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Advances in Remote Sensing and GIS Analysis

Author : Peter M. Atkinson, Nicholas Tate
ISBN 13 : 9788126539802
Pages : 288
Type : P

Advances in Remote Sensing and GIS Analysis


This book provides a current state- of -the -art review of the techniques used in the analysis of spatial data for remote sensing and GIS. The emphasis of the book is upon scale in both physical and human geography. The book covers a number of important topics in spatial analysis embracing areas such as geostatic and chaos and complexity.


An authoritative and state-of-the-art book bringing together some of the most recent developments in remote sensing and GIS analysis with a particular emphasis on mathematical techniques and their applications. With contributions from academia, industry and research institutes, all with a high standing, this book covers a range of techniques including: 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.

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 Approaches 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).



Researchers and Advanced Students of Remote Sensing and GIS within departments of Geography, Environmental Science, Earth Science, Those involved in the fields of Remote Sensing and GIS. The market for the book will therefore be quite broad.