Uncertainty in Geographical Information
As Geographic Information Systems (GIS) develop, there is a need to demystify the complex geographical world to facilitate computerization in GIS by the inaccuracies that emerge from man-machine interactions in data acquisition and by error propagation in geoprocessing. Users need to be aware of the impacts of uncertainties in spatial analysis and decision-making. Uncertainty in Geographical Information discusses theoretical and practical aspects of spatial data processing and uncertainties, and covers a wide range of types of errors and fuzziness and emphasizes description and modeling. High level GIS professionals, researchers and graduate students will find this a constructive book.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
analysis analytical approaches approximation areal areas calculated categorical data categorical maps categorical variables chapter classified data co-Kriging complex concepts continuous variables coordinates covariance data sets defined defuzzification derived digital photogrammetric data digitised discrete objects discussed domain elevation data entities epsilon error bands Equation error bands estimates evaluation example function fuzzy classes fuzzy membership fuzzy sets geographical data geographical information geostatistical Goodchild heterogeneous inaccuracy indicator Kriging interpolation land cover Landsat line segments locations measured methods pixels points polygons polyline positional errors possible probabilistic maps probabilistically classified probability probability density function propagation random variable raster cells realisations reference data remote sensing represented rough sets samples scale aerial photographs sensors shown in Figure simulated annealing slope spatial categories spatial correlation spatial data spatial dependence spatial variability spatially varying specific spectral spectral space spot heights standard deviations statistical stochastic simulation surface techniques terrain underlying vagueness variance vector data