ALBERT

Description: Geodesy utilizes state of the art data collection techniques such as GPS (Global Positioning System) to acquire locations of points. Traditionally, the coordinates of these points are estimated using the Least Squares (LS) method. Nevertheless, Robust Estimation (RE) yields more accurate results than LS method in the presence of blunders (gross errors) among the data set. For example, the Least Trimmed Squares (LTS) method and the Least Median Squares (LMS) method can be used for this purpose. The first method aims to minimize the sum of the squared residuals by trimming away observations with large residuals. On the other hand, the second method involves the minimization of the median of the squared residuals. Both methods can be implemented using an optimization method, i.e., Artificial Bee Colony (ABC) algorithm. The ABC algorithm is a swarm intelligence (a branch of artificial intelligence) technique that can be used for the solution of minimization or maximization problems. In this paper, using the LTS and LMS methods for GPS data by employing the ABC, a new approach is put forward. Firstly, some discussions about the theoretical principals of RE and ABC are given. Then, a numerical example is used to demonstrate the validity of the proposed approach. Numerical results show that application of the robust estimation to GPS data can easily be carried out by ABC and this approach helps to enhance the reliability of geospatial data for any application of geodesy.

Description: In the streams of the Mediterranean island of Crete (Greece), olive mill wastewater (OMW) has been reported to reduce biodiversity up to 85 %. Mere conduction of impact assessment based on pollutant concentrations, however, cannot reveal how impacted areas may be connected to the pollution sources. In this study, we developed a new methodology which allows for a dynamic cause-effect linking of pollution sources and impacted areas through the pathways of OMW. Risk is hierarchically assessed and mapped at three different scales and more specifically, at the source scale (targeting olive mill units and their waste tanks), at the receptor scale (targeting potential impacted sites in the streams) and at the watershed scale (which is the scale of overall water management). The approach is based mainly on remote sensing data without taking account of groundwater regimes or field measurements. Involvement of local experts for recognizing spatial features of interest and selecting appropriate risk parameters was proved necessary and efficient in order to model the stream pollution risk realistically. Potential impacted sites in the stream network were occasionally verified by a field survey. The results comprise a set of risk maps at the three different scales. The constructed digital geo-database can be updated or modified and thus is considered to be a dynamic tool for future environmental management in the service of the local community.

Description: This paper describes a technique to transform coordinates between map references based on NTv2 format grids. Using the grids rather than carrying out a transformation allows to avoid map archives doubling, thereby easing “on the fly” transformation between different map representations. The paper also includes a case-study on a highway stretch currently under construction, the ‘Pedemontana Lombarda’ highway.

Description: In contrary to the numbers of qualitative studies, there is few quantitative studies have been done on defining climate zone boundaries and on illustrating differences inside a zone. In order to find quantitative methods to demarcate a physical geography boundary and to reveal the agro-climatic resources differences of the South Subtropical Zone in Fujian Province of China based on the data collected from limited and discrete weather stations, this research tries to develop models that use mathematics methods and Geographical Information System (GIS) technology. Three modeling methods - Discriminant Analysis, Trend-surface with Residual (TSR) Analysis, and Digital Elevation Model (DEM) were applied in the study to produce a distribution grid system of a set of indicators, and to define the spatial location of the zone boundary precisely. The results of the study show that the outputs of the models have very high significant level in statistical tests.

Description: With GLONASS completed its full constellation and the rapid increasing number of GNSS receivers, it is worthwhile to investigate the availability of GLONASS-only in positioning. In this paper, two networks of different baseline length, located in two different regions are analyzed. For both networks, GLONASS and GPS observations are processed respectively for 175 days since GLONASS recovered FOC. The RMS and STD of the coordinates minus those from the International GNSS Service weekly solutions are analyzed. The statistics over a long period empirically demonstrate that the averaged coordinate repeatabilities of GLONASS are slightly worse than that of GPS results. The estimated ZTDs of GLONASS is about 1–2 mm worse than GPS results. For both networks, the GLONASS coordinates show some systematic effect as a function of antenna + radome type, caused by the using of GPS derived PCC models. The systematic effect varied form several mm to 1 cm for different stations with different antenna + radome types, which indicates that GLONASS-specific PCC models are mandatory in GLONASS high precision positioning.

Description: Cellular Automata (CA) simulation models have been increasingly used in land use studies. However, neighborhood configuration, an essential element of CA model, remarkably impacts the accuracy of simulated results. Moreover, errors from data source may propagate through the CA modeling process. The objective of this study is to analyze the effect of neighborhood configuration to CA model and further on to explore its capacity of resisting disturbance from data source error. With statistic-based CA model and several neighborhood configurations respectively, the land use changes of Wuhan, China were analyzed. It is demonstrated that there are significant differences on the simulated results produced by different neighborhoods. Besides, different neighborhoods respond differently to data source error. In light of these results, we find out that (1) neighborhood configurations with larger neighborhood size and planar neighborhood type, introduced in this paper, contribute to higher prediction accuracy; and (2) the neighborhood configurations above also have higher capacity of resisting disturbance from data source error and give rise to more stable simulated results. This study provides a comprehensive basis for scale selection of CA model with a meaningful consideration of data source error and thus will improve the research on land use change.

Description: Drought is a significant disaster in Beijing and it is important to find a method to assess the drought condition. First, this paper collected data of 85 soil monitoring stations in Beijing, such as soil dry bulk densities, saturated water contents, field capacities. Then, spatial variability characteristics of soil physics parameters were investigated by GIS and other three factors, 10 cm soil moisture content, organic matter and saturated water content which notably influenced soil moisture were extracted by Principal Component Analysis (PCA). Furthermore, four different nonlinear methods were put forward to predict crop-root zone soil water. 15555 single daily data from 2011 were used in parameters determination, while 15470 double daily data were used to test. The result showed that the Least Square Support Vector Machine coupling Particle Swarm Optimization Algorithm (PSO-LSSVM) ( R 2  = 0. 875) did better than BP Neural Network ( R 2  = 0. 840), Generalized Regression Neural Network (GRNN) ( R 2  = 0. 850) and Wavelet Neural Network (WNN) ( R 2  = 0. 853). As so the POS-LSSVM method was used to evaluate the drought conditions from October 2010 to March 2011 of Beijing, and the result showed that from October 2010 to January 2011, the drought conditions were getting increasingly worse while later relieved from January 2011 to March 2011.

Description: This study investigates the effect of discrete wavelet transform data pre-processing method on neural network-based successive-station monthly streamflow prediction models. For this aim, using data from two successive gauging stations on Çoruh River, Turkey, we initially developed eight different single-step-ahead neural monthly streamflow prediction models. Typical three-layer feed-forward (FFNN) topology, trained with Levenberg-Marquardt (LM) algorithm, has been employed to develop the best structure of each model. Then, the input time series of each model were decomposed into subseries at different resolution modes using Daubechies (db4) wavelet function. At the next step, eight hybrid neuro-wavelet (NW) models were generated using the subseries of each model. Ultimately, root mean square error and Nash-Sutcliffe efficiency measures have been used to compare the performance of both FFNN and NW models. The results indicated that the successive-station prediction strategy using a pair of upstream-downstream records tends to decrease the lagged prediction effect of single-station runoff-runoff models. Higher performances of NW models compared to those of FFNN in all combinations demonstrated that the db4 wavelet transform function is a powerful tool to capture the non-stationary feature of the successive-station streamflow process. The comparative performance analysis among different combinations showed that the highest improvement for FFNN occurs when simultaneous lag-time is considered for both stations.

Description: This paper describes the development of visual basic program called ‘Linfo’ which can be used for calculation of spatial properties (orientation, length, density, frequency and intersection density) of lineaments. The program allows the user to analyze the orientation of lineaments easily and shows the results in the form of rose diagram. Linfo can handle large number of lineaments at a time and calculates the results faster than any other software. Linfo generates regular square grids over lineament data and calculates the number, length and intersections of lineaments that fall within each cell. The program is validated with lineament data of Kerala state, India and prepared the spatial maps using Inverse Distance Weighted (IDW) interpolation method. The experimental results show that Linfo is useful for generating spatial maps using any interpolation method. Potential application of the program includes demarcation of groundwater potential zones, landslide risk assessment etc.

Description: The voltage stability problem in long-distance transmission systems can be exacerbated by geomagnetic disturbance (GMD) even in middle and low latitude areas where the effects of GMDs are considered to be mild compared to auroral areas. With the high voltage and the long-distance transmission lines, power system in China has to face the voltage instability risk. To clarify and measure the risk from GMD represented by geoelectric field, method for analysis of relationship between voltage stability of the long-distance transmission system and the size and direction of geoelectric field is provided. On the basis of calculation for geomagnetically induced currents (GICs) of power system and the additional reactive power losses of transformer due to GIC, the model of long-distance transmission line affected by geoelectric field is established. To measure the impact on the voltage stability of power system and the sensitivity of voltage to geoelectric field, the voltage stability index and the set of voltage limit violation nodes are proposed and calculated considering different geoelectric field and different initial operation conditions of power system. By taking the Northwest 750 kV power system in China as an example, voltage stability with geoelectric field magnitude from 1 V/km to 10 V/km, direction (0°) from north to south (180°) is analyzed and the voltage stability index is calculated, and the set of voltage limit violation nodes are summarized as well. The results show that the method is feasible and the index can reflect actually the relationship between the long-distance transmission system voltage stability and the geoelectric field, and the set of the voltage limit violation nodes can indicate which nodes are most susceptible to GMD.

Description: The strength of anisotropic rock masses can be evaluated through either theoretical or experimental methods. The latter is more precise but also more expensive and time-consuming especially due to difficulties of preparing high-quality samples. Numerical methods, such as finite element method (FEM), finite difference method (FDM), distinct element method (DEM), etc. have been regarded as precise and low-cost theoretical approaches in different fields of rock engineering. On the other hand, applicability of intelligent approaches such as fuzzy systems, neural networks and decision trees in rock mechanics problems has been recognized through numerous published papers. In current study, it is aimed to theoretically evaluate the strength of anisotropic rocks with through-going discontinuity using numerical and intelligent methods. In order to do this, first, strength data of such rocks are collected from the literature. Then FlAC, a commercially well-known software for FDM analysis, is applied to simulate the situation of triaxial test on anisotropic jointed specimens. Reliability of this simulation in predicting the strength of jointed specimens has been verified by previous researches. Therefore, the few gaps of the experimental data are filled by numerical simulation to prevent unexpected learning errors. Furthermore, a sensitivity analysis is carried out based on the numerical process applied herein. Finally, two intelligent methods namely feed forward neural network and a newly developed fuzzy modeling approach are utilized to predict the strength of above-mentioned specimens. Comparison of the results with experimental data demonstrates that the intelligent models result in desirable prediction accuracy.

Description: As large quantities of physical data are always collected for Ecoinformatics research, it is difficult for them to be cleaned, shared, visualized, and analyzed by research collaborators. To resolve this difficulty, this study presents online weather data analysis and visualization cyber-infrastructures consisting of (1) online weather data analysis and visualization tools and (2) near real-time online weather data portal. Firstly, these online tools at www.twibl.org/weather provide data sharing in three web pages: information on instruments and site; data access protected by simple password security; data analysis and visualization services so-called “Ecoinfows”. Secondly, the near real-time online weather data portal for visualizing and forecasting weather data from cloud storage of many automatic weather stations is online at www.twibl.org/aaportal . To overcome speed and accessibility problems, we developed these tools with many technologies - i.e. cloud computing, online computing XML ( webMathematica ), and binary access data conversion.

Description: Although the research and application of a geographic information system (GIS) in bibliometrics remains in its initial stage, several valuable attempts have been made in recent years. This paper provides our overview regarding this area. We first reviewed the spatial information mining derived from literature, including structured and unstructured data. The spatial display and the basic spatial operations for the geographic information derived from literature were then introduced, demonstrating that GIS can be directly used to construct digital libraries. Some literature database websites have begun to utilize WEBGIS to display the spatial distribution of an author’s location. Additionally, the spatial distribution information can be displayed in various modes with other specialized tools. Potential spatial analyses in bibliometrics were then discussed, introducing geostatistical and buffer analyses as case studies. Finally, several bibliometric indicators attached with research units were investigated. When the quantitative research index units are linked with the research spatial position, they can be displayed, queried and retrieved spatially. Future work to advance the application and research of GIS in bibliometrics is still warranted.

Description: As the characterization of primary productivity of wetland ecosystem, the Normalized Difference Vegetation Index (NDVI) plays an important role in local ecosystem conservation for environmental management. In this paper, the correlations of NDVI and hydro-meteorological variables were studied in a water scarce area with emphasis on different land use types, namely water, wetland, residential land and farmland, during the growing seasons of 1999 and 2000. The significant NDVI changes were detected between spring and summer for all land use types. The correlation analysis revealed that the NDVI-temperature correlation ( P  〈 0.001) was stronger than NDVI-precipitation correlation ( P  〈 0.01 for farmland and P  〈 0.05 for others) in all land use types. In addition, water level had no significant correlation with NDVI at such a small time scale. The sensitivity differences in different land use types based on the determination coefficient of the linear regression models are: R farmland 〉 R wetland 〉 R residential land 〉 R water for NDVI and precipitation correlations ( P  〈 0.05); and R water 〉 R wetland 〉 R residential land 〉 R farmland for NDVI and temperature correlations ( P  〈 0.001). The results would be valuable for the understandings of effects of hydro-meteorological variables on NDVI changes, as well as the potential effect on land use and land cover.

Description: The Regional Climate Model Evaluation System (RCMES) facilitates the rapid, flexible inclusion of NASA observations into climate model evaluations. RCMES provides two fundamental components. A database (RCMED) is a scalable point-oriented cloud database used to elastically store remote sensing observations and to make them available using a space time query interface. The analysis toolkit (RCMET) is a Python-based toolkit that can be delivered as a cloud virtual machine, or as an installer package deployed using Python Buildout to users in order to allow for temporal and spatial regridding, metrics calculation (RMSE, bias, PDFs, etc.) and end-user visualization. RCMET is available to users in an “offline”, lone scientist mode based on a virtual machine dynamically constructed with model outputs and observations to evaluate; or on an institution’s computational cluster seated close to the observations and model outputs. We have leveraged RCMES within the content of the Coordinated Regional Downscaling Experiment (CORDEX) project, working with the University of Cape Town and other institutions to compare the model output to NASA remote sensing data; in addition we are also working with the North American Regional Climate Change Assessment Program (NARCCAP). In this paper we explain the contribution of cloud computing to RCMES’s specifically describing studies of various cloud databases we evaluated for RCMED, and virtualization toolkits for RCMET, and their potential strengths in delivering user-created dynamic regional climate model evaluation virtual machines for our users.

Description: Land abandonment and stagnation of rural markets in the last few years have become one of the main concerns of rural administrations. The use of Web and GIS (Geographic Information System) technologies can help to mitigate the effects of these problems. This paper pro-poses a novel Web-GIS tool with spatial capabilities for the dynamization of rural land markets by encouraging the transfer of land from owners to farmers through the leasing of plots. The system, based on open source software, offers information about the properties, their environment and their owners. It uses standards for handling the geographic information and for communicating with external data sources. This system was used as the basis for the development of SITEGAL, the tool for the management of the Land Bank of Galicia ( www.bantegal.com/sitegal ). SITEGAL has been operational since 2007 obtaining benefits for both administration and users (farmers and land owners), and promoting the e-Government.

Description: Despite the extensive records on geomorphological studies in Iran, meteorite impact craters have so far not been considered in to account. Based on both remote sensing technique and field work we have recognized the circular structure of Zirouki crater in the Samsour desert, southeast of Iran, which if confirmed as an impact structure, would be the third impact structure candidate in the Middle East after the Wabar craters in Saudia Arabia and Jebel Waqf as Suwwan in Jordan. Geomorphological investigation of the possible impact structure of Zirouki crater was done based on multi criteria methodology including of geological, topographical, geophysical and petrographical studies. Among different studies, topographical investigation indicated that the crater shape morphology was quite obvious with a central uplift projection; as well geophysical pattern provided very strong evidence for possible impact structure, indicating the presence of circular negative gravity anomaly at the whole of the crater.

Description: Reconstruction of architectural structures from photographs has recently experienced intensive efforts in computer vision research. This is achieved through the solution of nonlinear least squares (NLS) problems to obtain accurate structure and motion estimates. In Photogrammetry, NLS contribute to the determination of the 3-dimensional (3D) terrain models from the images taken from photographs. The traditional NLS approach for solving the resection-intersection problem based on implicit formulation on the one hand suffers from the lack of provision by which the involved variables can be weighted. On the other hand, incorporation of explicit formulation expresses the objectives to be minimized in different forms, thus resulting in different parametric values for the estimated parameters at non-zero residuals. Sometimes, these objectives may conflict in a Pareto sense, namely, a small change in the parameters results in the increase of one objective and a decrease of the other, as is often the case in multi-objective problems. Such is often the case with error-in-all-variable (EIV) models, e.g., in the resection-intersection problem where such change in the parameters could be caused by errors in both image and reference coordinates. This study proposes the Pareto optimal approach as a possible improvement to the solution of the resection-intersection problem, where it provides simultaneous estimation of the coordinates and orientation parameters of the cameras in a two or multistation camera system on the basis of a properly weighted multi-objective function. This objective represents the weighted sum of the square of the direct explicit differences of the measured and computed ground as well as the image coordinates. The effectiveness of the proposed method is demonstrated by two camera calibration problems, where the internal and external orientation parameters are estimated on the basis of the collinearity equations, employing the data of a Manhattan-type test field as well as the data of an outdoor, real case experiment. In addition, an architectural structural reconstruction of the Merton college court in Oxford (UK) via estimation of camera matrices is also presented. Although these two problems are different, where the first case considers the error reduction of the image and spatial coordinates, while the second case considers the precision of the space coordinates, the Pareto optimality can handle both problems in a general and flexible way.

Description: Semantic Web technologies bring innovative ideas to computer applications in geoscience. As an essential part of the Semantic Web, ontologies are increasingly discussed in the geoscience community, in which geologic time scale is one of the topics that have received the most discussion and practices. This paper aims to carry out a review of the recent progress on geologic time ontologies, discuss further improvements, and make recommendations for other geoscience ontology works. Several models and ontologies of geologic time scale are collected and analyzed. Items such as ontology evaluation, ontology mapping, ontology governance, ontology delivery and multilingual labels are discussed for advancing the geologic time ontologies. We hope the discussion can be useful for other geoscience ontology works, and we also make a few further recommendations, such as referring to an ontology spectrum in ontology creation, collaborative working to improve interoperability, and balancing expressivity, implementability and maintainability to achieve better applications of ontologies.

Description: In optical image registration, the reference control points (RCPs) used as explanatory variables in the polynomial regression model are generally assumed to be error free. However, this most frequently used assumption is often invalid in practice because RCPs always contain errors. In this situation, the extensively applied estimator, the ordinary least squares (LS) estimator, is biased and incapable of handling the errors in RCPs. Therefore, it is necessary to develop new feasible methods to address such a problem. This paper discusses the scaled total least squares (STLS) estimator, which is a generalization of the LS estimator in optical remote sensing image registration. The basic principle and the computational method of the STLS estimator and the relationship among the LS, total least squares (TLS) and STLS estimators are presented. Simulation experiments and real remotely sensed image experiments are carried out to compare LS and STLS approaches and systematically analyze the effect of the number and accuracy of RCPs on the performances in registration. The results show that the STLS estimator is more effective in estimating the model parameters than the LS estimator. Using this estimator based on the error-in-variables model, more accurate registration results can be obtained. Furthermore, the STLS estimator has superior overall performance in the estimation and correction of measurement errors in RCPs, which is beneficial to the study of error propagation in remote sensing data. The larger the RCP number and error, the more obvious are these advantages of the presented estimator.

Description: We present a method to estimate the difference between quasigeoid and geoid heights globally from the Earth Gravitational Model EGM08 and a related topographic model. The numerical computations with the standard topographic density of 2.67 g/cm 3 show that the maximum and minimum of the separations are estimated to 5.47 m and −0.11 m on the Tibet plateau and in the Indian Ocean, respectively. These estimates do not consider possible topographic density variations, which result in topographic bias changes proportional to the topographic elevation squared. Assuming such density changes of 10% from the standard value, the separation may change up to 5 dm.

Description: The Global Geopotential Models (GGMs) are very significant because of their usefulness in determination of the parameters like geoidal undulations, height anomalies, gravity anomalies, and so on. In this paper, first, we review the calculation of such parameters and then present the GGMCalc software, which is prepared in Fortran 95 under GNU/Linux Operating System. This software is capable of using the files presented by the International Center for Global Earth Models (ICGEM) directly without need to apply any changes on them. The software is completely structural and user friendly and could be used conveniently for academic purposes.

Description: A new method for elevation and latitude decorrelation stretch of multi-temporal land surface temperature (LST) in the East Africa Rift System (EARS) from MODIS 2008 monthly average night imagery and Globe digital elevation model (DEM) is presented. Multiple linear regression analysis of principal components images (PCAs) quantifies the variance explained by elevation and latitude. Selective variance reduction (SVR) reconstructs the multi-temporal LST imagery from the residual images and selected PCAs by taking into account the portion of variance not related to elevation and latitude. Clustering of the reconstructed imagery identifies two major thermal anomalies a) in the Afar Triangle, and b) a new one in between the Ethiopia and Kenya. These regions present LST values higher than the elevation and latitude predicted ones through out the year. It is assumed that the new thermal anomaly corresponds to a triple junction formed in between the Ethiopian Rift and the Eastern and the Western branches of the EARS, in an area where active volcanoes and mantle plume activity concentrate. SVR is expected to assist tectonic and volcanic zones characterization on the basis of their thermal response.

Description: As many sensor networks are currently being deployed for environmental monitoring, there is a growing need to develop systems and applications for managing, processing and retrieving massive amounts of data generated from those networks. In this research, a query answering system with pattern mining techniques is investigated specifically for marine sensor data. We consider three applications of pattern mining: similar pattern search, predictive query and query by clustering. In pattern mining for query answering, we adopt the dynamic time warping (DTW) method for similarity measurement. We also propose the use of a query relaxation approach that recommends users change parameters of a given query to get an answer. Finally, we show implementation results of pattern query answering in a marine sensor network deployed in the South East of Tasmania, Australia. Pattern query answering system benefits in accessing and discovering knowledge from sensor data for decision making purposes.

Description: Establishing and successfully implementing new numerical computational technique(s) with simulation tool is one of the most important difficult tasks in order to carry out real time scientific astronomical and other sophisticated problems. The main focus and highlight of this paper is concerned with the introduction of a newly proposed simple embedded RKAHeM(4,4) technique to determine the distribution of thermodynamic variables inside protoplanets during pre-collapse stage, formed by gravitational instability, for protoplanetary masses between 0.3 to 10 Jupiter masses. The case of convection is a significant concern for transference of heat inside the protoplanet and the graphical solution demonstrates positively better performance by inducting the newly proposed effective RKAHeM(4,4) algorithm for any length of time in comparison with the results through Classical Runge–Kutta method. Furthermore, the analytic expression for local truncation error, global truncation error and error estimates are derived for better understanding. A viable quantitative analysis has been carried out to clearly visualize the goodness and robustness of the proposed RKAHeM(4,4) algorithm.

Description: Isostatic hypotheses are used for different purposes in geophysics and geodesy. The Erath crustal thickness modelling is more complicated than the classical isostatic models. In this study we try to modify Airy-Hesiskanen model, utilizing a smoothing factor, to a model with regional or global isostatic model through a modern solution of the gravimetric-isostatic Vening Meinesz model and CRUST.0. In Airy-Hesiskanen’s theory there is no correlation between neighbouring crustal columns, while this must be the case in reality due to the elasticity of the Earth. The idea is to keep the simplicity of the Airy-Heiskanen model, because it needs only the topographic data, and change the model which becomes to a model with regional/global isostatic model. The isostatic assumption for compensating the topographic potential is incomplete, as there are other geophysical phenomena which should be considered. Using the isostatic hypothesis for determining the depth of crust causes some disturbing signals in the gravity anomaly (approximately 285 mGal), which influence the crustal thickness determination. In this paper a simple method use for removing these effects. Spherical harmonic potential coefficients of the topographic compensation masses are used for modifying Airy-Heiskanen’s model in a least-square adjustment procedure by estimating smoothing factor. The numerical analysis shows that below degree 10, the modified Airy-Hesiskanen and Vening Meinesz models are close together. Smoothing factors for modifying the Airy-Hesiskanen model vary from 0.75 to 0.64 between degrees 200 and 2159.

Description: Each year destructive events might cause loss of data in members of an archival federation. This paper provides a ‘back-of-the-envelope’ model for the fraction of the federated data collection that survives after a certain number of years. It also discusses some simple parameterizations of factors that contribute to the trade offs between cost and survival of information.

Description: The water and energy transfer of land surface is complex due to its large spatial and temporal variability. The modeling and simulation is an important means to study land water and energy transfer, but most selection and analysis of model parameters are empirical and qualitative. This paper has proposed a method of quantitatively identifying the most influential parameters of Common Land Model through Sobol’ sensitivity analysis. Considering sensible heat flux as the model output, the first order and total sensitivity indices of 25 model input parameters are estimated using an improved Sobol’ method. The simulated results are resampled using a bootstrapping method and the corresponding sensitivity indices are calculated. Confidence intervals for the bootstrapping sensitivity indices are estimated by using a percentile method. The results show that the parameters phi0 and porsl are the most important parameters, followed by ref(2,1), tran(2,1) and bsw. Five out of 25 parameters need to have an accurate evaluation, while the other parameters are fixed to a certain value. The sensitivity indices of parameters phi0 and porsl are decreasing after precipitation, while the sensitivity indices of parameters tran(2, 1) and ref(2, 1) are increasing after precipitation.

Description: “Open science,” where researchers share and publish every element of their research process in addition to the final results, can foster novel ways of collaboration among researchers and has the potential to spontaneously create new virtual research collaborations. Based on scientific interest, these new virtual research collaborations can cut across traditional boundaries such as institutions and organizations. Advances in technology allow for software tools that can be used by different research groups and institutions to build and support virtual collaborations and infuse open science. This paper describes Talkoot, a software toolkit designed and developed by the authors to provide Earth Science researchers a ready-to-use knowledge management environment and an online platform for collaboration. Talkoot allows Earth Science researchers a means to systematically gather, tag and share their data, analysis workflows and research notes. These Talkoot features are designed to foster rapid knowledge sharing within a virtual community. Talkoot can be utilized by small to medium sized groups and research centers, as well as large enterprises such a national laboratories and federal agencies.

Description: This article presents research that aims to assess the accuracy of seabed bathymetry models on the basis of measurements carried out using a multibeam echosounder. It discusses the problem of accuracy assessment which occurs at particular stages of the creation of digital terrain models (DTMs), and analyzes the influence of both the individual multibeam echosounder parameters and the procedures adopted during the survey on the modeling process’s accuracy. Factors that may affect accuracy include the device’s measurement accuracy, the boat speed, the track configuration, the beam width and the selected interpolation method. The article does not deal with errors due to navigation and vessel motion, these being taken to be of the highest possible accuracy. For the research we developed a virtual survey simulator. Recommendations for how to optimize the measurement process while ensuring the created models are of a high quality are presented later in the paper.

Description: The nearest neighbor search algorithm is one of the major factors that influence the efficiency of grid interpolation. This paper introduces a KD-tree that is a two-dimensional index structure for use in grid interpolation. It also proposes an improved J-nearest neighbor search strategy based on “priority queue” and “neighbor lag” concepts. In the strategy, two types of J-nearest neighbor search algorithms can be used; these algorithms correspond to the consideration of a fixed number of points and a fixed radius. By using the KD-tree and proposed strategy, interpolation can be performed with methods such as Inverse Distance Weighting and Kriging. Experimental results show that the proposed algorithms has high operating efficiency, especially when the data amount is enormous, and high practical value for increasing the efficiency of grid interpolation.

Description: Rapid increases in remote sensing capability have made remotely sensed images an importance source for intelligence analysts to discover geospatial features. The overwhelming volume of routine image acquisition has greatly outpaced the increase in the capacity of manual image interpretation by intelligence analysts, and prompted automated methods for geospatial feature extraction from high spatial resolution images. Nevertheless, existing methods focus on automatic extraction of isolated or elementary features, such as buildings and roads. A compound geospatial feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., containment buildings, cooling ponds, and fences). The spatial relations among elementary features can assist the detection of compound features from images. This paper proposes a service-oriented approach for discovering compound geospatial features. The approach includes both a chaining strategy and an architecture. The chaining strategy is to discover sites of facilities by orchestrating services that compute spatial relations among elementary features. The architecture is a service-oriented framework to support the chaining for feature discovery. The approach not only takes advantages of spatial characteristics of complex features, but also enjoys the openness and flexibility of the Service-Oriented Architecture (SOA). A prototypical implementation is provided to illustrate the applicability of the approach.

Description: This study examined the spatial-temporal variations in seismicity parameters for the September 10 th , 2008 Qeshm earthquake in south Iran. To this aim, artificial neural networks and Adaptive Neural Fuzzy Inference System (ANFIS) were applied. The supervised Radial Basis Function (RBF) network and ANFIS model were implemented because they have shown the efficiency in classification and prediction problems. The eight seismicity parameters were calculated to analyze spatial and temporal seismicity pattern. The data preprocessing that included normalization and Principal Component Analysis (PCA) techniques was led before the data was fed into the RBF network and ANFIS model. Although the accuracy of RBF network and ANFIS model could be evaluated rather similar, the RBF exhibited a higher performance than the ANFIS for prediction of the epicenter area and time of occurrence of the 2008 Qeshm main shock. A proper training on the basis of RBF network and ANFIS model might adopt the physical understanding between seismic data and generate more effective results than conventional prediction approaches. The results of the present study indicated that the RBF neural networks and the ANFIS models could be suitable tools for accurate prediction of epicenteral area as well as time of occurrence of forthcoming strong earthquakes in active seismogenic areas.

Description: GIS and Remote Sensing have proved to be an indispensible tool in morphometric analysis. The identification of morphometric properties based on a geographic information system (GIS) was carried out in two watersheds in the Thrissur district of Kerala, India. These watersheds are parts of Western Ghats, which is an ecologically sensitive area. Quantitative geomorphometric analysis was carried out for the Chimmini and Mupily watersheds independently by estimating their (a) linear aspects like stream number, stream order, stream length, mean stream length, stream length ratio, bifurcation ratio, length of overland flow, drainage pattern (b) aerial aspects like circulatory ratio, elongation ratio, drainage density and (c) relief aspects like basin relief, relief ratio, relative relief and ruggedness number. The drainage areas of Chimmini and Mupily watersheds are 140 and 122 km 2 respectively and show patterns of dendritic to sub-dendritic drainage. The Chimmini watershed was classified as a sixth order drainage basin, whereas Mupily watershed was classified as a fifth order basin. The stream order of the basin was predominantly controlled by physiographic and structural conditions. The increase in the stream length ratio from lower to higher order suggests that the study area has reached a mature geomorphic stage. The development of stream segments is affected by rainfall and local lithology of the watersheds. The slope of both watersheds varied from 0° to 50° and 0° to 42° respectively and the slope variation is chiefly controlled by the local geology and erosion cycles. Moreover, these studies are useful for planning rain water harvesting and watershed management.

Description: Growth of grains having different initial sizes (10 −3  cm ≤  r 0  ≤ 1 cm) has been investigated by coagulation processes inside gas giant protoplanets, formed by disk instability, in the mass range 0.3 to 10 Jovian masses. In doing so, we have determined distribution of thermodynamic variables inside the protoplanets and using the results we have determined growth of the grains having assumed initial sizes. Regarding the transference of heat inside the protoplanets, we have considered the possible two cases of interest, namely convection and conduction-radiation. The results of our calculation show that growth of the grains depends on protoplanetary masses and on initial states of the protoplanets and eventually all the grains having assumed different initial sizes acquire almost the same distribution in the central regions of respective protoplanets in the respective cases.

Description: Understanding the hydrological response of small and large river basins is crucial for regional climate and hydrology studies. Also, rainfall space–time variability (Known in semi arid climate) has a major influence on hydrological dynamics. As consequent, we developed a software application (with MATLAB) in order to take into account the rainfall space-time variability, and that open a major prospects of studying hydrometeorological effects such scale effect and moving storms. In this context, in order to asses scale and dynamic rainy events effect in hydrologic modelling, this study focuses on instantaneous rainy data in central Tunisia (Merguellil and Skhira watershed): a rainfall runoff modelling was done to investigate basins responses and a developed geomorphology-based transfer function, was applied. A systematic hydro-meteorological analysis have been implemented to understand different types of variability and rainy fields dynamic, the relevance of rainfall network and scale effects. As result, two different behaviours of studied basins are detected. Responses of studied areas are much related to event dynamic (East/West and West/East) and hydrographs change according to event direction.

Description: In this paper an estimator for geoid is presented and applied for geoid computation which considers the topographic and atmospheric effects on the geoid. The total atmospheric effect is mathematically developed in terms of spherical harmonics to degree and order 2,160 based on a recent static atmospheric density model. Also the contribution of its higher degrees is formulated. Another idea of this paper is to combine one of the recent Earth gravity models (EGMs) of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) mission with EGM08 and the terrestrial gravimetric data of Fennoscandia in an optimum way. To do so, the GOCE EGMs are compared with the Global Positioning System (GPS)/levelling data over the area for finding the most suited one. This comparison is done in two different ways: with and without considering the errors of the EGMs. Comparison of the computed geoids with the GPS/levelling data shows that a) considering the total atmospheric effect will improve the geoid by about 5 mm, b) GOCO03S is the most suited GOCE EGM for Fennoscandia, c) the errors of some of the GOCE EGMs are optimistic and far from reality. Combination of GOCO03S from degree 120 to 210 and EGM08 for the rest of degrees shows its good quality in these frequencies.

Description: This paper presents the integration of desktop grid infrastructure with GIS technologies, by proposing a parallel resolution method in a generic distributed environment. A case study focused on a discrete facility location problem, in the biomass area, exemplifies the high amount of computing resources (CPU, memory, HDD) required to solve the spatial problem. A comprehensive analysis is undertaken in order to analyse the behaviour of the grid-enabled GIS system. This analysis, consisting of a set of the experiments on the case study, concludes that the desktop grid infrastructure is able to use a commercial GIS system to solve the spatial problem achieving high speedup and computational resource utilization. Particularly, the results of the experiments showed an increase in speedup of fourteen times using sixteen computers and a computational efficiency greater than 87 % compared with the sequential procedure.

Description: A new graphical user interface (GUI) for pre-processing reflectance spectra, built using MATLAB and expressly designed for the ASD FieldSpec® spectroradiometer, was developed to solve problems that generally affect experimental ASD data. The GUI is characterised by an easily readable, graphic visualisation of spectra, from which the absorption band depth (ABD) can be obtained for a selected wavelength. The output format of the ASD data is a binary file with an .asd extension. The binary file, that provides a single spectrum, can be processed using a software functionality, by means of a GUI, that allows to select one or more binary files to produce a spectral library in a unique .txt file. The spectral reflectance is re-calibrated with the “convex-hull” methodology to eliminate the convex shape, which is typical of reflectance spectra. Different examples of the use of the new GUI are provided.

Description: Interoperability is becoming essential for the today’s geographic information systems. Geographic information is usually available as datasets stored in databases and accessible via GIS. However, these information sources are increasingly heterogeneous and show differences in data formats, database schema and object concepts. To satisfy the increased demand for the use and sharing of geographic data in common applications, considering the heterogeneity and the methods to support interoperability are required by the GIS community. The implementation of Spatial Data Infrastructure (SDI) such as the European INSPIRE (Infrastructure for Spatial Information in the European Community) enables accessibility and the sharing of geographic data and interoperability among the systems. In addition to this, traditional GIS systems perform spatial queries using a keyword-based method. However, this approach remains incapable of fully expressing the users' needs due to a lack of geographic concepts (semantics) in the dataset. Different terms may refer to similar concepts, while the same terms may refer to different concepts. This causes semantic heterogeneity in the dataset. In this context, the most promising approach is the implementation of geospatial semantics by means of ontology in the geospatial dataset to overcome this kind of ambiguity. The aim of this research is to investigate the implementation of INSPIRE as a SDI standard and the use of Semantic Technology to empower the traditional GIS approach. In this regard, a public transportation geoportal has been developed for the experimental investigation which uses a revised sample transportation data complaint with the INSPIRE Transport Network Data Theme and a developed Transportation Ontology Domain, including concepts, relationships and individuals to provide a semantic spatial search.

Description: The aims of this research are: (i) to check availability of weather observations from automated stations in Spain, (ii) to qualitatively and quantitatively describe the networks identified, (iii) to analyze availability of the observations gathered for 3 different networks [two government (GOV): AEMET with national coverage and CASTILLA Y LEÓN on a regional level; and METEOCLIMATIC, a network of volunteer weather observation (VWO) stations on a national level], and (iv) to undertake a spatial redundancy and lacunarity analysis of them. The results reveal: the existence of heterogeneous VWO networks complementing the GOV, differences within and among networks as far as data acquisition frequency, varying delays in their publication, and semantic differences in the observations made. An inventory was made of 24 networks (16 GOV and 8 VWO) with 3,908 stations deployed in Spain. An analysis of observations from 3 networks reveals that 88 % of the stations in the volunteer network record more than two observations per hour. 56 % of the AEMET stations report more than 48 observations every day, 31 % report between 25 and 48 observations a day. Conversely, the CASTILLA Y LEÓN network records data every half hour. The redundancy analysis reveals a 3,429-drop in the number of unduplicated stations. Following the lacunarity analysis of spatial distribution, it is possible to conclude that 60.72 % of the cells do not contain any stations.

Description: An in-depth knowledge of the littoral system is essential for its conservation and for an accurate planning of due interventions. The parabolic bay shape equation, used to study the embayed beach planform, is a qualitatively assessed instrument to obtain information about beach equilibrium conditions. Nowadays the equation has been extended in order to be applicable not only to sand beaches but also to gravel beaches. In this paper Phoebus user-friendly software for an automatic use of the extended parabolic bay shape equation is presented. The software enables both technical experts and non-professionals to conduct expeditious analysis in order to evaluate the evolution and equilibrium conditions of embayed littoral beaches lying between natural headlands or man-made structures, as well as to artificially recreate stable embayed beaches by building new artificial structures on open beaches. The software can be also used for coastal planning, to anticipate beach modifications in response to new building or to changes in pre-existing structures. Highlights Development of a free software to automatically compute embayed beach planform The system can be used on every type of beach image The software allows to display the planform both for sand and gravel beaches Software reliability was demonstrated for natural and artificial bay beaches

Description: Morphotectonic analysis using geomorphic indexes has been developed as a basic tool to identify recent tectonic deformation in specific areas.This study was undertaken to develop an integrated quantitative geomorphic analysis of tectonic activity in the North–south axis, central of Tunisia. Different geomorphic indexes, including elongation ratio (E), drainage basin asymmetry (Af), hypsometric integral (Hi), Valley floor width-to-height ratio (Vf), mountain front sinuosity (Smf), and stream length gradient index (SL) were calculated. The relationships between the calculated indexes, their correlations and their significance (based on p-values) were also investigated.. Using the hierarchical cluster analysis based on Ward’s method, these indexes were classified into three classes describing the relative, different effect of tectonics in each fault segment. The higher deformation is concentrated in the NE-SW Boudinar fault, followed, in order of decreasing activity, by Goubrar, Gouleb, and Majoura normal faults. This pattern of variation in the relative degree of tectonic activity is consistent with field evidence.

Description: Linked Science is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation, curation, dissemination, and analysis of the data. In this paper, we make the case for the use of scientific scenarios in Linked Science. We propose a scenario in river-channel transport that requires biogeochemical experimental data and global climate-simulation model data from many sources. We focus on the use of ontologies—formal machine-readable descriptions of the domain—to facilitate search and discovery of this data. Mercury, developed at Oak Ridge National Laboratory, is a tool for distributed metadata harvesting, search and retrieval. Mercury currently provides uniform access to more than 100,000 metadata records; 30,000 scientists use it each month. We augmented search in Mercury with ontologies, such as the ontologies in the Semantic Web for Earth and Environmental Terminology (SWEET) collection by prototyping a component that provides access to the ontology terms from Mercury. We evaluate the coverage of SWEET for the ORNL Distributed Active Archive Center (ORNL DAAC).

Description: In this study, a novel method that integrates C4.5 decision tree, weights-of-evidence and m-branch smoothing techniques was proposed for mineral prospectivity mapping. First, a weights-of-evidence model was used to rank the importance of each evidential map and determine the optimal buffer distance. Second, a classification technique that uses a C4.5 decision tree in data mining was used to construct a decision tree classifier for the grid dataset. Finally, an m-branch smoothing technique was used as a predictor, which transformed the decision tree into a probability evaluation tree. The method makes no conditional independence assumption and can be applied for class imbalanced datasets like those collected during mineral exploration for prospectivity mapping of an area. The traits of comprehensibility, accuracy and efficiency were derived from the C4.5 decision tree. In addition, a case study for iron prospectivity mapping was performed in the eastern Kunlun Mountains, China. Sixty-two Skarn iron deposits and eight evidential maps related to iron mineralization were studied. On the final map, areas of low, moderate and high potential for iron deposit occurrence covered areas of 71,491, 14,298, and 9,532 km 2 , respectively. For the goodness-of-fit test, 91.94 % of the total 62 iron deposits were within a high-potential area, 8.06 % were within a moderate-potential area and 0 % were within a low-potential area. For ten-fold cross-validation, 82.26 % were within a high-potential area, 14.52 % were within a moderate-potential area and 3.22 % were within a low-potential area. To evaluate the predictive accuracy, Receiver Operating Characteristic (ROC) curves and Area Under ROC Curve (AUC) were employed. The accuracy of the goodness-of-fit test reached 97.07 %, and the accuracy of the ten-fold cross-validation was 95.10 %. The majority of the iron deposits were within high-potential and moderate-potential areas, which covered a small proportion of the study area.

Description: The sea level change is a crucial indicator of our climate. The spatial sampling offered by satellite altimetry and its continuity during the past years are the major assets to provide an improved vision of the Mediterranean sea level changes. In this paper, an automatic signal extraction approach, based on Singular Spectrum Analysis (SSA), is utilized for analysis and seasonal adjustment of the Mediterranean Sea level series. This automatic approach enables us to overcome the difficulties of visual identification of trend constituents that sometimes we encounter when using the conventional SSA method. The results indicate that the Mediterranean mean sea level is dominated by several harmonic components. The annual signal is particularly strong and almost covers 73.62 % of the original sea level series variation whiles its amplitude is about 15 cm. The extracted trend also indicates that the Mediterranean main sea level has significantly been raised during the period 1993–2012 by 2.44 ± 0.4 mm yr −1 . As an important consequence, considering the current situation, if this trend continues, the Mediterranean Sea level will be raised about 22 cm by the end of this century, which makes a dramatic effect on several issues such as land, flora, fauna, and people activities established along the Mediterranean coastlines.

Description: Estimations of annual suspended sediment loads are required for various types of water resources studies. Often estimation of the sediment load is needed for ungauged watersheds. Regionalization methods provide a practical solution to solve such problems. The purpose of this study is to classify suspended sediment yields in watersheds into homogeneous regions in order to identify their regional sediment rating curves. This study has been carried out for suspended sediment stations on 26 main basins of Turkey. Long term-scale suspended sediment rating curves of 115 gauging stations in Turkey were classified using cluster analysis on the basis of hydrological homogeneity. An agglomerative hierarchical clustering algorithm is used so that stations from different geographical locations are considered in the same cluster independently of their geographical location. 115 gauging stations were clustered into 4 different homogenous regions and the regional suspended sediment rating curve was developed for each region. The performance efficiencies of the developed regional rating curves were evaluated for 8 test stations and compared to the performances of rating curves in test sites. A regionalization model is developed for estimating suspended sediment rating curves for ungauged sites in Turkey. The developed regional rating curve models result in very close performances to those of their corresponding site rating curves.

Description: Terrestrial photogrammetry should be the survey technique of choice when updating large scale urban maps and GIS databases, where 3D data and attribute data are required. Its main drawback is the need for Ground Control Points (GCP) to reference the survey. To make image georeferencing easier and to provide control information, the use of a simple system, made of a photogrammetric camera fastened to a GPS antenna, is proposed. A photogrammetric block, composed by at least three images, is taken around the object with the receiver measuring in kinematic mode. Tie points are automatically extracted by Structure from Motion (SfM) algorithms or measured manually; block orientation is performed by GPS assisted Aerial Triangulation. Advantages as well as limitations of the system are discussed, with particular attention to GPS availability or ill-conditioned block configurations. The issue of system calibration (i.e. measurement of eccentricity between camera and antenna) is also addressed. Several test cases are presented, in which absolute accuracies, verified on check points independently surveyed range from 4 to 7 cm.