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.
Download or read book Multispectral Satellite Image Understanding written by Cem Unsalan and published by Springer. This book was released on 2011-08-10 with total page 186 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.
Download or read book Multispectral Satellite Image Understanding written by Cem Ünsalan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: A problem of major interest to regional planning organizations, disaster relief agencies, and the military is the identification and tracking of land development across large scale regions, and over time. We develop an autonomous image analysis system to understand land development, especially residential and urban building organizations from satellite images. We introduce a set of measures based on straight lines to assess land development levels in high resolution satellite images. Urban areas exhibit a preponderance of straight line features. Rural areas produce line structures in more random spatial arrangements. We use this observation to perform an initial triage on the image to restrict the attention of subsequent, more computationally intensive analyses. Vegetation indices have been used extensively to estimate the vegetation density from satellite and airborne images for many years. We use these as the multispectral information for classification and house and road extraction. We focus on the normalized difference vegetation index NDVI and introduce a statistical framework to analyze and extend it. Using the established statistical framework, we introduce new a group of shadow-water indices. We then extend our straight line based measures by developing a synergistic approach that combines structural and multispectral information. In particular, the structural features serve as cue regions for multispectral features. After the initial classification of regions, we introduce computationally more expensive but more precise graph theoretical measures over grayscale images to detect residential regions. The graphs are constructed using lines as vertices, while graph edges encode their spatial relationships. We introduce a set of measures based on various properties of the graph. These measures are monotonic with increasing structure (organization) in the image. We present a theoretical basis for the measures. Having detected the residential regions, we introduce a novel system to detect houses and street networks in these. We extensively use the multispectral information and graph theory to extract houses and road networks. We evaluated the performance of each step statistically and obtained very promising results. Especially, detection performances in house and street detection in residential regions is noteworthy. These results indicate the functionality of our satellite image understanding system.
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.
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.
Download or read book Multispectral Image Analysis Using the Object Oriented Paradigm written by Kumar Navulur and published by CRC Press. This book was released on 2006-12-05 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing a fresh new perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. Featuring various practical examples to provide understanding of this new modus operandi, Multispectral Image Analysis Using the Object-Oriented Paradigm reviews the current image analysis methods and demonstrates advantages to improve information extraction from imagery. This reference describes traditional image analysis techniques, introduces object-oriented technology, and discusses the benefits of object-based versus pixel-based classification. It examines the creation of object primitives using image segmentation approaches and the use of various techniques for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and concepts of semantic grouping of objects. He concludes by addressing accuracy assessment approaches. The accompanying downloadable resources present sample data that enable the use of different approaches to problem solving. Integrating remote sensing techniques and GIS analysis, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.
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.
Download or read book Handbook of Mathematical Geosciences written by B.S. Daya Sagar and published by Springer. This book was released on 2018-06-25 with total page 911 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences.
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.
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).
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.
Download or read book Digital Analysis of Remotely Sensed Imagery written by Jay Gao and published by McGraw Hill Professional. This book was released on 2009-05-01 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important text that identifies and introduces new trends in image analysis Digital Analysis of Remotely Sensed Imagery provides thorough coverage of the entire process of analyzing remotely sensed data for the purpose of producing accurate representations in thematic map format. Written in easy-to-follow language with minimal technical jargon, the book explores cutting-edge techniques and trends in image analysis, as well as the relationship between image processing and other recently emerged special technologies.
Download or read book Remote Sensing written by Robert A. Schowengerdt and published by Elsevier. This book was released on 2006-08-28 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. Remote Sensing, in its third edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standards. Dr. Schowengerdt presents an advanced unified framework and rationale that uniquely empowers the reader with the latest critical thinking skills and prerequisite knowledge needed to successfully design, develop and incorporate maintainable remote sensing solutions for real-world application. Advanced remote sensing image processing techniques such as hyperspectral image analysis, fusion of multisensor images and digital elevation model extraction from stereo imagery are discussed theoretically in terms of spectral, spatial, and geometric models. An expanded exercise section is also included at the end of each chapter allowing for the greatest level of mastery ever. - Features a new lively discussion of the NASA EOS satellites, Terra and Aqua, and the commercial satellites IKONOS and Quickbird - New larger format provides additional access to 32 PAGE - FULL COLOR plate insert and improved readability - Additional data processing algorithms help connect and enhance the collective understanding of engineering design and remotely sensed data
Download or read book Analysis Of Multi temporal Remote Sensing Images Proceedings Of The Second International Workshop On The Multitemp 2003 written by Paul C Smits and published by World Scientific. This book was released on 2004-08-10 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of effective methodologies for the analysis of multi-temporal data is one of the most important and challenging issues that the remote sensing community will face in the coming years. Its importance and timeliness are directly related to the ever-increasing quantity of multi-temporal data provided by the numerous remote sensing satellites that orbit our planet. The synergistic use of multi-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring of the Earth's surface and atmosphere at different scales. However, the advances in the methodologies for the analysis of multi-temporal data have been significantly under-illuminated with respect to other remote sensing data analysis topics. In addition, the link between the end-users' needs and the scientific community needs to be strengthened.This volume of proceedings contains 43 contributions from researchers representing academia, industry and governmental organizations. It is organized into three thematic sections: Image Analysis and Algorithms; Analysis of Synthetic Aperture Radar Data; Monitoring and Management of Resources.
Download or read book Multi resolution Image Fusion in Remote Sensing written by Manjunath V. Joshi and published by Cambridge University Press. This book was released on 2019-01-24 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written using clear and accessible language, this useful guide discusses fundamental concepts and practices of multi-resolution image fusion.
Download or read book Remote Sensing Digital Image Analysis written by John Alan Richards and published by Springer Science & Business Media. This book was released on 1999 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing Digital Image Analysis provides the non-specialist with 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. Problems conclude each chapter. This fourth edition has been developed to reflect the changes that have occurred in this area over the past several years. Its focus is on those procedures that seem now to have become part of the set of tools regularly used to perform thematic mapping. As with previous revisions, the fundamental material has been preserved in its original form because of its tutorial value; its style has been revised in places and it has been supplemented if newer aspects have emerged in the time since the third edition appeared. It still meets, however, the needs of the senior student and practitioner.
Download or read book Very High Resolution VHR Satellite Imagery written by Francisco Eugenio and published by MDPI. This book was released on 2019-11-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.
