To provide a complete local monitoring of the state of an unsaturated soil sample during triaxial testing, a local water content measurement device was adapted to a triaxial device comprising the measurement of local displacements (Hall effect transducers) and suction (High capacity transducer). Water content was locally monitored by means of a resistivity probe. The water content/resistivity calibration curves of an intact natural unsaturated loess from Northern France extracted by block sampling at two depths (1 and 3.3 m) were carefully determined, showing good accuracy and repeatability. The validity of two models giving the resistivity of unsaturated soils with respect to their water content was examined.

Surveying techniques such as Terrestrial Laser Scanner have recently been used to measure surface changes via 3D point cloud (PC) comparison. Two types of approaches have been pursued: 3D tracking of homologous parts of the surface to compute a displacement field, and distance calculation between two point clouds when homologous parts cannot be defined. This study deals with the second approach, typical of natural surfaces altered by erosion, sedimentation or vegetation between surveys. Current comparison methods are based on a closest point distance or require at least one of the PC to be meshed with severe limitations when surfaces present roughness elements at all scales. We introduce a new algorithm performing a direct comparison of point clouds in 3D. Surface normals are first estimated in 3D at a scale consistent with the local surface roughness. The measurement of the mean change along the normal direction is then performed with an explicit calculation of a confidence interval. Comparison with existing methods demonstrates the higher accuracy of our approach, as well as an easier workflow due to the absence of surface meshing or DEM generation. Application of the method in a rapidly eroding meandering bedrock river (Rangitikei river canyon) illustrates its ability to handle 3D differences in complex situations (flat and vertical surfaces on the same scene), to reduce uncertainty related to point cloud roughness by local averaging and to generate 3D maps of uncertainty levels. Combined with mm-range local georeferencing of the point clouds, levels of detection down to 6 mm can be routinely attained in situ over ranges of 50 m. We provide evidence for the self-affine behavior of different surfaces. We show how this impacts the calculation of normal vectors and demonstrate the scaling behavior of the level of change detection.

Topical observations of the thermosphere at altitudes below $200 \, km$ are of great benefit in advancing the understanding of the global distribution of mass, composition, and dynamical responses to geomagnetic forcing, and momentum transfer via waves. The perceived risks associated with such low altitude and short duration orbits has prohibited the launch of Discovery-class missions. Miniaturization of instruments such as mass spectrometers and advances in the nano-satellite technology, associated with relatively low cost of nano-satellite manufacturing and operation, open an avenue for performing low altitude missions. The time dependent coefficients of a second order non-homogeneous ODE which describes the motion have a double periodic shape. Hence, they will be approximated using Jacobi elliptic functions. Through a change of variables the original ODE will be converted into Hill's ODE for stability analysis using Floquet theory. We are interested in how changes in the coefficients of the ODE affect the stability of the solution. The expected result will be an allowable range of parameters for which the motion is dynamically stable. A possible extension of the application is a computational tool for the rapid evaluation of the stability of entry or re-entry vehicles in rarefied flow regimes and of satellites flying in relatively low orbits.

Several methods exist for surveying the dunes and estimate their migration rate. Among methods suitable for the macroscopic scale, the use of the satellite images available on Google Earth is a convenient resource, in particular because of its time series. Some examples of the use of this feature of Google Earth are here proposed.

The geoid is the true physical figure of the Earth, a particular equipotential surface of the gravity field of the Earth that accounts for the effect of all subsurface density variations. Its shape approximates best (in the sense of least squares) the mean level of oceans, but the geoid is more difficult to determine over continents. Satellite missions carry out distance measurements and derive the gravity field to provide geoid maps over the entire globe. However, they require calibration and extensive computations including integration, which is a non-unique operation. Here we propose a direct method and a new tool that directly measures geopotential differences on continents using atomic clocks. General Relativity Theory predicts constant clock rate at sea level, and faster (resp. slower) clock rate above (resp. below) sea level. The technology of atomic clocks is on the doorstep of reaching an accuracy level in clock rate that is equivalent to 1 cm in determining equipotential surface (including geoid) height. We discuss the value and future applicability of such measurements including direct geoid mapping on continents, and joint gravity and geopotential surveying to invert for subsurface density anomalies. Our synthetic calculations show that the geoid perturbation caused by a 1.5 km radius sphere with 20% density anomaly buried at 2 km depth in the crust of the Earth is already detectable by atomic clocks of achievable accuracy. Therefore atomic clock geopotential surveys, used together with relative gravity data to benefit from their different depth sensitivities, can become a useful tool in mapping density anomalies within the Earth.

The climate change attribution problem is addressed using empirical decomposition. Cycles in solar motion and activity of 60 and 20 years were used to develop an empirical model of Earth temperature variations. The model was fit to the Hadley global temperature data up to 1950 (time period before anthropogenic emissions became the dominant forcing mechanism), and then extrapolated from 1951 to 2009. After subtraction of the model, the residuals showed an approximate linear upward trend after 1942. Herein we assume that the residual upward warming observed during the second half of the 20th century has been mostly induced by a worldwide rapid increase of anthropogenic emissions, urbanization and land use change. The warming observed before 1942 is relatively small and it is assumed to have been mostly naturally induced by a climatic recovery since the Little Ice Age of the 17th century and the Dalton Minimum at the beginning of the 19th century. The resulting full natural plus anthropogenic model fits the entire 160 year record very well. Residual analysis does not provide any evidence for a substantial cooling effect due to sulfate aerosols from 1940 to 1970. The cooling observed during that period may be due to a natural 60-year cycle, which is visible in the global temperature since 1850 and has been observed also in numerous multisecular climatic records. New solar activity proxy models are developed that suggest a mechanism for both the 60-year climate cycle and a portion of the long-term warming trend. Our results suggest that because current models underestimate the strength of natural multidecadal cycles in the temperature records, the anthropogenic contribution to climate change since 1970 should be around half of that previously claimed by the IPCC [2007]. A 21st Century forecast suggests that climate may warm less than 1^{\circ}C by 2100.

We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function. We derive mathematically the principle of area-equivalence; wherein two alternative GMRs have an equivalent influence on the hazard if these GMRs have equivalent area functions. This includes local biases. An interpretation of the difference between these GMRs (an actual and a modeled one) as a random component leads to a general overestimation of residual variance and hazard. Beside this, we discuss important aspects of classical approaches and discover discrepancies with the state of the art of stochastics and statistics (model selection and significance, test of distribution assumptions, extreme value statistics). We criticize especially the assumption of logarithmic normally distributed residuals of maxima like the peak ground acceleration (PGA). The natural distribution of its individual random component (equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized extreme value. We show by numerical researches that the actual distribution can be hidden and a wrong distribution assumption can influence the PSHA negatively as the negligence of area equivalence does. Finally, we suggest an estimation concept for GMRs of PSHA with a regression-free variance estimation of the individual random component. We demonstrate the advantages of event-specific GMRs by analyzing data sets from the PEER strong motion database and estimate event-specific GMRs. Therein, the majority of the best models base on an anisotropic point source approach. The residual variance of logarithmized PGA is significantly smaller than in previous models. We validate the estimations for the event with the largest sample by empirical area functions. etc.

The availability of hyperspectral infrared remote sensing instruments, like AIRS and IASI, on board of Earth observing satellites opens the possibility of obtaining high vertical resolution atmospheric profiles. We present an objective and simple technique to derive the parameters used in the optimal estimation method that retrieve atmospheric states from the spectra. The retrievals obtained in this way are optimal in the sense of providing the best possible validation statistics obtained from the difference between retrievals and a chosen calibration/validation dataset of atmospheric states. This is demonstrated analytically. To illustrate this result several real world examples using IASI retrievals fine tuned to ECMWF analyses are shown. The analytical equations obtained give further insight into the various contributions to the biases and errors of the retrievals and the consequences of using other types of fine tuning. Retrievals using IASI show an error of 0.9 to 1.9 K in temperature and below 6.5 K in humidity dew point temperature in the troposphere on the vertical radiative transfer model pressure grid (RTIASI-4.1), which has a vertical spacing between 300 and 400 m. The more accurately the calibration dataset represents the true state of the atmosphere, the better the retrievals will be when compared to the true states.

The understanding of electrokinetics for unsaturated conditions is crucial for numerous of geophysical data interpretation. Nevertheless, the behaviour of the streaming potential coefficient C as a function of the water saturation Sw is still discussed. We propose here to model both the Richards' equation for hydrodynamics and the Poisson's equation for electrical potential for unsaturated conditions using 1-D finite element method. The equations are first presented and the numerical scheme is then detailed for the Poisson's equation. Then, computed streaming potentials (SPs) are compared to recently published SP measurements carried out during drainage experiment in a sand column. We show that the apparent measurement of DV / DP for the dipoles can provide the SP coefficient in these conditions. Two tests have been performed using existing models for the SP coefficient and a third one using a new relation. The results show that existing models of unsaturated SP coefficients C(Sw) provide poor results in terms of SP magnitude and behaviour. We demonstrate that the unsaturated SP coefficient can be until one order of magnitude larger than Csat, its value at saturation. We finally prove that the SP coefficient follows a non-monotonous behaviour with respect to water saturation. Key words: Electrical properties; Electromagnetic theory; Hydrogeophysics; Hydrology; Permeability and porosity; electrokinetic; streaming potential; self-potential; water content; water saturation; unsaturated condition; finite element modeling

Properties of data are frequently seen to vary depending on the sampled situations, which usually changes along a time evolution or owing to environmental effects. One way to analyze such data is to find invariances, or representative features kept constant over changes. The aim of this paper is to identify one such feature, namely interactions or dependencies among variables that are common across multiple datasets collected under different conditions. To that end, we propose a common substructure learning (CSSL) framework based on a graphical Gaussian model. We further present a simple learning algorithm based on the Dual Augmented Lagrangian and the Alternating Direction Method of Multipliers. We confirm the performance of CSSL over other existing techniques in finding unchanging dependency structures in multiple datasets through numerical simulations on synthetic data and through a real world application to anomaly detection in automobile sensors.

The K index was devised by Bartels et al. (1939) to provide an objective monitoring of irregular geomagnetic activity. The K index was then routinely used to monitor the magnetic activity at permanent magnetic observatories as well as at temporary stations. The increasing number of digital and sometimes unmanned observatories and the creation of INTERMAGNET put the question of computer production of K at the centre of the debate. Four algorithms were selected during the Vienna meeting (1991) and endorsed by IAGA for the computer production of K indices. We used one of them (FMI algorithm) to investigate the impact of the geomagnetic data sampling interval on computer produced K values through the comparison of the computer derived K values for the period 2009, January 1st to 2010, May 31st at the Port-aux-Francais magnetic observatory using magnetic data series with different sampling rates (the smaller: 1 second; the larger: 1 minute). The impact is investigated on both 3-hour range values and K indices data series, as a function of the activity level for low and moderate geomagnetic activity.

Many modern data mining applications are concerned with the analysis of datasets in which the observations are described by paired high-dimensional vectorial representations or "views". Some typical examples can be found in web mining and genomics applications. In this article we present an algorithm for data clustering with multiple views, Multi-View Predictive Partitioning (MVPP), which relies on a novel criterion of predictive similarity between data points. We assume that, within each cluster, the dependence between multivariate views can be modelled by using a two-block partial least squares (TB-PLS) regression model, which performs dimensionality reduction and is particularly suitable for high-dimensional settings. The proposed MVPP algorithm partitions the data such that the within-cluster predictive ability between views is maximised. The proposed objective function depends on a measure of predictive influence of points under the TB-PLS model which has been derived as an extension of the PRESS statistic commonly used in ordinary least squares regression. Using simulated data, we compare the performance of MVPP to that of competing multi-view clustering methods which rely upon geometric structures of points, but ignore the predictive relationship between the two views. State-of-art results are obtained on benchmark web mining datasets.

Slow Feature Analysis (SFA) extracts features representing the underlying causes of changes within a temporally coherent high-dimensional raw sensory input signal. Our novel incremental version of SFA (IncSFA) combines incremental Principal Components Analysis and Minor Components Analysis. Unlike standard batch-based SFA, IncSFA adapts along with non-stationary environments, is amenable to episodic training, is not corrupted by outliers, and is covariance-free. These properties make IncSFA a generally useful unsupervised preprocessor for autonomous learning agents and robots. In IncSFA, the CCIPCA and MCA updates take the form of Hebbian and anti-Hebbian updating, extending the biological plausibility of SFA. In both single node and deep network versions, IncSFA learns to encode its input streams (such as high-dimensional video) by informative slow features representing meaningful abstract environmental properties. It can handle cases where batch SFA fails.

Ecologists and conservation biologists need to identify the relative importance of species to make sound management decisions and effectively allocate scarce resources. We introduce a new method, termed environ centrality, to determine the relative importance of a species in an ecosystem network with respect to ecosystem energy--matter exchange. We demonstrate the uniqueness of environ centrality by comparing it to other common centrality metrics and then show its ecological significance. Specifically, we tested two hypotheses on a set of 50 empirically-based ecosystem network models. The first concerned the distribution of centrality in the community. We hypothesized that the functional importance of species would tend to be concentrated into a few dominant species followed by a group of species with lower, more even importance as is often seen in dominance--diversity curves. Second, we tested the systems ecology hypothesis that indirect relationships homogenize the functional importance of species in ecosystems. Our results support both hypotheses and highlight the importance of detritus and nutrient recyclers such as fungi and bacteria in generating the energy--matter flow in ecosystems. Our homogenization results suggest that indirect effects are important in part because they tend to even the importance of species in ecosystems. A core contribution of this work is that it creates a formal, mathematical method to quantify the importance species play in generating ecosystem activity by integrating direct, indirect, and boundary effects in ecological systems.

Understanding how an extinction event affects ecosystem is fundamental to biodiversity conservation. For this reason, food web response to species loss has been investigated in several ways in the last years. Several studies focused on secondary extinction due to biodiversity loss in a bottom-up perspective using in-silico extinction experiments in which a single species is removed at each step and the number of secondary extinctions is recorded. In these binary simulations a species goes secondarily extinct if it loses all its resource species, that is, when the energy intake is zero. This pure topological statement represents the best case scenario. In fact a consumer species could go extinct losing a certain fraction of the energy intake and the response of quantitative food webs to node loss could be very different with respect to simple binary predictions. The goal of this paper is to analyze how patterns of secondary extinctions change when higher species sensitivity are included in the analyses. In particular, we explored how food web secondary extinction, triggered by the removal of most connected nodes, varies as a function of the energy intake threshold assumed as the minimum needed for species persistence. As we will show, a very low increase of energy intake threshold stimulates a disproportionate growth of secondary extinction.

In recent years, a large number of geosynchronous satellites are being planned to provide augmentation services for enhancing the precision to global positioning systems, e.g., GPS, in applications such as aircraft landing. In this paper, we present a scheme for co-locating passive satellite observational facilities with a radio astronomy facility to open a new possibility of providing valuable data for radio astronomical imaging, ionospheric studies and satellite orbit estimation.

The most famous geoglyphs of Peru are the "Nazca Lines". Considered as one of the mysteries of the ancient world, they have been included among the UNESCO World Heritage Sites. Located in a large region between the towns of Nazca and Palpa, these lines create shapes of animals ranging in size up to 300 m. The archaeological site is under investigation with remote science technologies.

Groundwater age has become a fundamental concept in groundwater hydrology, but ages originating from isotopic analyses are still identified with a lack of clarity and using models that occasionally are unrealistic. If the effect of advection and dispersion on water ages has already been extensively identified, very few studies address the reliability of using radiometric ages as derived from isotopic data to estimate aquifer properties such as average velocities. Using simple one-dimensional and two-dimensional analytical solutions for single-site and two-sites mobile-immobile systems, we compare the radiometric ages to the mean ages (or residence times) as deduced from a direct, physically-based simulation approach (using the mean age equation), and show that the competition between isotope decay rate and dispersion coefficient can generate important discrepancies between the two types of ages. A correction for the average apparent velocity originating from apparent isotopic ages is additionally provided. The particular case of the Tritium age dating method is also addressed, and a numerical example is finally given for illustrating the analysis considering a more complex and heterogeneous aquifer system. Our results suggest that age definitions based on the radioactivity of isotopes may not be representative for the mean age of the sample or for the groundwater velocity at given locations, and may not always be suitable for constraining the calibration of hydrogeological models.

In the territory of the Campania region (southern Italy), critical rainfall events periodically trigger dangerous fast slope movements involving ashy and pyroclastic soils originated by the explosive phases of the Mt. Somma-Vesuvius volcano and deposited along the surrounding mountain ranges. In this paper, an integration of engineering-geological and geophysical measurements is presented to characterize unsaturated pyroclastic samples collected in a test area on the Sarno Mountains (Salerno and Avellino provinces, Campania region). The laboratory analyses were aimed at defining both soil water retention and electrical resistivity curves versus water content. From the matching of the experimental data, a direct relationship between electrical resistivity and matric suction is retrieved for the investigated soil horizons typical of a ash-fall pyroclastic succession. The obtained relation turns out to be helpful in characterizing soils up to close saturation, which is a critical condition for the trigger of slope failure. In such a regime, the water content and the matric suction have small variations, while electrical resistivity variations can be appreciated in a larger range of values. For this reason, besides suction measurements on very small soil volumes through classical tensiometers, our analyses suggest the direct monitoring of in-situ electrical resistivity values as an effective tool to recognise the hydrological state of larger and more representative soil volumes and to improve early warning of dangerous slope movements.

An arid land, known as the Syrian Desert, is covering a large part of the Middle East. In the past, this harsh environment, characterized by huge lava fields, the "harraat", was considered as a barrier between Levant and Mesopotamia. When we observe this desert from space, we discover that it is crossed by some stone structures, the "desert kites", which were the Neolithic traps for the game. Several stone circles are visible too, as many Stonehenge sites dispersed in the desert landscape.

The Belleplaine test site, located in the island of Guadeloupe (French Lesser Antilles) includes a three-accelerometer vertical array, designed for liquefac- tion studies. The seismic response of the soil column at the test site is computed using three methods: the spectral ratio method using the vertical array data, a numerical method using the geotechnical properties of the soil column, and an operative fre- quency domain decomposition (FDD) modal analysis method. The Belleplaine test site is characterized by a mangrove layer overlaid by a stiff sandy deposit. This con- figuration is widely found at the border coast of the Caribbean region, which is exposed to high seismic hazard. We show that the buried mangrove layer plays the role of an isolation system equivalent to those usually employed in earthquake engineering aimed at reducing the seismic shear forces by reducing the internal stress within the structure. In our case, the flexibility of the mangrove layer reduces the distortion and the stress in the sandy upper layer, and consequently reduces the potential of liquefaction of the site.

We propose the use of image processing to enhance the Google Maps of some archaeological areas of Egypt. In particular we analyse that place which is considered the cradle of pyramids, where it was announced the discovery of a new pyramid by means of an infrared remote sensing.

A recent announcement of some pyramids, buried under the sand of Egypt and discovered by means of infrared remote sensing, renewed the interest on the archaeological surveys aided by satellites. Here we propose the use of images, obtained from those of Google Maps after some processing to enhance their details, to locate archaeological remains in Egypt.

Global warming is affecting our Earth's environment. For example, sea level is rising with thermal expansion of water and fresh water input from the melting of continental ice sheets due to human-induced global warming. However, observing and modeling Earth's surface change has larger uncertainties in the changing rate and the scale and distribution of impacts due to the lack of direct measurements. Nowadays, the Earth observation from space provides a unique opportunity to monitor surface mass transfer and deformations related to climate change, particularly the global positioning system (GPS) and the Gravity Recovery and Climate Experiment (GRACE) with capability of estimating global land and ocean water mass. In this paper, the Earth's surface fluid variations and deformations are derived and analyzed from global GPS and GRACE measurements. The fluids loading deformation and its interaction with Earth system, e.g., Earth Rotation, are further presented and discussed.

Paleoclimate data help us assess climate sensitivity and potential human-made climate effects. We conclude that Earth in the warmest interglacial periods of the past million years was less than 1{\deg}C warmer than in the Holocene. Polar warmth in these interglacials and in the Pliocene does not imply that a substantial cushion remains between today's climate and dangerous warming, but rather that Earth is poised to experience strong amplifying polar feedbacks in response to moderate global warming. Thus goals to limit human-made warming to 2{\deg}C are not sufficient - they are prescriptions for disaster. Ice sheet disintegration is nonlinear, spurred by amplifying feedbacks. We suggest that ice sheet mass loss, if warming continues unabated, will be characterized better by a doubling time for mass loss rate than by a linear trend. Satellite gravity data, though too brief to be conclusive, are consistent with a doubling time of 10 years or less, implying the possibility of multi-meter sea level rise this century. Observed accelerating ice sheet mass loss supports our conclusion that Earth's temperature now exceeds the mean Holocene value. Rapid reduction of fossil fuel emissions is required for humanity to succeed in preserving a planet resembling the one on which civilization developed.

Motivation: Capillary electrophoresis (CE) of nucleic acids is a workhorse technology underlying high-throughput genome analysis and large-scale chemical mapping for nucleic acid structural inference. Despite the wide availability of CE-based instruments, there remain challenges in leveraging their full power for quantitative analysis of RNA and DNA structure, thermodynamics, and kinetics. In particular, the slow rate and poor automation of available analysis tools have bottlenecked a new generation of studies involving hundreds of CE profiles per experiment. Results: We propose a computational method called high-throughput robust analysis for capillary electrophoresis (HiTRACE) to automate the key tasks in large-scale nucleic acid CE analysis, including the profile alignment that has heretofore been a rate-limiting step in the highest throughput experiments. We illustrate the application of HiTRACE on thirteen data sets representing 4 different RNAs, three chemical modification strategies, and up to 480 single mutant variants; the largest data sets each include 87,360 bands. By applying a series of robust dynamic programming algorithms, HiTRACE outperforms prior tools in terms of alignment and fitting quality, as assessed by measures including the correlation between quantified band intensities between replicate data sets. Furthermore, while the smallest of these data sets required 7 to 10 hours of manual intervention using prior approaches, HiTRACE quantitation of even the largest data sets herein was achieved in 3 to 12 minutes. The HiTRACE method therefore resolves a critical barrier to the efficient and accurate analysis of nucleic acid structure in experiments involving tens of thousands of electrophoretic bands.

The project consists to determine, mathematically, the trajectory that will take an artificial satellite to fight against the air resistance. During our work, we had to consider that our satellite will crash to the surface of our planet. We started our study by understanding the system of forces that are acting between our satellite and the earth. In this work, we had to study the second law of Newton by taking knowledge of the air friction, the speed of the satellite which helped us to find the equation that relates the trajectory of the satellite itself, its speed and the density of the air depending on the altitude. Finally, we had to find a mathematic relation that links the density with the altitude and then we had to put it into our movement equation. In order to verify our model, we'll see what happens if we give a zero velocity to the satellite.

The course of the Nile in northern Sudan follows a contorted path through bedrocks, creating the Great Bend. Few years ago, the satellite images showed a fertile strip of land with villages, where paleochannels of the river hosted many fields with cultivations and archaeological sites. Now, a huge part of this valley is under the waters of Merowe Dam reservoir. Comparing the images of the region before and after the dam gates were closed, we can see that the reservoir created itself through flooding the paleochannels.

The Gravity Recovery and Climate Experiment (GRACE) provides quantitative measures of terrestrial water storage (TWS) change. GRACE data show a significant decrease in TWS in the lower (southern) La Plata river basin of South America over the period 2002-2009, consistent with recognized drought conditions in the region. GRACE data reveal a detailed picture of temporal and spatial evolution of this severe drought event, which suggests that the drought began in lower La Plata in around austral spring 2008 and then spread to the entire La Plata basin and peaked in austral fall 2009. During the peak, GRACE data show an average TWS deficit of ~12 cm (equivalent water layer thickness) below the 7 year mean, in a broad region in lower La Plata. GRACE measurements are consistent with accumulated precipitation data from satellite remote sensing and with vegetation index changes derived from Terra satellite observations. The Global Land Data Assimilation System model captures the drought event but underestimates its intensity. Limited available groundwater-level data in southern La Plata show significant groundwater depletion, which is likely associated with the drought in this region. GRAC-observed TWS change and precipitation anomalies in the studied region appear to closely correlate with the ENSO climate index, with dry and wet seasons corresponding to La Ni\~na and El Ni\~no events, respectively.

The Great Bend of the river Nile contains the Bayuda region with its volcanic core. Along the river, a fertile strip of land has attracting human settlement for thousands of years and is then rich of archaeological sites. The distribution of the sites near the Nile can be detected using Google Maps imagery. We can see many area covered by small mounds, probably burial sites. Some of the archaeological places are currently under the water of the Merowe Dam. With the satellite imagery, we have a portrait of the area close the dam before the closing of its gates.

The Arabia Shield has a volcanic nature inside. A region of the Western Saudi Arabia is in fact covered with vast fields of lava known as harraat. These lands are spotted by many stone circles and other quite interesting archaeological remains of the Neolithic period, such as the "desert kites", the hunters used to guide the game across the harrah in some corrals. With Google Maps, we can observe both sceneries, the volcanic nature of the land and a portrait of Arabia during the Neolithic times.

Summary: In the past decade both scientists and laymen have probably heard at least once through the newspapers, TV and Internet that a new asteroid has been discovered with non-zero (sometimes "high") probability of collision with the Earth in the near future. Since early 2000's, such probabilities are routinely calculated by two impact monitoring systems (one in the US, the other in Europe) on preliminary orbits of newly discovered Near Earth Asteroids (NEAs), and are regularly updated whenever additional new astrometric observations for each threatening object become available. A typical pattern is that as the orbit becomes more precisely determined, impact probability often increases initially, but then turns around and decreases until it falls to zero, or some very low number. In the present study we define a probability measure which provides a simple tool to evaluate from the very beginning the chance that the impact probability calculated by monitoring systems for a threatening object will reach unity at the end of the overall process of orbit refinement. We stress that this chance is independent of the specific (fluctuating) value of the probability calculated by the monitoring systems. In a precise sense, which should be clear throughout the paper, the concrete impact probability of a newly discovered asteroid is not that given by the monitoring systems.

Biodiversity widely observed in ecological systems is attributed to the dynamical balance among the competing species. The time-varying populations of the interacting species are often captured rather well by a set of deterministic replicator equations in the evolutionary game theory. However, intrinsic fluctuations arisen from the discreteness of populations lead to stochastic derivations from the smooth evolution trajectories. The role of these fluctuations is shown to be critical at causing extinction and deteriorating the biodiversity of ecosystem. We use children's rock-paper-scissors game to demonstrate how the intrinsic fluctuations arise from the discrete populations and why the biodiversity of the ecosystem decays exponentially, disregarding the detail parameters for competing mechanism and initial distributions. The dissipative trend in biodiversity can be analogized to the gradual erosion of kinetic energy of a moving particle due to air drag or fluid viscosity. The dissipation-fluctuation theorem in statistical physics seals the fate of these originally conserved quantities. This concept in physics can be generalized to scrutinize the errors that might be incurred in the ecological, biological, and quantitative economic modeling for which the ingredients are all discrete in number.

Maps are used to describe far-off places . It is an aid for navigation and military strategies. Mapping of the lands are important and the mapping work is based on (i). Natural resource management & development (ii). Information technology ,(iii). Environmental development ,(iv). Facility management and (v). e-governance. The Landuse / Landcover system espoused by almost all Organisations and scientists, engineers and remote sensing community who are involved in mapping of earth surface features, is a system which is derived from the united States Geological Survey (USGS) LULC classification system. The application of RS and GIS involves influential of homogeneous zones, drift analysis of land use integration of new area changes or change detection etc.,National Remote Sensing Agency(NRSA) Govt. of India has devised a generalized LULC classification system respect to the Indian conditions based on the various categories of Earth surface features , resolution of available satellite data, capabilities of sensors and present and future applications. The profusion information of the earth surface offered by the high resolution satellite images for remote sensing applications. Using change detection methodologies to extract the target changes in the areas from high resolution images and rapidly updates geodatabase information processing.Traditionally, classification approaches have focused on per-pixel technologies. Pixels within areas assumed to be automatically homogeneous are analyzed independently.

Recent studies demonstrate that chlorophyll a (chl a) concentrations in the surface ocean can be significantly enhanced due to typhoons. The present study investigated chl a concentrations in the middle of the South China Sea (SCS) from 1997-2007. Only the Category1 (minimal) Typhoon Hagibis (2007) had a notable effect on the chl a concentrations. Typhoon Hagibis had a strong upwelling potential due to its location near the equator, and the forcing time of the typhoon (>82 h) was much longer than the geostrophic adjustment time (~63 h). The higher upwelling velocity and the longer forcing time increased the depth of the mixed-layer, which consequently induced a strong phytoplankton bloom that accounted for about 30% of the total annual chl a concentration in the middle of the SCS. The implication is that the forcing time of a typhoon should be long enough to establish a strong upwelling and consequently for the induction of significant upper ocean responses.

We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive an approximate maximum-likelihood procedure for parameter estimation, which relies on variational methods to handle intractable posterior expectations. Prediction problems motivate this research: we use the fitted model to predict response values for new documents. We test sLDA on two real-world problems: movie ratings predicted from reviews, and the political tone of amendments in the U.S. Senate based on the amendment text. We illustrate the benefits of sLDA versus modern regularized regression, as well as versus an unsupervised LDA analysis followed by a separate regression.

An analytical method is proposed in this work for verification whether an artificial earth satellite during its orbital motion passes over a region of the earth surface. The method is based on undisturbed Keppler's approximation of the orbit and approximation of the region by a circular segment S. In order to define the situational condition, a conic surface is used with apex in the earth centre, cutting out the circular segment. The tangents of the conical surface with Keppler's plane determine the time intervals in which the satellite trace on the earth surface occurs inside the segment S. The transformation of these tangents in the plane of Keppler's orbit and the determination of their crossing points with Keppler's ellipse lies in the basis of the examined method.

This study presents theoretical investigation of the effects of particle and molecular extinction in horizontal remote sensing near the ground for several visibilities at UV wavelengths by neglecting the spatial inhomogeneity of aerosol in the atmosphere and taking into account the dependence of refracting on air temperature and pressure. Due to weak attenuation of oxygen and other gaseous atmospheric constituents in this region, we have only considered the effect of ozone in calculation. The results are important to estimate systematic errors in measuring gas concentration introduced by large wavelength separation in UV-DIAL. The total attenuation (km-1) at wavelengths is listed in the form of a table from 200 to 400 nm for several values of visibilities. It is found the aerosol attenuation in UV region varies quite smoothly with wavelength and therefore systematic error caused by aerosol scattering is negligible in remote sensing by UV-DIAL even with large wavelength separation. Moreover, it has been found that only aerosol extinction is dominant in lidar remote sensing in the lower atmosphere in UV region. In large altitude that aerosol concentration is lower; the molecular scattering is important especially for wavelengths larger than 310 nm.

Concerns about biodiversity and the long-term stability of forest ecosystems have lead to changing attitudes with respect to plantations. These artificial communities are ubiquitous, yet provide reduced habitat value in comparison to their naturally established counterparts, key factors being high density, homogeneous spatial structure, and their even-sized/aged nature. Transformation (manipulation of plantations to produce stands more reminiscent of natural ones) represents a major challenge for forest managers, and the shift from even- to uneven-aged stand management is far from simple. Tree species' attributes, too, vary dramatically. This study aims to identify generic aspects of forest population dynamics, in order to understand the temporal evolution of single species forest stands from an initial plantation lattice structure, into an ``old-growth'' state. This is achieved using a size-structured model, which implements simple rules to simulate the growth and fate of individuals in a spatial arena. We parameterise and discuss model behaviour in the context of available plantation and semi-natural data from Caledonian Scots Pine stands. We move on to illustrate the use of the model in predicting the outcome of silviculture, and discuss results in the context of stand transformation.

A good correlation between the growth rate of the cave speleothems and the annual precipitation at the cave site allow quantitative reconstruction of the precipitation. Measuring the growth rate of a speleothem from Duhlata Cave, Bulgaria we found that around 7500 B.P. the speleothem growth rate (averaged for 120 years) exceeds 53 times its recent value suggesting that enormous precipitation flooded the Black Sea basin at that time. Its possible connection with the Bible (Noahs) Flood is discussed. We propose a possible mechanism of the flooding of the Black Sea during the Flood involving production of a super- Tsunami by pushing of the Black Sea water towards the Crimea cost by Mediterranean waters. We propose also an Astronomical Theory of the origin of the Bible Flood. We attribute higher water evaporation and rainfall to be caused by rapid increasing of the solar radiation resulting from a collision of a large asteroid or comet with the Sun.

The normalized raw data of the Earth's electric field, monitored at PYR, ATH, HIO monitoring sites in Greece, are studied as far as it concerns the presence of electric seismic precursors. Electric preseismic pulses, plateau-like anomalous electric field and Very Long Period (VLP) anomalies were detected prior to the occurrence of the July 1st, 2009 large (Ms = 6.3R) EQ in Greece. Further processing of the same data revealed the true form of the generated preseimic potential thus providing an indirect estimation of the time window of the occurrence of the large EQ. Finally, by correlating, at pairs, the anomalous electric field from all monitoring sites it is possible to calculate the "strange attractor like" seismic electric precursor that provides a time window for the occurrence of the large EQ and utilizes the determination not only of the regional seismogenic area that has been activated but also a more precise epicenter too.

The interaction of a space system with its orbital environment is a major consideration in the design of any space system, since a variety of hazards are associated with the operation of spacecraft in the harsh space environment. In this brief review, two types of hazards to Earth-orbiting spacecraft are discussed: spacecraft charging and radiation hazards to spacecraft electronics, with emphasis on the natural environmental factors and interactions which contribute to these hazards. Following a summary of the historical eras of spacecraft charging and some observations from experimental satellites: SCATHA, CRRES and DMSP, environmental factors significant to spacecraft charging are discussed, including plasma interactions, electric and magnetic fields and solar radiation. Spacecraft charging depends on the spacecraft geometry, as well as on the characteristics of its orbit, since the natural environment may differ for each type of orbit. Low altitude orbiting satellites (LEO) usually experience less charging effects than high altitude geosynchronous (GEO) satellites, except for low altitude polar orbiting satellites which cross the auroral oval. Basic mechanisms of surface charging, differential charging and internal charging are described. Environmental factors including trapped and transient radiation, solar and galactic cosmic rays, which can profoundly damage spacecraft electronics are presented. Some effects such as ionization and atomic displacement damages to semiconductors and single event phenomena are also briefly mentioned.

The reliability of surface-based electrical resistivity tomography (ERT) for quantifying resistivities for shallow subsurface water processes is analysed. A method comprising numerical simulations of water movement in soil and forward-inverse modeling of ERT surveys for two synthetic data sets is presented. Resistivity contrast, e.g. by changing water content, is shown to have large influence on the resistivity quantification. An ensemble and clustering approach is introduced in which ensembles of 50 different inversion models for one data set are created by randomly varying the parameters for a regularisation based inversion routine. The ensemble members are sorted into five clusters of similar models and the mean model for each cluster is computed. Distinguishing persisting features in the mean models from singular artifacts in individual tomograms can improve the interpretation of inversion results. Especially in the presence of large resistivity contrasts in high sensitivity areas, the quantification of resistivities can be unreliable. The ensemble approach shows that this is an inherent problem present for all models inverted with the regularisation based routine. The results also suggest that the combination of hydrological and electrical modeling might lead to better results.

In order to study the mechanical behaviour of polar ice masses, the method of continuum mechanics is used. The newly developed CAFFE model (Continuum-mechanical, Anisotropic Flow model, based on an anisotropic Flow Enhancement factor) is described, which comprises an anisotropic flow law as well as a fabric evolution equation. The flow law is an extension of the isotropic Glen's flow law, in which anisotropy enters via an enhancement factor that depends on the deformability of the polycrystal. The fabric evolution equation results from an orientational mass balance and includes constitutive relations for grain rotation and recrystallization. The CAFFE model fulfills all the fundamental principles of classical continuum mechanics, is sufficiently simple to allow numerical implementations in ice-flow models and contains only a limited number of free parameters. The applicability of the CAFFE model is demonstrated by a case study for the site of the EPICA (European Project for Ice Coring in Antarctica) ice core in Dronning Maud Land, East Antarctica.

In this work the preseismic "strange attractor like" precursor is studied, in the domain of the Earth's oscillating electric field for T = 6 months. It is assumed that the specific oscillating electric field is generated by the corresponding lithospheric oscillation, triggered by the Ssa tidal wave of the same wave length (6 months) under excess strain load conditions met in the focal area of a future large earthquake. The analysis of the recorded Earth's oscillating electric field by the two distant monitoring sites of PYR and HIO and for a period of time of 26 months (October 1st, 2006 - December 2nd, 2008) suggests that the specific precursor can successfully resolve the predictive time window in terms of months and for a "swarm" of large EQs (Ms > 6.0R), in contrast to the resolution obtained by the use of electric fields of shorter (T = 1, 14 days, single EQ identification) wave length. More over, the fractal character of the "strange attractor like" precursor in the frequency domain is pointed out. Finally, a proposal is made that concerns the continuous monitoring of the specific preseismic attractor in distinct different wave lengths of the oscillating Earth's electric field so that an early warning system can be utilized. As a refinement of the "strange attractor like" methodology, the guide lines of a generalized inversion scheme are presented so that the epicenter of the driving mechanism (seismic epicentral area) can be estimated in a least squares sense.

We study the cyclic dominance of three species in two-dimensional constrained Newman-Watts networks with a four-state variant of the rock-paper-scissors game. By limiting the maximal connection distance $R_{max}$ in Newman-Watts networks with the long-rang connection probability $p$, we depict more realistically the stochastic interactions among species within ecosystems. When we fix mobility and vary the value of $p$ or $R_{max}$, the Monte Carlo simulations show that the spiral waves grow in size, and the system becomes unstable and biodiversity is lost with increasing $p$ or $R_{max}$. These results are similar to recent results of Reichenbach \textit{et al.} [Nature (London) \textbf{448}, 1046 (2007)], in which they increase the mobility only without including long-range interactions. We compared extinctions with or without long-range connections and computed spatial correlation functions and correlation length. We conclude that long-range connections could improve the mobility of species, drastically changing their crossover to extinction and making the system more unstable.

The detection of electron anti-neutrinos from natural radioactivity in the earth has been a goal of neutrino researchers for about half a century. It was accomplished by the KamLAND Collaboration in 2005, and opens the way towards studies of the Earth's radioactive content, with very important implications for geology. New detectors are operating (KamLAND and Borexino), building (SNO+) and being proposed (Hanohano, LENA, Earth and others) that will go beyond the initial observation and allow interesting geophysical and geochemical research, in a means not otherwise possible. Herein we describe the approaches being taken (large liquid scintillation instruments), the experimental and technical challenges (optical detectors, directionality), and prospects for growth of this field. There is related spinoff in particle physics (neutrino oscillations and hierarchy determination), astrophysics (solar neutrinos, supernovae, exotica), and in the practical matter of remote monitoring of nuclear reactors.

The interaction of multiple Coronal Mass Ejections (CMEs) has been observed by LASCO coronagraphs and by near-Earth spacecraft, and it is thought to be an important cause of geo-effective storms, large Solar Energetic Particles events and intense Type II radio bursts. New and future missions such as STEREO, the LWS Sentinels, and the Solar Orbiter will provide additional observations of the interaction of multiple CMEs between the Sun and the Earth. We present the results of simulations of two and more CMEs interacting in the inner heliosphere performed with the Space Weather Modeling Framework (SWMF). Based on those simulations, we discuss the observational evidence of the interaction of multiple CMEs, both in situ and from coronagraphs. The clearest evidence of the interaction of the CMEs are the large temperature in the sheath, due to the shocks merging, and the brightness increase in coronagraphic images, associated with the interaction of the leading edges. The importance of having multiple satellites at different distances and angular positions from the Sun is also discussed.

The Earth's preseismic oscillating (T = 24h) electric field recorded for a short-time period of some days is analyzed in terms of its intensity vector azimuthal direction calculated at one monitoring site. The calculated azimuthal directions are compared to the concurrent seismicity observed for the same period of time. Examples are presented for proving the agreement between the electric field intensity vectors calculated azimuths and the corresponding ones referring to the EQs - monitoring site location. Finally, an example is presented on account of the use of this methodology upon three different monitoring sites for the utilization of the estimation of the epicentral area of a large future EQ at the Methoni, Greece seismogenic area.

The use of GNSS signals as a source of opportunity for remote sensing applications, GNSS-R, has been a research area of interest for more than a decade. One of the possible applications of this technique is soil moisture monitoring. The retrieval of soil moisture with GNSS-R systems is based on the variability of the ground dielectric properties associated to soil moisture. Higher concentrations of water in the soil yield a higher dielectric constant and reflectivity, which incurs in signals that reflect from the Earth surface with higher peak power. Previous investigations have demonstrated the capability of GPS bistatic scatterometers to obtain high enough signal to noise ratios in order to sense small changes in surface reflectivity. Furthermore, these systems present some advantages with respect to others currently used to retrieve soil moisture. Upcoming satellite navigation systems, such as the European Galileo, will represent an excellent source of opportunity for soil moisture remote sensing for various reasons. First, the existence of pilot signals will provide the possibility to extend coherent integration times, which will contribute to the increase of received signals SNR. In addition, the availability of Galileo L1 and L5 signals will allow the multi-spectral analysis of the reflected signals and the development of inversion models which will be able to account more precisely for adverse effects, such as surface roughness and vegetation canopy. In this paper we present some of the recent theoretical work and experiments carried out at Starlab focusing on the development of dedicated Soil Moisture GNSS-R systems.