Advances in Remote Sensing and GIS Analysis

Remote sensing and GIS are technologies for the new millennium. This book brings together some of the most recent developments in these complimentary fields, with a particular emphasis on mathematical techniques and their application. The range of techniques covered includes fuzzy classification, artificial neural networks, geostatistical techniques (such as kriging, cokriging, stochastic simulation and regularization), texture classification, fractals, per–parcel classification, raster and vector data integration and process modelling. The range of applications includes land cover and land use mapping, cloud tracking, snow cover mapping and air temperature monitoring, topographic mapping, geological classification and soil erosion modelling. This book will be valuable to both researchers and advanced students of remote sensing and GIS. It contains several new approaches, recent developments and novel applications of existing techniques. Most chapters report the results of experiment and investigation. Some chapters form broad reviews of recent developments in the field. In all cases the mathematical basis is explained fully.

Spis treści:
Techniques for the Analysis of Spatial Data (P. Atkinson & N. Tate).
Land Cover Classification Revisited (P. Mather).
Image Classification with a Neural Network: From Completely–Crisp to Fully–Fuzzy Situations (G. Foody).
Cloud Motion Analysis (H. Lewis, et al. ).
Methods for Estimating Image Signal–to–Noise Ratio (SNR) (G. Smith & P. Curran).
Modelling and Efficient Mapping of Snow Cover in the UK for Remote Sensing Validation (R. Kelly & P. Atkinson).
Using Variograms to Evaluate a Model for the Spatial Prediction of Minimum Air Temperature (D. Cornford).
Modelling the Distribution of Cover Fraction of a Geophysical Field (J. Collins & C. Woodcock).
Classification of Digital Image Texture Using Variograms (J. Carr).
Geostatistical Appr oaches for Image Classification and Assessment of Uncertainty in Geologic Processing (F. van der Meer).
A Syntactic Pattern–Recognition Paradigm for the Derivation of Second–Order Thematic Information from Remotely Sensed Images (S. Barr & M. Barnsley).
The Rôle of Classified Imagery in Urban Spatial Analysis (V. Mesev & P. Longley).
Image Classification and Analysis Using Integrated GIS (J. Hinton).
Per–Field Classification of Land Use Using the Forthcoming Very Fine Spatial Resolution Satellite Sensors: Problems and Potential Solutions (P. Aplin, et al. ).
Modelling Soil Erosion at Global and Regional Scales Using Remote Sensing and GIS Techniques (N. Drake, et al. ).
Extracting Information from Remotely Sensed and GIS Data (P. Atkinson & N. Tate).
Index.

Okładka tylna:
Remote sensing and GIS are technologies for the new millennium. This book brings together some of the most recent developments in these complimentary fields, with a particular emphasis on mathematical techniques and their application. The range of techniques covered includes fuzzy classification, artificial neural networks, geostatistical techniques (such as kriging, cokriging, stochastic simulation and regularization), texture classification, fractals, per–parcel classification, raster and vector data integration and process modelling. The range of applications includes land cover and land use mapping, cloud tracking, snow cover mapping and air temperature monitoring, topographic mapping, geological classification and soil erosion modelling. This book will be valuable to both researchers and advanced students of remote sensing and GIS. It contains several new approaches, recent developments and novel applications of existing techniques. Most chapters report the results of experiment and investigation. Some chapters form broad reviews of recent developments in the field. In all cases the mathematical basis is expla ined fully.