This paper discusses some methodological aspects for the production of susceptibility maps of slope instability developed within the CARG Project (Geological Cartography of Italy at 1:50,000 scale). It describes an ex...This paper discusses some methodological aspects for the production of susceptibility maps of slope instability developed within the CARG Project (Geological Cartography of Italy at 1:50,000 scale). It describes an example of a susceptibility map in the presence of low susceptibility, using database having zero or negligible cost, with the aim to test some methodologies that can be easily reproducible to get a first estimate of the landslide susceptibility on a wide area. Two statistical approaches have been applied: the non-parametric conditional analysis and the logistic analysis for rare events. The predictive ability obtained from the two methodologies, was evaluated by the success-prediction curves for the conditional analysis, and by the Receiver Operating Characteristic curve (ROC), for the logistic model. The landslide susceptibility maps have been classified into four classes using both the Natural Breaks algorithm and the method proposed by Chung and Fabbri (2003). The paper considers the influence of these two classification methods on the quality of final results.展开更多
Images collected by optical and radar satellite sensors represent a most viable solution for the extraction of biophysical parameters of the earth surface. The mid-resolution dataset acquired by Landsat and Sentinel s...Images collected by optical and radar satellite sensors represent a most viable solution for the extraction of biophysical parameters of the earth surface. The mid-resolution dataset acquired by Landsat and Sentinel satellites have recently become available free of charge for all users. At the same time, some software for image processing and GIS, like QGIS, R, and ImageJ, have reached a high level of maturity and a large community of users, thanks to their open source license. In this project, free satellite images and open source software have been used for the assessment of the grassland biomass. The overall goal is the enhancement of the statistics of grassland production and dried fodder for the animal breeding. Currently, the National Institute of Statistics collects this kind of dataset at the province level. The project consists in some “in situ” surveys in a specific site in central Italy and in the building of a regression model between the grassland heights and the corresponding radiometric values of the most relevant image bands.展开更多
Maximally-localised Wannier functions(MLWFs)are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding mode...Maximally-localised Wannier functions(MLWFs)are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations.At the same time,high-throughput(HT)computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target properties.The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is,in general,very challenging.We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks.Our approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA workflow.We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space.We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations.Finally,we provide a downloadable virtual machine that can be used to reproduce the results of this paper,including all first-principles and atomistic simulations as well as the computational workflows.展开更多
文摘This paper discusses some methodological aspects for the production of susceptibility maps of slope instability developed within the CARG Project (Geological Cartography of Italy at 1:50,000 scale). It describes an example of a susceptibility map in the presence of low susceptibility, using database having zero or negligible cost, with the aim to test some methodologies that can be easily reproducible to get a first estimate of the landslide susceptibility on a wide area. Two statistical approaches have been applied: the non-parametric conditional analysis and the logistic analysis for rare events. The predictive ability obtained from the two methodologies, was evaluated by the success-prediction curves for the conditional analysis, and by the Receiver Operating Characteristic curve (ROC), for the logistic model. The landslide susceptibility maps have been classified into four classes using both the Natural Breaks algorithm and the method proposed by Chung and Fabbri (2003). The paper considers the influence of these two classification methods on the quality of final results.
文摘Images collected by optical and radar satellite sensors represent a most viable solution for the extraction of biophysical parameters of the earth surface. The mid-resolution dataset acquired by Landsat and Sentinel satellites have recently become available free of charge for all users. At the same time, some software for image processing and GIS, like QGIS, R, and ImageJ, have reached a high level of maturity and a large community of users, thanks to their open source license. In this project, free satellite images and open source software have been used for the assessment of the grassland biomass. The overall goal is the enhancement of the statistics of grassland production and dried fodder for the animal breeding. Currently, the National Institute of Statistics collects this kind of dataset at the province level. The project consists in some “in situ” surveys in a specific site in central Italy and in the building of a regression model between the grassland heights and the corresponding radiometric values of the most relevant image bands.
基金V.V.acknowledges support from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No.676531(project E-CAM)G.P.,A.M.,and N.M.acknowledge support by the NCCR MARVEL of the Swiss National Science Foundation and the European Union’s Centre of Excellence MaX“Materials design at the Exascale”(Grant No.824143)+3 种基金G.P.,A.M.,and N.M.acknowledge PRACE for awarding us simulation time on Piz Daint at CSCS(project ID 2016153543)Marconi at CINECA(project ID 2016163963)V.V.and A.A.M.acknowledge support from the Thomas Young Centre under grant TYC-101J.R.Y.is grateful for computational support from the UK national high performance computing service,ARCHER,for which access was obtained via the UKCP consortium and funded by EPSRC Grant Ref EP/P022561/1.
文摘Maximally-localised Wannier functions(MLWFs)are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations.At the same time,high-throughput(HT)computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target properties.The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is,in general,very challenging.We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks.Our approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA workflow.We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space.We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations.Finally,we provide a downloadable virtual machine that can be used to reproduce the results of this paper,including all first-principles and atomistic simulations as well as the computational workflows.
