Approaches to modelling land erodibility by wind

Land susceptibility to wind erosion is governed by complex multiscale interactions between soil erodibility and non-erodible roughness elements populating the land surface. Numerous wind erosion modelling systems have been developed to quantify soil loss and dust emissions at the field, regional and global scales. All of these models require some component that defines the susceptibility of the land surface to erosion, ie, land erodibility. The approaches taken to characterizing land erodibility have advanced through time, following developments in empirical and process-based research into erosion mechanics, and the growing availability of moderate to high-resolution spatial data that can be used as model inputs. Most importantly, the performance of individual models is highly dependent on the means by which soil erodibility and surface roughness effects are represented in their land erodibility characterizations. This paper presents a systematic review of a selection of wind erosion models developed over the last 50 years. The review evaluates how land erodibility has been modelled at different spatial and temporal scales, and in doing this the paper identifies concepts behind parameterizations of land erodibility, trends in model development, and recent progress in the representation of soil, vegetation and land management effects on the susceptibility of landscapes to wind erosion. The paper provides a synthesis of the capabilities of the models in assessing dynamic patterns of land erodibility change, and concludes by identifying key areas that require research attention to enhance our capacity to achieve this task

A Quarter of Century in Artificial Intelligence and Law: Projects, Personal Trajectories, a Subjective PerspectiveLanguage, Culture, Computation. Computing of the Humanities, Law, and Narratives

This article describes projects in the domain of artificial intelligence and law, which resulted from the research of the five authors listed, when they formed teams (of the first author named and each one of the other authors). Therefore, the present paper offers a subjective perspective, from the viewpoint of personal trajectories within AI & Law. Several, though not all, of the projects concerned dealt with facets of legal evidence. These projects include: ALIBI (an AI planner generating exonerating accounts); a representation of Italy’s regional constitutions in a nested-relation representation (a precursor of XML); the application of kappa calculus and a probabilistic interpretation to a Scandinavian approach to evidential strength; the application of Petri Nets for representing temporal relations in mutual wills; Daedalus (Judge Asaro’s software assisting Italy’s examining magistrates with inquiries, and then when they turn prosecutors); a study in occurrences in court of allegations echoing the pretext archetype “The dog ate my homework” (even when the claim was not pretextuous); an application of Wigmore Charts to an analysis of both the argumentation and the rhetoric of an Italian arringa (final submissions to the court) from a real court case; editorial projects which promoted the emergence of evidence as a conspicuous field within AI & Law (thus overturning previous neglect); and a magnum opus (Nissan 2012a) which presents the state of the art of computational applications to legal evidence, police inquiries, or argumentation