17,609 research outputs found

    Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

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    Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

    Towards the use of sequential patterns for detection and characterization of natural and agricultural areas

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    Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the different natural habitats and farming practices in a remote way. However, satellite images content strongly depends on the season of the acquisition. Due to the periodicity of natural and agricultural dynamics throughout seasons, sequential patterns arise as a new opportunity to model the behaviour of these environments. In this paper, we describe some preliminary results obtained with a new framework for studying spatiotemporal evolutions over natural and agricultural areas using k-partite graphs and sequential patterns extracted from segmented Landsat images.Postprint (author’s final draft

    A survey of outlier detection methodologies

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    Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review

    Historical forest biomass dynamics modelled with Landsat spectral trajectories

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    Acknowledgements National Forest Inventory data are available online, provided by Ministerio de Agricultura, Alimentación y Medio Ambiente (España). Landsat images are available online, provided by the USGS.Peer reviewedPostprin

    State-of-the-art in studies of glacial isostatic adjustment for the British Isles: a literature review

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    Understanding the effects of glacial isostatic adjustment (GIA) of the British Isles is essential for the assessment of past and future sea-level trends. GIA has been extensively examined in the literature, employing different research methods and observational data types. Geological evidence from palaeo-shorelines and undisturbed sedimentary deposits has been used to reconstruct long-term relative sea-level change since the Last Glacial Maximum. This information derived from sea-level index points has been employed to inform empirical isobase models of the uplift in Scotland using trend surface and Gaussian trend surface analysis, as well as to calibrate more theory-driven GIA models that rely on Earth mantle rheology and ice sheet history. Furthermore, current short-term rates of GIA-induced crustal motion during the past few decades have been measured using different geodetic techniques, mainly continuous GPS (CGPS) and absolute gravimetry (AG). AG-measurements are generally employed to increase the accuracy of the CGPS estimates. Synthetic aperture radar interferometry (InSAR) looks promising as a relatively new technique to measure crustal uplift in the northern parts of Great Britain, where the GIA-induced vertical land deformation has its highest rate. This literature review provides an in-depth comparison and discussion of the development of these different research approaches

    Land-cover change monitoring in Obuasi, Ghana: an integration of earth observation, geoinformation systems and stochastic modelling

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    For over twenty years, Obuasi Municipality, Ghana, has experienced land-cover change arising from gold mining and urbanisation. This project quantified the land-cover changes that have taken place and projected likely future land-cover. An integration of Earth Observation (or EO), Geographical Information Science (or GIS) and Stochastic Modelling was examined. Post-Classification Change Detection employed Landsat TM or ETM+ images from 1986, 2002 and 2008. Subsequently, Markov Chain Analysis projected the land-cover distribution for 2020. Seven broad land-use and land-cover classes were identified and mapped, namely: built-up areas; mine sites; tailing ponds; barren land; forestland; farmland; and, rangeland. The results obtained for the 2008 to 2020 projection revealed a continuous expansion of built-up areas (1.63%), mine sites (0.89%) and farmland (3.4%), and a reduction of forestland (4.17%) and rangeland (2.59%). Despite the advent of very high resolution satellite imagery, this use of EO and GIS technology focussed on low-cost and lower resolution satellite imagery, coupled with Markov Modelling and was found to be beneficial in describing and analysing land-cover change processes in the study area, and was hence potentially useful for strategic planning purposes
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