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Commercial Unmanned Areal Vehicles (UAV) are taking a flight: it has never been more accessible to own an UAV and as easy to operate one, e.g. a drone. For coastal monitoring these advances open a new world of monitoring such as inter-tidal beach topography through Structure for Motion. This paper aims to 1) show the potential of the UAV-based depth inversion with 2) limited georeferencing resources for rectification, comparing traditional field-based GCPs and fully remote standalone methods (few local GCPs and Google Earth derived GCPs) and a 3) novel automated error reduction inclusion for the breakpoint location. Unlike with shore-based cameras, image stabilisation is key airborne bathymetry estimation. At places that are hard to reach it is not always possible to get ground control points. We discuss the use of Google Earth to obtain ground control points. In all video-derived bathymetries obtained in this work, great overestimation of the depth is found around wave breaking which is often linked to a phase shift in pixel intensity (dark wave front to white foam). A new method to overcome phase shift issues around breaking is presented that results in a significant error reduction of 58% around the break point.

Commensal rodents such as mice that live in the proximity of human are well-known pests that can transmit diseases to man. An agent-based model is presented to formalize the spread of rodents in human habitations. We focus in this paper on the specific behaviour of mice consisting in walking along the walls (thigmotaxis). In order to simulate this behaviour we combine a cognitive architecture with an algorithm simulating rodents’ moves following residential walls. The cognitive model and the ‘wall following’ algorithm developed are successively described. Simulation configurations are tested to evaluate the robustness of the ‘wall following’ algorithm alone. In a data poor context this simple combined algorithm, using a discrete space, fulfils the basic needs to simulate a plausible mouse activity, towards a detailed representation of mice moves within a fluctuating environment.