903 resultados para Satellite Monitoring Systems


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En el departamento Bermejo, provincia de Chaco, a fines del siglo XIX se origina uno de los ingenios azucareros más importantes del país: Las Palmas del Chaco Austral S.A. En la década de los noventa es víctima de las políticas de privatización imperantes del momento. Como consecuencia, se produce su cierre y posterior desaparición, lo que supuso la eliminación de la principal fuente de trabajo de la localidad. Las tendencias actuales y novedosas en teledetección, cartografía digital y Sistemas de Información Geográfica (SIG) son una forma útil e importante de ofrecer conocimientos actualizados para el diagnóstico, monitoreo y su aplicación en la gestión e investigación de recursos presentes en los distintos lugares de nuestro país. En el presente trabajo se pretende analizar los cambios producidos en el uso de suelo en las tierras del ex Ingenio a partir del cierre del mismo, mediante el uso de imágenes satelitales de los años 1987 y 2001, y de sistemas de información geográfica (SIG). El análisis multiespectral y multitemporal de las mismas permitirá discriminar los tipos de cobertura del suelo sobre la base de su respuesta espectral.

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The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.

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Long-term environmental time series of continuously collected data are fundamental to identify and classify pulses and determine their role in aquatic systems. This paper presents a web based archive for limnological and meteorological data collected by integrated system for environmental monitoring (SIMA). The environmental parameters that are measured by SIMA are: chlorophyll-a (µg/L), water surface temperature (ºC), water column temperature by a thermistor string (ºC), turbidity (NTU), pH, dissolved oxygen concentration (mg/L), electric conductivity (µS/cm), wind speed (m/s) and direction (º), relative humidity (%), short wave radiation (W/m**2), barometric pressure (hPa). The data are collected in preprogrammed time interval (1 hour) and are transmitted by satellite in quasi-real time for any user in a range of 2500 km from the acquisition point. So far 11 hydroelectric reservoirs being monitored using the SIMA buoy. A basic statistics (mean and standard deviation) for some parameters and an example of time series were displayed. The main observed problem are divided into sensors and satellite. The sensors problems is due to the environmental characteristics of each water body. In acid waters the sensors of water quality rapidly degrade, and the collected data are invalid. Another problem is the infestation of periphyton in the sensor. SIMA buoy makes the parameters readings every hour, or 24 readings per day. However, not always received all readings because the system requires satellites passing over the buoy antenna to complete the transfer and due to the satellite constellation position, some locations inland are not met as often as necessary to complete all transmissions. This is the more often causes for lack in the time series.

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The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

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The Yangtze River Basin downstream of China's Three Gorges Dam (TGD) (thereafter referred to as "downstream" basin) hosts the largest cluster of freshwater lakes in East Asia. These lakes are crucial water stocks to local biophysical environments and socioeconomic development. Existing studies document that individual lakes in this region have recently experienced dramatic changes under the context of enduring meteorological drought, continuous population growth, and extensive water regulation since TGD's initial impoundment (i.e., June, 2003). However, spatial and temporal patterns of lake dynamics across the complete downstream Yangtze basin remain poorly characterized. Using daily MODIS imagery and an advanced thematic mapping scheme, this study presents a comprehensive monitoring of area dynamics in the downstream lake system at a 10-day temporal resolution during 2000-2011. The studied lakes constitute ~76% (~11,400 km**2) of the total downstream lake area, including the entire +70 major lakes larger than 20 km**2. The results reveal a decadal net decline in lake inundation area across the downstream Yangtze Basin, with a cumulative decrease of 849 km**2 or 7.4% from 2000 to 2011. Despite an excessive precipitation anomaly in the year 2010, the decreasing trend was tested significant in all seasons. The most substantial decrease in the post-TGD period appears in fall (1.1%/yr), which intriguingly coincides with the TGD water storage season. Regional lake dynamics exhibit contrasting spatial patterns, manifested as evident decrease and increase of aggregated lake areas respectively within and beyond the Yangtze Plain. This contrast suggests a marked vulnerability of lakes in the Yangtze Plain, to not only local meteorological variability but also intensified human water regulations from both the upstream Yangtze main stem (e.g., the TGD) and tributaries (e.g., lakes/reservoirs beyond the Yangtze Plain). The produced lake mapping result and derived lake area dynamics across the downstream Yangtze Basin provides a crucial monitoring basis for continuous investigations of changing mechanisms in the Yangtze lake system.

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Coastal upwelling systems account for approximately half of global ocean primary production and contribute disproportionately to biologically driven carbon sequestration. Diatoms, silica-precipitating microalgae, constitute the dominant phytoplankton in these productive regions, and their abundance and assemblage composition in the sedimentary record is considered one of the best proxies for primary production. The study of the sedimentary diatom abundance (SDA) and total organic carbon content (TOC) in the five most important coastal upwelling systems of the modern ocean (Iberia-Canary, Benguela, Peru-Humboldt, California and Somalia-Oman) reveals a global-scale positive relationship between diatom production and organic carbon burial. The analysis of SDA in conjunction with environmental variables of coastal upwelling systems such as upwelling strength, satellite-derived net primary production and surface water nutrient concentrations shows different relations between SDA and primary production on the regional scale. At the global-scale, SDA appears modulated by the capacity of diatoms to take up silicic acid, which ultimately sets an upper limit to global export production in these ocean regions.

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Segmented ionization chambers represent a good solution to monitor the position, the intensity and the shape of ion beams in hadrontherapy. Pixel and strip chambers have been developed for both passive scattering and active scanning dose delivery systems. In particular, strip chambers are optimal for pencil beam scanning, allowing for spatial and time resolutions below 0.1 mm and 1 ms, respectively. The MATRIX pixel and the Strip Accurate Monitor for Beam Applications (SAMBA) detectors are described in this paper together with the results of several beam tests and industrial developments based on these prototypes.

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The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

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The antenna presented in this article will be developed for satellite communications onboard systems based on the recommendations ITU-R S.580-6 and ITU-R S.465-5. The antenna consists of printed elements grouped in an array, this terminal works in a frequency band from 7.25 up to 8.4 GHz (14.7% of bandwidth), where both bands, reception (7.25 - 7.75 GHz) and transmission (7.9 - 8.4 GHz), are included simultaneously. The antenna reaches a gain about 31 dBi, and it has a radiation pattern with a beamwidth smaller than 10° and a dual circular polarization. The antenna has the capability to steer in elevation from 90° to 40° electronically and 360° in azimuth with a motorized junction.

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Current nanometer technologies are subjected to several adverse effects that seriously impact the yield and performance of integrated circuits. Such is the case of within-die parameters uncertainties, varying workload conditions, aging, temperature, etc. Monitoring, calibration and dynamic adaptation have appeared as promising solutions to these issues and many kinds of monitors have been presented recently. In this scenario, where systems with hundreds of monitors of different types have been proposed, the need for light-weight monitoring networks has become essential. In this work we present a light-weight network architecture based on digitization resource sharing of nodes that require a time-to-digital conversion. Our proposal employs a single wire interface, shared among all the nodes in the network, and quantizes the time domain to perform the access multiplexing and transmit the information. It supposes a 16% improvement in area and power consumption compared to traditional approaches.

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Variabilities associated with CMOS evolution affect the yield and performance of current digital designs. FPGAs, which are widely used for fast prototyping and implementation of digital circuits, also suffer from these issues. Proactive approaches start to appear to achieve self-awareness and dynamic adaptation of these devices. To support these techniques we propose the employment of a multi-purpose sensor network. This infrastructure, through adequate use of configuration and automation tools, is able to obtain relevant data along the life cycle of an FPGA. This is realised at a very reduced cost, not only in terms of area or other limited resources, but also regarding the design effort required to define and deploy the measuring infrastructure. Our proposal has been validated by measuring inter-die and intra-die variability in different FPGA families.

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This paper presents a multiprotocol mobile application for building automation which supports and enables the integration of the most representative control technologies such as KNX, LonWorks and X-10. The application includes a real-time monitoring service. Finally, advanced control functionalities based on gestures recognition and predefined scenes have been implemented. This application has been developed and tested in the Energy Efficiency Research Facility located at CeDInt-UPM, where electrical loads, blinds and HVAC and lighting systems can be controlled.

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Ponencia invitada sobre asignacion y gestion de losts en el curso de verano de la UPM Research in Decisión Support Systems for future Air Traffic Management