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An introduction to ocean remote sensing
\"Fully updated, with significant new coverage of advances in satellite oceanography and results from new satellite missions, the second edition of this popular textbook introduces students to how remote sensing works, how to understand observations from Earth-observing systems, and the observations' importance to physical and biological oceanography. It provides full explanations of radiative transfer, ocean surface properties, satellite orbits, instruments and methods, visible remote sensing of biogeochemical properties, infrared and microwave retrieval of sea surface temperature, sea surface salinity retrieval, passive microwave measurements, scatterometer wind retrieval, altimetry and SAR. This new edition now also includes descriptions of the online archives where data can be obtained, and where readers can obtain online tools for working with the data - enabling hands-on engagement with real-world observations. This is an ideal textbook for graduate and advanced undergraduate students taking courses in oceanography, remote sensing and environmental science, and provides a practical resource for researchers and Earth science professionals working with oceanographic satellite data\"-- Provided by publisher.
Book
Applicability of personal laser scanning in forestry inventory
Light Detection and Ranging (LiDAR) technology has been widely used in forestry surveys in the form of airborne laser scanning (ALS), terrestrial laser scanning (TLS), and mobile laser scanning (MLS). The acquisition of important basic tree parameters (e.g., diameter at breast height and tree position) in forest inventory did not solve the problem of low measurement efficiency or weak GNSS signal under the canopy. A personal laser scanning (PLS) device combined with SLAM technology provides an effective solution for forest inventory under complex conditions with its light weight and flexible mobility. This study proposes a new method for calculating the volume of a cylinder using point cloud data obtained by a PLS device by fitting to a polygonal cylinder to calculate the diameter of the trunk. The point cloud data of tree trunks of different thickness were modeled using different fitting methods. The rate of correct tree trunk detection was 93.3% and the total deviation of the estimations of tree diameter at breast height (DBH) was -1.26 cm. The root mean square errors (RMSEs) of the estimations of the extracted DBH and the tree position were 1.58 cm and 26 cm, respectively. The survey efficiency of the personal laser scanning (PLS) device was 30m2/min for each investigator, compared with 0.91m2/min for the field survey. The test demonstrated that the PLS device combined with the SLAM algorithm provides an efficient and convenient solution for forest inventory.
Journal Article
Geoinformation : remote sensing, photogrammetry, and geographic information systems
\"Preface In the 1990s, surveying and mapping underwent a transition from disciplineoriented technologies, such as geodesy, surveying, photogrammetry, and cartography, to the methodology-oriented integrated discipline of geoinformatics. This is based on Global Navigation Satellite System (GNSS), or GPS, positioning, remote sensing, digital photography for data acquisition, and a geographic information system (GIS) for data manipulation and data output. This book attempts to present the required basic background for remote sensing, digital photogrammetry, and GIS in the new geoinformatics concept in which the different methodologies must be combined. For remote sensing, the basic fundamentals are the properties of electromagnetic radiation and their interaction with matter. This radiation is received by sensors and platforms in an analogue or digital form, and is subject to image processing. In photogrammetry, the stereo concept is used for the location of information in 3D. With the advent of high-resolution satellite systems in stereo, the theory of analytical photogrammetry restituting 2D image information into 3D is of increasing importance, merging the remote sensing approach with that of photogrammetry. The result of the restitution is a direct input into geographic information systems in vector or raster form. The fundamentals of these are described in detail, with an emphasis on global, regional, and local applications. In the context of data integration, a short introduction to the GPS satellite positioning system is provided. This book will appeal to a wide range of readers from advanced undergraduates to all professionals in the growing field of geoinformation\"-- Provided by publisher.
Book
All-solid-state spatial light modulator with independent phase and amplitude control for three-dimensional LiDAR applications
Spatial light modulators are essential optical elements in applications that require the ability to regulate the amplitude, phase and polarization of light, such as digital holography, optical communications and biomedical imaging. With the push towards miniaturization of optical components, static metasurfaces are used as competent alternatives. These evolved to active metasurfaces in which light-wavefront manipulation can be done in a time-dependent fashion. The active metasurfaces reported so far, however, still show incomplete phase modulation (below 360°). Here we present an all-solid-state, electrically tunable and reflective metasurface array that can generate a specific phase or a continuous sweep between 0 and 360° at an estimated rate of 5.4 MHz while independently adjusting the amplitude. The metasurface features 550 individually addressable nanoresonators in a 250 × 250 μm
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area with no micromechanical elements or liquid crystals. A key feature of our design is the presence of two independent control parameters (top and bottom gate voltages) in each nanoresonator, which are used to adjust the real and imaginary parts of the reflection coefficient independently. To demonstrate this array’s use in light detection and ranging, we performed a three-dimensional depth scan of an emulated street scene that consisted of a model car and a human figure up to a distance of 4.7 m.
By controlling two voltage gates separately from one another, a spatial light modulator has been made that can continuously vary the phase of 360 degrees while independently adjusting the amplitude.
Journal Article
Environmental remote sensing and systems analysis
\"Preface: In the last few decades, rapid urbanization and industrialization have altered the priority of environmental protection and restoration of air, soil, and water quality many times. Yet it is recognized that the sustainable management of human society is necessary at all phases of impact from the interactions between energy, environment, ecology, public health, and socioeconomic paradigms. The multidisciplinary nature of this concern for sustainability is truly a challenging task that requires employing a systems analysis approach. Such a systems analysis approach links several disciplinary areas with each other to promote the concept of sustainable management. Just as a sophisticated piece of music involves many different instruments played in unison, systems analysis requires a holistic viewpoint and a plethora of tools in sensing, monitoring, and modeling that have to be woven together to explore the state and function of air, water, and land resources at all levels. With the aid of systems analysis, this comprehensive collection includes a variety of research work that results from years of experience and that reflects the contemporary advances of remote sensing technologies. This unique publication presents and applies the most recent synergy of remote sensing technologies that will advance the overall understanding of the sensitivity of key environmental quality issues in relation to human perturbations. These perturbations can be caused by collective or individual impacts of economic development and globalization, population growth and migration, and climate change on atmospheric, terrestrial, and aquatic environmental systems\"-- Provided by publisher.
Book
Forest fire detection system using wireless sensor networks and machine learning
Forest fires have become a major threat around the world, causing many negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are some of the consequences of such destruction. Interestingly, a higher percentage of forest fires occur due to human activities. Therefore, to minimize the destruction caused by forest fires, there is a need to detect forest fires at their initial stage. This paper proposes a system and methodology that can be used to detect forest fires at the initial stage using a wireless sensor network. Furthermore, to acquire more accurate fire detection, a machine learning regression model is proposed. Because of the primary power supply provided by rechargeable batteries with a secondary solar power supply, a solution is readily implementable as a standalone system for prolonged periods. Moreover, in-depth attention is given to sensor node design and node placement requirements in harsh forest environments and to minimize the damage and harmful effects caused by wild animals, weather conditions, etc. to the system. Numerous trials conducted in real tropical forest sites found that the proposed system is effective in alerting forest fires with lower latency than the existing systems.
Journal Article
GIS fundamentals
\"Aimed at readers with a knowledge of Geographic Information Systems (GIS) but no formal training in computer science, this book provides a clear and accessible introduction to how GIS store and process spatial data. This updated edition includes two new chapters on databases and future developments, substantial additional material on raster imagery, and revisions throughout that incorporate up-to-date applications such as GPS on mobile devices and Internet-based services. The chapter on future technologies includes discussions of 3D GIS, handling time in GIS, spatial SQL, and handling imprecise geographies\"-- Provided by publisher.
Book
Distributed Fiber-Optic Sensors for Vibration Detection
Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.
Journal Article
Regularization, optimization, kernels, and support vector machines
\"Obtaining reliable models from given data is becoming increasingly important in a wide range of different applications fields including the prediction of energy consumption, complex networks, environmental modelling, biomedicine, bioinformatics, finance, process modelling, image and signal processing, brain-computer interfaces, and others. In data-driven modelling approaches one has witnessed considerable progress in the understanding of estimating flexible nonlinear models, learning and generalization aspects, optimization methods, and structured modelling. One area of high impact both in theory and applications is kernel methods and support vector machines. Optimization problems, learning, and representations of models are key ingredients in these methods. On the other hand, considerable progress has also been made on regularization of parametric models, including methods for compressed sensing and sparsity, where convex optimization plays an important role. At the international workshop ROKS 2013 Leuven, 1 July 8-10, 2013, researchers from diverse fields were meeting on the theory and applications of regularization, optimization, kernels, and support vector machines. At this occasion the present book has been edited as a follow-up to this event, with a variety of invited contributions from presenters and scientific committee members. It is a collection of recent progress and advanced contributions on these topics, addressing methods including ...\"-- Provided by publisher.
Book
Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery
Recent technological advances in remote sensing sensors and platforms, such as high-resolution satellite imagers or unmanned aerial vehicles (UAV), facilitate the availability of fine-grained earth observation data. Such data reveal vegetation canopies in high spatial detail. Efficient methods are needed to fully harness this unpreceded source of information for vegetation mapping. Deep learning algorithms such as Convolutional Neural Networks (CNN) are currently paving new avenues in the field of image analysis and computer vision. Using multiple datasets, we test a CNN-based segmentation approach (U-net) in combination with training data directly derived from visual interpretation of UAV-based high-resolution RGB imagery for fine-grained mapping of vegetation species and communities. We demonstrate that this approach indeed accurately segments and maps vegetation species and communities (at least 84% accuracy). The fact that we only used RGB imagery suggests that plant identification at very high spatial resolutions is facilitated through spatial patterns rather than spectral information. Accordingly, the presented approach is compatible with low-cost UAV systems that are easy to operate and thus applicable to a wide range of users.
Journal Article