emphasizes the application of digital image processing algorithms rather than engineering "signal processing" to extract useful earth resource information from remotely sensed imagery. organizes content according to the general flow or method by which digital remote sensor data is actually analyzed. presents all algorithms in relatively simple algebra terms. contains new, specially developed detailed graphics and uses color more extensively . features a larger (8 1/2x11) format. summarizes the "remote sensing process" hypothesis testing procedures, data collection, data analysis, and information presentation (display) alternatives. reviews new methods of image digitization and data compression the national aerial photography program (NAPP); multispectral imaging using discrete detectors and scanning mirrors; multispectral imaging using linear arrays; imagine spectrometry using linear and area arrays; the proposed Earth Observing System (EOS) and summarizes new formats for digital imagery. surveys the state-of-the- art of digital image processing hardware and software configurations using mainframe, workstation, and personal computers.

discusses the functionality of 25 commercial and 6 public digital image processing systems. contains a more detailed treatment of univariate and multivariate statistics which are routinely extracted from remotely sensed data. introduces the concept of "scientific visualization" and presents alternatives for producing scaled, color, hardcopy output. contains detailed information on how to radiometrically correct for atmospheric attenuation in remotely sensed data using "relative image normalization" and "absolute radiometric correction" techniques. describes how linear and non-linear contrast enhancement is performed and provides in-depth coverage of histogram equalization. contains a new section on spatial filtering in the frequency domain using the Fourier Transform. introduces classification schemes including the new NOAA CoastWatch scheme. describes all the major supervised classification algorithms including methods for making them efficient and shows how to incorporate a priori and a posteriori probabilities.

features a new section based on the ISODATA clustering algorithm, with informative graphics which describes how the feature space is iteratively partitioned. contains a flow diagram of the general steps required to perform digital change detection of remotely sensed data, and presents 9 change detection algorithms along with diagrams which depict exactly how to perform the change direction. includes a complete description of the major vector (e.g., TIGER, DLG) and raster data sets (e.g., remotely sensed data) available as well as a discussion of the various data analysis functions typically available in a GIS. includes a case study which predicts the geographic distribution of wetlands in a freshwater lake based on the GIS analysis of various biophysical variables.