1,140 research outputs found

    Evaluation of a global soil moisture product from finer spatial resolution sar data and ground measurements at Irish sites

    Get PDF
    In the framework of the European Space Agency Climate Change Initiative, a global, almost daily, soil moisture (SM) product is being developed from passive and active satellite microwave sensors, at a coarse spatial resolution. This study contributes to its validation by using finer spatial resolution ASAR Wide Swath and in situ soil moisture data taken over three sites in Ireland, from 2007 to 2009. This is the first time a comparison has been carried out between three sets of independent observations from different sensors at very different spatial resolutions for such a long time series. Furthermore, the SM spatial distribution has been investigated at the ASAR scale within each Essential Climate Variable (ECV) pixel, without adopting any particular model or using a densely distributed network of in situ stations. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values in temperate grasslands. Temporal and spatial variability analysis provided high levels of correlation (p < 0.025) and low errors between the three datasets, leading to confidence in the new ECV SM global product, despite limitations in its ability to track the driest and wettest conditions

    Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches

    Get PDF
    Accurate inventories of grasslands are important for studies of carbon dynamics, biodiversity conservation and agricultural management. For regions with persistent cloud cover the use of multi-temporal synthetic aperture radar (SAR) data provides an attractive solution for generating up-to-date inventories of grasslands. This is even more appealing considering the data that will be available from upcoming missions such as Sentinel-1 and ALOS-2. In this study, the performance of three machine learning algorithms; Random Forests (RF), Support Vector Machines (SVM) and the relatively underused Extremely Randomised Trees (ERT) is evaluated for discriminating between grassland types over two large heterogeneous areas of Ireland using multi-temporal, multi-sensor radar and ancillary spatial datasets. A detailed accuracy assessment shows the efficacy of the three algorithms to classify different types of grasslands. Overall accuracies ≥ 88.7% (with kappa coefficient of 0.87) were achieved for the single frequency classifications and maximum accuracies of 97.9% (kappa coefficient of 0.98) for the combined frequency classifications. For most datasets, the ERT classifier outperforms SVM and RF

    Antenna Modeller for Synthetic Aperture Radar Applications. Electromagnetic and Radiometric Considerations

    Get PDF
    The objective of the present Master Thesis is designing an optimizer of the excitation coefficients of a phased array antenna

    Agulhas current variability determined from space : a multi-sensor approach

    Get PDF
    Includes bibliographical references (p. 119-132).Satellite remote sensing datasets including more than 6 years of high frequency Sea Surface Temperature (SST) imagery as well as surface current observations derived from 18 years of merged-altimetry and over 2 years of Advanced Synthetic Aperture Radar (ASAR) observations are combined to study the variability of the Agulhas Current. The newly available rangedirected surface currents velocities from ASAR, which rely on the careful analysis of the measured Doppler shift, show strong promise for monitoring the meso to sub-mesoscale features of the surface circulation. While the accuracy of ASAR surface current velocities suffers from occasional bias due to our current inability to systematically account for the wind-induced contribution to the Doppler shift signal, the ASAR surface current velocities are able to consistently highlight regions of strong current and shear. The synaptic nature and relatively high resolution of ASAR acquisitions make the ASAR derived current velocities a good complement to altimetry for the study of sub-mesoscale processes and western boundary current dynamics. Time-averaged range-directed surface currents derived from ASAR provide an improved map of the mean Agulhas Current flow, clearly showing the location of the Agulhas Current core over the 1000 m isobath and identifying the region at the shelf edge of the north-eastern Agulhas Bank as one of the most variable within the Agulhas Current. To determine the variability of the Agulhas Current, an algorithm to track the position of the current is developed and applied to the longer merged-altimetry and SST records. Limitations associated with altimetry near the coast favour the use of the SST dataset to track the position of the Agulhas Current in its northern region. In the southern Agulhas, where the current lies further from the coast, altimetry is suited to monitoring the position of the Agulhas Current. The front detection analysis conducted on the SST dataset in the northern Agulhas reveals the complex nature of Natal Pulses. The downstream passage of the Natal Pulses is associated with the generation of secondary offshore meanders at the inshore edge of the current. Perturbations formed during the passage of Natal Pulses evolve rapidly to either dissipate, re-merge with the initial Natal Pulse or in some rare occasion, detach from the Agulhas Current

    Improving InSAR geodesy using global atmospheric models

    Get PDF
    Spatial and temporal variations of pressure, temperature and water vapor content in the atmosphere introduce significant confounding delays in Interferometric Synthetic Aperture Radar (InSAR) observations of ground deformation and bias estimatesof regional strain rates. Producing robust estimates of tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation measurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to mitigate the impact of tropospheric delays, motivating further exploration of their potential. Here, we explore the effectiveness of these models in several geographic and tectonic settings on both single interferograms and time series analysis products. Both hydrostatic and wet contributions to the phase delay are important to account for. We validate these path delay corrections by comparing with estimates of vertically integrated atmospheric water vapor content derived from the passive multi-spectral imager MERIS, onboard the ENVISAT satellite. Generally, the performance of the prediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric and orbital contributions allows one to better measure long wavelength deformation, (2) how atmospheric delays affect measurements of surface deformation following earthquakes and (3) we show that such a method allows us to reduce biases in multi-year strain rate estimates by reducing the influence of unevenly sampled seasonal oscillations of the tropospheric delay

    Use of microwave remote sensing data to monitor spatio temporal characteristics of surface soil moisture at local and regional scales

    Get PDF
    Hydrologic processes, such as runoff production or evapotranspiration, largely depend on the variation of soil moisture and its spatial pattern. The interaction of electromagnetic waves with the land surface can be dependant on the water content of the uppermost soil layer. Especially in the microwave domain of the electromagnetic spectrum, this is the case. New sensors as e.g. ENVISAT ASAR, allow for frequent, synoptically and homogeneous image acquisitions over larger areas. Parameter inversion models are therefore developed to derive bio- and geophysical parameters from the image products. The paper presents a soil moisture inversion model for ENVISAT ASAR data for local and regional scale applications. The model is validated against in situ soil moisture measurements. The various sources of uncertainties, being related to the inversion process are assessed and quantified

    Utilização da Norma JPEG2000 para codificar proteger e comercializar Produtos de Observação Terrestre

    Get PDF
    Applications like, change detection, global monitoring, disaster detection and management have emerging requirements that need the availability of large amounts of data. This data is currently being capture by a multiplicity of instruments and EO (Earth Observation) sensors originating large volumes of data that needs to be stored, processed and accessed in order to be useful – as an example, ENVISAT accumulates, in a yearly basis, several hundred terabytes of data. This need to recover, store, process and access brings some interesting challenges, like storage space, processing power, bandwidth and security, just to mention a few. These challenges are still very important on today’s technological world. If we take a look for example at the number of subscribers of ISP (Internet Service Providers) broadband services on the developed world today, one can notice that broadband services are still far from being common and dominant. On the underdeveloped countries the picture is even dimmer, not only from a bandwidth point of view but also in all other aspects regarding information and communication technologies (ICTs). All this challenges need to be taken into account if a service is to reach the broadest audience possible. Obviously protection and securing of services and contents is an extra asset that helps on the preservation of possible business values, especially if we consider such a costly business as the space industry. This thesis presents and describes a system which allows, not only the encoding and decoding of several EO products into a JPEG2000 format, but also supports some of the security requirements identified previously that allows ESA (European Space Agency) and related EO services to define and apply efficient EO data access security policies and even to exploit new ways to commerce EO products over the Internet.Aplicações como, detecção de mudanças no terreno, monitorização planetária, detecção e gestão de desastres, têm necessidades prementes que necessitam de vastas quantidades de dados. Estes dados estão presentemente a ser capturados por uma multiplicidade de instrumentos e sensores de observação terrestre, que originam uma enormidade de dados que necessitam de ser armazenados processados e acedidos de forma a se tornarem úteis – por exemplo, a ENVISAT acumula anualmente varias centenas de terabytes de dados. Esta necessidade de recuperar, armazenar, processar e aceder introduz alguns desafios interessantes como o espaço de armazenamento, poder de processamento, largura de banda e segurança dos dados só para mencionar alguns. Estes desafios são muito importantes no mundo tecnológico de hoje. Se olharmos, por exemplo, ao número actual de subscritores de ISP (Internet Service Providers) de banda larga nos países desenvolvidos podemos ficar surpreendidos com o facto do número de subscritores desses serviços ainda não ser uma maioria da população ou dos agregados familiares. Nos países subdesenvolvidos o quadro é ainda mais negro não só do ponto de vista da largura de banda mas também de todos os outros aspectos relacionados com Tecnologias da Informação e Comunicação (TICs). Todos estes aspectos devem ser levados em consideração se se pretende que um serviço se torne o mais abrangente possível em termos de audiências. Obviamente a protecção e segurança dos conteúdos é um factor extra que ajuda a preservar possíveis valores de negócio, especialmente considerando industrias tão onerosas como a Industria Espacial. Esta tese apresenta e descreve um sistema que permite, não só a codificação e descodificação de diversos produtos de observação terrestre para formato JPEG2000 mas também o suporte de alguns requisitos de segurança identificados previamente que permitem, á Agência Espacial Europeia e a outros serviços relacionados com observação terrestre, a aplicação de politicas eficientes de acesso seguro a produtos de observação terrestre, permitindo até o aparecimento de novas forma de comercialização de produtos de observação terrestre através da Internet

    Earth observation for water resource management in Africa

    Get PDF

    Managing Warehouse Utilization: An Analysis of Key Warehouse Resources

    Get PDF
    The warehousing industry is extremely important to businesses and the economy as a whole, and while there is a great deal of literature exploring individual operations within warehouses, such as warehouse layout and design, order picking, etc., there is very little literature exploring warehouse operations from a systems approach. This study uses the Theory of Constraints (TOC) to develop a focused resource management approach to increasing warehouse capacity and throughput, and thus overall warehouse performance, in an environment of limited warehouse resources. While TOC was originally developed for reducing operational bottlenecks in manufacturing, it has allowed companies in other industries, such as banking, health care, and the military, to save millions of dollars. However, the use of TOC has been limited to case studies and individual situations, which typically are not generalizable. Since the basic steps of TOC are iterative in nature and were not designed for survey research, modifications to the original theory are necessary in order to provide insight into industry-wide problems. This study further develops TOC\u27s logistics paradigm and modifies it for use with survey data, which was collected from a sample of warehouse managers. Additionally, it provides a process for identifying potentially constrained key warehouse resources, which served as a foundation of this study. The findings of the study confirm that TOC\u27s methods of focused resource capacity management and goods flow scheduling coordination with supply chain partners can be an important approach for warehouse managers to use in overcoming resource capacity constraints to increase warehouse performance
    corecore