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Satellite Image Analysis Clustering And Classification
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Book Synopsis Satellite Image Analysis: Clustering and Classification by : Surekha Borra
Download or read book Satellite Image Analysis: Clustering and Classification written by Surekha Borra and published by Springer. This book was released on 2019-02-08 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Book Synopsis Artificial Intelligence Techniques for Satellite Image Analysis by : D. Jude Hemanth
Download or read book Artificial Intelligence Techniques for Satellite Image Analysis written by D. Jude Hemanth and published by Springer Nature. This book was released on 2019-11-13 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing.
Book Synopsis Remote Sensing Digital Image Analysis by : John A. Richards
Download or read book Remote Sensing Digital Image Analysis written by John A. Richards and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Image Analysis, Classification and Change Detection in Remote Sensing by : Morton J. Canty
Download or read book Image Analysis, Classification and Change Detection in Remote Sensing written by Morton J. Canty and published by CRC Press. This book was released on 2014-06-06 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Multispectral Satellite Image Understanding by : Cem Ünsalan
Download or read book Multispectral Satellite Image Understanding written by Cem Ünsalan and published by Springer Science & Business Media. This book was released on 2011-05-18 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.
Book Synopsis An Overview of Technological Revolution in Satellite Image Analysis by : Jenice Aroma R.
Download or read book An Overview of Technological Revolution in Satellite Image Analysis written by Jenice Aroma R. and published by Infinite Study. This book was released on with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: The satellite image based applications are highly utilized nowadays from simple purposes like vehicle navigation to complex surveillance and virtual environment modeling projects. On increased population rate, the depletion of natural resources is highly unavoidable and it leads to increased threats on natural hazards. In order to protect and overcome the physical losses on devastation of properties, the risk mapping models such as weather forecasts, drought modeling and other hazard assessment models are in need.
Book Synopsis Clustering Parameters for Multispectral Satellite Image Analysis by : Prasad Kaviti
Download or read book Clustering Parameters for Multispectral Satellite Image Analysis written by Prasad Kaviti and published by . This book was released on 2023-01-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering parameters for multispectral satellite image analysis is a method used in image processing and remote sensing to extract useful information from satellite images. Clustering is an unsupervised learning technique that groups similar pixels together based on their spectral and spatial characteristics. The process of clustering in multispectral satellite image analysis involves using various parameters to extract relevant features and reduce the dimensionality of the data. Spectral information, such as the reflectance values of different spectral bands, is used to group similar pixels together. Spatial information, such as the location and shape of the clusters, is also considered. Different clustering algorithms can be used, such as K-means, Expectation-Maximization, hierarchical clustering, density-based clustering, and spectral-spatial clustering. The choice of algorithm and parameters will depend on the specific application and the desired level of accuracy for the image segmentation and classification. To evaluate the performance of the clustering, various validation metrics can be used, such as the confusion matrix, overall accuracy, F1-score, Jaccard similarity coefficient, and Kappa coefficient. These metrics provide a quantitative measure of the clustering performance and can be used to compare different clustering methods and parameters. Overall, Clustering Parameters for Multispectral Satellite Image Analysis is a powerful method for extracting useful information from satellite images and it is widely used in various applications such as land use/land cover mapping, crop identification, and natural resources management. Image analysis is a widely used technique, which is necessary for understanding and speculating specific aspects of the information. Images are analyzed and pro- cessed to help single users, professional bodies, and government organizations. In today's world, remotely sensed multispectral images processing is a major research area used to deal with problems such as landuse-landcover, fire detection, crop es- timation, and flood prediction to name a few, which greatly impact the economic and environmental concerns, and the techniques developed through this technol- ogy allows many real-life applications with high social value [CVTGC]11]. Classification is the most common operation used to analyze these multispec- tral images. The critical objective of the image classification technique is to group all pixel data of an image into land cover classes or thematic maps automatically [JL05]. In general, multispectral images pixels have an inherent spectral pattern which is the numerical basis for the classification of multispectral images i.e. the inherent spectral reflectance and emittance properties of the electromagnetic spec- trum are indexed with different combinations of Digital Numbers in the image to recognize various types of features or objects. Spectral pattern recognition is a classification procedure that performs automated landcover classification with the help of pixel-by-pixel spectral information. Remote sensing is one of the efficient ways to procure multispectral images. Re- mote sensing is a procedure to acquire data from any distance without physically interacting with objects. Remote sensing can be made possible with the help of satellites or aircrafts which have sensors mounted on them to capture electromag- netic radiation scattered or emitted from the Earth's surface.
Book Synopsis Big Data Analytics for Satellite Image Processing and Remote Sensing by : Swarnalatha, P.
Download or read book Big Data Analytics for Satellite Image Processing and Remote Sensing written by Swarnalatha, P. and published by IGI Global. This book was released on 2018-03-09 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.
Book Synopsis Object-Based Image Analysis by : Thomas Blaschke
Download or read book Object-Based Image Analysis written by Thomas Blaschke and published by Springer Science & Business Media. This book was released on 2008-08-09 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).
Book Synopsis Non-traditional Approaches to Classification of High Resolution Satellite Imagery by : Martin Paul Buchheim
Download or read book Non-traditional Approaches to Classification of High Resolution Satellite Imagery written by Martin Paul Buchheim and published by . This book was released on 1988 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Signal and Image Processing for Remote Sensing by : C.H. Chen
Download or read book Signal and Image Processing for Remote Sensing written by C.H. Chen and published by CRC Press. This book was released on 2024-06-11 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing. Features Includes all new content and does not replace the previous edition Covers machine learning approaches in both signal and image processing for remote sensing Studies deep learning methods for remote sensing information extraction that is found in other books Explains SAR, microwave, seismic, GPR, and hyperspectral sensors and all sensors considered Discusses improved pattern classification approaches and compressed sensing approaches Provides ample examples of each aspect of both signal and image processing This book is intended for university academics, researchers, postgraduate students, industry, and government professionals who use remote sensing and its applications.
Book Synopsis Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification by : Anil Kumar
Download or read book Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification written by Anil Kumar and published by CRC Press. This book was released on 2020-07-19 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.
Book Synopsis Remote Sensing Digital Image Analysis by : John A. Richards
Download or read book Remote Sensing Digital Image Analysis written by John A. Richards and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and enlarged to reflect new developments in the field, the fourth edition of this well-established text provides an introduction to quantitative evaluation of satellite- and aircraft-derived remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations.
Book Synopsis Satellite Image Classification - a Guided Clustering Approach by : Naeem Shahzad
Download or read book Satellite Image Classification - a Guided Clustering Approach written by Naeem Shahzad and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: In supervised classification of remotely sensed imagery the analysts require a plenty of time for generating the representative signatures of the possible land-cover classes present in the image. Although the notion of picking a large number of input signatures leads to more efficient results but in most of the situations the time is an important factor. To save the lavish time, besides to obtain the reliable results, is the requirement of most of the analysts. In this study the results of supervised classification are used as reference for checking the reliability of the results obtained with guided clustering technique as this technique is based on ground truth data and the ancillary information.
Book Synopsis Remote Sensing Time Series by : Claudia Kuenzer
Download or read book Remote Sensing Time Series written by Claudia Kuenzer and published by Springer. This book was released on 2015-04-28 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises an outstanding variety of chapters on Earth Observation based time series analyses, undertaken to reveal past and current land surface dynamics for large areas. What exactly are time series of Earth Observation data? Which sensors are available to generate real time series? How can they be processed to reveal their valuable hidden information? Which challenges are encountered on the way and which pre-processing is needed? And last but not least: which processes can be observed? How are large regions of our planet changing over time and which dynamics and trends are visible? These and many other questions are answered within this book “Remote Sensing Time Series Analyses – Revealing Land Surface Dynamics”. Internationally renowned experts from Europe, the USA and China present their exciting findings based on the exploitation of satellite data archives from well-known sensors such as AVHRR, MODIS, Landsat, ENVISAT, ERS and METOP amongst others. Selected review and methods chapters provide a good overview over time series processing and the recent advances in the optical and radar domain. A fine selection of application chapters addresses multi-class land cover and land use change at national to continental scale, the derivation of patterns of vegetation phenology, biomass assessments, investigations on snow cover duration and recent dynamics, as well as urban sprawl observed over time.
Book Synopsis Time Series Analysis and Applications by : Nawaz Mohamudally
Download or read book Time Series Analysis and Applications written by Nawaz Mohamudally and published by IntechOpen. This book was released on 2018-01-24 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time Series Analysis (TSA) and Applications offers a dense content of current research and development in the field of data science. The book presents time series from a multidisciplinary approach that covers a wide range of sectors ranging from biostatistics to renewable energy forecasting. Contrary to previous literatures on time, serious readers will discover the potential of TSA in areas other than finance or weather forecasting. The choice of the algorithmic transform for different scenarios, which is a key determinant in the application of TSA, can be understood through the diverse domain applications. Readers looking for deep understanding and practicability of TSA will be delighted. Early career researchers too will appreciate the technicalities and refined mathematical complexities surrounding TSA. Our wish is that this book adds to the body of TSA knowledge and opens up avenues for those who are looking forward to applying TSA in their own context.
Book Synopsis Remote Sensing Image Processing by : Gustavo Camps-Valls
Download or read book Remote Sensing Image Processing written by Gustavo Camps-Valls and published by Morgan & Claypool Publishers. This book was released on 2011-12-11 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / Classification / Spectral Mixture Analysis / Estimation of Physical Parameters
