Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services

Locate full-text(opens in a new window)|View at Publisher| Export | Download | More... Atmospheric Measurement Techniques Volume 8, Issue 5, 27 May 2015, Pages 2183-2193 Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services (Article) Angulo, I.a, Grande, O.a, Jenn, D.b, Guerra, D.a, De La Vega, D.a a University of the Basque Country (UPV/EHU), Bilbao, Spain b Naval Postgraduate School, Monterey, United States View references (28) Abstract The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Current signal processing techniques to mitigate wind turbine clutter (WTC) are scarce, so the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the radar cross section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver.

For the proposed model, a representative scenario has been chosen in which both the weather radar and the wind farm are placed on clear areas; i.e., wind turbines are supposed to be illuminated only by the lowest elevation angles of the radar beam.

This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the physical optics theory and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.

Ecosystem-based Management for Protected Species in the North Pacific Fisheries

In the North Pacific Ocean, an ecosystem-based fishery management approach has been adopted. A significant objective of this approach is to reduce interactions between fishery-related activities and protected species. We review management measures developed by the North Pacific Fishery Management Council and the National Marine Fisheries Service to reduce effects of the groundfish fisheries off Alaska on marine mammals and seabirds, while continuing to provide economic opportunities for fishery participants. Direct measures have been taken to mitigate known fishery impacts, and precautionary measures have been taken for species with potential (but no documented) interactions with the groundfish fisheries. Area closures limit disturbance to marine mammals at rookeries and haulouts, protect sensitive benthic habitat, and reduce potential competition for prey resources. Temporal and spatial dispersion of catches reduce the localized impact of fishery removals. Seabird avoidance measures have been implemented through collaboration with fishery participants and have been highly successful in reducing seabird bycatch. Finally, a comprehensive observer monitoring program provides data on the location and extent of bycatch of marine mammals and seabirds. These measures provide managers with the flexibility to adapt to changes in the status of protected species and evolving conditions in the fisheries. This review should be useful to fishery managers as an example of an ecosystem-based approach to protected species management that is adaptive and accounts for multiple objectives.

SIG aplicado na identificação de áreas potenciais aos investimentos habitacionais Estudo de caso: porção oeste do Município do Rio de Janeiro.

A expansão industrial e o desenvolvimento territorial na porção oeste do Município do Rio de Janeiro trazem inúmeras modificações no cenário socioeconômico da região e adjacências. O destaque de investimentos na indústria de transformação é a implantação da Companhia Siderúrgica do Atlântico (CSA), que se mostra como o maior empreendimento privado em realização no país. Investimentos públicos e privados no setor de infraestrutura estão previstos, considerando as características naturais e a localização geográfica privilegiada da região. A influência do porto de Itaguaí e a construção do Arco Metropolitano configuram um corredor de desenvolvimento com reflexos positivos logísticos e socioeconômicos, não só para o estado do Rio de Janeiro, mas também para outros estados brasileiros. Os impactos da reordenação do espaço urbano, com a possibilidade de incremento populacional nas proximidades do novo eixo rodoviário e industrial, tende a gerar um aumento da demanda por serviços no setor terciário. Dessa forma, o planejamento territorial se faz obrigatório, apoiado por geotecnologias. O objetivo da pesquisa foi atender às necessidades do setor habitacional, analisando fatores relevantes e condições favoráveis à implantação de novas construções habitacionais. Baseando-se em dados provenientes do censo do IBGE de 2010 e do Instituto de Urbanismo Pereira Passos (IPP), a Tecnologia da Informação integrada com os dados de mapas digitais e imagens de satélite de alta resolução (World View-2), permitiram uma análise geral do contexto do crescimento regional. Além da análise das variáveis existentes nos dados socioeconômicos, outras variáveis de pesquisa foram empregadas em ambiente SIG, tais como: segurança, proximidades de logradouros principais, existências de escolas e hospitais municipais e estaduais, distância dos centros industriais e de shopping. Após as análises multicriteriais de dados socioeconômicos e bases cartográficas, relatórios na forma de mapas foram emitidos, com a finalidade de orientar o poder público e as construtoras nas tomadas de decisões.

Uso de web services e softwares livres na disseminação de informações georreferenciadas sobre produtos da floresta amazônica.

Georreferenced information has been increasingly required for the planning and decision-making in different sectors of society. New ways of dissemination of data, such as the Open Geospatial Consortium (OGC) web services, have contributed to the ease of access to this information. Even with all the technological advances in the area of data distribution, there is still low availability of georreferenced data about the Amazon. The goal of the present work is the development of a spatial data infrastructure (SDI), that is, an environment of sharing and use of georreferenced data based on the technology of web services, metadata and interfaces that allow the user easy access to these data. The present work discussess the OGC patterns, the most relevant georeferrenced data servers, the main web clients, and the revolution in the dissemination of georeferrenced data which geobrowsers and web clients offered to regular users. Data to be released for the case study come from the project Exploitation of Non-wooden Forest Products-PFNM-in progress at the National Institute of Research in the Amazon-INPA-as well as from inventories of NGOs and other government bodies. Besides contributing to the enhancement of PFNM, this project aims at encouraging the use of GIS in the state of Amazonas offering tech support for the deployment of geographic databases and sharing between agencies, optimizing the resources applied in this area through the use of free software and integration of diffuse information currently available.

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers.

The coupling of St. John, US Virgin Islands Marine Protected Areas based on reef fish habitat affinities and movements across management boundaries [Poster]

NOAA's Biogeograpy Branch, the National Park Service (NPS), US Geological Survey, and the University of the Virgin Islands (UVI) are using acoustice telemetry to quantify spatial patterns and habitat affinities of reef fishes in the US Virgin Islands (USVI). The objective of the study is to define the movements of reef fishes among habitats within and between the Virgin Islands Coral Reef Nationla Monument (VICRNM), adjacent to Virgin Islands National Park (VIIS), and USVI Territorial waters. In order to better understand species habitat utilization patterns and movement of fishes among management regimes and areas open to fishing around St. John, we deployed an array of hydroacoutstic receivers and acoustically tagged reef fishes. A total of 150 fishes, representing 18 species and 10 families were acoustically tagged along the south shore of St. John from July 2006 to June 2008. Thirty six receivers with a detection range of approximately 300m each were deployed in shallow nearshore bays and across the shelf to depths of approximately 30m. Receivers were located within reefs and adjacent to reefs in seagrass, algal beds, or sand habitats. Example results include the movement of lane snappers and blue striped grunts that demonstrated diel movement from reef habitats during daytime hours to offshore seagrass beds at night. Fish associated with reefs that did not have adjacent seagrass beds made more extensive movements than those fishes associated with reefs that had adjacent seagrass habitats. The array comprised of both nearshore and cross shelf location of receives provides information on fine to broad scale fish movement patterns across habitats and among management units to examine the strength of ecological connectivity between management areas and habitats. For more information go to: http://ccma.nos.noaa.gov/ecosystems/ coralreef/acoustic_tracking.html

Shallow-water benthic habitats of St. John, U.S. Virgin Islands

Coral reef ecosystems of the Virgin Islands Coral Reef National Monument, Virgin Islands National Park and the surrounding waters of St. John, U.S. Virgin Islands are a precious natural resource worthy of special protection and conservation. The mosaic of habitats including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important ecosystem services to the community of St. John, such as fishing, tourism and shoreline protection. However, coral reef ecosystems throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy the natural heritage of these marine habitats. Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding St. John to support more effective management and conservation of ocean resources within the National Park system. This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new maps to a previous NOAA effort. Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at each level of the scheme. The ability to apply any component of this scheme was dependent on being able to identify and delineate a given feature in remotely sensed imagery.

An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula japonica in Lake Abashiri, Japan

We present a growth analysis model that combines large amounts of environmental data with limited amounts of biological data and apply it to Corbicula japonica. The model uses the maximum-likelihood method with the Akaike information criterion, which provides an objective criterion for model selection. An adequate distribution for describing a single cohort is selected from available probability density functions, which are expressed by location and scale parameters. Daily relative increase rates of the location parameter are expressed by a multivariate logistic function with environmental factors for each day and categorical variables indicating animal ages as independent variables. Daily relative increase rates of the scale parameter are expressed by an equation describing the relationship with the daily relative increase rate of the location parameter. Corbicula japonica grows to a modal shell length of 0.7 mm during the first year in Lake Abashiri. Compared with the attain-able maximum size of about 30 mm, the growth of juveniles is extremely slow because their growth is less susceptible to environmental factors until the second winter. The extremely slow growth in Lake Abashiri could be a geographical genetic variation within C. japonica.

Enhanced supply chain tracking based on the EPC network: A Bayesian approach

Supply chain tracking information is one of the main levers for achieving operational efficiency. RFID technology and the EPC Network can deliver serial-level product information that was never before available. However, these technologies still fail to meet the managers' visibility requirements in full, since they provide information about product location at specific time instances only. This paper proposes a model that uses the data provided by the EPC Network to deliver enhanced tracking information to the final user. Following a Bayesian approach, the model produces realistic ongoing estimates about the current and future location of products across a supply network, taking into account the characteristics of the product behavior and the configuration of the data collection points. These estimates can then be used to optimize operational decisions that depend on product availability at different locations. The enhancement of tracking information quality is highlighted through an example. © 2009 IFAC.

Exploring geographical dispersion in Thailand-based food supply chain (FSC)

Purpose: The purpose of this paper is to explore the key influential factors and their implications on food supply chain (FSC) location decisions from a Thailand-based manufacturer's view. Design/methodology/approach: In total, 21 case studies were conducted with eight Thailand-based food manufacturers. In each case, key influential factors were observed along with their implications on upstream and downstream FSC location decisions. Data were collected through semi-structured interviews and documentations. Data reduction and data display in tables were used to help data analysis of the case studies. Findings: This exploratory research found that, in the food industry, FSC geographical dispersion pattern could be determined by four factors: perishability, value density, economic-political forces, and technological forces. Technological forces were found as an enabler for FSC geographical dispersion whereas the other three factors could be both barriers and enablers. The implications of these four influential factors drive FSC towards four key patterns of FSC geographical dispersion: local supply chain (SC), supply-proximity SC, market-proximity SC, and international SC. Additionally, the strategy of the firm was found to also be an influential factor in determining FSC geographical dispersion. Research limitations/implications: Despite conducting 21 cases, the findings in this research are based on a relatively small sample, given the large size of the industry. More case evidence from a broader range of food product market and supply items, particularly ones that have significantly different patterns of FSC geographical dispersions would have been insightful. The consideration of additional influential factors such as labour movement between developing countries, currency fluctuations and labour costs, would also enrich the framework as well as improve the quality and validity of the research findings. The different strategies employed by the case companies and their implications on FSC location decisions should also be further investigated along with cases outside Thailand, to provide a more comprehensive view of FSC geographical location decisions. Practical implications: This paper provides insights how FSC is geographically located in both supply-side and demand-side from a manufacturing firm's view. The findings can also provide SC managers and researchers a better understanding of their FSCs. Originality/value: This research bridges the existing gap in the literature, explaining the geographical dispersion of SC particularly in the food industry where the characteristics are very specific, by exploring the internationalization ability of Thailand-based FSC and generalizing the key influential factors - perishability (lead time), value density, economic-political forces, market opportunities, and technological advancements. Four key patterns of FSC internationalization emerged from the case studies. © Emerald Group Publishing Limited.

Modelling information requirements in complex engineering services

Services based around complex engineering equipment and systems provide substantial challenges in both the long-term management of the equipment and the need for guaranteed delivery of the related service. One of the challenges for an organisation providing these services is the management of the information that is required to design, deliver and subsequently assess the success of the service. To assist in this process this paper develops a model for capturing, organising and assessing information requirements for these Complex Engineering Services in which information required to support key decisions in the life cycle of the service is identified. The model – referred to as The 12-Box Model for Service Information Requirements – is embedded in a three-phase procedure for providing an assessment of information requirements of a service contract which also provides insight into the capabilities of available information systems in supporting the contract. An illustrative example examining service information in an aircraft availability contract is used to demonstrate the use of the 12-Box Model and associated assessment procedure.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Initializing Vision Based Trackers Using Semantic Texton Forests

Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

Shape-Based Retrieval of Construction Site Photographs

Digital photographs of construction site activities are gradually replacing their traditional paper based counterparts. Existing digital imaging technologies in hardware and software make it easy for site engineers to take numerous photographs of “interesting” processes and activities on a daily basis. The resulting photographic data are evidence of the “as-built” project, and can therefore be used in a number of project life cycle tasks. However, the task of retrieving the relevant photographs needed in these tasks is often burdened by the sheer volume of photographs accumulating in project databases over time and the numerous objects present in each photograph. To solve this problem, the writers have recently developed a number of complementary techniques that can automatically classify and retrieve construction site images according to a variety of criteria (materials, time, date, location, etc.). This paper presents a novel complementary technique that can automatically identify linear (i.e., beam, column) and nonlinear (i.e., wall, slab) construction objects within the image content and use that information to enhance the performance of the writers’ existing construction site image retrieval approach.