Very High Resolution (VHR) Satellite Imagery - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Very High Resolution (VHR) Satellite Imagery write by Francisco Eugenio. This book was released on 2019-11-06. Very High Resolution (VHR) Satellite Imagery available in PDF, EPUB and Kindle. 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.
Very High Resolution (VHR) Satellite Imagery: Processing and Applications
Very High Resolution (VHR) Satellite Imagery: Processing and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Very High Resolution (VHR) Satellite Imagery: Processing and Applications write by Javier Marcello. This book was released on 2019. Very High Resolution (VHR) Satellite Imagery: Processing and Applications available in PDF, EPUB and Kindle. 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.
Urban Remote Sensing
Urban Remote Sensing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Urban Remote Sensing write by Qihao Weng. This book was released on 2018-02-20. Urban Remote Sensing available in PDF, EPUB and Kindle. 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
Multispectral Satellite Image Understanding
Multispectral Satellite Image Understanding - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multispectral Satellite Image Understanding write by Cem Ünsalan. This book was released on 2011-05-18. Multispectral Satellite Image Understanding available in PDF, EPUB and Kindle. 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.
Understanding High Resolution Aerial Imagery Using Computer Vision Techniques
Understanding High Resolution Aerial Imagery Using Computer Vision Techniques - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Understanding High Resolution Aerial Imagery Using Computer Vision Techniques write by Fan Wang. This book was released on 2017. Understanding High Resolution Aerial Imagery Using Computer Vision Techniques available in PDF, EPUB and Kindle. "Computer vision can make important contributions to the analysis of remote sensing satellite or aerial imagery. However, the resolution of early satellite imagery was not sufficient to provide useful spatial features. The situation is changing with the advent of very-high-spatial-resolution (VHR) imaging sensors. This change makes it possible to use computer vision techniques to perform analysis of man-made structures. Meanwhile, the development of multi-view imaging techniques allows the generation of accurate point clouds as ancillary knowledge. This dissertation aims at developing computer vision and machine learning algorithms for high resolution aerial imagery analysis in the context of application problems including debris detection, building detection and roof condition assessment. High resolution aerial imagery and point clouds were provided by Pictometry International for this study. Debris detection after natural disasters such as tornadoes, hurricanes or tsunamis, is needed for effective debris removal and allocation of limited resources. Significant advances in aerial image acquisition have greatly enabled the possibilities for rapid and automated detection of debris. In this dissertation, a robust debris detection algorithm is proposed. Large scale aerial images are partitioned into homogeneous regions by interactive segmentation. Debris areas are identified based on extracted texture features. Robust building detection is another important part of high resolution aerial imagery understanding. This dissertation develops a 3D scene classification algorithm for building detection using point clouds derived from multi-view imagery. Point clouds are divided into point clusters using Euclidean clustering. Individual point clusters are identified based on extracted spectral and 3D structural features. The inspection of roof condition is an important step in damage claim processing in the insurance industry. Automated roof condition assessment from remotely sensed images is proposed in this dissertation. Initially, texture classification and a bag-of-words model were applied to assess the roof condition using features derived from the whole rooftop. However, considering the complexity of residential rooftop, a more sophisticated method is proposed to divide the task into two stages: 1) roof segmentation, followed by 2) classification of segmented roof regions. Deep learning techniques are investigated for both segmentation and classification. A deep learned feature is proposed and applied in a region merging segmentation algorithm. A fine-tuned deep network is adopted for roof segment classification and found to achieve higher accuracy than traditional methods using hand-crafted features. Contributions of this study include the development of algorithms for debris detection using 2D images and building detection using 3D point clouds. For roof condition assessment, the solutions to this problem are explored in two directions: features derived from the whole rooftop and features extracted from each roof segments. Through our research, roof segmentation followed by segments classification was found to be a more promising method and the workflow processing developed and tested. Deep learning techniques are also investigated for both roof segmentation and segments classification. More unsupervised feature extraction techniques using deep learning can be explored in future work."--Abstract.
