Assessing Similarity of Geographic Processes and Events

The increased availability of spatiotemporal data collected from satellite imagery and other remote sensors provides opportunities for enhanced analysis of geographic phenomena. Much of the new data includes regular snapshots of the environment. Comparison of these snapshots can provide information about changes to the phenomena of interest. However, conventional GIS data models and analytical tools lack capabilities to adequately handle massive multidimensional data. One of the fundamental tools necessary to meet such challenges is query support to retrieve and summarize data according to dynamic geographic phenomena, such as geographic events and processes, of interest. Such query support depends upon abilities to assess spatiotemporal similarity so that data representing geographic events that exhibit the spatiotemporal characteristics of interest can be identified in a GIS database. To this end, this paper introduces a method to assess similarity of geographic events and processes (such as storms) based on their spatiotemporal characteristics (such as distribution of precipitation). We developed six indices to capture static and dynamic characteristics of geographic events and applied the Dynamic Time Warping method to temporal sequences of the six indices to examine the similarity among these events. With a case study, we demonstrated the proposed indices and method capable of comparing spatiotemporal characteristics of events as recorded in a GIS database and categorizing spatiotemporal data into groups of events according to their behavior in space and time.     

Modelling and predicting the spatial dispersion of skin cancer considering environmental and socio-economic factors using a digital earth approach

ABSTRACT

Almost all causative factors of diseases depend on location. The Digital Earth approach is suitable for studying diseases globally. Geospatial information systems integrated with statistical models can be used to model the relationship between a disease and its causative factors. Through modelling, the most important causative factors can be extracted and the epidemiology of the disease can be observed. In this paper, skin cancer (the most common type of cancer) has been modelled based on its causative factors, including climate factors, people's occupations, nutrition habits, socio-economic factors, and usage of chemical fertiliser. To fit the model, a data framework was first designed, and then data were gathered and processed. Finally, the disease was modelled using Generalised Linear Models (GLM), a statistical model based on the location of the factors. The results of this study identify the most important causative factors together with their relative priority. Furthermore, a model was used to predict the change in skin cancer occurrences caused by a change in one of its causative factors. This work illustrates the ability of the model to predict disease occurrence. Thus, by using this Digital Earth approach, skincancer can be studied in all the key countries around the world.     

Estimates of current status of forest types in Kolli Hill using remote sensing

The vegetation of Kolli Hill, has been classified for its forest cover types using landsat TM FCCs of two season namely summer (March) and winter (November). The FCCs of two seasons were interpreted visually based on the standard interpretation elements. Extensive field checks were done and corrections were made in both the maps wherever found necessary’. Finally the forest cover type map of Kolli Hill on 1:50,000 scale was drawn by overlaying the interpreted maps of the two seasons The different types of forest were named following Champion and Seth’s classification scheme and the areas of different forest types estimated.     

Effect of Drain Pipes on Uplift Force and Exit Hydraulic Gradient and the Design of Gravity Dams Using the Finite Element Method

Geotechnical and Geological Engineering - The effects of diameter and location of drain pipes on the uplift force and exit hydraulic gradient for a gravity dam are investigated. A numerical model...     

Co-simulated Size Number: An Elegant Novel Algorithm for Identification of Multivariate Geochemical Anomalies

Natural Resources Research - Identification of geochemical anomalies is of particular importance for tracing the footprints of anomalies. This can be implemented by advanced techniques of...     

A tertiary lamprophyre dike with high pressure xenoliths and megacrysts from Wiedemanns Fjord,East Greenland

Lamprophyric dikes, mainly of camptonite/monchiquite affinities occur in the Wiedemanns Fjord area. One example contains a complex assemblage of olivine-orthopyroxene-chrome spinel nodules, megacrysts of kaersutite, diopside, strongly reverse-zoned green salite and various spinel phases. Microprobe analyses are presented for all these phases and for the lilac-coloured titansalites and strongly-coloured kaersutites of the groundmass. It is concluded that these minerals record evolution under various P, T and oxidation regimes during the formation of a lamprophyric parent magma. The nodules provide evidence for deep fractures in this area supposedly associated with early rifting in the North Atlantic.     

The major‐ and trace‐element whole‐rock fingerprints of Egyptian basalts and the provenance of Egyptian artefacts

Discrimination diagrams have been developed that source Egyptian basaltic artefacts using whole‐rock major element geochemistry. These include K₂O versus SiO₂, TiO₂ and P₂O₅ against MgO/Fe₂O₃^t (total Fe as Fe₂O₃), and a discriminant analysis diagram using SiO₂, Fe₂O₃^t, CaO, and MnO. A complementary set of diagrams uses easily obtained trace element data (Nb/Y versus Zr/Nb; Zr [ppm] versus Rb/Sr; TiO₂ [wt % volatile free] versus V; and Cr [ppm] versus Zr/Y) to determine the bedrock sources. These diagrams have been applied to seven First Dynasty basalt vessels (Abydos), two Fourth Dynasty basalt paving stones (Khufu's funerary temple, Giza), and two Fifth Dynasty paving stones (Sahure's complex, Abu Sir). They show that the bedrock source for all the artefacts was the Haddadin flow in northern Egypt. Multidimensional scaling and cluster analysis applied to the whole‐rock data (major elements and trace elements together) and previously published mineral fingerprinting studies confirm these results. Comparing mineral versus whole‐rock fingerprinting techniques, a major advantage of the former is the small sample size required (0.001 g compared to ≥ 0.1 g). Analytical costs are similar for both methods assuming that a comparison (bedrock) database can be assembled from the literature. For most archaeological problems, a whole‐rock bedrock database is more likely to exist than a mineral database, and whole‐rock analyses on artefacts will generally be easier to obtain than mineral analyses. Whole‐rock fingerprinting may be more sensitive than mineral‐based fingerprinting. Thus, if sample quantity is not an issue, whole‐rock analysis may have a slight cost, convenience, and technical advantage over mineral‐based methods. Our results also emphasize that the Egyptians cherished their Haddadin basalt flow and used it extensively and exclusively for manufacturing basalt vessels and paving stones for at least 600 years (∼3150 B.C. to 2500 B.C., approximate ages of the vessels and Abu Sir paving stones, respectively). © 2001 John Wiley & Sons, Inc.