Download Free Research Methods In Remote Sensing Book in PDF and EPUB Free Download. You can read online Research Methods In Remote Sensing and write the review.

This book introduces the overall concepts of research methods in Remote Sensing. It also addresses the entire research framework, ranging from ontology to documentation. As such, it covers the theory while providing a solid basis for engaging in concrete research activities. It is not intended as a textbook on remote sensing; rather, it offers guidance to those conducting research by examining philosophical and other issues that are generally not covered by textbooks. Various stages of research are discussed in detail, including illustrative discussions and helpful references. The topics considered in this book cover a part of the research methodologies explored in Master of Philosophy (M.Phil.) and Doctor of Philosophy (Ph.D.) programs. The book’s physical format has been kept to a compact, handy minimum in order to maximize its accessibility and readability for a broad range of researchers in the field of remote sensing.
This concise, much-needed guide takes readers step by step through planning and executing field work associated with many different types of remote sensing projects. Remote sensing texts and research reports typically focus on data-analytic techniques while offering a dearth of information on procedures followed in the field. In contrast, this book provides clear recommendations for defining field work objectives, devising a valid sampling plan, finding locations using GPS, and selecting and using effective measurement techniques for field reflectance spectra and for studies of vegetation, soils, water, and urban areas. Appendices feature sample field note forms, an extensive bibliography on advanced and specialized methods, and online metadata sources.
With the widespread availability of satellite and aircraft remote sensing image data in digital form, and the ready access most remote sensing practitioners have to computing systems for image interpretation, there is a need to draw together the range of digital image processing procedures and methodologies commonly used in this field into a single treatment. It is the intention of this book to provide such a function, at a level meaningful to the non-specialist digital image analyst, but in sufficient detail that algorithm limitations, alternative procedures and current trends can be appreciated. Often the applications specialist in remote sensing wishing to make use of digital processing procedures has had to depend upon either the mathematically detailed treatments of image processing found in the electrical engineering and computer science literature, or the sometimes necessarily superficial treatments given in general texts on remote sensing. This book seeks to redress that situation. Both image enhancement and classification techniques are covered making the material relevant in those applications in which photointerpretation is used for information extraction and in those wherein information is obtained by classification.
The versatile and available GNSS signals can detect the Earth’s surface environments as a new, highly precise, continuous, all-weather and near-real-time remote sensing tool. This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. Ground-based atmospheric sensing, space-borne atmospheric sensing, reflectometry, ocean remote sensing, hydrology sensing as well as cryosphere sensing with the GNSS will be discussed per chapter in the book.
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.
This book presents a spatially-based multiple methods approach to research serving academic and organizational researchers from across a wide variety of disciplines. For many, consideration of spatial relationships is an important component of their research questions, including those who may not have yet recognized GIS as a valuable tool. The book will provide readers essential steps to conceptualize and implement research and analysis, develop meaningful quantitative and qualitative geographic results and to communicate their findings using the visualization capabilities of GIS to assist decision-makers and affect policy. Furthermore it offers researchers a deeper understanding of social, economic and environmental questions considering spatial relationships in their data.The broad subject area of the project is the integration of spatial analysis as a research methodology. More specifically the book provides practical guidance for the identification, collection and analysis of appropriate research data for analysis in an Esri/ArcGIS context without being specific to a particular version of the software. The objective is to present ArcGIS with an eye towards incorporating spatial analysis as a fundamental component of mixed methods research. Because GIS is, by nature, an integrative technology which can draw together multiple data sources via a common spatial attribute, it is a natural fit for mixed-methods research. GIS provides the researcher an unparalleled ability to enhance their research incorporating a geographic perspective.
This comprehensive textbook offers a conceptual and practical introduction to research methodology, data collection, and techniques used in both human and physical geography. Explores a full range of contemporary geographic techniques, including statistics, mathematical analysis, GIS, and remote sensing Unique in both content and organization, it brings together a team of internationally recognized specialists to create a balanced approach between physical geography, human geography, and research techniques Includes a series of foundational chapters offering multiple perspectives on the central questions in research methods Examines the conceptual frameworks and practical issues behind data acquisition and analysis, and how to interpret results Includes explanations of key terminology and exercises throughout
Written by world renowned scientists, this book provides an excellent overview of a wide array of methods and techniques for the processing and analysis of multitemporal remotely sensed images. These methods and techniques include change detection, multitemporal data fusion, coarse-resolution time series processing, and interferometric SAR multitemporal processing, among others. A broad range of multitemporal datasets are used in their methodology demonstrations and application examples, including multispectral, hyperspectral, SAR and passive microwave data. This book features a variety of application examples covering both land and aquatic environments. Land applications include urban, agriculture, habitat disturbance, vegetation dynamics, soil moisture, land surface albedo, land surface temperature, glacier and disaster recovery. Aquatic applications include monitoring water quality, water surface areas and water fluctuation in wetland areas, spatial distribution patterns and temporal fluctuation trends of global land surface water, as well as evaluation of water quality in several coastal and marine environments. This book will help scientists, practitioners, students gain a greater understanding of how multitemporal remote sensing could be effectively used to monitor our changing planet at local, regional, and global scales.
An outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference. * Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs. * Covers existing aircraft and satellite programs and several future programs *An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
"Covers a broad range of subjects that undergraduates in the discipline should be familiar and comfortable with upon graduation. From chapters on the scientific method and fundamental research concepts, to experimental design, sampling and statistical analysis, the text offers an excellent introduction to the key concepts of geographical research. The content is applicable for students at the beginning of their studies right through to planning and conducting dissertations. The book has also been of particular support in designing my level 1 and 2 tutorials which cover similar ground to several of the chapters." - Joseph Mallalieu, School of Geography, Leeds University "Montello and Sutton is one of the best texts I′ve used in seminars on research methodology. The text offers a clear balance of quantitative vs. qualitative and physical vs. human which I′ve found particularly valuable. The chapters on research ethics, scientific communication, information technologies and data visualization are excellent." - Kenneth E. Foote, Department of Geography, University of Colorado at Boulder This is a broad and integrative introduction to the conduct and interpretation of scientific research, covering both geography and environmental studies. Written for undergraduate and postgraduate students, it: Explains both the conceptual and the technical aspects of research, as well as all phases of the research process Combines approaches in physical geography and environmental science, human geography and human-environment relations, and geographic and environmental information techniques (such as GIS, cartography, and remote sensing) Combines natural and social scientific approaches common to subjects in geography and environmental studies Includes case studies of actual research projects to demonstrate the breadth of approaches taken It will be core reading for students studying scientific research methods in geography, environmental studies and related disciplines such as planning and earth science.