Distribution and pattern of moraines in Far NE Russia reveal former glacial extent

Here we present a series of six maps illustrating the distribution of end moraines in Far NE Russia. The maps are the first to systematically document the distribution of moraines across this region from the Verkhoyansk Mountains at the westernmost limit of our study area to the Chukchi Peninsula in the NE and to Kamchatka in the south, covering almost 4 million km2. Moraines were identified and mapped from analysis of satellite images and digital elevation model data. A total of 2173 moraines are identified, and we highlight some 197 more speculative features (perhaps moraines) that require further investigation. The distribution of moraines indicates that much of the region, now largely ice-free, was formerly occupied by glaciers centred upon the region’s uplands and that glacier outlets were typically < 200 km in length. The maps demonstrate the usefulness of remote sensing to derive an improved understanding of the glacial history of this vast and isolated region, and we present them to stimulate further work and act as a systematic framework for targeted geochronometric dating.

Late Quaternary glaciations in Far NE Russia; combining moraines, topography and chronology to assess regional and global glaciation synchrony

During various periods of Late Quaternary glaciation, small ice-sheets, -caps, -fields and valley glaciers, occupied the mountains and uplands of Far NE Russia (including the Verkhoyansk, Suntar-Khayata, and Chersky Mountains; the KolymaeAnyuy and Koryak Highlands; and much of the Kamchatka and Chukchi
Peninsulas). Here, the margins of former glaciers across this region are constrained through the comprehensive mapping of moraines from remote sensing data (Landsat 7 ETM+ satellite images; ASTER Global Digital Elevation Model (GDEM2); and Viewfinder Panorama DEM data). A total of 8414 moraines
are mapped, and this record is integrated with a series of published age-estimates (n = 25), considered to chronologically-constrain former ice-margin positions. Geomorphological and chronological data are compiled in a Geographic Information System (GIS) to produce ‘best estimate’ reconstructions of ice extent during the global Last Glacial Maximum (gLGM) and, to a lesser degree, during earlier phases of glaciation. The data reveal that much of Far NE Russia (~1,092,427 km2) preserves a glaciated landscape (i.e. is bounded by moraines), but there is no evidence of former ice masses having extended more than 270 km beyond mountain centres (suggesting that, during the Late Quaternary, the region has not been occupied by extensive ice sheets). During the gLGM, specifically, glaciers occupied ~253,000 km2, and rarely extended more than 50 km in length. During earlier (pre-gLGM) periods, glaciers were more extensive, though the timing of former glaciation, and the maximum Quaternary extent, appears to have been asynchronous across the region, and out-of-phase with ice-extent maxima elsewhere in the Northern Hemisphere. This glacial history is partly explained through consideration of climatic-forcing
(particularly moisture-availability, solar insolation and albedo), though topographic-controls upon the former extent and dynamics of glaciers are also considered, as are topographic-controls upon moraine deposition and preservation. Ultimately, our ability to understand the glacial and climatic history of this region is restricted when the geomorphological-record alone is considered, particularly as directly-dated glacial deposits are few, and topographic and climatic controls upon the moraine record are difficult to
distinguish.

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Difference equation approach to two-thermocouple sensor characterization in constant velocity flow environments

Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in certain harsh environments, for example, in combustion systems and engine exhausts, large wire diameters are required, and consequently the measurement bandwidth is reduced. This article discusses a software compensation technique to address the loss of high frequency fluctuations based on measurements from two thermocouples. In particular, a difference equation (DE) approach is proposed and compared with existing methods both in simulation and on experimental test rig data with constant flow velocity. It is found that the DE algorithm, combined with the use of generalized total least squares for parameter identification, provides better performance in terms of time constant estimation without any a priori assumption on the time constant ratios of the thermocouples.

Securing the smart grid

The availability of electricity is fundamental to modern society. It is at the top of the list of critical infrastructures and its interruption can have severe consequences. This highly important system is now evolving to become more reliable, efficient, and clean. This evolving infrastructure has become known as the smart grid; and these future smart grid systems will rely heavily on ICT. This infrastructure will require many servers and due to the nature of the grid, many of these systems will be geographically diverse requiring communication links. At the heart of this ICT infrastructure will be security. At each level of the smart grid from smart metering right through to remote sensing and control networks, security will be a key factor for system design consideration. With an increased number of ICT systems in place the security risk also increases. In this paper the authors discuss the changing nature of security in relation to the smart grid by looking at the move from legacy systems to more modern smart grid systems. The potential planes of attack for future smart grid systems are identified, and the general anatomy of a cyber-attack is presented. The authors then introduce the various threat levels of different types of attack and the mitigation techniques that could be put in place for each. Finally, the authors' introduce a Phasor Measurement Unit (PMU) communication system (operated by the authors) that can be used as a test-bed for some of the proposed future security research.

Geotechnical failure risk reviewed

Slope instabilities – commonly triggered by rainfall – pose a geotechnical risk causing disruption to transport routes and incur significant financial resources. This article details laboratory, ground and remote sensing investigations carried out by Queen’s University Belfast and Transport Northern Ireland (TNI) to characterise and monitor slope instability on two higher risk infrastructure slopes in Northern Ireland. The research is used to update a noninvasive risk assessment model of slopes across the country’s road network to direct resources for future investigation.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Offshore wind resource estimation using wave buoy data

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys. © 2012 IEEE.

Characteristics of Offshore Wind Speeds using Buoy Measurements

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys

An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.

Rapid glacial retreat on the Kamchatka Peninsula during the early 21st Century

Monitoring glacier fluctuations provides insights into changing glacial environments and recent climate change. The availability of satellite imagery offers the opportunity to view these changes for remote and inaccessible regions. Gaining an understanding of the ongoing changes in such regions is vital if a complete picture of glacial fluctuations globally is to be established. Here, satellite imagery (Landsat 7, 8 and ASTER) is used to conduct a multi-annual remote sensing survey of glacier fluctuations on the Kamchatka Peninsula (eastern Russia) over the 2000–2014 period. Glacier margins were digitised manually and reveal that, in 2000, the peninsula was occupied by 673 glaciers, with a total glacier surface area of 775.7 ± 27.9 km2 . By 2014, the number of glaciers had increased to 738 (reflecting the fragmentation of larger glaciers), but their surface area had decreased to 592.9 ± 20.4 km2 . This represents a ∼ 24 % decline in total glacier surface area between 2000 and 2014 and a notable acceleration in the rate of area loss since the late 20th century. Analysis of possible controls indicates that these glacier fluctuations were likely governed by variations in climate (particularly rising summer temperatures), though the response of individual glaciers was modulated by other (non-climatic) factors, principally glacier size, local shading and debris cover.

Sistemas de recepção de imagens de satélite: implementação e aplicações

A presente dissertação pretende focalizar-se sobre algumas aplicações da detecção remota por satélite. Assim, será exposto neste trabalho o resultado do desenvolvimento de sistemas de recepção de imagens obtidas por satélites de órbita polar e geostacionária, assim como um conjunto de três aplicações implementadas: a detecção de focos de incêndio em Portugal com dados do MSG-1, o desenvolvimento de um conjunto de actividades de exploração da Detecção Remota no contexto do 1' Ciclo do Ensino Básico e a validação dos resultados de previsão do modelo de mesoescala MM5 com imagens de satélite. A análise destas imagens desempenha um papel crucial, por exemplo nos estudos sobre tempo e clima. É por essa razão que tanto os Estados Unidos como outros países têm vindo a desenvolver um esforço contínuo para que possam ser lançados novos satélites que permitam uma constante aquisição de conhecimentos sobre os fenómenos meteorológicos. Deste modo, a implementação de sistemas de recepção que possibilitem transformar as medidas disponibilizadas por instrumentos a bordo de satélites em informação constitui um empreendimento de extrema utilidade para as mais diversas áreas do saber (como as Geociências ou a Meteorologia), revestindo-se de inúmeras aplicações de interesse para a Sociedade, nomeadamente nos sectores agrícola, energético, dos transportes e da conservação do meio ambiente.

Hidrogeomorfologia e sustentabilidade de recursos hídricos subterrâneos

A água subterrânea de rochas duras é uma fonte importante para fins domésticos, industriais e agrícolas e mesmo para o consumo humano. A geologia, a tectónica, a geomorfologia e as características hidrológicas controlam o fluxo, ocorrência e armazenamento das águas subterrâneas. A disponibilidade da água subterrânea no meio geológico está totalmente dependente das áreas de recarga e de descarga numa determinada bacia. A precipitação é a principal fonte de recarga em aquíferos descontínuos, enquanto que a descarga depende dos declives do terreno e dos gradientes do nível hidrostático e ainda das condições hidrogeológicas do solo. A hidrogeomorfologia é um domínio interdisciplinar emergente, que estuda as relações entre as unidades geomorfológicas e o regime das águas superficiais e subterrâneas de uma determinada área. A compreensão do papel da geomorfologia é essencial para avaliar de forma rigorosa os sistemas hidrogeológicos e os recursos hídricos. Os dados de detecção remota providenciam uma informação espacial valiosa e actualizada da superfície terrestre e dos recursos naturais. Os recentes avanços tecnológicos colocaram as técnicas de detecção remota e os sistemas de informação geográfica (SIG) numa posição cimeira como ferramentas de gestão metodológica. Foi criada, em ambiente SIG, uma base de geo-dados, essencialmente derivada da detecção remota, da cartografia e do trabalho de campo. Esta base de dados, organizada em diferentes níveis de informação, inclui uma avaliação principalmente focalizada no uso do solo, climatologia, declives, geologia, geomorfologia e hidrogeologia. No presente estudo foram cruzados diversos níveis de informação, com a geração de múltiplos mapas temáticos para atingir um quadro integrado dos diversos sectores no Norte e Centro de Portugal. Os sectores em estudo (Caldas da Cavaca, Termas de Entre-os-Rios, Águas de Arouca e Águas do Alardo) estão localizados em sistemas hidrogeológicos predominantemente constituídos por rochas graníticas, por vezes intersectadas por filões de quartzo, aplito-pegmatíticos e doleríticos. Para apoiar a elaboração dos mapas hidrogeomorfológicos foi criada uma base SIG, contendo diversa informação, nomeadamente topografia, hidrografia, litologia, tectónica, morfoestrutura, hidrogeologia, geofísica e uso do solo. Além disso, foram realizadas várias campanhas de campo, as quais permitiram: o estabelecimento dum mapeamento geológico, geomorfológico e hidrogeológico; a caracterização in situ do grau de alteração, resistência e grau de fracturação dos maciços rochosos; o desenvolvimento de um inventário hidrogeológico em conjunto com alguns ensaios expeditos in situ. A interligação entre os parâmetros geomorfológicos, hidrológicos e hidrogeológicos dos sistemas de água subterrânea “normal” e hidromineral destaca a importância de uma cartografia e duma modelação conceptual hidrogeomorfológica. Além disso, contribuirá para um melhor apoio à decisão na gestão sustentável dos recursos hídricos.