This book presents a comprehensive coverage of remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies in detail how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence. The author explains multiple methods of attaining data, describes the pros and cons of each method, and encourages readers to choose the best method applicable to their case. The author offers a practical approach to data analysis using the most appropriate methods and software. 1. Covers all major natural hazards including hurricanes, tornadoes, wildfires, and avalanches. 2. Studies each natural hazard holistically, ranging from spatial extent, severity, impact assessment, causes, and prediction of occurrence. 3. Explains different remotely sensed data and the most appropriate method used. 4. Compares different ways of sensing and clarifies the pros and cons of any selected data or their analysis. 5. Provides ample examples of each aspect of a natural hazard studied augmented with graphic illustrations and quality assurance information. All professionals working in the field of natural hazards, senior undergraduate, and graduate students, will find in-depth approaches and sufficient information to become knowledgeable in the methods of yielding and analyzing data provided with remote sensing technology, ultimately providing a deeper understanding of natural hazards.

This textbook provides comprehensive and in-depth explanations of all topics related to spatial analysis and spatiotemporal simulation, including how spatial data are acquired, represented digitally, and spatially aggregated. Also features the nature of space and how it is measured. Descriptive, explanatory, and inferential analyses are covered for point, line, and area data. It captures the latest developments in spatiotemporal simulation with cellular automata and agent-based modelling, and through practical examples discusses how spatial analysis and modelling can be implemented in different computing platforms. A much-needed textbook for a course at upper undergraduate and postgraduate levels.

By reimagining episodes from Homer's Odyssey, Jay Gao's highly anticipated debut collection, Imperium, introduces an innovative talent whose work cuts across poetic traditions, traversing mythic cartographies and imperial formations. Exploring forms of absolute and intimate power, Imperium is an imaginative meditation on how the past lives on in the present by way of, and beyond, a global poetics of diaspora.

This book offers a comprehensive review of the landscapes and ecosystems of the Upper Yellow River. It focuses on landscapes as a platform for considering environmental values and issues across the region. The book is based on extensive field-based analyses, applications, and photographs.

This book offers a comprehensive review of the landscapes and ecosystems of the Upper Yellow River. It focuses on landscapes as a platform for considering environmental values and issues across the region. The book is based on extensive field-based analyses, applications, and photographs.

"Jay Gao's book on the analysis of remote sensing imagery is a well-written, easy-to-read, and informative text best serving graduate students in geosciences, and practitioners in the field of digital image analysis. Although Dr. Gao states that he has targeted his book at upper-level undergraduates and lower-level postgraduate students, its rigor and depth of mathematical analysis would challenge most students without prior experience in remote sensing and college-level mathematics. The book covers a lot of ground quickly, beginning with a basic explanation of pixels, digital numbers and histograms and advancing rapidly through a description of the most well-known satellite systems to data storage formats, rectification and classification. It best serves students who have already taken an introductory course in remote sensing. Following a three-chapter description of the basics the remaining eleven chapters are dedicated to the description of the most common image processing systems and the details of the image analysis functions which can be carried out. The largest portion of the text covers classification - spectral and spatial, neural networks, decision trees and expert systems - and is an invaluable reference to anyone interested in understanding image analysis terminology and the algorithms behind these different systems. The last chapter of the text is addressed to practitioners wishing to integrate remote sensing image data with GIS and/or GPS data. The text is nicely structured so that individual chapters can easily be skipped when their content is not of interest to the reader without impairing the understanding of later chapters.

"The first three chapters of the book cover introductory material that the reader should be familiar with for the most part, but also includes a very handy summary of today's satellite systems. Chapter one addresses basic material, such as pixel DN, coordinates, feature space, histograms, and spatial, spectral, temporal and radiometric resolution normally covered in an introductory course in remote sensing. Chapter two presents a very informative and up-to-date overview of today's satellite instruments including meteorological, oceanographic, earth resources, hyperspectral and radar instruments. Instrument and orbital parameters are presented in tabular form and make it easy to look up technical details such as spectral and spatial resolution, orbit type, repeat cycle and other instrument characteristics quickly. Written explanations are clear, readable and provide lots of interesting insight and useful tidbits of information such as potential problems and the cost of imagery. For technicians and programmers the third chapter provides details on storage formats, including descriptions of BSQ, BIL and BIP binary formats, and the most common graphics formats like GIF, TIFF and JPEG together with data compression techniques. Non-technicians can skip this chapter since image processing software will generally take care of format conversions internally without a need for understanding the nuances of each.

"Chapters four will be of interest to anyone considering the purchase of image processing software, or trying to understand the differences between systems. Gao provides a useful overview of existing software - IDRISI, ERDAS Imagine, ENVI, ER Mapper, PCI, eCognition and GRASS. A brief history of each provides useful background, and a discussion of the features of each together with a comparison (also given in tabular form) is informative to anyone considering a purchase.

"Chapter five can also be viewed as a stand-alone reference on rectification, but also serves as an excellent overview of the problems of dealing with mapping on a curved surface and has particular application for geographers and cartographers. It discusses the sources of geometric distortion, coordinated systems and projections, how image rectification is done - including the use of ground control points and implications for the order of transformation employed. There is a nice example showing how accuracy is influenced by the number of GCPs employed for SPOT and Landsat TM. For non-technical students the transformation mathematics can be skipped. A rather minimal section on image subsetting and mosaicking is included. Chapter six continues in much the same vein as the previous chapter, but discussing image enhancement - techniques that improve the visual quality of an image. The terms introduced here, such as density slicing, linear enhancement, stretching, and histogram equalization, will be familiar to users of image processing software and Gao provides a useful explanation of each in turn. Other application-oriented utilities such as band ratioing, vegetation indices, IHS and Tasseled Cap transformations and principal component analysis are presented in a form which is understandable to students with good mathematical grounding.

"The remainder of the text deals, to a large extent, with the topic of classification. Chapter seven initially discusses elements of image interpretation, but then devotes the chapter to a detailed presentation of the most common (and affordable) of these - spectral analysis. Gao presents the different algorithms used to define spectral distance, and then devotes text to a discussion of the inner workings of unsupervised classification systems. The section on supervised classification is a very useful reference for anyone undertaking this process - describing how to set about the classification process, the differences between the different classifiers, and how to choose an appropriate one. The concepts of fuzzy logic and sub-pixels classifiers are also presented briefly.

"From this point on, the text becomes much more specialized and technical and is geared towards graduate students, those carrying out research projects, and those interested in algorithmic detail. Chapter 8 is the first dealing with artificial intelligence and describes th