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Author : James Patrick Lacy
Publisher :
ISBN 13 :
Total Pages : 300 pages
Book Rating : 4.:/5 (89 download)
Download or read book An Artificial Neural Network for Large Scale Wetlands Mapping written by James Patrick Lacy and published by . This book was released on 1994 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Masoud Mahdianpari
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (132 download)
Download or read book Advanced Machine Learning Algorithms for Canadian Wetland Mapping Using Polarimetric Synthetic Aperture Radar (PolSAR) and Optical Imagery written by Masoud Mahdianpari and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wetlands are complex land cover ecosystems that represent a wide range of biophysical conditions. They are one of the most productive ecosystems and provide several important environmental functionalities. As such, wetland mapping and monitoring using cost- and time-efficient approaches are of great interest for sustainable management and resource assessment. In this regard, satellite remote sensing data are greatly beneficial, as they capture a synoptic and multi-temporal view of landscapes. The ability to extract useful information from satellite imagery greatly affects the accuracy and reliability of the final products. This is of particular concern for mapping complex land cover ecosystems, such as wetlands, where complex, heterogeneous, and fragmented landscape results in similar backscatter/spectral signatures of land cover classes in satellite images. Accordingly, the overarching purpose of this thesis is to contribute to existing methodologies of wetland classification by proposing and developing several new techniques based on advanced remote sensing tools and optical and Synthetic Aperture Radar (SAR) imagery. Specifically, the importance of employing an efficient speckle reduction method for polarimetric SAR (PolSAR) image processing is discussed and a new speckle reduction technique is proposed. Two novel techniques are also introduced for improving the accuracy of wetland classification. In particular, a new hierarchical classification algorithm using multi-frequency SAR data is proposed that discriminates wetland classes in three steps depending on their complexity and similarity. The experimental results reveal that the proposed method is advantageous for mapping complex land cover ecosystems compared to single stream classification approaches, which have been extensively used in the literature. Furthermore, a new feature weighting approach is proposed based on the statistical and physical characteristics of PolSAR data to improve the discrimination capability of input features prior to incorporating them into the classification scheme. This study also demonstrates the transferability of existing classification algorithms, which have been developed based on RADARSAT-2 imagery, to compact polarimetry SAR data that will be collected by the upcoming RADARSAT Constellation Mission (RCM). The capability of several well-known deep Convolutional Neural Network (CNN) architectures currently employed in computer vision is first introduced in this thesis for classification of wetland complexes using multispectral remote sensing data. Finally, this research results in the first provincial-scale wetland inventory maps of Newfoundland and Labrador using the Google Earth Engine (GEE) cloud computing resources and open access Earth Observation (EO) collected by the Copernicus Sentinel missions. Overall, the methodologies proposed in this thesis address fundamental limitations/challenges of wetland mapping using remote sensing data, which have been ignored in the literature. These challenges include the backscattering/spectrally similar signature of wetland classes, insufficient classification accuracy of wetland classes, and limitations of wetland mapping on large scales. In addition to the capabilities of the proposed methods for mapping wetland complexes, the use of these developed techniques for classifying other complex land cover types beyond wetlands, such as sea ice and crop ecosystems, offers a potential avenue for further research.
Author : U.S. Fish and Wildlife Service
Publisher :
ISBN 13 :
Total Pages : 110 pages
Book Rating : 4.:/5 (319 download)
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:
Author : Ralph W. Tiner
Publisher : CRC Press
ISBN 13 : 1439853703
Total Pages : 631 pages
Book Rating : 4.4/5 (398 download)
Download or read book Wetland Indicators written by Ralph W. Tiner and published by CRC Press. This book was released on 2016-12-19 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the current concept of wetland and methods for identifying, describing, classifying, and delineating wetlands in the United States with Wetland Indicators - capturing the current state of science's role in wetland recognition and mapping. Environmental scientists and others involved with wetland regulations can strengthen their knowledge about wetlands, and the use of various indicators, to support their decisions on difficult wetland determinations. Professor Tiner primarily focuses on plants, soils, and other signs of wetland hydrology in the soil, or on the surface of wetlands in his discussion of Wetland Indicators. Practicing - and aspiring - wetland delineators alike will appreciate Wetland Indicators' critical insight into the development and significance of hydrophytic vegetation, hydric soils, and other factors. Features Color images throughout illustrate wetland indicators. Incorporates analysis and coverage of the latest Army Corps of Engineers delineation manual. Provides over 60 tables, including extensive tables of U.S. wetland plant communities and examples for determining hydrophytic vegetation.
Author : Mohammad Rezaee
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)
Download or read book Developing a Deep Learning Network Suitable for Automated Classification of Heterogeneous Land Covers in High Spatial Resolution Imagery written by Mohammad Rezaee and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The incorporation of spatial and spectral information within multispectral satellite images is the key for accurate land cover mapping, specifically for discrimination of heterogeneous land covers. Traditional methods only use basic features, either spatial features (e.g. edges or gradients) or spectral features (e.g. mean value of Digital Numbers or Normalized Difference Vegetation Index (NDVI)) for land cover classification. These features are called low level features and are generated manually (through so-called feature engineering). Since feature engineering is manual, the design of proper features is time-consuming, only low-level features in the information hierarchy can usually be extracted, and the feature extraction is application-based (i.e., different applications need to extract different features). In contrast to traditional land-cover classification methods, Deep Learning (DL),adapting the artificial neural network (ANN) into a deep structure, can automatically generate the necessary high-level features for improving classification without being limited to low-level features. The higher-level features (e.g. complex shapes and textures) can be generated by combining low-level features through different level of processing. However, despite recent advances of DL for various computer vision tasks, especially for convolutional neural networks (CNNs) models, the potential of using DL for land-cover classification of multispectral remote sensing (RS) images have not yet been thoroughly explored. The main reason is that a DL network needs to be trained using a huge number of images from a large scale of datasets. Such training datasets are not usually available in RS. The only few available training datasets are either for object detection in an urban area, or for scene labeling. In addition, the available datasets are mostly used for land-cover classification based on spatial features. Therefore, the incorporation of the spectral and spatial features has not been studied comprehensively yet. This PhD research aims to mitigate challenges in using DL for RS land cover mapping/object detection by (1) decreasing the dependency of DL to the large training datasets, (2) adapting and improving the efficiency and accuracy of deep CNNs for heterogeneous classification, (3) incorporating all of the spectral bands in satellite multispectral images into the processing, and (4) designing a specific CNN network that can be used for a faster and more accurate detection of heterogeneous land covers with fewer amount of training datasets. The new developments are evaluated in two case studies, i.e. wetland detection and tree species detection, where high resolution multispectral satellite images are used. Such land-cover classifications are considered as challenging tasks in the literature. The results show that our new solution works reliably under a wide variety of conditions. Furthermore, we are releasing the two large-scale wetland and tree species detection datasets to the public in order to facilitate future research, and to compare with other methods.
Author : Saurabh Prasad
Publisher : Elsevier
ISBN 13 : 044319078X
Total Pages : 366 pages
Book Rating : 4.4/5 (431 download)
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 2024-06-01 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 geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter
Author : Ralph W. Tiner
Publisher : CRC Press
ISBN 13 : 1482237385
Total Pages : 574 pages
Book Rating : 4.4/5 (822 download)
Download or read book Remote Sensing of Wetlands written by Ralph W. Tiner and published by CRC Press. This book was released on 2015-03-23 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effectively Manage Wetland Resources Using the Best Available Remote Sensing TechniquesUtilizing top scientists in the wetland classification and mapping field, Remote Sensing of Wetlands: Applications and Advances covers the rapidly changing landscape of wetlands and describes the latest advances in remote sensing that have taken place over the pa
Author :
Publisher :
ISBN 13 : 9780662157878
Total Pages : 18 pages
Book Rating : 4.1/5 (578 download)
Download or read book The Canadian Wetland Classification System written by and published by . This book was released on 1987 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: A classification system for Canadian wetlands based on the collective expertise and research of scientists across Canada. The system is provisional and subject to revision in future editions.
Author : Aboul-Ella Hassanien
Publisher : Springer Nature
ISBN 13 : 3030442896
Total Pages : 880 pages
Book Rating : 4.0/5 (34 download)
Download or read book Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-03-23 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.
Author : Prem C. Pandey
Publisher : John Wiley & Sons
ISBN 13 : 1119616026
Total Pages : 528 pages
Book Rating : 4.1/5 (196 download)
Download or read book Advances in Remote Sensing for Natural Resource Monitoring written by Prem C. Pandey and published by John Wiley & Sons. This book was released on 2021-01-18 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable management of natural resources is an urgent need, given the changing climatic conditions of Earth systems. The ability to monitor natural resources precisely and accurately is increasingly important. New and advanced remote sensing tools and techniques are continually being developed to monitor and manage natural resources in an effective way. Remote sensing technology uses electromagnetic sensors to record, measure and monitor even small variations in natural resources. The addition of new remote sensing datasets, processing techniques and software makes remote sensing an exact and cost-effective tool and technology for natural resource monitoring and management. Advances in Remote Sensing for Natural Resources Monitoring provides a detailed overview of the potential applications of advanced satellite data in natural resource monitoring. The book determines how environmental and - ecological knowledge and satellite-based information can be effectively combined to address a wide array of current natural resource management needs. Each chapter covers different aspects of remote sensing approach to monitor the natural resources effectively, to provide a platform for decision and policy. This important work: Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring Includes new and emerging approaches for resource monitoring with case studies Covers different aspects of forest, water, soil- land resources, and agriculture Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies Showcases disaster studies s
Author : Shalini Dhyani
Publisher : Springer Nature
ISBN 13 : 9811547122
Total Pages : 474 pages
Book Rating : 4.8/5 (115 download)
Download or read book Nature-based Solutions for Resilient Ecosystems and Societies written by Shalini Dhyani and published by Springer Nature. This book was released on 2020-07-07 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few decades, the frequency and severity of natural and human-induced disasters have increased across Asia. These disasters lead to substantial loss of life, livelihoods and community assets, which not only threatens the pace of socio-economic development, but also undo hard-earned gains. Extreme events and disasters such as floods, droughts, heat, fire, cyclones and tidal surges are known to be exacerbated by environmental changes including climate change, land-use changes and natural resource degradation. Increasing climate variability and multi-dimensional vulnerabilities have severely affected the social, ecological and economic capacities of the people in the region who are, economically speaking, those with the least capacity to adapt. Climatic and other environmental hazards and anthropogenic risks, coupled with weak and wavering capacities, severely impact the ecosystems and Nature’s Contributions to People (NCP) and, thereby, to human well-being. Long-term resilience building through disaster risk reduction and integrated adaptive climate planning, therefore, has become a key priority for scientists and policymakers alike. Nature-based Solutions (NbS) is a cost-effective approach that utilizes ecosystem and biodiversity services for disaster risk reduction and climate change adaptation, while also providing a range of co-benefits like sustainable livelihoods and food, water and energy security. This book discusses the concept of Nature-based Solutions (NbS) – both as a science and as art – and elaborates on how it can be applied to develop healthy and resilient ecosystems locally, nationally, regionally and globally. The book covers illustrative methods and tools adopted for applying NbS in different countries. The authors discuss NbS applications and challenges, research trends and future insights that have wider regional and global relevance. The aspects covered include: landscape restoration, ecosystem-based adaptation, ecosystem-based disaster risk reduction, ecological restoration, ecosystem-based protected areas management, green infrastructure development, nature-friendly infrastructure development in various ecosystem types, agro-climatic zones and watersheds. The book offers insights into understanding the sustainable development goals (SDGs) at the grass roots level and can help indigenous and local communities harness ecosystem services to help achieve them. It offers a unique, essential resource for researchers, students, corporations, administrators and policymakers working in the fields of the environment, geography, development, policy planning, the natural sciences, life sciences, agriculture, health, climate change and disaster studies.
Author : Timothy A Warner
Publisher : SAGE
ISBN 13 : 1446246140
Total Pages : 538 pages
Book Rating : 4.4/5 (462 download)
Download or read book The SAGE Handbook of Remote Sensing written by Timothy A Warner and published by SAGE. This book was released on 2009-06-18 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′A magnificent achievement. A who′s who of contemporary remote sensing have produced an engaging, wide-ranging and scholarly review of the field in just one volume′ - Professor Paul Curran, Vice-Chancellor, Bournemouth University Remote Sensing acquires and interprets small or large-scale data about the Earth from a distance. Using a wide range of spatial, spectral, temporal, and radiometric scales Remote Sensing is a large and diverse field for which this Handbook will be the key research reference. Organized in four key sections: • Interactions of Electromagnetic Radiation with the Terrestrial Environment: chapters on Visible, Near-IR and Shortwave IR; Middle IR (3-5 micrometers); Thermal IR ; Microwave • Digital sensors and Image Characteristics: chapters on Sensor Technology; Coarse Spatial Resolution Optical Sensors ; Medium Spatial Resolution Optical Sensors; Fine Spatial Resolution Optical Sensors; Video Imaging and Multispectral Digital Photography; Hyperspectral Sensors; Radar and Passive Microwave Sensors; Lidar • Remote Sensing Analysis - Design and Implementation: chapters on Image Pre-Processing; Ground Data Collection; Integration with GIS; Quantitative Models in Remote Sensing; Validation and accuracy assessment; • Remote Sensing Analysis - Applications: LITHOSPHERIC SCIENCES: chapters on Topography; Geology; Soils; PLANT SCIENCES: Vegetation; Agriculture; HYDROSPHERIC and CRYSOPHERIC SCIENCES: Hydrosphere: Fresh and Ocean Water; Cryosphere; GLOBAL CHANGE AND HUMAN ENVIRONMENTS: Earth Systems; Human Environments & Links to the Social Sciences; Real Time Monitoring Systems and Disaster Management; Land Cover Change Illustrated throughout, an essential resource for the analysis of remotely sensed data, the SAGE Handbook of Remote Sensing provides researchers with a definitive statement of the core concepts and methodologies in the discipline.
Author : Monica Rivas Casado
Publisher : MDPI
ISBN 13 : 3039212052
Total Pages : 132 pages
Book Rating : 4.0/5 (392 download)
Download or read book Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers written by Monica Rivas Casado and published by MDPI. This book was released on 2019-08-22 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, there has been an increase in the development of strategies for water ecosystem mapping and monitoring. Overall, this is primarily due to legislative efforts to improve the quality of water bodies and oceans. Remote sensing has played a key role in the development of such approaches—from the use of drones for vegetation mapping to autonomous vessels for water quality monitoring. Within the specific context of vegetation characterization, the wide range of available observations—from satellite imagery to high-resolution drone aerial imagery—has enabled the development of monitoring and mapping strategies at multiple scales (e.g., micro- and mesoscales). This Special Issue, entitled “Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers”, collates recent advances in remote sensing-based methods applied to ocean, river, and lake vegetation characterization, including seaweed, kelp, submerged and emergent vegetation, and floating-leaf and free-floating plants. A total of six manuscripts have been compiled in this Special Issue, ranging from area mapping substrates in riverine environments to the identification of macroalgae in marine environments. The work presented leverages current state-of-the-art methods for aquatic vegetation monitoring and will spark further research within this field.
Author : Albertina C. Dickman
Publisher :
ISBN 13 :
Total Pages : 234 pages
Book Rating : 4.:/5 (19 download)
Download or read book Large Scale Mapping of Wetlands in Amherst, Massachusetts written by Albertina C. Dickman and published by . This book was released on 1988 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Prem C. Pandey
Publisher : John Wiley & Sons
ISBN 13 : 1119615976
Total Pages : 528 pages
Book Rating : 4.1/5 (196 download)
Download or read book Advances in Remote Sensing for Natural Resource Monitoring written by Prem C. Pandey and published by John Wiley & Sons. This book was released on 2021-01-26 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable management of natural resources is an urgent need, given the changing climatic conditions of Earth systems. The ability to monitor natural resources precisely and accurately is increasingly important. New and advanced remote sensing tools and techniques are continually being developed to monitor and manage natural resources in an effective way. Remote sensing technology uses electromagnetic sensors to record, measure and monitor even small variations in natural resources. The addition of new remote sensing datasets, processing techniques and software makes remote sensing an exact and cost-effective tool and technology for natural resource monitoring and management. Advances in Remote Sensing for Natural Resources Monitoring provides a detailed overview of the potential applications of advanced satellite data in natural resource monitoring. The book determines how environmental and - ecological knowledge and satellite-based information can be effectively combined to address a wide array of current natural resource management needs. Each chapter covers different aspects of remote sensing approach to monitor the natural resources effectively, to provide a platform for decision and policy. This important work: Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring Includes new and emerging approaches for resource monitoring with case studies Covers different aspects of forest, water, soil- land resources, and agriculture Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies Showcases disaster studies such as floods, tsunami, showing where remote sensing technologies have been used This edited book is the first volume of the book series Advances in Remote Sensing for Earth Observation.
Author : Prashant K. Srivastava
Publisher : Elsevier
ISBN 13 : 0128235942
Total Pages : 482 pages
Book Rating : 4.1/5 (282 download)
Download or read book Radar Remote Sensing written by Prashant K. Srivastava and published by Elsevier. This book was released on 2022-08-27 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar Remote Sensing: Applications and Challenges advances the scientific understanding, development, and application of radar remote sensing using monostatic, bistatic and multi-static radar geometry. This multidisciplinary reference pulls together a collection of the recent developments and applications of radar remote sensing using different radar geometry and platforms at local, regional and global levels. Radar Remote Sensing is for researchers and practitioners with earth and environmental and meteorological sciences, who are interested in radar remote sensing in ground based scatterometer and SAR systems; air borne scatterometer and SAR systems; space borne scatterometer and SAR systems. Covers monostatic, bistatic and multi-static radar geometry Features case studies, including experimental investigations, for practical application Includes geophysical, oceanographical, and meteorological Synthetic Aperture Radar data
Author : Xin Hong
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)
Download or read book A Convolutional Neural Network for Detecting and Mapping Built Environment at Neighborhood Scale written by Xin Hong and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing interest in the connection between built environment and health has encouraged the development of new tools for describing health-related built environment. With the development of deep learning, scholars have been exploring the applications of convolutional neural networks (CNNs) to the field of remote sensing. Nevertheless, applying deep learning in remote sensing is still a young field. Instead of treating deep learning as a "black-box" technology, this study embraced deep learning as the key to solving large-scale and high-resolution remote sensing scenes. This study applied U-net, an encoder-decoder CNN architecture, for detecting greenness at street level. A new operational definition of the concept of neighborhoods: sidewalk-homogenous neighborhoods, which corresponds to different economic levels and habits of using sidewalks, was also proposed as a novel and practical delineation of neighborhood boundaries. As a pilot study, this study tested that deep learning is a sufficient method for detecting built environment on high volume unmanned aerial vehicle (UAV) images. The sidewalk-homogenous neighborhoods is a reasonable spatial scale that can help to reveal the disparities in sidewalk environments between neighborhoods.
