Visibility Analysis In Vision Metrology Network Design

The aim of this paper is to present a method whereby accuracy enhancement of an existing photogrammetric network is achieved through the automatic selection of additional camera stations. The determination of the positions of these 'accuracy fulfilment' camera stations is based upon what has been termed 'visibility uncertainty prediction modelling' of visibility constraints derived from the existing network geometry. Following a review of vision constraints in network design, the concepts of visibility uncertainty prediction and visibility uncertainty spheres are introduced. These provide a mechanism to predict the visibility of current object target points for the new accuracy fulfilment images. This in turn aids in network design improvement. The visibility uncertainty modelling is then illustrated for two close range photogrammetric network configurations, for which the test results demonstrate that the proposed model can reliably predict target visibility with an overall certainty of 75%.     

Comprehensive evaluation of regional flood frequency analysis by L- and LH-moments. II. Development of LH-moments parameters for the generalized Pareto and generalized logistic distributions

As part II of a sequence of two papers, previously developed L-moments by Hosking (1990), and the LH-moments by Wang (1997) are further investigated. The LH-moments (L to L₄) are used to develop the regional parameters of the generalized extreme value distribution, generalized Pareto (GPA) distribution and the generalized logistic (GLO) distributions. These respective probability distribution functions (PDFs) are evaluated in terms of their performances. Flood peaks by the corresponding PDFs are compared with those generated by Monte Carlo simulation of randomized data, considering the respective LH-moments. The influence of the LH-moments on estimated PDFs are studied by evaluating the relative bias (RBIAS) in quantile estimation due to variability of the k parameter. Karkhe watershed located in western Iran was used as a case study area. Part I of this study identified the study area as regions A and B. The minimum calculated relative root mean square error (RRMSE) and RBIAS between simulated flood peaks and flood peaks by the corresponding PDFs were used in PDF selection, considering the respective LH-moments. The boxplots of the RRMSE tests identified the L₃ level of the GPA distribution as the suitable PDF for sample sizes 20 and 80; for region A. Similar results were found for the RBIAS test. As for region B, the boxplots of the RRMSE tests indicated similar results for the three PDFs. However, the boxplots of the RBIAS tests identified the L₄ level of the GLO most suitable for sample sizes 20 and 80. Relative efficiencies of the LH-moments were investigated, measured as RRMSE ratios of L-moments over the respective LH-moments. For the most parts the findings of this part of the study were similar to those of part I.     

Fluid Inclusion Studies and Geochemistry of Rare Earth Elements of Hydrothermal Fluorites from Pohrenk, Kirsehir, Central Turkey

Fluorite mineralization occurs along fractures and cracks of Middle Eocene and Pliocene limestones and marls in the north and northeast of the Pohrenk region (Qicekdagi, Kirsehir). Tb/Ca - Tb/La and Y/Ho ratios were obtained from REE contents of fluorites which have revealed that mineralization is of hydrothermal type. Negative Ce anomalies and positive Eu anomalies reflect that hydrothermal solutions once had high oxygen fugacity. Fluid inclusion studies indicate that homogenization temperatures of mineralization varied between 90℃ and 200℃, and hydrothermal solutions are composed of NaCl + KCl + MgCl2 + H2O. In addition, salinity measurements show that hydrothermal solutions were mixed with meteoric or rock formation water. Geologic setting, REE geochemistry and fluid inclusion studies suggest that mineralization was deposited from a solution generated by mixing of magmatic and meteoric water under epithermal conditions.     

Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai??i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at M??kaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2?h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather data generation and disaggregation methods were concentrated in a few Hawaiian watersheds, the results presented can be used to similar mountainous location settings, as well as any specific locations aimed at furthering the site-specific performance evaluation of these tested models.     

Prediction of safety factors for slope stability: comparison of machine learning techniques

Natural Hazards - Because of the disasters associated with slope failure, the analysis and forecasting of slope stability for geotechnical engineers are crucial. In this work, in order to forecast...     

Emeishan large igneous province, SW China

In recent years, there have been major advances in our understanding of the Emeishan large igneous province (LIP) of SW China following publication of a number of LIP-focused investigations of the terrain and associated rocks. This paper reviews the current state of knowledge. The volcanic and upper-intrusive portion of the province is relatively small (0.3×10⁶ km³), even when offset fragments, eroded sections and buried portions are included in the volume calculation. The most reliable radiometric age dates (zircon U–Pb SHRIMP from an associated layered intrusive body several kilometers in area) indicate generation at 259 Ma, consistent with the end-Guadalupian (end Middle Permian) stratigraphic age. In addition, several Ar–Ar dating studies have been carried out, mainly on the volcanic rocks, with a number of reported dates 253–251 Ma (Late Permian), but a consensus is emerging that these ages are problematic because they are in conflict with the stratigraphic data (possibly due to a monitor standard miscalibration). The Ar–Ar investigations have also yielded a large number of secondary ages, which are clustered at 175, 142, 98 and 42 Ma, and these are inferred to record sub-regional tectonic events that affected the western Yangtze Block as East Asia was assembled and later deformed by India’s collision–indentation into Asia. Magnetostratigraphic data and field observations suggest that the bulk of the volcanic sequence formed within 1–2 my. The geochemistry of the volcanic rocks and bio-lithostratigraphic studies of the underlying Maokou Formation suggests a mantle plume generated the province. The basalts can be classified into low and high Ti groups with different parental magmas. The low Ti basalts are confined to the western part of the province and are overlain by the high Ti basalts. The low Ti magmas formed at shallow mantle depths in the spinel–garnet field transition zone (60–80 km), whereas the high Ti magmas formed by low degrees of partial melting within the deeper garnet stability field. This observation suggests a deepening of the melting column as the lithosphere thickened due to under-plating and a transition from peak basalt generation to the waning stage. Outstanding issues, which might focus future studies, are also outlined.     

An investigation of the effects of important grouting and rock parameters on the grouting process

Today, grouting is used as an aid in ground improvement in most civil and mining engineering projects. Groutability and grout penetration depth are among the most important issues that are considered in grouting operation. Various parameters such as in-situ stress, pore water pressure, joint geometric and geomechanical characteristics, grout properties (viscosity and yield stress) and technical factors such as grouting pressure and flow rate affect the groutability and grout penetration depth in a jointed rock mass. Knowledge of the effect of these parameters has advantages in the prediction of grouting results. Typically, cement-based grout is used in jointed rock masses. Unlike water, stable cement-based grout usually acts as a Bingham fluid. In this study the effect of important parameters on grouting process in a jointed rock mass was investigated numerically using the DEM method. In the conducted study, the problem geometry represents a horizontal section in a regularly jointed rock mass with two joint sets. The analyses results show that the grout penetration depth and intake increase as joint aperture, normal stiffness and grouting pressure increase and in-situ stress and pore water pressure decrease. Increase in joint spacing does not have any effect on the grout penetration depth but decreases the grout intake. The effect of joint orientation on grouting process is strongly dependent on in-situ stress state. On the other hand, increase in grout yield stress decreases the grout penetration depth and intake, while grout viscosity does not have any effect on maximum grout penetration depth and intake. To further investigate the above mechanisms, the grouting process conducted in Gotvand dam-Iran was simulated numerically.     

Determination of Polycyclic Aromatic Hydrocarbons in Soil by Miniaturized Ultrasonic Extraction and Gas Chromatography‐Mass Selective Detection

A miniaturized ultrasonic extraction procedure was developed for the determination of polycyclic aromatic hydrocarbons (PAHs) in soil by gas chromatography‐mass spectrometry. After determination of the most suitable extraction solvent with 5 min sonication time, several other parameters (sample amount, solvent volume and number of extraction times) were optimized using a 2³ factorial experimental design. Recoveries of PAHs from spiked soil samples were over 90% for three different fortification levels between 50 and 300 μg/kg, and relative standard deviations of the recoveries were in the range of < 1–15%. The limits of detection ranged from 0.002 to 1.87 μg/kg. The performance of the developed procedure was also compared with other traditional Soxhlet, shake flask and large scale ultrasonic extraction procedures on real soil samples, and extraction methods showed comparable efficiencies. The proposed procedure required small volumes of solvent and sample. It was practicable, rapid and easy to use for analysis of PAHs in soils.     

Comparison of ordinary kriging and artificial neural network for spatial mapping of arsenic contamination of groundwater

In this technical note, we investigate the hypothesis that ‘non-linearity matters in the spatial mapping of complex patterns of groundwater arsenic contamination’. The spatial mapping pertained to data-driven techniques of spatial interpolation based on sampling data at finite locations. Using the well known example of extensive groundwater contamination by arsenic in Bangladesh, we find that the use of a highly non-linear pattern learning technique in the form of an artificial neural network (ANN) can yield more accurate results under the same set of constraints when compared to the ordinary kriging method. One ANN and a variogram model were used to represent the spatial structure of arsenic contamination for the whole country. The probability for successful detection of a well as safe or unsafe was found to be atleast 15% larger than that by kriging under the country-wide scenario. The probability of false hopes, which is a serious issue in public health monitoring was found to be significantly lower (by more than 10%) than that by kriging.     

Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations

The importance of satellite datasets as alternative sources of precipitation information has been argued in numerous studies. Future developments in satellite precipitation algorithms as well as utilization of satellite data in operational applications rely on a more in‐depth understanding of satellite errors and biases across different spatial and temporal scales. This paper investigates the capability of satellite precipitation data sets with respect to detecting heavy precipitation rates over different temporal accumulations. In this study, the performance of Tropical Rainfall Measuring Mission real time (TRMM‐RT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks and CPC MORPHing (CMORPH) is compared against radar‐based gauge‐adjusted Stage IV data. The results show that none of the high temporal resolution (3‐h) datasets are ideal for detecting heavy precipitation rates. In fact, the detection skill of all products drops as the precipitation thresholds (i.e. 75 and 90 percentiles) increase. At higher temporal accumulations (6, 12 and 24 h), the detection skill improves for all precipitation products, with CMORPH showing a better detection skill compared to all other products. On the other hand, all precipitation products exhibit high false alarm ratios above the heavy precipitation thresholds, although TRMM‐RT lead to a relatively smaller level of false alarms. These results indicate that further efforts are necessary to improve the precipitation algorithms so that they can capture heavy precipitation rates more reliably. Copyright © 2013 John Wiley & Sons, Ltd.