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Qualitative spaces: Integrating spatial analysis for a mixed methods approach

Qualitative spaces: Integrating spatial analysis for a mixed methods approach

Spatial data generally are used in two main ways in qualitative research studies, with varying descriptive and analytical power. First, statistics (e.g., demographic data) associated with specific geographic boundaries provide a broader sense of the context in which social processes emerge. These kinds of statistics are most often deployed descriptively in the form of tables or maps. Second, some scholars use spatial data to examine patterns and trends, integrating spatial data into the analysis. This comes in the form of maps as tools for identifying patterns between the area of study and its surrounding areas, and the triangulation of spatial and qualitative data sources to analyze qualitative data by its spatial characteristics. These approaches can be leveraged analytically to address research questions and to reveal new areas of inquiry. Spatial description is prevalent in ethnographic and case study inquiries, as well as some qualitative interviews, participant observation, and archival or document review projects, due to their attention to contextual factors. However, we argue that the analysis of spatial data is largely missing from qualitative research, particularly in sociology. In this article, we argue that spatial analysis should play a larger role in qualitative inquiry. We present a theoretical argument for integrating spatial analysis in qualitative methods by comparing illustrative examples in three areas of sociological research: social capital, immigration, and education. Additionally, we share strategies for triangulating spatial and qualitative data. Although we target our critique to sociology, our conclusions and recommendations are relevant across the social sciences. The article proceeds as follows: First, we describe some key historical precedents for the use of spatial analysis in sociological qualitative research and provide a working definition of spatial analysis. We provide empirical evidence of the lack of spatial analysis in qualitative sociological inquiry. Next, we highlight a study in each of the selected topic areas—social capital,
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Spatial Analysis of Jembrana Disease in South Kalimantan Province

Spatial Analysis of Jembrana Disease in South Kalimantan Province

Jembrana Disease (JD) is an acute infectious disease in Bali cattle that caused by Jembrana Disease Virus. It is causes high economical losses and endemic in several provinces in Indonesia. Studies on the epidemiology of JD rarely consider the spatial dimension of disease prevalence. Geographic Information System (GIS) has been increasingly used in spatial epidemiology to analyze the disease pattern based on the geographical data. This study presents the spatial analysis of JD to provide information about the distribution of JD in South Kalimantan province. Serological data were obtained based on the surveillance throughout the province and screened using PCR diagnostic technique during 2008 to 2010 to determine JD seropositive. JD was found mostly in the northern, southern, and western parts of the province. The seroprevalence of JD was higher in district of Banjarbaru, Banjar, and Tanah Laut. Using spatial scan statistic, the distribution of JD was spatial clustered in specific area. This elevated risk within the cluster was significant (p<0.001). JD seropositive positively associated with cattle density and distance to the main rivers and negatively associated with cattle density and elevation. It indicates that JD seropositive was higher in lowland and the area with higher cattle density.
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Spatial Analysis Based on Variance of Mo

Spatial Analysis Based on Variance of Mo

A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease sur- vey data encompassing both airborne and soilborne diseases. The results obtained using the VMWA method were generally different from those obtained with Lloyd’s index of patchiness and beta-binomial distribution methods, were in partial agreement with the results from spatial analysis by distance indices, and were highly consistent with the results from semi- variogram and spatial autocorrelation analysis meth- ods. Results demonstrated that the VMWA method can be applied to many types of data, including bino- mial diseased or healthy plant counts, incidence, sever- ity, and number of diseased plants or pathogen propagules although directional and edge effects may limit its application.
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Predicted stand volume for Eucalyptus plantations by spatial analysis

Predicted stand volume for Eucalyptus plantations by spatial analysis

Focus concentrated on physical measures of growth and yield in this study area namely, merchantable volume, because it forms the basis of value measures. Multiple Regression analysis are used for the modeling and analysis of numerical data consisting of values of a dependent variable (response variable) and independent variables (explanatory variables). This method enables one to determine whether the models follow the real world, can be examined using chi-square test of goodness of fit.

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isprs archives XLII 4 W2 91 2017

isprs archives XLII 4 W2 91 2017

The aim of this paper is to measure the spatial accessibility to public health care facilities in Greece. We look at population groups disaggregated by age and socioeconomic characteristics. The purpose of the analysis is to identify potential spatial inequalities in the accessibility to public hospitals among population groups or service areas. The data refer to the accessibility of all residents to public hospitals in Greece. The spatial datasets include the location of settlements (communities), the administrative boundaries of municipalities and the location of public hospitals. The methodology stems from spatial analysis theory (gravity models), economics theory (inequalities) and geocomputation practice (GIS and programming). Several accessibility measures have been calculated using the newly developed R package SpatialAcc, which is available in CRAN. The results are interesting and tend to show an urban-rural and social class divide: younger, working age population as well as people with the highest educational attainment have better accessibility to public hospitals compared to older or low educated residents. This finding has serious policy making implications and should be taken into account in the future spatial (re)organisation of hospitals in Greece.
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Spatial Analysis of Agricultural Landscape and Hymenoptera Biodiversity at Cianjur Watershed

Spatial Analysis of Agricultural Landscape and Hymenoptera Biodiversity at Cianjur Watershed

Hymenoptera is one of the four largest insect order (the other three are Coleoptera, Diptera, and Lepidoptera). There are curerently over 115 000 described Hymenoptera species. It is clear that Hymenoptera is one of the major components of insect biodiversity. However, Hymenoptera biodiversity is affected by ecology, environment, and ecosystem management. In an agricultural areas, the spatial structure, habitat diversity, and habitat composition may vary from cleared landscapes to structurally rich landscape. Thus, it is very likely that such large-scale spatial patterns (landscape effects) may influence local biodiversity and ecological functions. Therefore, the objective of this research were to study diversity and configuration elements of agricultural landscapes at Cianjur Watershed with geographical information sytems (GIS) and its influence on Hymenoptera biodiversity. The structural differences between agricultural landscapes of Nyalindung, Gasol, and Selajambe were characterized by patch analyst with ArcView 3.2 of digital land use data. Results indicated that class of land uses of Cianjur Watershed landscape were housing, mixed gardens, talun and rice, vegetable, and corn fields. Landscape structure influenced the biodiversity of Hymenoptera. Species richness and the species diversity were higher in Nyalindung landscape compare to Gasol and Selajambe landscape.
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isprsarchives XXXIX B4 321 2012

isprsarchives XXXIX B4 321 2012

Thus, for planners and others to do so in a spatial geographic world, Geoscientists provided spatial tools which if used effectively, the indicators of sustainability will start to flow in the same stream or perhaps same direction, and the closeness of some works or activities to satisfy an indicator can be much more comprehensively planned, implemented and measured. Giving an example of which, someone might say the emission level of greenhouse gases is an indicator or part of an indicator, or the closeness of industrial areas to dwelling is a negative indicator, or whatever valuable measures they can be that are set by specialized organizations, and herein comes the role of spatial analysis tools to provide an assistant for thinking about, understanding it, acting in accordance to, and living a life of such. This paper reflects role assessment using some activity works with practical examples of sustainability spatial analysis, targeting monitoring and protecting our world environment letting the process work flow show and prove how to use the different sustainability indicators particularly in urban planning. 1.2 Analysis of some layers affecting CO2 emission
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SPATIAL ANALYSIS FOR LAND CAPABILITY ASSESSMENT USING GEOGRAPHIC INFORMATION SYSTEM

SPATIAL ANALYSIS FOR LAND CAPABILITY ASSESSMENT USING GEOGRAPHIC INFORMATION SYSTEM

Land utilization in Wampu Hulu Sub Watershed should be based on its land capability. This research was conducted in March-September 2011 at Wampu Watershed, Langkat, North Sumatra, Indonesia. Land capability classification was conducted by spatial analysis for capability of land criteria using Geographic Information System (GIS) (overlay technique). The land criteria are slope, soil erodibility, level of erosion hazard, soil depth, soil texture, permeability and drainage. Soil analyze was done in order to obtain the data of soil texture, permeability, soil erodibility, while slope, soil depth, level of erosion hazard and drainage was obtain from land system map. The result showed that the land capability classification at Wampu Hulu Sub Watershed, divided by three classes, namely: Class III, V, and VI.
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Pemetaan Penderita Pneumonia di Surabaya dengan Menggunakan Geostatistik Stefanie Hartanto1, Siana Halim2, Oviliani Yenty

Pemetaan Penderita Pneumonia di Surabaya dengan Menggunakan Geostatistik Stefanie Hartanto1, Siana Halim2, Oviliani Yenty

dilakukan untuk mengetahui keterkaitan data secara spasial pada suatu titik dalam area tertentu, dalam hal ini adalah area Surabaya. Secara garis besar, spatial analysis melalui beberapa tahap, yaitu plot geodata, deteksi dependensi data secara spasial, pemetaan penyebaran penyakit dengan kriging, serta deteksi data outlier dengan algoritma Route Outlier Detection. Data yang diolah dalam spatial analysis adalah proporsi penderita penyakit tertentu di setiap area, yang diperoleh dari perbandingan antara jumlah penderita penyakit bersangkutan dengan jumlah keseluruhan penduduk di area kelurahan tersebut. Deteksi dependensi data secara spasial dilakukan melalui plot empirical variogram. Gambar 5 menunjukkan plot empirical variogram untuk penyakit Pneumonia. Plot empirical variogram menggambarkan semiva- riance data terhadap suatu distance tertentu, bukan terhadap posisi koordinat tertentu. Plot empirical Hartanto., et al. / Pemetaan Penderita Pneumonia di Surabaya /
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isprs archives XLI B2 527 2016

isprs archives XLI B2 527 2016

Intermediate cities are urged to change and adapt their mobility systems from a high energy-demanding motorized model to a sustainable low-motorized model. In order to accomplish such a model, city administrations need to better understand active mobility patterns and their links to socio-demographic and cultural aspects of the population. During the last decade, researchers have demonstrated the potential of geo-location technologies and mobile devices to gather massive amounts of data for mobility studies. However, the analysis and interpretation of this data has been carried out by specialized research groups with relatively narrow approaches from different disciplines. Consequently, broader questions remain less explored, mainly those relating to spatial behaviour of individuals and populations with their geographic environment and the motivations and perceptions shaping such behaviour. Understanding sustainable mobility and exploring new research paths require an interdisciplinary approach given the complex nature of mobility systems and their social, economic and environmental impacts. Here, we introduce the elements for a multidisciplinary analytical framework for studying active mobility patterns comprised of three components: a) Methodological, b) Behavioural, and c) Perceptual. We demonstrate the applicability of the framework by analysing mobility patterns of cyclists and pedestrians in an intermediate city integrating a range of techniques, including: GPS tracking, spatial analysis, auto-ethnography, and perceptual mapping. The results demonstrated the existence of non-evident spatial behaviours and how perceptual features affect mobility. This knowledge is useful for developing policies and practices for sustainable mobility planning.
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Spatial Analysis and Modeling 2017 Dasar

Spatial Analysis and Modeling 2017 Dasar

Information systems that manage, manipulate and analyze spatial data. (Theobald, 2005, p. 2). Generic GIS can be viewed as a number of specialized spatial routines laid over a standard relational data base management system. (Goodchild, 1985) (Current GIS increasingly rely on object oriented technology.)

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isprs archives XLII 2 W5 483 2017

isprs archives XLII 2 W5 483 2017

This paper takes the spatial analysis of Geographic Information System (GIS) as the basic technological means and all historical and cultural resources in China’s Zhejiang Province as research objects, and finds out in the space the accumulation areas and accumulation belts of Zhejiang Province’s historic cities and cultural resources through overlay analysis and density analysis, etc. It then discusses the reasons of the formation of these accumulation areas and accumulation belts by combining with the analysis of physical geography and historical geography and so on, and in the end, linking the tourism planning and traffic planning at the provincial level, it provides suggestions on the exhibition and use of accumulation areas and accumulation belts of historic cities and cultural resources.
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Spatial source area analysis of three di

Spatial source area analysis of three di

The Los Alamos National Laboratory scanning Raman lidar was used to measure the three-dimensional moisture field over a salt cedar canopy. A critical question concerning these measurements is; what are the spatial properties of the source region that contributes to the observed three-dimensional moisture field? Traditional methods used to address footprint properties rely on point sensor time-series data and the assumption of Taylor’s hypothesis to transform temporal data into the spatial domain. In this paper, the analysis of horizontal source-area size is addressed from direct lidar-based spatial analysis of the moisture field, eddy covariance co-spectra, and a dedicated footprint model. The results of these analysis techniques converged on the microscale average source region of between 25 and 75 m under ideal conditions. This work supports the concept that the scanning lidar can be used to map small scale boundary layer processes, including riparian zone moisture fields and fluxes. Published by Elsevier Science B.V.
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ITN-2 RIVER BASIN HYDROLOGY MODEL, A DISTRIBUTED CONCEPTUAL MODEL FOR PREDICTING FLOOD WITHOUT USING CALIBRATION

ITN-2 RIVER BASIN HYDROLOGY MODEL, A DISTRIBUTED CONCEPTUAL MODEL FOR PREDICTING FLOOD WITHOUT USING CALIBRATION

Improvement has been made in the analysis process as well, i.e., the separation of spatial analysis process and numeri- cal computation found in the former model is replaced by per- forming them simultaneously in the current model. In the former ITN-1 River Basin Hydrology Model, the spatial analysis was conducted by means of ArcView GIS, while the numerical analy- sis was performed by using Fortran. In ITN-2 River Basin Hy- drology Model, on the other hand, the spatial and numerical ana- lysis is conducted by means of Model Builder found in ArcGIS. This is expected to provide ease in its execution.
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An Analysis of Spatial Patterns of Disabled Persons in West Bengal

An Analysis of Spatial Patterns of Disabled Persons in West Bengal

Persons with disabilities are the most oppressed, demoralized, marginalized, excluded section of the society. The concentration of disabled persons varies from place to place and time to time (Islam et al., 2016). The geographer‟s task is to analyze the diversity of phenomena in different spatial units (Shivalingappa et al, 2011). Disabled persons is one of the significant phenomena in the contemporary period which has affected most of the part of the world including India, West Bengal is not an exception for this. Though the distributional patterns in all over the world is not same and differed drastically because of biological, social, cultural, economical, political as well as geographical factors.
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isprs archives XLII 4 W5 97 2017

isprs archives XLII 4 W5 97 2017

OK can be used for spatial pattern of groundwater arsenic concentrations since of its high uneven distribution. OK is used to estimate values when data point values vary or fluctuate around a constant mean value (Serón et al, 2001). It is applied for an unbiased estimate of spatial variation of a component. The estimation variance of OK is used to generate a confidence interval for the corresponding estimate assuming a normal distribution of errors (Goovaerts et al, 2005). The unknown local mean is filtered from the linear estimator by making the sum of kriging weights to one. OK also provides a measure of uncertainty attached to each estimated value through calculating the OK variance (Delbari et al, 2016):
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Spatial Planning in Perspective of Good Governance (A Study on Analysis of Spatial Planning in Batu City as a Tourism City)

Spatial Planning in Perspective of Good Governance (A Study on Analysis of Spatial Planning in Batu City as a Tourism City)

3) Batu City’s government officers (especially the member of Local House Representatives) should join in short course continuously, and comparative study to the others cities to improve them understanding about urban design science and regional spatial planning policy. In government level, the quality of human resources was very important, because human resources were a tools in product some policies and an activator, and determine production process. Human resources brought the main role in determine progress and development of government institution. Therefore, the progress of government institutions development determined by the quality of human resources inside of government institutions.
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6 BAB II LANDASAN TEORI 2.1 Pasar Modal 2.1.1 Pengertian Pasar Modal

6 BAB II LANDASAN TEORI 2.1 Pasar Modal 2.1.1 Pengertian Pasar Modal

Pada prosesnya data mining akan mengekstrak informasi yang berharga dengan cara menganalisis adanya pola-pola ataupun hubungan keterkaitan tertentu dari data- data yang berukuran besar. Data mining berkaitan dengan bidang ilmu-ilmu lain, seperti Database System, Data Warehousing, Statistic, Machine Learning, Information Retrieval, dan Komputasi Tingkat Tinggi. Selain itu data mining didukung oleh ilmu lain seperti Neural Network, Pengenalan Pola, Spatial Data Analysis, Image Database, Signal Processing.[ADIT15]

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isprsarchives XXXIX B3 467 2012

isprsarchives XXXIX B3 467 2012

It is well known that combining spatial and spectral information is a good strategy to improve urban land use classification. Features extracted by using co-occurrence matrices, Gabor wavelets, morphological profiles, and Markov random fields have been widely used in the literature to model spatial information in neighborhoods of pixels (Akcay & Aksoy, 2008). Spatial autocorrelation as spatial information is an inherent feature of remote sensing data and a reliable indicator of statistical separability between spatial objects. In remote sensing , spatial autocorrelation means the spectral dependence existing between a pixel and its neighbors, that is, spectral value of a pixel is usually not independent but correlated with those of its neighboring ones. Spatial autocorrelation provides us the structural information between spectral values of pixels, which is usually more stable and robust to noise than individual pixel. This information may be used to improve the segmentation quality or classification accuracy for spectrally heterogeneous classes and overcome the current spectral limitations of very high spatial resolution satellite images.
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