318 research outputs found

    Guidance note on the application of coastal monitoring for small island developing states : Part of the NOC-led project “Climate Change Impact Assessment: Ocean Modelling and Monitoring for the Caribbean CME states”, 2017-2020; under the Commonwealth Marine Economies (CME) Programme in the Caribbean.

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    Small Island Developing States (SIDS) are a diverse group of 51 countries and territories vulnerable to human-induced climate change, due to factors including their small size, large exclusive economic zones and limited resources. They generally have insufficient critical mass in scientific research and technical capability to carry out coastal monitoring campaigns from scratch and limited access to data. This guidance report will go some way to addressing these issues by providing information on monitoring methods and signposting data sources. Coastal monitoring, the collection, analysis and storage of information about coastal processes and the response of the coastline, provides information on how the coast changes over time, after storm events and due to the effects of human intervention. Accurate and repeatable observational data is essential to informed decision making, particularly in light of climate change, the impacts of which are already being felt. In this report, we review the need for monitoring and the development of appropriate strategies, which include good baseline data and long-term repeatable data collection at appropriate timescales. We identify some of the methods for collection of in situ data, such as tide gauges and topographic survey, and highlight where resources in terms of data and equipment are currently available. We then go on to explore the range of remote sensing methods available from satellites to smart phone photography. Both in situ and remotely sensed data are important as inputs into models, which in turn feed in to visualisations for decision-making. We review the availability of a wide range of datasets, including details of how to access satellite data and links to international and regional data banks. The report concludes with information on the use of Geographical Information Systems (GIS) and good practice in managing data

    Remote Sensing of Environment: Current status of Landsat program, science, and applications

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    Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat- 1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while incorporating technological advancements, has resulted in an increased operational use of Landsat data. Governments and international agencies, among others, can now build an expectation of Landsat data into a given operational data stream. International programs and conventions (e.g., deforestation monitoring, climate change mitigation) are empowered by access to systematically collected and calibrated data with expected future continuity further contributing to the existing multi-decadal record. The increased breadth and depth of Landsat science and applications have accelerated following the launch of Landsat-8, with significant improvements in data quality. Herein, we describe the programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs. We then present the key trends in Landsat science that underpin many of the recent scientific and application developments and followup with more detailed thematically organized summaries. The historical context offered by archival imagery combined with new imagery allows for the development of time series algorithms that can produce information on trends and dynamics. Landsat-8 has figured prominently in these recent developments, as has the improved understanding and calibration of historical data. Following the communication of the state of Landsat science, an outlook for future launches and envisioned programmatic developments are presented. Increased linkages between satellite programs are also made possible through an expectation of future mission continuity, such as developing a virtual constellation with Sentinel-2. Successful science and applications developments create a positive feedback loop—justifying and encouraging current and future programmatic support for Landsat

    GMES-service for assessing and monitoring subsidence hazards in coastal lowland areas around Europe. SubCoast D3.5.1

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    This document is version two of the user requirements for SubCoast work package 3.5, it is SubCoast deliverable 3.5.1. Work package 3.5 aims to provide a European integrated GIS product on subsidence and relative sea level rise. The first step of this process was to contact the European Environment Agency as the main user to discover their user requirements. This document presents these requirments, the outline methodology that will be used to carry out the integration and the datasets that will be used. In outline the main user requirements of the EEA are: 1. Gridded approach using an Inspire compliant grid 2. The grid would hold data on: a. Likely rate of subsidence b. RSLR c. Impact (Vulnerability) d. Certainty (confidence map) e. Contribution of ground motion to RSLR f. A measure of certainty in the data provided g. Metadata 3. Spatial Coverage - Ideally entire coastline of all 37 member states a. Spatial resolution - 1km 4. Provide a measure of the degree of contribution of ground motion to RSLR The European integration will be based around a GIS methodology. Datasets will be integrated and interpreted to provide information on data vlues above. The main value being a likelyhood of Subsidence. This product will initially be developed at it’s lowest level of detail for the London area. BGS have a wealth of data for london this will enable this less detialed product to be validated and also enable the generation of a more detailed product usig the best data availible. One the methodology has been developed it will be pushed out to other areas of the ewuropean coastline. The initial input data that have been reviewed for their suitability for the European integration are listed below. Thesea re the datasets that have European wide availibility, It is expected that more detailed datasets will be used in areas where they are avaiilble. 1. Terrafirma Data 2. One Geology 3. One Geology Europe 4. Population Density (Geoland2) 5. The Urban Atlas (Geoland2) 6. Elevation Data a. SRTM b. GDEM c. GTOPO 30 d. NextMap Europe 7. MyOceans Sea Level Data 8. Storm Surge Locations 9. European Environment Agencya. Elevation breakdown 1km b. Corine Land Cover 2000 (CLC2000) coastline c. Sediment Discharges d. Shoreline e. Maritime Boundaries f. Hydrodynamics and Sea Level Rise g. Geomorphology, Geology, Erosion Trends and Coastal Defence Works h. Corine land cover 1990 i. Five metre elevation contour line 10. FutureCoas

    Remote sensing in the coastal and marine environment. Proceedings of the US North Atlantic Regional Workshop

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    Presentations were grouped in the following categories: (1) a technical orientation of Earth resources remote sensing including data sources and processing; (2) a review of the present status of remote sensing technology applicable to the coastal and marine environment; (3) a description of data and information needs of selected coastal and marine activities; and (4) an outline of plans for marine monitoring systems for the east coast and a concept for an east coast remote sensing facility. Also discussed were user needs and remote sensing potentials in the areas of coastal processes and management, commercial and recreational fisheries, and marine physical processes

    Supplementary report to the final report of the coral reef expert group: S6. Novel technologies in coral reef monitoring

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    [Extract] This report summarises a review of current technological advances applicable to coral reef monitoring, with a focus on the Great Barrier Reef Marine Park (the Marine Park). The potential of novel technologies to support coral reef monitoring within the Reef 2050 Integrated Monitoring and Reporting Program (RIMReP) framework was evaluated based on their performance, operational maturity and compatibility with traditional methods. Given the complexity of this evaluation, this exercise was systematically structured to address the capabilities of technologies in terms of spatial scales and ecological indicators, using a ranking system to classify expert recommendations.An accessible copy of this report is not yet available from this repository, please contact [email protected] for more information

    Guidance for benthic habitat mapping: an aerial photographic approach

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    This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor

    Coral Reef Change Detection in Remote Pacific Islands Using Support Vector Machine Classifiers

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    Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of this study is to develop a machine learning classifier for coral dominated benthic cover-type class (CDBCTC) based on ground truth observations and Landsat images, evaluate the performance of this classifier when tested against new data, then deploy the classifier to perform CDBCTC change analysis of multiple locations. The proposed framework includes image calibration, support vector machine (SVM) training and tuning, statistical assessment of model accuracy, and temporal pixel-based image dierencing. Validation of the methodology was performed by cross-validation and train/test split using ground truth observations of benthic cover from four dierent reefs. These four locations (Palmyra Atoll, Kingman Reef, Baker Island Atoll, and Howland Island) as well as two additional locations (Kiritimati Island and Tabuaeran Island) were then evaluated for CDBCTC change detection. The in-situ training accuracy against ground truth observations for Palmyra Atoll, Kingman Reef, Baker Island Atoll, and Howland Island were 87.9%, 85.7%, 69.2%, and 82.1% respectively. The classifier attained generalized accuracy scores of 78.8%, 81.0%, 65.4%, and 67.9% for the respective locations when trained using ground truth observations from neighboring reefs and tested against the local ground truth observations of each reef. The classifier was trained using the consolidated ground truth data of all four sites and attained a cross-validated accuracy of 75.3%. The CDBCTC change detection analysis showed a decrease in CDBCTC of 32% at Palmyra Atoll, 25% at Kingman Reef, 40% at Baker Island Atoll, 25% at Howland Island, 35% at Tabuaeran Island, and 43% at Kiritimati Island. This research establishes a methodology for developing a robust classifier and the associated Controlled Parameter Cross-Validation (CPCV) process for evaluating how well the model will generalize to new data. It is an important step for improving the scientific understanding of temporal change within coral reefs around the globe
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