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Remote sensing and geographical information science (GIS) haveadvanced considerably in recent years. However, the potential ofremote sensing and GIS within the environmental sciences is limitedby uncertainty, especially in connection with the data sets andmethods used. In many studies, the issue of uncertainty has beenincompletely addressed. The situation has arisen in part from alack of appreciation of uncertainty and the problems it can causeas well as of the techniques that may be used to accommodateit. This book provides general overviews on uncertainty in remotesensing and GIS that…mehr
Remote sensing and geographical information science (GIS) haveadvanced considerably in recent years. However, the potential ofremote sensing and GIS within the environmental sciences is limitedby uncertainty, especially in connection with the data sets andmethods used. In many studies, the issue of uncertainty has beenincompletely addressed. The situation has arisen in part from alack of appreciation of uncertainty and the problems it can causeas well as of the techniques that may be used to accommodateit. This book provides general overviews on uncertainty in remotesensing and GIS that illustrate the range of uncertainties that mayoccur, in addition to describing the means of measuring uncertaintyand the impacts of uncertainty on analyses and interpretationsmade. Uncertainty in Remote Sensing and GIS provides readers withcomprehensive coverage of this largely undocumented subject: * Relevant to a broad variety of disciplines including geography,environmental science, electrical engineering and statistics * Covers range of material from base overviews to specificapplications * Focuses on issues connected with uncertainty at various pointsalong typical data analysis chains used in remote sensing andGIS Written by an international team of researchers drawn from avariety of disciplines, Uncertainty in Remote Sensing and GISprovides focussed discussions on topics of considerable importanceto a broad research and user community. The book is invaluablereading for researchers, advanced students and practitioners whowant to understand the nature of uncertainty in remote sensing andGIS, its limitations and methods of accommodating it.
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List of contributors. Foreward. Preface. Uncertainty in remote sensing and GIS: an overview (P. M. Atkinson and G. M. Foody). Uncertainty in remote sensing (C. E. Woodcock). Toward a comprehensive view of uncertainty in remote sensing analysis (J. L. Dungan). On the ambiguity induced by a remote sensor's PSF (J. F. Manslow and M. S. Nixon) . Pixel unmixing at the sub-pixel scale based on land cover class probabilities: application to urban areas (Q. Zhan M. Molenaar and A. Lucieer). Super-resolution land cover mapping from remotely-sensed imagery using a Hopfield neural network (A. J. Tatem H. G. Lewis P. M. Atkinson and M. S. Nixon). Uncertainty in land cover mapping from remotely sensed data using textural algorithms and artificial neural networks (A. M. Jakomulska and J. P. Radomski). Remote monitoring of the impact of ENSO-related drought on Sabah rainforest using NOAA AVHRR middle infrared reflectance: exploring emissivity uncertainty (D. S. Boyd P. C. Phipps W. J. Duane and G. M. Foody). Land Cover Map 2000 and meta-data at the land parcel level (G. M. Smith and R. M. Fuller). Analysing uncertainty propagation in GIS: why is it not that simple? (G. B.M. Heuvelink). Managing uncertainty in a geospatial model of biodiversity (A. J. Warren M. J. Collins E. A. Johnson and P. F. Ehlers). The effects of uncertainty in deposition data on predicting exceedances of acidity critical loads for sensitive UK ecosystems (E. Heywood J. R. Hall and R. A. Wadsworth). Vertical and horizontal spatial variation of geostatistical prediction (A. Wameling). Geostatistical prediction and simulation of the lateral and vertical extent of soil horizons (B. Warr I. O. A. Odeh and M. A. Oliver). Increasing the accuracy of predictions of monthly precipitation in Great Britain using kriging with an external drift (C. D. Lloyd). Conditional simulation applied to uncertainty assessment in DTMs (J. Sénégas M. Schmitt and P. Nonin). Current status of uncertainty issues in remote sensing and GIS (G. M. Foody and P. M. Atkinson). Subject index.
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