Analytical methods for error propagation in planar space–time prisms

The space–time prism demarcates all locations in space–time that a mobile object or person can occupy during an episode of potential or unobserved movement. The prism is central to time geography as a measure of potential mobility and to mobile object databases as a measure of location possibilities given sampling error. This paper develops an analytical approach to assessing error propagation in space–time prisms and prism–prism intersections. We analyze the geometry of the prisms to derive a core set of geometric problems involving the intersection of circles and ellipses. Analytical error propagation techniques such as the Taylor linearization method based on the first-order partial derivatives are not available since explicit functions describing the intersections and their derivatives are unwieldy. However, since we have implicit functions describing prism geometry, we modify this approach using an implicit function theorem that provides the required first-order partials without the explicit expressions. We describe the general method as well as details for the two spatial dimensions case and provide example calculations.     

Design of an adaptive GPS vector tracking loop with the detection and isolation of contaminated channels

GPS Solutions - In vector tracking loop (VTL), the relativity among received signals is exploited to deeply integrate the entire information within signal processing channels. However, the tracking...     

Distribution of Indus born mica along Gulf of Kachchh coast: Implications in understanding current dynamics

Indus is one of the major sources of sediments to the Gulf of Kachchh. Yet only its <63 micron fraction is studied in detail with regards to the offshore current dynamics. Hence here we present our study on characteristic signature of the Indus sediment load (i.e. mica minerals) in >63 micron size fraction along the coast of Gulf of Kachchh. The spatial distribution of mica minerals along the Gulf of Kachchh coast was studied which showed in general decreasing trend as we move along the northern and southern coast of the Gulf of Kachchh but, an increase in amount near the southern mouth at Okha. The study shows that the earlier proposed tidal barrier is ineffective in restricting movement of mica across the mouth of the gulf due to its characteristic transport mechanism. Also the presence of mudflats along the gulf of Kachchh coast plays a vital role as sediment receptors in the active sediment transport processes and mica minerals prove to be a promising simple tracer in studying the Indus born sediments in the region.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.     

Hydrogeochemical and isotopic study of groundwater in the Habor Lake Basin of the Ordos Plateau,NW China

Hydrogeochemistry and isotopes were used to understand the origin and geochemical evolution in the Habor Lake Basin, northwestern China. Groundwater samples were taken, and the isotopic compositions δD, δ¹⁸O and major ions were analyzed. The groundwater can be divided into three types: the Quaternary groundwater, the shallow Cretaceous groundwater and the deep Cretaceous groundwater. The groundwater chemistry is mainly controlled by the feldspar weathering and dolomite weathering, the dissolution of Glauber’s salt, and cation exchange. Chemistry of lake water is mainly controlled by evaporation and precipitation. The stable isotopes of oxygen and hydrogen in groundwater cluster along the local meteoric water line, indicating that groundwater is of meteoric origin. Comparing with shallow groundwater, deep groundwater is depleted in heavy isotopes indicating that deep groundwater was recharged during late Pleistocene and Holocene, during which the climate was more wetter and colder than today.     

Changing depositional environment revealed from sediment components,west of “Swatch of No Ground”, northern Bay of Bengal

The sediment cores of 20 cm length collected from 31 to 83 m range of water depth from the inner shelf of Bay of Bengal west of “Swatch of No Ground” were analyzed for grain size, organic carbon, total nitrogen, calcium carbonate and clay mineralogy. Grain size analysis revealed that the sediment size decreases from west to east within the study area indicating a possible direction of transport towards east parallel to the coast. The grain size also decreases with increasing water depth, i.e. north to south, indicating sediment contribution to the area of study from Hooghly and other local rivers. In the cores studied, illite was the dominant clay mineral which seems to be a product of glacial weathering under arid conditions with its source being the Himalayan region. The organic carbon content was low in the sediments and was attributed to low plankton production or intense oxidation processes. Low calcium carbonate percentage also supports the view of a low productivity in this region. Organic carbon increases gradually from west to east indicating its association with finer sediments and also indicates transport due to currents which drift the organic carbon away before it settles down within the sediments. Higher values relatively closer to the coast in the eastern side indicate additional contribution from Sunderban mangroves. The C/N ratio obtained indicates mixed source of terrestrial and marine for the organic matter in the sediments. Sedimentation rates available for deltaic plains and shelves off Bangladesh when adopted for the present area revealed that a 20 cm long sediment column was deposited in around 10 years. In most of the cores studied, a change in the trend of sediment components and organic carbon was observed at around 10 cm where grain size increases and organic carbon decreases towards the surface inferring that during the last 5 years, possible floods during NE monsoon or due to melting of ice in Himalaya are responsible for releasing additional water and material which brought a change in hydrodynamic conditions. The surface depletion of organic carbon indicates its dilution by the addition of coarser materials.     

Landfill site selection using combination of fuzzy logic and multi-attribute decision-making approach

During the last decades, growth of urbanization and industrialization led to an increase in solid waste generation. Landfilling is the most prevalent ultimate disposal method for the municipal solid wastes in developing countries. The rapid municipal solid waste generation in Markazi province (central part of Iran) causes the need for precision in finding a suitable landfill site selection. In the present study, 12 factors (environmental and socioeconomic factors) have been applied to select the landfill site in Markazi province, Iran. The different methods including the analytic network process (ANP) combined with fuzzy linguistic quantifier, ordered weighted average (OWA), and weighted linear combination (WLC) approach in geographic information system was applied to find an appropriate landfill site. The OWA operator function permits the evaluation of the wide spectrum of consequences (with different scenario) obtained from different management strategies. Results revealed that integration of fuzzy logic, ANP, and OWA provides flexible and better ideas compared to the Boolean logic and WLC to select a suitable landfill site.