐from‐Motion (SfM) photogrammetry to obtain crowdsourced information based on smartphone images. The results highlight how it is possible to provide a rough estimate of the damages with relatively low or null cost of application, and limited expert knowledge and expenditure of time, depending on the scale of analysis. The proposed technique provides a fresh approach to a known long‐standing issue, offering a new source of information for farmers, researchers, wildlife managers, as well as for land managers and planners. The potential applications of such a technique and its unprecedented ease of use and very low cost offer effective tools for management plans and scientific research, providing a basis to relate eroded volumes to the functioning of the drainage system and the connected agroecosystem. The method would also enable the opportunity of participatory and opportunistic crowdsourced sensing. Further scientific research on the crowd‐based data on erosion should encourage standardisation of data gathering and accessibility, together with a public involvement in information exchange, to generate a better understanding and awareness of erosion problems also for other fields of research. Copyright

Open-pit mine geomorphic changes analysis using multi-temporal UAV survey

Mining activities, and especially open-pit mines, have a significant impact on the Earth’s surface. They influence vegetation cover, soil properties, and hydrological conditions, both during mining and for many years after the mines have been deactivated. Exploring a fast, accurate, and low-cost method to monitor changes, through years, in such an anthropogenic environment is, therefore, an open challenge for the Earth Science community. We selected a case study located in the northeast of Beijing, to assess geomorphic changes related to mining activities. In 2014 and 2016, an unmanned aerial vehicle (UAV) collected two series of high-resolution images. Through the structure-from-motion photogrammetric technique, the images were used to generate high-resolution digital elevation models (DEMs). The assessment of geomorphic changes was carried out by two methodologies. At first, we quantitatively estimated the detectable area, volumetric changes, and the mined tonnage by using the DEM of difference (DoD), which calculated the differences between two DEMs on a cells-by-cells basis. Secondly, the slope local length of autocorrelation (SLLAC) allowed determining the surface covered by open-pit mining by using an empirical model extracting the extent of the open-pit. The analysis of the DoD allows estimating the areal changes and the volumetric changes. The analysis of the SLLAC and its derived parameter allows for the accurate depiction of terraces and the extent of changes within the open-pit mine. Our results underlined how UAVs equipped with high-resolution cameras can be fast, precise, and low-cost instruments for obtaining multi-temporal topographic information, especially when combined with suitable methodologies to analyze the surface geomorphology, for dynamic monitoring of open-pit mines.

Assessment of Social Vulnerability to Floods in the Floodplain of Northern Italy

AbstractPractices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates ...

Automatic characterization of road networks under forest cover: Advances in the analysis of roads and geomorphic process interaction

Mountain road networks support rural development, timber harvesting as well as local travel, trade, and tourism. However, roads represent a difficult and pressing environmental challenge because of their impacts on hydrogeomorphic processes in many locations around the world. For this reason, identifying the location and the structure of a road network is crucial. The position of the infrastructures relative to the valley floor and to ridges results in roads working as a sediment sources (inducing erosion/landslides) or sinks (acting as stopping/storage sites). Currently, the identification of roads and the analysis of their interaction with earth surface processes is based mostly on field surveys. To this point, this work tests an automatic approach to characterize the road network configuration (Sofia et al., 2016), and further extends its significance by analysing the interaction between the network morphology and geomorphic processes. The method considers LiDAR topography and specific topographic metrics that measure the homogeneity and the organization of the slope of a landscape (the Slope Local Length of Auto-Correlation –SLLAC, Sofia et al., 2014, and the derived average SLLAC and Surface Peak Curvature –Spc- per square kilometre). The Lookout Creek watershed (western Cascade Range, Oregon, USA) offers the ideal case study. The area is covered entirely by LiDAR topography; a database of roads and slides (debris flows, shallow and deep landslides) locations, including specific information on events connected to the roads, is available for the whole catchment. The results show how it is possible to automatically characterize the road network conformation also under vegetation cover. The procedure successfully detects areas presenting different shapes of the network, and it allows to deepen the analysis of the connection between the network structure and earth surface processes. To this point, given a similar geological domain and without denying the importance that the natural forcing has on geomorphic systems, networks created by short roads with sharp angles might be related to a greater surface instability, if compared to networks having similar densities, but longer roads and fewer road junctions. Further investigation on additional study cases is needed to confirm the effects of the road network configuration on surface processes, to substantiate the hypothesis that there is a connection between network morphology and surface instabilities. Nevertheless, the automatic characterization of road networks, especially under forest cover, represents a great opportunity to advance the science, while solving important environmental and planning problems.

The Geomorphology of the Human Age

The Earths surface morphology is a consequence of dominant forcing such as tectonic uplift, erosion, sediment transport, and climate. Recently, the Earth science community also started to consider biota as a geomorphological agent that has a role in shaping the Earth surface, even if at a different scale and magnitude than that of other major forcings. Human activities directly or indirectly move large quantities of soil, which leave clear topographic signatures on the Earths morphology. These signatures have the capability to affect Earth surface processes. This article provides an overview of the role of humans as a geological agent in shaping the morphology of the Earth. We consider agricultural landscapes, mining activities, and road networks. We provide examples in different regions of the world. The final section considers concluding observations and open challenges, where we focus on future challenges, related to Anthropocene, in the Earth science community.