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A Comparison Of Classification Techniques In Environmental Applications Of Remote Sensing
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Book Synopsis A Comparison of Classification Techniques in Environmental Applications of Remote Sensing by : Melanie Bean
Download or read book A Comparison of Classification Techniques in Environmental Applications of Remote Sensing written by Melanie Bean and published by . This book was released on 1998 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a comparison of remote sensing classification techniques as an extension of the environmental applications of remote sensing using Landsat data. It explores the history of remotes sensing, the principles of electromagnetic energy, and the general steps involved in remote sensing. Further, it describes the remote sensing features of Landsat 4, and 5. Finally, it applies classification techniques using Idrisi software.
Book Synopsis Advances in Environmental Remote Sensing by : Qihao Weng
Download or read book Advances in Environmental Remote Sensing written by Qihao Weng and published by CRC Press. This book was released on 2011-02-16 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generating a satisfactory classification image from remote sensing data is not a straightforward task. Many factors contribute to this difficulty including the characteristics of a study area, availability of suitable remote sensing data, ancillary and ground reference data, proper use of variables and classification algorithms, and the analyst's e
Book Synopsis Classification Methods for Remotely Sensed Data by : Taskin Kavzoglu
Download or read book Classification Methods for Remotely Sensed Data written by Taskin Kavzoglu and published by CRC Press. This book was released on 2024-09-04 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. New in this edition: Provides comprehensive background on the theory of deep learning and its application to remote sensing data. Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications. Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies. Discusses the methods used for explaining inherent structures and weighing the features of ML and AI algorithms that are critical for explaining the robustness of the models. This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc.
Book Synopsis Satellite Information Classification and Interpretation by : Rustam B. Rustamov
Download or read book Satellite Information Classification and Interpretation written by Rustam B. Rustamov and published by BoD – Books on Demand. This book was released on 2019-05-29 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Without a doubt, understanding what we must do to save our home, our planet, and how we are to do it is of the gravest importance for the present generation and the next. Clearly, advances won through space technology and applications of the same to the study of Earth play an excellent and vital role in classification and interpretation of the processes taking place on the Earth and in space. Today, space technology helps us understand Earth and how we can support and manage its state, to keep it in working condition under the current circumstances.How can we do this? Obviously, we must use appropriate methods and instruments to collect the information we need. In the meantime, it is necessary to develop systems to analyze and process the data collected.
Book Synopsis A Land Use and Land Cover Classification System for Use with Remote Sensor Data by : James Richard Anderson
Download or read book A Land Use and Land Cover Classification System for Use with Remote Sensor Data written by James Richard Anderson and published by . This book was released on 1976 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Environmental Applications of Remote Sensing and GIS in Libya by : Hamdi A. Zurqani
Download or read book Environmental Applications of Remote Sensing and GIS in Libya written by Hamdi A. Zurqani and published by Springer Nature. This book was released on 2022-06-29 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the environmental challenges that Libya and similar countries in the regions are currently facing. Each chapter of this book provides a methodology using remote sensing (RS) and geographical information systems (GIS) dealing with one of these environmental challenges such as monitoring and mapping soil salinity and prediction of soil properties, monitoring and mapping of land degradation, spatiotemporal land use/cover, agricultural drought monitoring, hydrological applications such as spatial rainfall distribution, surface runoff, geo-morphometric analysis, flood hazard assessment and mapping, hydrologic and hydraulic modeling, pollution hazard assessment, and climate-related geophysical processes. This book also assesses the impacts of climate change on natural resources using both RS and GIS, as well as other applications, covering different parts of Libya. This book is beneficial for graduate students, researchers, policy planners, and stakeholders in Libya as well as other countries that share similar environmental issues. Also, the methodologies followed in the book's chapters can be applied to any other regions around the world with similar landscapes and climatic conditions.
Book Synopsis Classification Methods for Remotely Sensed Data by : Paul Mather
Download or read book Classification Methods for Remotely Sensed Data written by Paul Mather and published by CRC Press. This book was released on 2001-12-06 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pul
Book Synopsis Classification Methods for Remotely Sensed Data, Second Edition by : Brandt Tso
Download or read book Classification Methods for Remotely Sensed Data, Second Edition written by Brandt Tso and published by CRC Press. This book was released on 2009-05-12 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keeping abreast of new developments, this new edition provides a comprehensive and up-to-date review of the entire field of classification methods applied to remotely sensed data. It provides seven fully revised chapters and two new chapters covering support vector machines (SVM) and decision trees.
Book Synopsis Urban Remote Sensing by : Qihao Weng
Download or read book Urban Remote Sensing written by Qihao Weng and published by CRC Press. This book was released on 2018-02-20 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban Remote Sensing, Second Edition assembles a team of professional experts to provide a much-needed update on the applications of remote sensing technology to urban and suburban areas. This book reflects new developments in spaceborne and airborne sensors, image processing methods and techniques, and wider applications of urban remote sensing to meet societal and economic challenges. In various sections of the book the authors address methods for upscaling urban feature extraction to the global scale, new methods in mapping and detecting urban landscape features and structures, and mapping and monitoring urbanization in developing countries. Additionally, readers are provided with valuable case studies such as the HEAT (Heat Energy Assessment Technologies) project in Calgary, Canada and the use of VHR (very high resolution) satellite monitoring in Salzburg, Austria to tackle challenges of urban green planning. Features Explores the most up-to-date developments in the field of urban remote sensing Integrates both technical and practical aspects covering all different topics of global urban growth issues Provides new and updated contributions addressing data mining of remotely sensed big data, recent urban studies on a global scale, accuracy assessment and validation, and new technical challenges Examines various applications of urban remote sensing in support of urban planning, environmental management, and sustainable urban development Authors are renowned figures in the field of remote sensing
Book Synopsis Satellite Remote Sensing of Wetlands and a Comparison of Classification Techniques by : Stacy Lee Özesmi
Download or read book Satellite Remote Sensing of Wetlands and a Comparison of Classification Techniques written by Stacy Lee Özesmi and published by . This book was released on 2000 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Comparison of Random Forests, Support Vector Machine and Artificial Neural Network Methods for Agriculture Land Cover Classification by : Xin Zhou
Download or read book Comparison of Random Forests, Support Vector Machine and Artificial Neural Network Methods for Agriculture Land Cover Classification written by Xin Zhou and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Land cover classification is critical in remote sensing. Reliable classification on land cover is required to address a wide range of environmental issues. Over recent years, the application of machine learning techniques in remote sensing has attracted wide attention. Machine learning has the capacity to classify land cover in remotely sensed photos effectively and efficiently. Machine learning techniques, such as Random Forests (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) can be applied in land cover classification. However, putting a machine learning categorization system in place is not easy, especially in the field of agricultural land classifications. Very limited research can be found using the machine learning techniques for agriculture land cover classifications. In the Canadian prairies, the cropping systems are based on simplified input-driven production of annual crops, which could affect land cover classification. To investigate the performance of machine learning techniques, the present research is conducted in the southern prairie region of Saskatchewan. The satellite images used for classification are from Sentinel-2, which is a publicly data from the European Space Agency. In total, 133,080 samples were analyzed using stratified random sampling, divided into training (70%) and test (30%) subsets. The accuracy is assessed by a variety of indicators. It is found that RF has the highest overall accuracy while the SVM has the lowest accuracy. The ANN has more advantages compared to others. Future agricultural land cover classifications can be based on the current research.
Book Synopsis Innovations in Remote Sensing and Photogrammetry by : Simon Jones
Download or read book Innovations in Remote Sensing and Photogrammetry written by Simon Jones and published by Springer Science & Business Media. This book was released on 2009-10-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing of our environment is becoming increasingly accessible and important in today’s society. This book aims to highlight some of the broad and multi-disciplinary applications, and emerging practices, that remote sensing and photogrammetric technologies lend themselves to. The papers have been selected from the 13th and 14th Australasian Remote Sensing and Photogrammetry Conferences given by experts in remote sensing, spatial analysis and photogrammetry from across the Asia Pacific region. They are presented here as a collection of peer reviewed papers covering research into areas such as data fusion techniques and their applications in environmental monitoring, synoptic monitoring and data processing, terrestrial and marine applications of remote sensing, and photogrammetry.
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 Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management by : Vijay P. Singh
Download or read book Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management written by Vijay P. Singh and published by Springer Nature. This book was released on 2023-01-01 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the problems in planning, building, and management strategies in the wake of application and expansion of remote sensing and GIS products in natural resources and infrastructure management. The book suggests proactive solutions to problems of natural resources and infrastructure management, providing alternatives for strategic planning, effective delivery, and growth perspectives. The uniqueness of the book is its broader spectrum of coverage with related interconnections and interdependences across science, engineering, and innovation. The book contains information that can be downscaled to the local level. Presenting a wide spectrum of viewpoints and approaches, the book is a collective of topics such as application to agriculture and forestry (land and landscape, agriculture, forestry management and deforestation), water resources and ecology (hydro-meteorological, climate diagnostics, and prognostics, water resources management, environment management, cross-scale ecology and resilience), urban management (urban planning, design, construction and operations of infrastructure, natural disasters, novel approaches to upgrade old infrastructure), hydro informatics, predictive and geospatial data analytics, synthesis, and management through the various processes, tools, and technologies.
Book Synopsis International Journal of Advanced Remote Sensing and GIS by : Cloud Publications
Download or read book International Journal of Advanced Remote Sensing and GIS written by Cloud Publications and published by Cloud Publications. This book was released on 2012-01-01 with total page 3465 pages. Available in PDF, EPUB and Kindle. Book excerpt: International Journal of Advanced Remote Sensing and GIS (IJARSG, ISSN 2320 – 0243) is an open-access peer-reviewed scholarly journal publishes original research papers, reviews, case study, case reports, and methodology articles in all aspects of Remote Sensing and GIS including associated fields. This Journal commits to working for quality and transparency in its publishing by following standard Publication Ethics and Policies.
Book Synopsis Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing by : Hyung-Sup Jung
Download or read book Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing written by Hyung-Sup Jung and published by MDPI. This book was released on 2019-09-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
Book Synopsis Land Cover Classification of Remotely Sensed Images by : S. Jenicka
Download or read book Land Cover Classification of Remotely Sensed Images written by S. Jenicka and published by Springer Nature. This book was released on 2021-03-10 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab source codes. The sixth chapter describes land cover classification procedure using multivariate (statistical and spectral) texture models and minimum distance classifier with Matlab source codes. A few performance metrics are also explained. The seventh chapter explains how texture based segmentation and land cover classification are performed using the hidden Markov model with relevant Matlab source codes. The eighth chapter gives an overview of spatial data analysis and other existing land cover classification methods. The ninth chapter addresses the research issues and challenges associated with land cover classification using textural approaches. This book is useful for undergraduates in Computer Science and Civil Engineering and postgraduates who plan to do research or project work in digital image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab source codes listed. In short, the book will be a valuable resource for growing academicians to gain expertise in their area of specialization and students who aim at gaining in-depth knowledge through practical implementations. The exercises given under texture based segmentation (excluding land cover classification exercises) can serve as lab exercises for the undergraduate students who learn texture based image processing.
