Geographic Phenomena Research Articles

Shared Space, Divided Space: Narrating Ethnic Histories of Osh

In June 2010 the Kyrgyzstani city of Osh was engulfed in three days of mass killing, arson, and looting. Accounts by journalists, academics, politicians, and organisations tend to either overdetermine ethnicity as a causal factor, or dismiss its significance as a social process. As a result, internal responses to the tragedy have been viewed by outsiders as mendaciously irrational. To overcome this impasse, this paper foregrounds the idea of Osh as national territory. Based on ongoing ethnographic study since 1995, plus an analysis of media reports, it shows the ways in which Uzbek and Kyrgyz residents of the city have narrated its ethnic past as one of divided or shared space. The resonance of these narratives can both help account for responses to the violence within Kyrgyzstan that have puzzled outsiders, and also uncover resources of hope. The paper highlights the importance of considering nationalism as a geographical phenomenon in explicating ethnic-based violence in contemporary Central Asia.

Eugeniusza Romera zabiegi o odbudowę i bezpieczny kształt granic niepodległej Polski

This article presents Eugeniusz Romer (1871–1954), a great humanist and patriot, world-famous scientist, one of the most prominent Polish geographers of the first part of the 20th century, a founder of modern Polish cartography, author of many maps and atlases, and an outstanding climatologist and glaciologist. He was also interested in hydrography, geomorphology, regional and economic geography and the influence of geographic phenomena on social and economic life, and was the first scientist to point at a link between geography and politics, and Poland’s geopolitical location and her relations with neighbours. Since his early years he had been very active politically and socially. He lived in the middle of great social and political transformations, wars and revolutions, shaping Poles social and national awareness, Polish independence fight, battles for territories and the future nature of Poland – in all those events he also took an active part.

Cenozoic Tectonic Migration Characteristics in Qikou Sag of Bohai Basin, China

Tectonic migration, a widespread geographic phenomenon prevailing in China basins, refers to that tectonic movement, sedimentation, magmatism and other geological process in basin have regularly migrated towards a particular direction in a certain geological evolution period, which are triggered by tectonization such as tectonic plate motion, mantle uplift and so on. Statistics obtained from elements of faults and materials on sedimentary and volcanic in Qikou sag are analyzed to study the movement and characteristics of tectonic migration. It is shown in the research that in Cenozoic fault activity, sedimentation and magmatism of the sag presented the characteristics of regular migration from the southwest to northeast. Besides, the faults strikes, controlling sedimentary fault strike and controlling magmatic activity structural trend changed from northeast in Sha-3 period to nearly east-west in Sha-1 period. And this phenomenon of migration is also common in other sags of Bohai basin. The regional geological background and thermodynamic characteristics of Qikou sag together demonstrate that this tectonic migration may be the performance of the deep mantle material activities on the superficial layer in Bohai basin as a result of both mantle motion and plate movement. In Qikou sag the tectonic migration has important influences on hydrocarbon accumulation.

The Structuration Approach of Anthony Giddens

Structuration Theory developed by Anthony Giddens, a British sociologist, in response to claims by post-structuralism, holds that the structures that humans find themselves in are determined for them, and volunteerism, that suggests that humans are completely free to create their lived environment. Structuration theory has a several unique nomenclature to explain the relationships that the human “agency” has with institutions or “structure”. This paper explains the use of the words and relates them to relevant examples. The understanding that Structuration Theory gives us can be very useful for understanding geographic phenomenon such as the idea of the time-space continuum. Urban arenas have a very complex set of relationships between humans and their environments; housing, movement within the environment, etcetera. The paper is also focused on understanding the connections between Giddens’ theory and the field of geography. The main focus of this paper is on exploring the complexities of Giddens’ Structuration Theory and understanding how it is currently being implemented in societies.DOI: http://dx.doi.org/10.3126/hjsa.v5i0.7043 Himalayan Journal of Sociology & Anthropology-Vol. V (2012) 111-122

Discussion on Type-I fuzzy boundary and Research on Boundary Definition of High Order Fuzzy Region

The definition of fuzzy boundary is crucial in research of modeling and analysis of fuzzy geographical phenomena. The problem “boundary syndrome” has been a longstanding problem in this domain, and this problem has seriously affected the research and application of fuzzy geographical model. The existing fuzzy boundary models were discussed at first, and then some models based on type-I fuzzy sets were analyzed in detail. This paper pointed out the fuzzy boundary models should have three kinds of meaning: “frontier”, “transition” and “division”. Three types of boundary models of high order fuzzy region were proposed based on interval type-2 fuzzy set, and they embody three kinds of meaning of fuzzy boundary respectively. The models proposed by this paper have a positive effect to high order geographical phenomena modeling and analysis. DOI: http://dx.doi.org/10.11591/telkomnika.v10i6.1544 Full Text: PDF

Slope Analysis of Fuzzy Surfaces

AbstractAnalysis of the slope is one of the fundamental analyses within geoinformatics, especially its initial calculation. Slope analysis is usually used as the first step in much more sophisticated analyses as well as in complex models of natural phenomena. Fuzzy surfaces provide representation of geographical phenomena with all aspects of the uncertainty (i.e. both in terms of the description of reality or the uncertainty of measurement). The uncertainty in the input surface is crucial for analysis of slope. A high level of uncertainty can significantly affect the result of slope analysis. The Neighbourhood method was utilized for calculating with fuzzy numbers and to perform slope analysis of the fuzzy surface. The main reason for choosing this method is that it belongs to the most common tools in GIS software (e.g. both ArcGIS and GRASS). The computation with fuzzy numbers instead of crisp numbers allows evaluation of uncertainty of the resultant slope. The aim of this article is to present the process of slope calculation with fuzzy numbers as well as all necessary algorithms that are needed for such calculation. The further analysis of uncertainty provides important information for the process of decision making. The level of uncertainty in the results of the above‐mentioned analysis can be as important as the actual result. It is especially important in situations where the amount of uncertainty varies at higher values.

Prototyping an open environment for sharing geographical analysis models on cloud computing platform

The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems (e.g. Digital Earth), but there remain some issues that have not been completely resolved. The challenges include, eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models. Taking advantage of cloud computing, this article aims to address the above issues and develop an open environment for geographical analysis model sharing. On the basis of the analysis of the applicability of cloud computing, the architecture of the open environment is proposed. More importantly, key strategies designed for heterogeneous model description, model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment. Finally, the prototype environment is implemented, and experiments were conducted to verify the environment's feasibility to support the sharing of geographical analysis models.

Exploiting empirical knowledge for automatic delineation of city centres from large-scale topographic databases

Current topographic databases rarely represent higher order geographic phenomena, such as city centres. However, such concepts are often referred to by humans and used in various forms of spatial analysis. Hence, the value and usability of topographic databases can greatly be improved by methods that automatically create such higher order phenomena through cartographic pattern recognition techniques, departing from the very detailed, geometry-oriented representations of topographic databases. As many higher order phenomena are only vaguely defined, this paper develops and evaluates a methodology to acquire definitional knowledge about geographic phenomena by participant experiments and use this knowledge to drive the cartographic pattern recognition process. The method is applied to acquire knowledge about British city centres and delineate referents of city centre from topographic data. City centres produced for ten British cities are compared to areas derived from alternative sources. F1-scores between 0.45 and 0.88 are achieved, suggesting that the delineation produced plausible city centre areas. The benefits of our work are better (and user-driven) descriptions of complex geographic phenomena that can form the basis for accurately enriching topographic databases with additional semantics, thus yielding added value for the data producer and the end user.

Molecular Phylogeny and Phylogeography of the Australian Freshwater Fish Genus Galaxiella, with an Emphasis on Dwarf Galaxias (G. pusilla)

The freshwater fauna of Southern Australia is primarily restricted to the southwestern and southeastern corners of the continent, and is separated by a large, arid region that is inhospitable to this biota. This geographic phenomenon has attracted considerable interest from biogeographers looking to explain evolutionary diversification in this region. Here, we employed phylogenetic and phylogeographic approaches to evaluate the effect of this barrier on a group of four galaxiid fish species (Galaxiella) endemic to temperate Southern Australia. We also tested if continental shelf width has influenced connectivity among populations during low sea levels when rivers, now isolated, could have been connected. We addressed these questions by sampling each species across its range using multiple molecular markers (mitochondrial cytochrome b sequences, nuclear S7 intron sequences, and 49 allozyme loci). These data also allowed us to assess species boundaries, to refine phylogenetic affinities, and to estimate species ages. Interestingly, we found compelling evidence for cryptic species in G. pusilla, manifesting as allopatric eastern and western taxa. Our combined phylogeny and dating analysis point to an origin for the genus dating to the early Cenozoic, with three of the four species originating during the Oligocene-Miocene. Each Galaxiella species showed high levels of genetic divergences between all but the most proximate populations. Despite extensive drainage connections during recent low sea levels in southeastern Australia, populations of both species within G. pusilla maintained high levels of genetic structure. All populations experienced Late Pleistocene-Holocene population growth, possibly in response to the relaxation of arid conditions after the last glacial maximum. High levels of genetic divergence and the discovery of new cryptic species have important implications for the conservation of this already threatened group of freshwater species.

Differences between physical and human process simulation in geography: Empirical analysis of two cases

Physical geography and human geography are the principal branches of the geographical sciences. Physical process simulation and human process simulation in geography are both quantitative methods used to recover past events and even to forecast events based on precisely determined parameters. There are four differences between physical process simulation and human process simulation in geography, which we summarize with two specific cases, one of which is about a typhoon’s development and its precipitation, and the other of which is regarding the evolution of three industrial structures in China. The differences focus on four aspects: the main factors of the research framework; the knowledge background of the systematic analysis framework; the simulation data sources and quantitative method; and the core of the study object and the method of forecast application. As the human-land relationship is the key ideology of the man-land system, the relationship between the physical and human factors is becoming increasingly close at present. Physical process simulation and human process simulation in geography will exhibit crossing and blending in the future to reflect the various geographical phenomena better.

Integrating spatial relations into case-based reasoning to solve geographic problems

Case-based reasoning (CBR) method has been widely used to study environmental and spatial problems since the 1990s. Spatial relations among geographic cases and between case and environment (hereinafter to be referred as spatial relations) were not well considered in most of the previous studies. However, these relations are extremely important in geographic problems solving as spatially closer geographic phenomena are more likely to be similar than those are disperse in space. This paper presents a generic application paradigm based on CBR to solve geographic problems. To better consider the spatial relations, a new component of “Geographic Environment” was added into the standard CBR case representation model. A rough set-based algorithm was used to prune essential spatial relations, which were then used to extract key decision rules and retrieve similar past cases for the new problem. Standard CBR directly accepts the solution that was derived from the past similar cases to solve the new problem. In this study, however, solution was not accepted unless it also satisfied the key decision rules. An illustrating example was used to demonstrate how the general framework and algorithm could be applied to solve geographic problems. The algorithm was then evaluated by examining two datasets, the 2003 land use in the Pearl River Estuary and land use change from 1995 to 2000 in Zhuhai city of China. These two datasets were also examined by the standard CBR and Bayesian Networks (BNs) methods. Comparison of the stratified 10-fold cross-validation results indicated that the algorithm proposed in this study yielded statistically significant higher overall validation accuracy than the standard CBR and BNs methods.

공간현상 분석을 위한 GIS 기반의 공간통계적 접근방법에 관한 고찰: 공간 군집지역 탐색을 위한 공간검색통계량의 실증적 사례분석

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

Lessons from learner experiences in a field-based inquiry in geography using mobile devices

Geographical inquiry involves collecting, using and making sense of the data to investigate some geographical phenomena. With the increasing number of mobile devices equipped with Internet access capabilities, there is a wide scope for using it in field inquiry where learning can take place in the form of social interactions between team members while performing a common task. The authors examine the use of MobiTOP (Mobile Tagging of Objects and People), a geospatial digital library system which allows users to contribute and share multimedia annotations via mobile devices, within a geographical field inquiry. A key feature of MobiTOP that is well suited for collaborative learning is that annotations are hierarchical, allowing annotations to be annotated by other users to an arbitrary depth. A group of student and teachers involved in an inquiry-based learning activity in geography was instructed to identify rock types and associated landforms by collaborating with each other using the MobiTOP system. A method combining several data collection methods was used. Four main findings on the affordances of the mobile phone, the need for specialized training in using the application with the mobile phone, design considerations of the application and the authentic context of learning with fieldwork are reported. A discussion on the implication of these findings and how mobile technology may be used for geographical field learning are also included in this paper.

POSTKOMUNIZMAS KAIP IDEOLOGINĖ KONSTRUKCIJA

The main task of this article is the conceptualization of post-communism. The article seeks to challenge the persistence tendency to describe post-communism only as a political and geographical phenomenon. Post-communism is shown to be a complex process that fits uneasily into pre-given categories. Ideology as a complex of theories, convictions, beliefs, argumentative procedures is one of the most important dimen­sions of post-communism. This article insists on the importance of ideology without falling into the traps of either determinism or historicism.The article challenges the dominant universal discourse of political liberalism, which sees post-communist change as a one-way process of transition to liberal de­mocracy and free market. This universal politics of post-communism produces new hierarchies and forms of exclusion between ‘postmodern’ West and ‘post-communist’ East. Thus we need to employ the tools of post-colonialism and postmodernism to explore and deconstruct the operation of the concept of post-communism through language, culture and institutions.The article argues that so called neutral ‘post-ideological consensus’ is actually ideological and contradictory. Post-communism is not the objective ‘transitional’ re­ality, rather it is the subjective (mis)perception of ideological representations. The ar­ticle also challenges the myths of ‘the end of ideology’, ‘the end of communism’ and ‘the end of modernity’. Post-communism is not the transitional condition from ideo­logy of communism to ‘post-ideological’ liberal democracy, but rather the complex, ambivalent and long historical norm, or, in other words, specific type of modernity.

Geovisualization of tropical cyclone behaviour in the South Pacific

Abstract A combination of computational power, dynamic graphics and geographical information system (GIS) packages creates a powerful platform for advanced visualization tools to explore complex geographical phenomena in an interactive computer environment – known as geovisualization. Geovisualization is a relatively new computer-based approach that refers to a set of methods and techniques to support geospatial data analysis through the use of four-dimensional (4D), multi-variable and interactive visualization. In this paper, we illustrate and discuss the value of several spatialization techniques that are used to perform analysis of spatial structures of climatic and meteorological elements, especially through the geovisualization of characteristics and behaviour of tropical cyclones in the South Pacific Ocean. Preliminary findings are encouraging, allowing patterns and dependencies between chosen cyclone features to be identified, in turn indicating the enormous potential of geovisualization for analysing multi-variate spatial attributes within large tropical cyclone datasets.

Un modèle UML et des contraintes OCL pour les entrepôts de données spatiales. De la représentation conceptuelle à l'implémentation

Spatial Data Warehouses (SDW) and Spatial OLAP (SOLAP) systems represent an effective solution to perform spatial analysis on geographical phenomena. However, the quality of such analysis heavily depends on the quality of stored data and how these data are explored: how the different indicators are computed (What aggregate functions are applied to summarize the measures and in what order these functions are applied?). In this context, a number of studies have been attempted to address the issues of data quality in SDW by using Integrity Constraints (IC). In this paper, motivated by the lack of Model Driven Architecture (MDA)-based implementations, we propose a conceptual framework based on two new classifications to ease identification and implementation of SDW IC. Moreover, following an MDA approach, we propose the MDA-based modeling of most IC categories using the UML (Unified Modeling Language) and OCL (Object Constraint Language) standard languages; and show the automatic implementation of some IC classes using an MDA-based code generator, called Spatial OCL2SQL.

Mobile Telephone Ownership and Usage among Urban Residents in Nigeria

Since the launch of GSM in 2001 in Nigeria, mobile telephony has rapidly become the most popular method of voice communication in Nigeria. Statistics from Nigerian Communications Commission show that there are more than 8 million subscribers as at mid 2011. Since communication is spatial in nature, there is a view That the advent of GSMs may influence geographic phenomenon, particularly human spatial interaction and location decision in urban settings. This study investigates mobile telephone ownership and usage among urban residents in Nigeria using Ibadan North Local Government Area as the study area. Random sampling was used To select two hundred and twenty two (222) respondents. The study found that there is a significant relationship between Telephone ownership and socio-economic characteristics of urban residents (r = 0.54 at P < 0.05). Household size. income and job type was found to be the must important variables influencing telephone ownership. Results of analysis showed that The most important use of mobile telephone is for business, interpersonal communication and social connectivity. Study also suggests urban Trip scheduling, rescheduling and elimination via The use of mobile Telephone. The study advocates the optimum use of mobile telephone in urban areas to reduce frequency of trips and to serve as Traffic reduction strategy.

Testing local versions of correlation coefficients

The aim of this paper is to define and test local versions of standard correlation coefficients in statistical analysis. This research is motivated by the increasing number of applications using local versions of explanatory spatial data analysis methods such as local regression. Local statistical methods should be applied together with local measures of statistical inference in order to check their performance and to provide an indication of the quality of their results. One example of local explanatory data analysis method is the Geographically Weighted Regression, the application of which allows the researcher to check for the existence of spatial nonstationarity in the relationships between a geographic phenomenon and its determinants. In this paper, a local version of Pearson correlation coefficient is defined and applied to internal migration data in Sweden. The results suggest that globally independent variables are not necessarily independent locally, thus the independence criterion may be violated when local regression analysis is performed. Thus, the results of local regression analysis should be presented in light of the local statistical inference and their interpretation should be made with care.

A general method of spatio-temporal clustering analysis

Spatio-temporal clustering has been a hot topic in the field of spatio-temporal data mining and knowledge discovery. It can be employed to uncover and interpret developmental trends of geographic phenomenon in the real world. However, existing spatio-temporal clustering methods seldom consider both spatiotemporal autocorrelations and heterogeneities among spatio-temporal entities, and the coupling in space and time has not been well highlighted. In this paper, a unified framework for the clustering analysis of spatio-temporal data is proposed, and a novel spatio-temporal clustering algorithm is developed by means of a spatio-temporal statistics methodology and intelligence computation technology. Our method is applied successfully to finding spatio-temporal cluster in China’s annual temperature database for the period 1951–1992.

A Contextual Mann‐Kendall Approach for the Assessment of Trend Significance in Image Time Series

AbstractOne of the most common problems in estimating trends in image time series is the presence of contaminants such as clouds. There are many techniques for estimating robust trends but evaluating the significance of the trends can be difficult due to this increased variance. This article presents a novel approach called the Contextual Mann‐Kendall (CMK) test for assessing significant trends. This test uses the principle of spatial autocorrelation to characterize geographical phenomena, according to which a pixel would not be expected to exhibit a radically different trend from neighboring pixels. The procedure removes serial correlation through a prewhitening process. Then, similar to the logic of the Regionally Averaged Mann‐Kendall (RAMK) test, it combines the information from neighboring pixels while adjusting for cross‐correlation. CMK was compared with the Mann‐Kendall (MK) test in which contextual information was not involved for the mean annual NDVI over 22 years (1982–2003) in West Africa. With the MK test, ∼11% of the study area showed significant (p < 0.001) trends which increased to 16% when tested using the CMK test. Thus the CMK test produces a result that makes intuitive sense from a geographical perspective and enhances the ability to detect trends in relatively short time series.