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Author: Murat İlsever
Publisher: Springer Science & Business Media
ISBN: 1447142551
Category : Computers
Languages : en
Pages : 77
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Book Description
Change detection using remotely sensed images has many applications, such as urban monitoring, land-cover change analysis, and disaster management. This work investigates two-dimensional change detection methods. The existing methods in the literature are grouped into four categories: pixel-based, transformation-based, texture analysis-based, and structure-based. In addition to testing existing methods, four new change detection methods are introduced: fuzzy logic-based, shadow detection-based, local feature-based, and bipartite graph matching-based. The latter two methods form the basis for a structural analysis of change detection. Three thresholding algorithms are compared, and their effects on the performance of change detection methods are measured. These tests on existing and novel change detection methods make use of a total of 35 panchromatic and multi-spectral Ikonos image sets. Quantitative test results and their interpretations are provided.
Author: Murat İlsever
Publisher: Springer Science & Business Media
ISBN: 1447142551
Category : Computers
Languages : en
Pages : 77
Get Book Here
Book Description
Change detection using remotely sensed images has many applications, such as urban monitoring, land-cover change analysis, and disaster management. This work investigates two-dimensional change detection methods. The existing methods in the literature are grouped into four categories: pixel-based, transformation-based, texture analysis-based, and structure-based. In addition to testing existing methods, four new change detection methods are introduced: fuzzy logic-based, shadow detection-based, local feature-based, and bipartite graph matching-based. The latter two methods form the basis for a structural analysis of change detection. Three thresholding algorithms are compared, and their effects on the performance of change detection methods are measured. These tests on existing and novel change detection methods make use of a total of 35 panchromatic and multi-spectral Ikonos image sets. Quantitative test results and their interpretations are provided.
Author: Morton J. Canty
Publisher: CRC Press
ISBN: 1466570377
Category : Mathematics
Languages : en
Pages : 575
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Book Description
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Author: Abdourrahmane M. Atto
Publisher: John Wiley & Sons
ISBN: 178945056X
Category : Computers
Languages : en
Pages : 306
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Book Description
Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.
Author: Morton John Canty
Publisher: CRC Press
ISBN: 0429875347
Category : Technology & Engineering
Languages : en
Pages : 445
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Book Description
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty’s fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.
Author: John R. Jensen
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 584
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Book Description
For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. This revision of Introductory Digital Image Processing: A Remote Sensing Perspective continues to focus on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects. Part of the Prentice Hall Series Geographic Information Science.
Author: Manfred Owe
Publisher:
ISBN:
Category : Environmental monitoring
Languages : en
Pages : 294
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Book Description
This publication is a compilation of papers that were presented at the IAHS Symposium on Remote Sensing for Environmental Monitoring and Change Detectionorganised by the IAHS International Commission on Remote Sensing, in Perugia, 2007. The 30 contributions cover approaches using the thermal infrared, microwave and radar; studies monitoring vegetation, snow and ice, and evapotranspiration; and the combination of remote sensing techniques and GISfor hydrological applications.
Author: Shashi Shekhar
Publisher: Springer Science & Business Media
ISBN: 038730858X
Category : Computers
Languages : en
Pages : 1392
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Book Description
The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.
Author: Yifang Ban
Publisher: Springer
ISBN: 331947037X
Category : Technology & Engineering
Languages : en
Pages : 448
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Book Description
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.
Author: Martin Wegmann
Publisher: Pelagic Publishing Ltd
ISBN: 1784270245
Category : Science
Languages : en
Pages : 410
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Book Description
This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS. Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided. This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.
Author: Vineeth Balasubramanian
Publisher: Newnes
ISBN: 0124017150
Category : Computers
Languages : en
Pages : 323
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Book Description
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. - Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning - Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering - Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection
