ALBERT

Description: Despite landslides impact the society worldwide every day, landslide information is inhomogeneous and lacking. When landslides occur in remote areas or where the availability of optical images is rare due to cloud persistence, they might remain unknown, or unnoticed for long time, preventing studies and hampering civil protection operations. The unprecedented availability of SAR C-band images provided by the Sentinel-1 constellation offers the opportunity to propose new solutions to detect landslides events. In this work, we perform a systematic assessment of Sentinel-1 SAR C-band images acquired before and after known events. We present the results of a pilot study on 32 worldwide cases of rapid landslides entailing different types, sizes, slope expositions, as well as pre-existing land cover, triggering factors and climatic regimes. Results show that in about eighty-four percent of the cases, changes caused by landslides on SAR amplitudes are unambiguous, whereas only in about thirteen percent of the cases there is no evidence. On the other hand, the signal does not allow for a systematic use to produce inventories because only in 8 cases, a delineation of the landslide borders (i.e., mapping) can be manually attempted. In a few cases, cascade multi-hazard (e.g., floods caused by landslides) and evidences of extreme triggering factors (e.g., strong earthquakes or very rapid snow melting) were detected. The method promises to increase the availability of information on landslides at different spatial and temporal scales with benefits for event magnitude assessment during weather-related emergencies, model tuning, and landslide forecast model validation, in particular when accurate mapping is not required.

Description: The emergence of new technologies such as the Internet of Things, big data, and advanced robotics, together with risks such as climate change, rising labour costs, and a fluctuating economy, are challenging the current UK manufacturing model. In this paper, business models for re-distributed manufacture (RdM) are developed using anIDEF (Icam DEFinition for Function Modelling) description to serve as a guide for the implementation of the RdM concept in the consumer goods industry. This paper explores the viability of a re-distributed business model for manufacturers employing new manufacturing technologies such as additive manufacturing or three-dimensional (3D) printing, as part of a sustainable and circular production and consumption system. An As-Is value chain model is presented alongside the proposed new business model for a sustainable re-distributed manufacturing system. Both are illustrated via a case study drawn from the shoe manufacturing industry. The case study shows that there is a need for robust facilities in close proximity to the customer. These facilities are store fronts which can also manufacture, remanufacture, and provide services. The reduction in transportation and increase in customer involvement throughout the process are the main benefits that would accrue if a re-distributed model is implemented in the given industry.

Description: Climate, Vol. 5, Pages 90: Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling Climate doi: 10.3390/cli5040090 Authors: Mauro Rossi Dalia Kirschbaum Daniela Valigi Alessandro Mondini Fausto Guzzetti Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF) are compared with the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

Description: Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF) are compared with the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

Description: This paper reports the results on the agronomic performance of organic amendments in the EU 7th FP project “FERTIPLUS—reducing mineral fertilizers and agro-chemicals by recycling treated organic waste as compost and bio-char”. Four case studies on field-scale application of biochar, compost and biochar-blended compost were established and studied for three consecutive years in four distinct cropping systems and under different agro-climatic conditions in Europe. These included the following sites: olive groves in Murcia (Spain), greenhouse grown tomatoes in Almeria (Spain), an arable crop rotation in Oost-Vlaanderen (Merelbeke, Belgium), and three vineyards in Friuli Venezia Giulia (Italy). A slow pyrolysis oak biochar was applied, either alone or in combination with organic residues: compost from olive wastes in Murcia (Spain), sheep manure in Almeria (Spain), and compost from biowaste and green waste in Belgium and Italy. The agronomical benefits were evaluated based on different aspects of soil fertility (soil total organic carbon (TOC), pH, nutrient cycling and microbial activity) and crop nutritional status and productivity. All amendments were effective in increasing soil organic C in all the field trials. On average, the increase with respect to the control was about 11% for compost, 20% for biochar-blended compost, and 36% for biochar. The amendments also raised the pH by 0.15–0.50 units in acidic soils. Only biochar had a negligible fertilization effect. On the contrary, compost and biochar-blended compost were effective in enhancing soil fertility by increasing nutrient cycling (25% mean increase in extractable organic C and 44% increase in extractable N), element availability (26% increase in available K), and soil microbial activity (26% increase in soil respiration and 2–4 fold enhancement of denitrifying activity). In general, the tested amendments did not show any negative effect on crop yield and quality. Furthermore, in vineyards and greenhouse grown tomatoes cropping systems, compost and biochar-blended compost were also effective in enhancing key crop quality parameters (9% increase in grape must acidity and 16% increase in weight, 9% increase in diameter and 8% increase in hardness of tomato fruits) important for the quality and marketability of the crops. The overall results of the project suggest that the application of a mixture of biochar and compost can benefit crops. Therefore, biochar-blended compost can support and maintain soil fertility.