Repository logo
 

Scholarly Works - Fitzwilliam College

Browse

Recent Submissions

Now showing 1 - 3 of 3
  • ItemOpen AccessAccepted version Peer-reviewed
    Agency, Knowledge and Good Faith in Land Registration: Knightsbridge Property Development Corporation (UK) Limited v South Chelsea Properties Limited
    Lees, EFI; Lees, Emma [0000-0001-5998-8242]
    The decision of Newey LJ in the High Court in Knightsbridge Property Development Corp v South Chelsea Properties Ltd is notable by its very orthodoxy in respect of the way in which the principles of land registration are applied. The jurisprudence surrounding the Land Registration Act 2002, and in particular the provisions relating to rectification of title and indemnity, has been vexed (as has been very well documented ). In this respect, the clear, sensible and ‘statute-focussed’ approach taken by Newey LJ in this case is enormously welcome. It also casts some light on the scope of the Court of Appeal decision in NRAM v Evans, providing, in doing so, an easy to apply ‘schema’ which can be taken forward by future courts in resolving disputes of this type. However, the case itself raises the wider question of how the principles of agency and company law rules interact with land registration, and raises the uncomfortable point that whilst the state of mind of a transferee is almost always irrelevant to the ‘quality’ of the registration, that will not be the case in situations involving an agent overstepping their authority. This note will first consider the facts and decision in this case, before considering the wider implications for the relationship between agency and registration.
  • ItemOpen AccessAccepted version Peer-reviewed
    Semi-Automated Signal Surveying Using Smartphones and Floorplans
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) Gao, C; Harle, R; Gao, C [0000-0001-9585-0689]
    Location fingerprinting locates devices based on pattern matching signal observations to a pre-defined signal map. This paper introduces a technique to enable fast signal map creation given a dedicated surveyor with a smartphone and floorplan. Our technique (PFSurvey) uses accelerometer, gyroscope and magnetometer data to estimate the surveyor’s trajectory post-hoc using Simultaneous Localisation and Mapping and particle filtering to incorporate a building floorplan. We demonstrate conventional methods can fail to recover the survey path robustly and determine the room unambiguously. To counter this we use a novel loop closure detection method based on magnetic field signals and propose to incorporate the magnetic loop closures and straight-line constraints into the filtering process to ensure robust trajectory recovery. We show this allows room ambiguities to be resolved. An entire building can be surveyed by the proposed system in minutes rather than days. We evaluate in a large office space and compare to state-of-the-art approaches. We achieve trajectories within 1.1 m of the ground truth 90% of the time. Output signal maps well approximate those built from conventional, laborious manual survey. We also demonstrate that the signal maps built by PFSurvey provide similar or even better positioning performance than the manual signal maps.
  • ItemOpen AccessAccepted version Peer-reviewed
    Two centuries of masting data for European beech and Norway spruce across the European continent
    (Wiley, 2017-05) Ascoli, D; Maringer, J; Hacket-Pain, A; Conedera, M; Drobyshev, I; Motta, R; Cirolli, M; Kantorowicz, W; Zang, C; Schueler, S; Croisé, L; Piussi, P; Berretti, R; Palaghianu, C; Westergren, M; Lageard, JGA; Burkart, A; Bichsel, RG; Thomas, PA; Beudert, B; Övergaard, R; Vacchiano, G
    Tree masting is one of the most intensively studied ecological processes. It affects nutrient fluxes of trees, regeneration dynamics in forests, animal population densities, and ultimately influences ecosystem services. Despite a large volume of research focused on masting, its evolutionary ecology, spatial and temporal variability and environmental drivers are still matter of debate. Understanding the proximate and ultimate causes of masting at broad spatial and temporal scales will enable us to predict tree reproductive strategies and their response to changing environment. Here we provide broad spatial (distribution range-wide) and temporal (century) masting data for the two main masting tree species in Europe, European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst.). We collected masting data from a total of 359 sources through an extensive literature review and from unpublished surveys. The dataset has a total of 1747 series and 18348 yearly observations from 28 countries and covering a time span of years 1677-2016 and 1791-2016 for beech and spruce, respectively. For each record, the following information is available: identification code; species; year of observation; proxy of masting (flower, pollen, fruit, seed, dendrochronological reconstructions); statistical data type (ordinal, continuous); data value; unit of measurement (only in case of continuous data); geographical location (country, Nomenclature of Units for Territorial Statistics NUTS-1 level, municipality, coordinates); first and last record year and related length; type of data source (field survey, peer reviewed scientific literature, grey literature, personal observation); source identification code; date when data were added to the database; comments. To provide a ready-to-use masting index we harmonized ordinal data into five classes. Furthermore, we computed an additional field where continuous series with length >4 years where converted into a five classes ordinal index. To our knowledge, this is the most comprehensive published database on species-specific masting behaviour. It is useful to study spatial and temporal patterns of masting and its proximate and ultimate causes, to refine studies based on tree-ring chronologies, to understand dynamics of animal species and pests vectored by these animals affecting human health, and it may serve as calibration-validation data for dynamic forest models.