Satellite Remote Sensing of Natural Resources

Auteur
Verbyla, David L.

Texte du rabat

Satellite Remote Sensing of Natural Resources offers an introduction to digital remote sensing. This comprehensive text emphasizes the basics, with simple concepts presented in clear, easy-to-understand language. For those who are interested in practical remote sensing but do not have an extensive background in math and statistics, this primer is invaluable. The main topics covered include satellite images, image processing systems, spectral regions, radiometric and geometric corrections, supervised and unsupervised classification, and accuracy assessment. Each chapter concludes with a section of sample problems and list of additional readings.

Résumé
Offers an introduction to digital remote sensing. This text emphasizes the basics, with concepts presented in an easy-to-understand language. It covers such topics as satellite images, image processing systems, spectral regions, radiometric and geometric corrections, supervised and unsupervised classification, and accuracy assessment.

Contenu
CONTENTS: Preface. Satellite Images: Raster Image Data. Remote Sensing Detectors. Scanning Systems. Image Scale and Resolution. Major Satellite Systems Used in Natural Resources Management. Problems. Additional Readings. Image Processing Systems: Computer Fundamentals. Display of Panchromatic Images. Contrast Enhancements. Display of Color Images. Image Magnification and Reduction. Problems. Additional Readings. Spectral Regions: Introduction. Spectral Regions. Vegetation Spectral Relationships. Water Spectral Relationships. Soil Spectral Relationships. Snow and Cloud Spectral Relationships. Thermal Remote Sensing. Potential Problems. Problems. Literature Cited. Additional Readings. Radiometric Corrections: Detector Errors. Correction for Atmospheric Scattering. Problems. Literature Cited. Additional Readings. Geometric Corrections: Map Projections. Map Coordinate Systems. National Map Accuracy Standards. Selection of Ground Control Points. Image Rectification Models. Pixel Resampling Methods. Ordering Rectified Data. Problems. Additional Readings. Unsupervised Classification: Introduction. Histogram-Based Unsupervised Classification. Sequential Clustering. Isodata Clustering. Grouping of Spectral Classes. Problems. Additional Readings. Supervised Classification: Introduction. Training Fields. Basic Classifiers. Problems. Additional Readings. Accuracy Assessment: Introduction. The Error Matrix. Collection of Reference Data. Problems. Additional Readings. Appendix: Solutions to Even-Numbered Problems. Index.