Remote Sensing: Models and Methods for Image Processing
Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth’s surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standards. Dr. Schowengerdt presents an advanced unified framework and rationale that uniquely empowers the reader with the latest critical thinking skills and prerequisite knowledge needed to successfully design, develop and incorporate maintainable remote sensing solutions for real-world application. Advanced remote sensing image processing techniques such as hyperspectral image analysis, fusion of multisensor images and digital elevation model extraction from stereo imagery are discussed theoretically in terms of spectral, spatial, and geometric models. An expanded exercise section is also included at the end of each chapter allowing for the greatest level of mastery ever.
*Features a new lively discussion of the NASA EOS satellites, Terra and Aqua, and the commercial satellites IKONOS and Quickbird.
*New larger format provides additional access to 32 PAGE - FULL COLOR plate insert and improved readability
*Additional data processing algorithms help connect and enhance the collective understanding of engineering design and remotely sensed data
2 Optical Radiation Models
3 Sensor Models
4 Data Models
5 Spectral Transforms
6 Spatial Transforms
7 Correction and Calibration
Other editions - View all
Remote Sensing, Models, and Methods for Image Processing
Robert A. Schowengerdt
Limited preview - 1997
aerial algorithm angle applied at-sensor radiance atmospheric AVHRR AVIRIS calculated calibration Chapter classification cluster color components contrast convolution correction correlation covariance cross-track Cuprite decision boundaries detector distortion distribution earth earth’s surface endmembers ETM+ example feature space FIGURE filter Fourier transform fractal dimension function Gaussian GCPs geometric GIFOV global histogram hyperspectral IKONOS image histogram image processing imagery in-track Landsat linear maximum-likelihood measured MODIS MODTRAN multispectral image noise normal optical original image output pan band panchromatic parameters pixels polynomial pushbroom QuickBird radiation radiometric reflectance region remote sensing resampling resolution sample satellite scale-space scan scanner scattergram scatterplot scene Schowengerdt semivariogram sensor shown in Fig signal signatures simulated soil solar spatial frequency spectral bands spectrum TABLE target techniques thermal threshold TM band TM image topographic values vector vegetation wavelength zero zero-crossings
Page 472 - Landsat-4 MSS and Thematic Mapper Data Quality and Information Content Analysis," IEEE Transactions on Geoscience and Remote Sensing, Vol.
Page 495 - Combining panchromatic and multispectral imagery from dual resolution satellite instruments," Remote Sensing Environment, vol.