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Aerial Lidar Data Classification Using Machine Learning
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Book Synopsis Aerial Lidar Data Classification Using Machine Learning by : Darren M. Fitzpatrick
Download or read book Aerial Lidar Data Classification Using Machine Learning written by Darren M. Fitzpatrick and published by . This book was released on 2007 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis UAV Photogrammetry and Remote Sensing by : Fernando Carvajal-Ramírez
Download or read book UAV Photogrammetry and Remote Sensing written by Fernando Carvajal-Ramírez and published by MDPI. This book was released on 2021-09-06 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites. The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained. More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products. This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry.
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.
Download or read book Urban Informatics written by Wenzhong Shi and published by Springer Nature. This book was released on 2021-04-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Book Synopsis Remote Sensing Based Building Extraction by : Mohammad Awrangjeb
Download or read book Remote Sensing Based Building Extraction written by Mohammad Awrangjeb and published by MDPI. This book was released on 2020-03-27 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D
Book Synopsis Classifying Aerial Lidar Data with Support Vector Machines by : Edward Jay Kreps
Download or read book Classifying Aerial Lidar Data with Support Vector Machines written by Edward Jay Kreps and published by . This book was released on 2005 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :David Francis Maune Publisher :American Society for Photogrammetry & Remote Sensing ISBN 13 : Total Pages :688 pages Book Rating :4.:/5 (319 download)
Book Synopsis Digital Elevation Model Technologies and Applications by : David Francis Maune
Download or read book Digital Elevation Model Technologies and Applications written by David Francis Maune and published by American Society for Photogrammetry & Remote Sensing. This book was released on 2007 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: This DE Users Manual is designed to help potential users of digital elevation data understand and articulate their requirements in a way that their expectations are satisfied. if you have a dream that DEM's can help you do a better job, or you need to know more about DEM technologies and applications then this manual is for you.
Book Synopsis Classification of Wetlands and Deepwater Habitats of the United States by : U.S. Fish and Wildlife Service
Download or read book Classification of Wetlands and Deepwater Habitats of the United States written by U.S. Fish and Wildlife Service and published by . This book was released on 1979 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Artificial Intelligence and Machine Learning in Big Data Processing by : R. Geetha
Download or read book Advances in Artificial Intelligence and Machine Learning in Big Data Processing written by R. Geetha and published by Springer Nature. This book was released on with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis LiDAR Principles, Processing and Applications in Forest Ecology by : Qinghua Guo
Download or read book LiDAR Principles, Processing and Applications in Forest Ecology written by Qinghua Guo and published by Academic Press. This book was released on 2023-03-10 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: LiDAR Principles, Processing and Applications in Forest Ecology introduces the principles of LiDAR technology and explains how to collect and process LiDAR data from different platforms based on real-world experience. The book provides state-of the-art algorithms on how to extract forest parameters from LiDAR and explains how to use them in forest ecology. It gives an interdisciplinary view, from the perspective of remote sensing and forest ecology. Because LiDAR is still rapidly developing, researchers must use programming languages to understand and process LiDAR data instead of established software. In response, this book provides Python code examples and sample data. Sections give a brief history and introduce the principles of LiDAR, as well as three commonly seen LiDAR platforms. The book lays out step-by-step coverage of LiDAR data processing and forest structure parameter extraction, complete with Python examples. Given the increasing usefulness of LiDAR in forest ecology, this volume represents an important resource for researchers, students and forest managers to better understand LiDAR technology and its use in forest ecology across the world. The title contains over 15 years of research, as well as contributions from scientists across the world. - Presents LiDAR applications for forest ecology based in real-world experience - Lays out the principles of LiDAR technology in forest ecology in a systematic and clear way - Provides readers with state-of the-art algorithms on how to extract forest parameters from LiDAR - Offers Python code examples and sample data to assist researchers in understanding and processing LiDAR data - Contains over 15 years of research on LiDAR in forest ecology and contributions from scientists working in this field across the world
Book Synopsis Reconstruction and Analysis of 3D Scenes by : Martin Weinmann
Download or read book Reconstruction and Analysis of 3D Scenes written by Martin Weinmann and published by Springer. This book was released on 2016-03-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique work presents a detailed review of the processing and analysis of 3D point clouds. A fully automated framework is introduced, incorporating each aspect of a typical end-to-end processing workflow, from raw 3D point cloud data to semantic objects in the scene. For each of these components, the book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the-art techniques. Topics and features: reviews techniques for the acquisition of 3D point cloud data and for point quality assessment; explains the fundamental concepts for extracting features from 2D imagery and 3D point cloud data; proposes an original approach to keypoint-based point cloud registration; discusses the enrichment of 3D point clouds by additional information acquired with a thermal camera, and describes a new method for thermal 3D mapping; presents a novel framework for 3D scene analysis.
Book Synopsis Remote Sensing Platforms by : Alden P. Colvocoresses
Download or read book Remote Sensing Platforms written by Alden P. Colvocoresses and published by . This book was released on 1974 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Building Information Modeling for a Smart and Sustainable Urban Space by : Rafika Hajji
Download or read book Building Information Modeling for a Smart and Sustainable Urban Space written by Rafika Hajji and published by John Wiley & Sons. This book was released on 2021-12-21 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban spaces are being called upon to develop a capacity for resilience and sustainability in order to meet the major challenges they face. To achieve such a goal, a practical development framework must be implemented in order to take advantage of the technological innovations that characterize the field of construction and urban engineering. Today, multi-scale BIM is bringing about significant changes that are redefining the paradigms of urban management. It facilitates simulations of the sustainability of urban spaces with respect to several criteria; most notably relating to energy, the economy and the environment. Building Information Modeling for a Smart and Sustainable Urban Space proposes a theoretical and practical framework for implementing BIM models for the creation of sustainable and intelligent urban spaces. It addresses the issues of acquisition, modeling, interoperability, and BIM and GIS integration for the production of BIM models. Case studies are presented, providing a practical dimension that demonstrates the production process of the urban model and its contribution to multiscale simulations, particularly in real estate evaluation and urban renewal.
Book Synopsis LiDAR Remote Sensing and Applications by : Pinliang Dong
Download or read book LiDAR Remote Sensing and Applications written by Pinliang Dong and published by CRC Press. This book was released on 2017-12-12 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ideal for both undergraduate and graduate students in the fields of geography, forestry, ecology, geographic information science, remote sensing, and photogrammetric engineering, LiDAR Remote Sensing and Applications expertly joins LiDAR principles, data processing basics, applications, and hands-on practices in one comprehensive source. The LiDAR data within this book is collected from 27 areas in the United States, Brazil, Canada, Ghana, and Haiti and includes 183 figures created to introduce the concepts, methods, and applications in a clear context. It provides 11 step-by-step projects predominately based on Esri’s ArcGIS software to support seamless integration of LiDAR products and other GIS data. The first six projects are for basic LiDAR data visualization and processing and the other five cover more advanced topics: from mapping gaps in mangrove forests in Everglades National Park, Florida to generating trend surfaces for rock layers in Raplee Ridge, Utah. Features Offers a comprehensive overview of LiDAR technology with numerous applications in geography, forestry and earth science Gives necessary theoretical foundations from all pertinent subject matter areas Uses case studies and best practices to point readers to tools and resources Provides a synthesis of ongoing research in the area of LiDAR remote sensing technology Includes carefully selected illustrations and data from the authors' research projects Before every project in the book, a link is provided for users to download data
Book Synopsis Using Aerial Lidar Data to Segment and Model Buildings by : Oliver Wang
Download or read book Using Aerial Lidar Data to Segment and Model Buildings written by Oliver Wang and published by . This book was released on 2006 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Machine Learning and Image Analysis for GeoAI by : Saurabh Prasad
Download or read book Advances in Machine Learning and Image Analysis for GeoAI written by Saurabh Prasad and published by Elsevier. This book was released on 2024-04-26 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. - Covers the latest machine learning and signal processing techniques that can effectively leverage multimodal geospatial imagery at scale - Chapters cover a variety of algorithmic frameworks pertaining to GeoAI, including superresolution, self-supervised learning, data fusion, explainable AI, among others - Presents cutting-edge deep learning architectures optimized for a wide array of geospatial imagery
Book Synopsis Data Stream Mining & Processing by : Sergii Babichev
Download or read book Data Stream Mining & Processing written by Sergii Babichev and published by Springer Nature. This book was released on 2020-11-04 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the third International Conference on Data Stream and Mining and Processing, DSMP 2020, held in Lviv, Ukraine*, in August 2020. The 36 full papers presented in this volume were carefully reviewed and selected from 134 submissions. The papers are organized in topical sections of hybrid systems of computational intelligence; machine vision and pattern recognition; dynamic data mining & data stream mining; big data & data science using intelligent approaches. *The conference was held virtually due to the COVID-19 pandemic.