LEADER 03979nam 2200637Ia 450 001 9910143171203321 005 20170815120128.0 010 $a1-280-27108-6 010 $a9786610271085 010 $a0-470-29911-8 010 $a0-470-03526-9 010 $a0-470-85924-5 035 $a(CKB)111087027094290 035 $a(EBL)154955 035 $a(OCoLC)53890426 035 $a(SSID)ssj0000263929 035 $a(PQKBManifestationID)11227561 035 $a(PQKBTitleCode)TC0000263929 035 $a(PQKBWorkID)10283376 035 $a(PQKB)11617777 035 $a(MiAaPQ)EBC154955 035 $a(PPN)124570763 035 $a(EXLCZ)99111087027094290 100 $a20021025d2002 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aUncertainty in remote sensing and GIS$b[electronic resource] /$fedited by Giles M. Foody and Peter M. Atkinson 210 $aChichester ;$aHoboken, NJ $cWiley$dc2002 215 $a1 online resource (327 p.) 300 $aDescription based upon print version of record. 311 $a0-470-84408-6 320 $aIncludes bibliographical references and index. 327 $aUncertainty in Remote Sensing and GIS; Contents; List of Contributors; Foreword; Preface; 1 Uncertainty in Remote Sensing and GIS: Fundamentals; 2 Uncertainty in Remote Sensing; 3 Toward a Comprehensive View of Uncertainty in Remote Sensing Analysis; 4 On the Ambiguity Induced by a Remote Sensor's PSF; 5 Pixel Unmixing at the Sub-pixel Scale Based on Land Cover Class Probabilities: Application to Urban Areas; 6 Super-resolution Land Cover Mapping from Remotely Sensed Imagery using a Hopfield Neural Network 327 $a7 Uncertainty in Land Cover Mapping from Remotely Sensed Data using Textural Algorithm and Artificial Neural Networks8 Remote Monitoring of the Impact of ENSO-related Drought on Sabah Rainforest using NOAA AVHRR Middle Infrared Reflectance: Exploring Emissivity Uncertainty; 9 Land Cover Map 2000 and Meta-data at the Land Parcel Level; 10 Analysing Uncertainty Propagation in GIS: Why is it not that Simple?; 11 Managing Uncertainty in a Geospatial Model of Biodiversity 327 $a12 The Effects of Uncertainty in Deposition Data on Predicting Exceedances of Acidity Critical Loads for Sensitive UK Ecosystems13 Vertical and Horizontal Spatial Variation of Geostatistical Prediction; 14 Geostatistical Prediction and Simulation of the Lateral and Vertical Extent of Soil Horizons; 15 Increasing the Accuracy of Predictions of Monthly Precipitation in Great Britain using Kriging with an External Drift; 16 Conditional Simulation Applied to Uncertainty Assessment in DTMs; 17 Current Status of Uncertainty Issues in Remote Sensing and GIS; Index 330 $aRemote sensing and geographical information science (GIS) have advanced considerably in recent years. However, the potential of remote sensing and GIS within the environmental sciences is limited by uncertainty, especially in connection with the data sets and methods used. In many studies, the issue of uncertainty has been incompletely addressed. The situation has arisen in part from a lack of appreciation of uncertainty and the problems it can cause as well as of the techniques that may be used to accommodate it.This book provides general overviews on uncertainty in remote sensing and GIS 606 $aRemote sensing 606 $aGeographic information systems 606 $aUncertainty (Information theory) 615 0$aRemote sensing. 615 0$aGeographic information systems. 615 0$aUncertainty (Information theory) 676 $a550.28 676 $a910/.285 701 $aFoody$b Giles M$0884213 701 $aAtkinson$b Peter M$0884214 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143171203321 996 $aUncertainty in remote sensing and GIS$91974481 997 $aUNINA