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Comparative Performance Of Classification And Stratification Methods In Remote Sensing And Forest Applications
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Book Synopsis Comparative Performance of Classification and Stratification Methods in Remote Sensing and Forest Applications by : Fredrik Norström
Download or read book Comparative Performance of Classification and Stratification Methods in Remote Sensing and Forest Applications written by Fredrik Norström and published by . This book was released on 2003 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Sampling Methods, Remote Sensing and GIS Multiresource Forest Inventory by : Michael Köhl
Download or read book Sampling Methods, Remote Sensing and GIS Multiresource Forest Inventory written by Michael Köhl and published by Springer Science & Business Media. This book was released on 2006-10-19 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art of forest resources assessments and monitoring. It provides links to practical applications of forest and natural resource assessment programs. It offers an overview of current forest inventory systems and discusses forest mensuration, sampling techniques, remote sensing applications, geographic and forest information systems, and multi-resource forest inventory. Attention is also given to the quantification of non-wood goods and services.
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:
Download or read book Earth Resources written by and published by . This book was released on 1976 with total page 910 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of Classification Techniques in Environmental Applications of Remote Sensing by :
Download or read book A Comparison of Classification Techniques in Environmental Applications of Remote Sensing written by and published by . This book was released on 1998 with total page 0 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.
Download or read book General Technical Report NC. written by and published by . This book was released on 1981 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Factors Influencing the Accuracy of Remote Sensing Classifications by :
Download or read book Factors Influencing the Accuracy of Remote Sensing Classifications written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Within last 20 years, a number of methods have been employed for classifying remote sensing data, including parametric methods (e.g. the maximum likelihood classifier) and non-parametric classifiers (such as neural network classifiers). Each of these classification algorithms has some specific problems which limits its use. This research studies some alternative classification methods for land cover classification and compares their performance with the well established classification methods. The areas selected for this study are located near Littleport (Ely), in East Anglia, UK and in La Mancha region of Spain. Images in the optical bands of the Landsat ETM+ for year 2000 and InSAR data from May to September of 1996 for UK area, DAIS hyperspectral data and Landsat ETM+ for year 2000 for Spain area are used for this study. In addition, field data for the year 1996 were collected from farmers and for year 2000 were collected by field visits to both areas in the UK and Spain to generate the ground reference data set. The research was carried out in three main stages. The overall aim of this study is to assess the relative performance of four approaches to classification in remote sensing - the maximum likelihood, artificial neural net, decision tree and support vector machine methods and to examine factors which affect their performance in term of overall classification accuracy. Firstly, this research studies the behaviour of decision tree and support vector machine classifiers for land cover classification using ETM+ (UK) data. This stage discusses some factors affecting classification accuracy of a decision tree classifier, and also compares the performance of the decision tree with that of the maximum likelihood and neural network classifiers. The use of SVM requires the user to set the values of some parameters, such as type of kernel, kernel parameters, and multi-class methods as these parameters can significantly affect the accuracy of the resulting classification. This stage involves studying the effects of varying the various user defined parameters and noting their effect on classification accuracy. It is concluded that SVM perform far better than decision tree, maximum likelihood and neural network classifiers for this type of study. The second stage involves applying the decision tree, maximum likelihood and neural network classifiers to InSAR coherence and intensity data and evaluating the utility of this type of data for land cover classification studies. Finally, the last stage involves studying the response of SVMs, decision trees, maximum likelihood and neural classifier to different training data sizes, number of features, sampling plan, and the scale of the data used. The conclusion from the experiments presented in this stage is that the SVMs are unaffected by the Hughes phenomenon, and perform far better than the other classifiers in all cases. The performance of decision tree classifier based feature selection is found to be quite good in comparison with MNF transform. This study indicates that good classification performance depends on various parameters such as data type, scale of data, training sample size and type of classification method employed.
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 Proceedings, 32nd International Symposium on Remote Sensing of Environment by :
Download or read book Proceedings, 32nd International Symposium on Remote Sensing of Environment written by and published by . This book was released on 2007 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of Pixel-based and Object-oriented Image Classification Techniques for Forest Cover Type Determination in East Texas by : Jason Clark Raines
Download or read book A Comparison of Pixel-based and Object-oriented Image Classification Techniques for Forest Cover Type Determination in East Texas written by Jason Clark Raines and published by . This book was released on 2008 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to qualify and quantify the forest resources of east Texas through remote sensing techniques is a timely, cost-efficient manner to assist resource managers and policy-makers in planning and decision-making. Improved image classification techniques would reduce costs and timelines of resource inventory and analysis as well as increase the accuracy of cover type maps produced from medium resolution satellite imagery. Object-oriented image classification techniques take advantage of the spatial autocorrelation innately present in remotely sensed data, while pixel-based classifiers focus solely on the spectral signature of each pixel. Leaf-off Landsat TM data were used to classify land cover in east Texas into four classes. Object-oriented classification techniques were compared with traditional pixel-based classification methods. Accuracy assessment was conducted to generate error matrices for each method tested. Statistical tests showed supervised object-oriented classification using Feature Analyst(TM) performed significantly poorer than all other methods tested except unsupervised pixel-based classification.
Book Synopsis Comparing the Cost Effectiveness of Conventional Ground Sampling and Remote Sensing Techniques for Mapping Forest Vegetation by : James. L. Lowe
Download or read book Comparing the Cost Effectiveness of Conventional Ground Sampling and Remote Sensing Techniques for Mapping Forest Vegetation written by James. L. Lowe and published by . This book was released on 1995 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 2016-04-19 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publishing of the first edition of Classification Methods for Remotely Sensed Data in 2001, the field of pattern recognition has expanded in many new directions that make use of new technologies to capture data and more powerful computers to mine and process it. What seemed visionary but a decade ago is now being put to use and refined in
Book Synopsis Proceedings of the ... International Symposium on Remote Sensing of Environment by :
Download or read book Proceedings of the ... International Symposium on Remote Sensing of Environment written by and published by . This book was released on 2007 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Earth Resources written by and published by . This book was released on 1982 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International Aerospace Abstracts (IAA).
Book Synopsis Proceedings of the Fourth Annual Forest Inventory and Analysis Symposium by :
Download or read book Proceedings of the Fourth Annual Forest Inventory and Analysis Symposium written by and published by . This book was released on 2005 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
