898 resultados para Remote sensing - Data acquisitions


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Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors. (C) 2006 Elsevier Ltd. All rights reserved.

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Sea surface salinity is a key physical parameter in ocean science. It is important in the ocean remote sensing to retrieve sea surface salinity by the microwave probe technology. Based on the in situ measurement data and remote sensing data of the Yellow Sea, we have built a new empirical model in this paper, which can be used to retrieve sea surface salinity of the Yellow Sea by means of the brightness temperature of the sea water at L-band. In this model, the influence of the roughness of the sea surface is considered, and the retrieved result is in good agreement with the in situ measurement data, where the mean absolute error of the retrieved sea surface salinity is about 0.288 psu. This result shows that our model has greater retrieval precision compared with similar models.

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Quantification of areal evapotranspiration from remote sensing data requires the determination of surface energy balance components with support of field observations. Much attention should be given to spatial resolution sensitivity to the physics of surface heterogeneity. Using the Priestley-Taylor model, we generated evapotranspiration maps at several spatial resolutions for a heterogeneous area at Haibei, and validated the evapotranspiration maps with the flux tower data. The results suggested that the mean values for all evapotranspiration maps were quite similar but their standard deviations decreased with the coarsening of spatial resolution. When the resolution transcended about 480 m, the standard deviations drastically decreased, indicating a loss of spatial structure information of the original resolution evapotranspiration map. The absolute values of relative errors of the points for evapotranspiration maps showed a fluctuant trend as spatial resolution of input parameter data layers coarsening, and the absolute value of relative errors reached minimum when pixel size of map matched up to measuring scale of eddy covariance system. Finally, based on the analyses of the semi-variogram of the original resolution evapotranspiration map and the shapes of spatial autocorrelation indices of Moran and Geary for evapotranspiration maps at different resolutions, an appropriate resolution was suggested for the areal evapotranspiration simulation in this study area.

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On the issue of geological hazard evaluation(GHE), taking remote sensing and GIS systems as experimental environment, assisting with some programming development, this thesis combines multi-knowledges of geo-hazard mechanism, statistic learning, remote sensing (RS), high-spectral recognition, spatial analysis, digital photogrammetry as well as mineralogy, and selects geo-hazard samples from Hong Kong and Three Parallel River region as experimental data, to study two kinds of core questions of GHE, geo-hazard information acquiring and evaluation model. In the aspect of landslide information acquiring by RS, three detailed topics are presented, image enhance for visual interpretation, automatic recognition of landslide as well as quantitative mineral mapping. As to the evaluation model, the latest and powerful data mining method, support vector machine (SVM), is introduced to GHE field, and a serious of comparing experiments are carried out to verify its feasibility and efficiency. Furthermore, this paper proposes a method to forecast the distribution of landslides if rainfall in future is known baseing on historical rainfall and corresponding landslide susceptibility map. The details are as following: (a) Remote sensing image enhancing methods for geo-hazard visual interpretation. The effect of visual interpretation is determined by RS data and image enhancing method, for which the most effective and regular technique is image merge between high-spatial image and multi-spectral image, but there are few researches concerning the merging methods of geo-hazard recognition. By the comparing experimental of six mainstream merging methods and combination of different remote sensing data source, this thesis presents merits of each method ,and qualitatively analyzes the effect of spatial resolution, spectral resolution and time phase on merging image. (b) Automatic recognition of shallow landslide by RS image. The inventory of landslide is the base of landslide forecast and landslide study. If persistent collecting of landslide events, updating the geo-hazard inventory in time, and promoting prediction model incessantly, the accuracy of forecast would be boosted step by step. RS technique is a feasible method to obtain landslide information, which is determined by the feature of geo-hazard distribution. An automatic hierarchical approach is proposed to identify shallow landslides in vegetable region by the combination of multi-spectral RS imagery and DEM derivatives, and the experiment is also drilled to inspect its efficiency. (c) Hazard-causing factors obtaining. Accurate environmental factors are the key to analyze and predict the risk of regional geological hazard. As to predict huge debris flow, the main challenge is still to determine the startup material and its volume in debris flow source region. Exerting the merits of various RS technique, this thesis presents the methods to obtain two important hazard-causing factors, DEM and alteration mineral, and through spatial analysis, finds the relationship between hydrothermal clay alteration minerals and geo-hazards in the arid-hot valleys of Three Parallel Rivers region. (d) Applying support vector machine (SVM) to landslide susceptibility mapping. Introduce the latest and powerful statistical learning theory, SVM, to RGHE. SVM that proved an efficient statistic learning method can deal with two-class and one-class samples, with feature avoiding produce ‘pseudo’ samples. 55 years historical samples in a natural terrain of Hong Kong are used to assess this method, whose susceptibility maps obtained by one-class SVM and two-class SVM are compared to that obtained by logistic regression method. It can conclude that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping. (e) Predicting the distribution of rainfall-induced landslides by time-series analysis. Rainfall is the most dominating factor to bring in landslides. More than 90% losing and casualty by landslides is introduced by rainfall, so predicting landslide sites under certain rainfall is an important geological evaluating issue. With full considering the contribution of stable factors (landslide susceptibility map) and dynamic factors (rainfall), the time-series linear regression analysis between rainfall and landslide risk mapis presented, and experiments based on true samples prove that this method is perfect in natural region of Hong Kong. The following 4 practicable or original findings are obtained: 1) The RS ways to enhance geo-hazards image, automatic recognize shallow landslides, obtain DEM and mineral are studied, and the detailed operating steps are given through examples. The conclusion is practical strongly. 2) The explorative researching about relationship between geo-hazards and alteration mineral in arid-hot valley of Jinshajiang river is presented. Based on standard USGS mineral spectrum, the distribution of hydrothermal alteration mineral is mapped by SAM method. Through statistic analysis between debris flows and hazard-causing factors, the strong correlation between debris flows and clay minerals is found and validated. 3) Applying SVM theory (especially one-class SVM theory) to the landslide susceptibility mapping and system evaluation for its performance is also carried out, which proves that advantages of SVM in this field. 4) Establishing time-serial prediction method for rainfall induced landslide distribution. In a natural study area, the distribution of landslides induced by a storm is predicted successfully under a real maximum 24h rainfall based on the regression between 4 historical storms and corresponding landslides.

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Population data which collected and saved according to administrative region is a kind of statistical data. As a traditional method of spatial data expression, average distribution in every administrative region brings population data on a low spatial and temporal precision. Now, an accurate population data with high spatial resolution is becoming more and more important in regional planning, environment protection, policy making and rural-urban development. Spatial distribution of population data is becoming more important in GIS study area. In this article, the author reviewed the progress of research on spatial distribution of population. Under the support of GIS, correlative geographical theories and Grid data model, Remote Sensing data, terrain data, traffic data, river data, resident data, and social economic statistic were applied to calculate the spatial distribution of population in Fujian province, which includes following parts: (1) Simulating of boundary at township level. Based on access cost index, land use data, traffic data, river data, DEM, and correlative social economic statistic data, the access cost surface in study area was constructed. Supported by the lowest cost path query and weighted Voronoi diagram, DVT model (Demarcation of Villages and Towns) was established to simulate the boundary at township level in Fujian province. (2) Modeling of population spatial distribution. Based on the knowledge in geography, seven impact factors, such as land use, altitude, slope, residential area, railway, road, and river were chosen as the parameters in this study. Under the support of GIS, the relations of population distribution to these impact factors were analyzed quantificationally, and the coefficients of population density on pixel scale were calculated. Last, the model of population spatial distribution at township level was established through multiplicative fusion of population density coefficients and simulated boundary of towns. (3) Error test and analysis of population spatial distribution base on modeling. The author not only analyzed the numerical character of modeling error, but also its spatial distribution. The reasons of error were discussed.

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Access to the remote sensing data was increasing in Poland since 1989. This procccess had stimulating impact on scientific research in the scope of changes in the environment. Special attention should be given to the thermal imagery methods because of its information potential. Presented paper discusses the possibilities of using information from thermal images for detecting of places of illegal dumping of animal waste in the ground. On the basis of earlier survey and gathered data draft fl ight plan was created, covering the sorroundings of Śmiłowo (around 30 sq km). Theoretical thesis for the subject was an assumption that all disturbances of the ground and soil structure should give visible representation in both thermal and visible images. Moreover the process of decay of animal tissues should be the source of heat, which can be observed through thermal sensor. Several places of potential dumping of animal waste were selected. For detailed ground verifi cation eight of them were chosen. In these location geological drillings were performed and than analysis of the samples. Thermovision is a method with great potential for the monitoing of the environment, but its effectiveness depends on the access to another sources of geoinformation.

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Analysis of satellite remote sensing data has revealed changes in distribution of chlorophyll-a (Chl-a) and sea surface temperature (SST) in the Indian Ocean during the South Asian tsunami in December 2004. Chl-a data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-ofview Sensor (SeaWiFS) images were examined for the period from 1998 to 2005. Around the epicentre of the Sumatra earthquake, the Chl-a concentrationwas found to increase prior to the main event on 26 December 2004 and then decrease during the tsunami event, while a high SST (~30-31°C) was observed in and around the epicentral region. Chl-a concentrations in the coastal waters of the Southeast Asian countries were remarkably low during and after the tsunami. Similar but relatively small variations inChl-a and SST were observed during the second earthquake on 28 March 2005. Analysis of Chl-a, SST, wind and upwelling water has provided information for understanding the changes in Chl-a concentration during the tsunami. A very large offshore phytoplankton bloom (~300 km2) appeared to the southeast of Sri Lanka about 3 weeks after the tsunami; this might have been caused by a tropical storm that could be responsible for the enhancement of nutrients. © 2009 Taylor & Francis.

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Les recherches récapitulées dans cette thèse de doctorat ont porté sur les causes de l’organisation spatiale des végétations périodiques. Ces structures paysagères aux motifs réguliers, tachetés, tigrés ou labyrinthiques, d’échelle décamétrique à hectométrique, couvrant des étendues considérables sur au moins trois continents, constituent un cas d’école dans l’étude des processus endogènes présidant à l’hétérogénéité du couvert végétal. Ces structures prennent place sur un substrat homogène, mis à part la rétroaction du couvert lui-même, et sont marquées par des écotones abrupts et la persistance d’une proportion considérable de sol nu. Plusieurs modèles ont mis en avant l’existence possible d’un phénomène d’auto-organisation du couvert, qui verrait une structure d’ensemble émerger des interactions locales entre individus. Ces modèles se basent sur le jeu simultané de la consommation de la ressource (compétition) et de l’amélioration de l’un ou l’autre des éléments du bilan de la même ressource par le couvert (facilitation). La condition à l’existence d’une structure d’ensemble spatialement périodique et stable réside dans une différence entre la portée de la compétition (plus grande) et celle de la facilitation. L’apparition de ces structures est modulée par le taux de croissance biologique, qui est le reflet des contraintes extérieures telles que l’aridité, le pâturage ou la coupe de bois. Le modus operandi des interactions spatiales supposées entre individus reste largement à préciser.

Nos recherches ont été menées au sud-ouest de la République du Niger, à l’intérieur et dans les environs du parc Régional du W. Trois axes ont été explorés :(i) Une étude de la dépendance spatiale entre la structure de la végétation (biovolumes cartographiés) et les paramètres du milieu abiotique (relief, sol), sur base d’analyses spectrales et cross-spectrales par transformée de Fourier (1D et 2D). (ii) Une étude diachronique (1956, 1975 et 1996) à large échelle (3000 km²) de l’influence de l’aridité et des pressions d’origine anthropique sur l’auto-organisation des végétations périodiques, basée sur la caractérisation de la structure spatiale des paysages sur photos aériennes via la transformée de Fourier en 2D. (iii) Trois études portant sur les interactions spatiales entre individus :En premier lieu, via l’excavation des systèmes racinaires (air pulsé) ;Ensuite, par un suivi spatio-temporel du bilan hydrique du sol (blocs de gypse) ;Enfin, via le marquage de la ressource par du deutérium.

Nous avons ainsi pu établir que les végétations périodiques constituent bien un mode d’auto-organisation pouvant survenir sur substrat homogène et modulé par les contraintes climatiques et anthropiques. Un ajustement rapide entre l’organisation des végétations périodiques et le climat a pu être montrée en zone protégée. La superficie et l’organisation des végétations périodiques y ont tour à tour progressé et régressé en fonction d’épisodes secs ou humides. Par contre, en dehors de l’aire protégée, la possibilité d’une restauration du couvert semble fortement liée au taux d’exploitation des ressources végétales. Ces résultats ont d’importantes implications quant à la compréhension des interactions entre climat et écosystèmes et à l’évaluation de leurs capacités de charge. La caractérisation de la structure spatiale des végétations arides, notamment par la transformée de Fourier d’images HR, devrait être généralisée comme outil de monitoring de l’état de ces écosystèmes. Nos études portant sur les modes d’interactions spatiales ont permis de confirmer l’existence d’une facilitation à courte portée du couvert végétal sur la ressource. Cependant, cette facilitation ne semble pas s’exercer sur le terme du bilan hydrique traditionnellement avancé, à savoir l’infiltration, mais plutôt sur le taux d’évaporation (deux fois moindre à l’ombre des canopées). Ce mécanisme exclut l’existence de transferts diffusifs souterrains entre sols nu et fourrés. Des transferts inverses semblent d’ailleurs montrés par le marquage isotopique. L’étude du bilan hydrique et la cartographie du micro-relief, ainsi que la profondeur fortement réduite de la zone d’exploitation racinaire, jettent de sérieux doutes quant au rôle communément admis des transferts d’eau par ruissellement/diffusion de surface en tant que processus clé dans la compétition à distance entre les plantes. L’alternative réside dans l’existence d’une compétition racinaire de portée supérieure aux canopées. Cette hypothèse trouve une confirmation tant par les rhizosphères excavées, superficielles et étendues, que dans le marquage isotopique, montrant des contaminations d’arbustes situés à plus de 15 m de la zone d’apport. De même, l’étude du bilan hydrique met en évidence les influences simultanées et contradictoires (facilitation/compétition) des ligneux sur l’évapotranspiration.

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This PhD thesis gathers results of a research dealing with the causes of the spatial organisation of periodic vegetations. These landscape structures, featuring regular spotted, labyrinthine or banded patterns of decametric to hectometric scale, and extending over considerable areas on at least three continents, constitute a perfect study case to approach endogenous processes leading to vegetation heterogeneities. These patterns occur over homogeneous substratum, except for vegetation’s own feedbacks, and are marked by sharp ecotones and the persistence of a considerable amount of bare soil. A number of models suggested a possible case of self-organized patterning, in which the general structure would emerge from local interactions between individuals. Those models rest on the interplay of competitive and facilitative effects, relating to soil water consumption and to soil water budget enhancement by vegetation. A general necessary condition for pattern formation to occur is that negative interactions (competition) have a larger range than positive interactions (facilitation). Moreover, all models agree with the idea that patterning occurs when vegetation growth decreases, for instance as a result of reduced water availability, domestic grazing or wood cutting, therefore viewing patterns as a self-organised response to environmental constraints. However the modus operandi of the spatial interactions between individual plants remains largely to be specified.

We carried out a field research in South-West Niger, within and around the W Regional Park. Three research lines were explored: (i) The study of the spatial dependency between the vegetation pattern (mapped biovolumes) and the factors of the abiotic environment (soil, relief), on the basis of spectral and cross-spectral analyses with Fourier transform (1D and 2D). (ii) A broad scale diachronic study (1956, 1975, 1996) of the influence of aridity and human induced pressures on the vegetation self-patterning, based on the characterisation of patterns on high resolution remote sensing data via 2D Fourier transform. (iii) Three different approaches of the spatial interactions between individuals: via root systems excavation with pulsed air; via the monitoring in space and time of the soil water budget (gypsum blocks method); and via water resource labelling with deuterated water.

We could establish that periodic vegetations are indeed the result of a self-organisation process, occurring in homogeneous substratum conditions and modulated by climate and human constraints. A rapid adjustment between vegetation patterning and climate could be observed in protected zones. The area and patterning of the periodic vegetations successively progressed and regressed, following drier or wetter climate conditions. On the other hand, outside protected areas, the restoration ability of vegetation appeared to depend on the degree of vegetation resource exploitation. These results have important implications regarding the study of vegetation-climate interactions and the evaluation of ecosystems’ carrying capacities. Spatial pattern characterisation in arid vegetations using Fourier transform of HR remote sensing data should be generalised for the monitoring of those ecosystems. Our studies dealing with spatial interaction mechanisms confirmed the existence of a short range facilitation of the cover on water resource. However, this facilitation does not seem to act through the commonly accepted infiltration component, but rather on the evaporative rate (twice less within thickets). This mechanism excludes underground diffusive transfers between bare ground and vegetation. Inverse transfers were even shown by deuterium labelling. Water budget study and micro-elevation mapping, along with consistent soil shallowness, together cast serious doubts on the traditional mechanism of run-off/diffusion of surface water as a key process of the long range competition between plants. An alternative explanation lies in long range root competition. This hypothesis find support as well in the excavated root systems, shallow and wide, as in isotopic labelling, showing contaminations of shrubs located up to 15 m of the irrigated area. Water budget study also evidenced simultaneous contradictory effects (facilitation/competition) of shrubs on evapotranspiration.

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The crescent shaped Mascarene Plateau (southwestern Indian Ocean), some 2200 km in length, forms a partial barrier to the (predominantly westward) flow of the South Equatorial Current. Shallow areas of the Mascarene Plateau effectively form a large shelf sea without an associated coastline. Zooplankton sampling transects were made across the plateau and also the basin to the west, to investigate the role the partial interruption of flow has on zooplankton biomass and community structure over the region. Biomass data from Optical Plankton Counter (OPC) analysis, and variability in community structure from taxonomic analysis, appear to indicate that the obstruction by the plateau causes upwelling, nutrient enrichment and enhanced chlorophyll and secondary production levels downstream. The Mascarene Basin is clearly distinguishable from the ridge itself, and from the waters to the south and north, both in terms of size-distributed zooplankton biomass and community structure. Satellite remote sensing data, particularly remotely-sensed ocean colour imagery and the sea surface height anomaly (SSHA), indicate support for this hypothesis. A correlation was found between OPC biovolume and SSHA and sea surface temperature (SST), which may indicate the physical processes driving mesozooplankton variability in this area. Biomass values away from the influence of the ridge averaged 24 mg m-3, but downstream if the ridge biomass averaged 263 mg m-3. Copepods comprised 60% of the mean total organisms. Calanoid copepods varied considerably between regions, being lowest away from the influence of the plateau, where higher numbers of the cyclopoid copepods Oithona spp., Corycaeus spp. and Oncaea spp., and the harpacticoid Microsetella spp. were found.

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Characteristics of the spring and fall phytoplankton blooms in spawning areas on the Scotian Shelf, Canada, were estimated from remote sensing data. These blooms, along with anomalies in the North Atlantic Oscillation, were used to explain variation in the recruitment of 4 populations of cod and haddock. We tested the effects of the timing of the bloom using the chlorophyll a (chl a) signal, the maximum amount of chl a, the timing of the diatom bloom, and the maximum relative dominance of diatoms on the recruitment (to Age 1) of cod and haddock on the Scotian Shelf. Models were run separately for the effects of the spring and fall blooms. Only 3 of 10 models tested (0-lag) explained significant (80 to 92%) variation in recruitment. However, the performance of these models was not consistent across populations or species, suggesting that generalities about how spring and fall phytoplankton blooms affect recruitment cannot yet be made. The differences among models suggest that fish larvae are probably adapted locally to food production and thus indirectly to the characteristics of the phytoplankton bloom, which in turn are influenced by regional (meso-scale) oceanographic conditions.

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Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

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The presence of a quasi-stationary anticyclonic eddy within the southeastern Bay of Biscay (centred around 44°30′N-4°W) has been reported on various occasions in the bibliography. The analysis made in this study for the period 2003–2010, by using in situ and remote sensing measurements and model results shows that this mesoscale coherent structure is present almost every year from the end of winter-beginning of spring, to the beginning of fall. During this period it remains in an area limited to the east by the Landes Plateau, to the west by Le Danois Bank and Torrelavega canyon and to the northwest by the Jovellanos seamount. All the observations and analysis made in this contribution, suggest that this structure is generated between Capbreton and Torrelavega canyons. Detailed monitoring from in situ and remote sensing data of an anticyclonic quasi-stationary eddy, in 2008, shows the origin of this structure from a warm water current located around 43°42′N-3°30′W in mid-January. This coherent structure is monitored until August around the same area, where it has a marked influence on the Sea Level Anomaly, Sea Surface Temperature and surface Chlorophyll-a concentration. An eddy tracking method, applied to the outputs of a numerical model, shows that the model is able to reproduce this type of eddy, with similar 2D characteristics and lifetimes to that suggested by the observations and previous works. This is the case, for instance, of the simulated MAY04 eddy, which was generated in May 2004 around Torrelavega canyon and remained quasi-stationary in the area for 4 months. The diameter of this eddy ranged from 40 to 60 km, its azimuthal velocity was less than 20 cm s−1, its vertical extension reached 3000–3500 m depth during April and May and it was observed to interact with other coherent structures.

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The presence of a quasi-stationary anticyclonic eddy within the southeastern Bay of Biscay (centred around 44°30′N-4°W) has been reported on various occasions in the bibliography. The analysis made in this study for the period 2003–2010, by using in situ and remote sensing measurements and model results shows that this mesoscale coherent structure is present almost every year from the end of winter-beginning of spring, to the beginning of fall. During this period it remains in an area limited to the east by the Landes Plateau, to the west by Le Danois Bank and Torrelavega canyon and to the northwest by the Jovellanos seamount. All the observations and analysis made in this contribution, suggest that this structure is generated between Capbreton and Torrelavega canyons. Detailed monitoring from in situ and remote sensing data of an anticyclonic quasi-stationary eddy, in 2008, shows the origin of this structure from a warm water current located around 43°42′N-3°30′W in mid-January. This coherent structure is monitored until August around the same area, where it has a marked influence on the Sea Level Anomaly, Sea Surface Temperature and surface Chlorophyll-a concentration. An eddy tracking method, applied to the outputs of a numerical model, shows that the model is able to reproduce this type of eddy, with similar 2D characteristics and lifetimes to that suggested by the observations and previous works. This is the case, for instance, of the simulated MAY04 eddy, which was generated in May 2004 around Torrelavega canyon and remained quasi-stationary in the area for 4 months. The diameter of this eddy ranged from 40 to 60 km, its azimuthal velocity was less than 20 cm s−1, its vertical extension reached 3000–3500 m depth during April and May and it was observed to interact with other coherent structures.

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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.

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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.