Functional Reuse and Intensification of Rural-Urban Context

2016 ◽  
Vol 7 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Tiziano Cattaneo ◽  
Roberto De Lotto ◽  
Elisabetta Maria Venco
Keyword(s):  
Best Practices ◽  
Dynamic Balance ◽  
Methodological Approach ◽  
Data Sets ◽  
Logical Framework ◽  
Urban Context ◽  
Specific Knowledge ◽  
Data Set ◽  
Whole Process

In regional and urban planning such as in design actions they are usually involved different themes and disciplines; especially when the goal is to improve, restore and re-functionalize existing minor settlements in rural-urban context. For this reason it is necessary to define integrated methodologies able to face inter-scalar issues and interdisciplinary themes. Authors propose a framework for a decision support system based on the treatment of geographical data and on the integration of the data sets that have dissimilar origin, diverse formats (they may be not only digital) and different meaning value. This complete data set refers to various disciplines and it is possible to deduce specific knowledge throughout analytical passages and assessment steps. In the paper authors describe: a methodological approach to support planning activities; the technical support to seek a (dynamic) balance between urban density and rural fragmentation; a Best Practices database to support scenarios in rural-urban context. Authors first expose the application field, than the logical framework of the whole process, then describe some related spatial analysis applications and finally they introduce comprehensive case study of the whole procedure.

Functional Reuse and Intensification of Rural-Urban Context

2018 ◽  
pp. 459-485
Author(s):  
Tiziano Cattaneo ◽  
Roberto De Lotto ◽  
Elisabetta Maria Venco
Keyword(s):  
Spatial Analysis ◽  
Dynamic Balance ◽  
Methodological Approach ◽  
Data Sets ◽  
Logical Framework ◽  
Urban Context ◽  
Specific Knowledge ◽  
Data Set ◽  
Whole Process

In regional and urban planning such as in design actions they are usually involved different themes and disciplines; especially when the goal is to improve, restore and re-functionalize existing minor settlements in rural-urban context. For this reason it is necessary to define integrated methodologies able to face inter-scalar issues and interdisciplinary themes. Authors propose a framework for a decision support system based on the treatment of geographical data and on the integration of the data sets that have dissimilar origin, diverse formats (they may be not only digital) and different meaning value. This complete data set refers to various disciplines and it is possible to deduce specific knowledge throughout analytical passages and assessment steps. In the paper authors describe: a methodological approach to support planning activities; the technical support to seek a (dynamic) balance between urban density and rural fragmentation; a Best Practices database to support scenarios in rural-urban context. Authors first expose the application field, then the logical framework of the whole process, then describe some related spatial analysis applications and finally they introduce comprehensive case study of the whole procedure.

Improving Quality and Safety Through Use of Secondary Data: Methods Case Study

2016 ◽  
Vol 39 (11) ◽  
pp. 1477-1501 ◽  
Author(s):  
Victoria Goode ◽  
Nancy Crego ◽  
Michael P. Cary ◽  
Deirdre Thornlow ◽  
Elizabeth Merwin
Keyword(s):  
Research Question ◽  
Secondary Data ◽  
Data Access ◽  
Data Sets ◽  
Complex Data ◽  
Management Skills ◽  
Data Set ◽  
Large Numbers ◽  
Need To Evaluate

Researchers need to evaluate the strengths and weaknesses of data sets to choose a secondary data set to use for a health care study. This research method review informs the reader of the major issues necessary for investigators to consider while incorporating secondary data into their repertoire of potential research designs and shows the range of approaches the investigators may take to answer nursing research questions in a variety of context areas. The researcher requires expertise in locating and judging data sets and in the development of complex data management skills for managing large numbers of records. There are important considerations such as firm knowledge of the research question supported by the conceptual framework and the selection of appropriate databases, which guide the researcher in delineating the unit of analysis. Other more complex issues for researchers to consider when conducting secondary data research methods include data access, management and security, and complex variable construction.

scholarly journals Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011 ◽  
Vol 5 (1) ◽  
pp. 271-290 ◽  
Author(s):  
C. Nuth ◽  
A. Kääb
Keyword(s):  
Regional Scale ◽  
Statistical Error ◽  
Data Sets ◽  
Data Set ◽  
Thickness Change ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Changes

Abstract. There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the back-looking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

scholarly journals What's in an elevation difference? Accuracy and corrections of satellite elevation data sets for quantification of glacier changes

2010 ◽  
Vol 4 (4) ◽  
pp. 2013-2077 ◽  
Author(s):  
C. Nuth ◽  
A. Kääb
Keyword(s):  
New Zealand ◽  
Regional Scale ◽  
Statistical Error ◽  
Data Sets ◽  
Methodological Framework ◽  
Data Set ◽  
Aster Gdem ◽  
Elevation Data ◽  
Elevation Changes

Abstract. There is an increasing number of DEMs available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes impossible and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: remove DEM shifts, check for elevation-dependent biases, and check for higher-order, sensor-specific biases. An analytic, simple and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is exemplified using the three global elevation data sets available, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After three-dimensional co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite \\emph{jitter}, most effective in the back-looking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system. The proposed methodological framework is exemplified for elevation changes on the Fox, Franz Joseph, Tasman and Murchison glaciers of New Zealand and the glaciers of central Spitsbergen, Svalbard.

scholarly journals Revealing Structure in Visualizations of Dense 2D and 3D Parallel Coordinates

2006 ◽  
Vol 5 (2) ◽  
pp. 125-136 ◽  
Author(s):  
Jimmy Johansson ◽  
Patric Ljung ◽  
Mikael Jern ◽  
Matthew Cooper
Keyword(s):  
High Precision ◽  
Transfer Functions ◽  
Multivariate Data ◽  
Data Sets ◽  
Parallel Coordinates ◽  
Data Set ◽  
Number Of Clusters ◽  
Analysis Process ◽  
2D And 3D

Parallel coordinates is a well-known technique used for visualization of multivariate data. When the size of the data sets increases the parallel coordinates display results in an image far too cluttered to perceive any structure. We tackle this problem by constructing high-precision textures to represent the data. By using transfer functions that operate on the high-precision textures, it is possible to highlight different aspects of the entire data set or clusters of the data. Our methods are implemented in both standard 2D parallel coordinates and 3D multi-relational parallel coordinates. Furthermore, when visualizing a larger number of clusters, a technique called ‘feature animation’ may be used as guidance by presenting various cluster statistics. A case study is also performed to illustrate the analysis process when analysing large multivariate data sets using our proposed techniques.

Impacts of the Tax System on Poverty and Social Exclusion: A Case Study on Turkey

2008 ◽  
Vol 38 ◽  
pp. 159-179 ◽  
Author(s):  
Fatoş Gökşen ◽  
Gökhan Özertan ◽  
İsmail Sağlam ◽  
Ünal Zenginobuz
Keyword(s):  
Social Exclusion ◽  
Public Services ◽  
Data Sets ◽  
Data Set ◽  
Tax System ◽  
Statistical Institute ◽  
Qualitative Part ◽  
Consumption Taxes ◽  
The Relationship

AbstractThis article makes use of two different data sets on Turkey to explore the relationship between the tax structure and issues such as democratic representation, citizenship rights, and poverty and social exclusion. The first of these data sets is the extensive Household Consumption Survey (2003) by the Turkish Statistical Institute (TURKSTAT). This extensive survey data allows a very comprehensive quantitative analysis of the tax burden on the consumption baskets of households in different income groups, as well as in different regions of Turkey. The second data set incorporates qualitative data on Turkish citizens' views and attitudes towards different aspects of the Turkish tax system—such as its fairness (justice), transparency, and efficiency in generating funds for public activities—obtained through focus group meetings and in-depth interviews conducted with citizen groups and various stakeholders in cities in different regions in Turkey. The quantitative findings presented in the study clearly reveal that, if anything, taxes are expected to exacerbate the problem of inequality and poverty in Turkey. Heavily relying on regressive consumption taxes results in the poor paying a disproportionate amount of their income as indirect taxes, more so for those in Eastern and Southeastern Anatolia where poverty is more extreme. On the other hand, the qualitative part reveals that ordinary citizens find the current tax system highly unfair and feel that they receive very little in terms of public services in return for the taxes they pay. In spite of the merits attributed in theory to taxation as a means to provide services and thereby legitimize the state, the payment of taxes is met with considerable reluctance. Most of this reluctance is attributable to factors such as the citizens' inability to pay, and a lack of clarity with respect to the obligations and reasons for paying. It also emerges that the unwillingness to pay is a protest against the degradation of public services and the perceptions of unfairness, corruption, and other administrative failings.

Becoming a transformative vice-principal in culturally and linguistically rich diverse schools

2017 ◽  
Vol 6 (2) ◽  
pp. 82-98
Author(s):  
Lyle Hamm
Keyword(s):  
Leadership Role ◽  
Data Sets ◽  
Structured Interviews ◽  
Data Set ◽  
Case Study Methodology ◽  
Content Type ◽  
Vice Principals ◽  
Diverse Schools ◽  
Building Leadership Capacity

Purpose The purpose of this paper is to examine the leadership role(s) of vice-principals in diverse, multi-ethnic schools and communities and understand the supervision and mentoring support they require to help them become more effective leaders within them. The research questions guiding this study were: what forms of mentoring do vice-principals, who serve in diverse schools in rapidly changing communities, require? Who is in the best position to provide mentoring for them? Design/methodology/approach The author used a qualitative case study methodology. Data that were analyzed for this paper were drawn from surveys, semi-structured interviews, one focus group interview and school and community documents from three data sets within two case studies in Canada. The first data set was part of the author’s doctoral research program in a diverse school in Alberta; the other case study was part of a larger collective case study that the author is currently involved with and leading in New Brunswick. Several vice-principals were part of both studies. The author then constructed a survey questionnaire specifically focused on mentoring vice-principals in diverse schools. Vice-principals in both provinces, who were part of the two studies, were invited to respond to the follow-up survey. Using a constant comparative analytical approach, the author coded and analyzed the data from all three sets together. The author formed several categories and ultimately collapsed the categories into five distinct themes that illustrated and confirmed the social realities of the vice-principals in their schools and communities. Findings Five key findings emerged from the analysis of the data sets. They were building leadership capacity, fostering positive relationships, increasing global awareness, reducing stress and anxiety and becoming a diversity champion and peace-builder. Originality/value To this researcher’s knowledge, this paper contributes to a significant gap in the literature on vice-principals who serve in diverse schools and communities.

scholarly journals Decreasing uncertainty in flood frequency analyses by including historic flood events in an efficient bootstrap approach

2019 ◽  
Author(s):  
Anouk Bomers ◽  
Ralph Schielen ◽  
Suzanne Hulscher
Keyword(s):  
Bootstrap Method ◽  
River System ◽  
Weather Conditions ◽  
Flood Frequency ◽  
Data Sets ◽  
Rhine River ◽  
Flood Events ◽  
Data Set ◽  
Bootstrap Approach

Abstract. Flood frequency curves are usually highly uncertain since they are based on short data sets of measured discharges or weather conditions. To decrease the confidence intervals, an efficient bootstrap method is developed in this study. The Rhine river delta is considered as a case study. A hydraulic model is used to normalize historic flood events for anthropogenic and natural changes in the river system. As a result, the data set of measured discharges could be extended with approximately 600 years. The study shows that flood events decrease the confidence interval of the flood frequency curve significantly, specifically in the range of large floods. This even applies if the maximum discharges of these historic flood events are highly uncertain themselves.

scholarly journals Decreasing uncertainty in flood frequency analyses by including historic flood events in an efficient bootstrap approach

2019 ◽  
Vol 19 (8) ◽  
pp. 1895-1908
Author(s):  
Anouk Bomers ◽  
Ralph M. J. Schielen ◽  
Suzanne J. M. H. Hulscher
Keyword(s):  
Bootstrap Method ◽  
River System ◽  
Weather Conditions ◽  
Flood Frequency ◽  
Data Sets ◽  
Rhine River ◽  
Flood Events ◽  
Data Set ◽  
Bootstrap Approach

Abstract. Flood frequency curves are usually highly uncertain since they are based on short data sets of measured discharges or weather conditions. To decrease the confidence intervals, an efficient bootstrap method is developed in this study. The Rhine river delta is considered as a case study. We use a hydraulic model to normalize historic flood events for anthropogenic and natural changes in the river system. As a result, the data set of measured discharges could be extended by approximately 600 years. The study shows that historic flood events decrease the confidence interval of the flood frequency curve significantly, specifically in the range of large floods. This even applies if the maximum discharges of these historic flood events are highly uncertain themselves.

scholarly journals Assessment and comparison of extreme sea levels and waves during the 2013/14 storm season in two UK coastal regions

2015 ◽  
Vol 15 (10) ◽  
pp. 2209-2225 ◽  
Author(s):  
M. P. Wadey ◽  
J. M. Brown ◽  
I. D. Haigh ◽  
T. Dolphin ◽  
P. Wisse
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Data Sets ◽  
Return Periods ◽  
Data Set ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Study Sites

Abstract. The extreme sea levels and waves experienced around the UK's coast during the 2013/14 winter caused extensive coastal flooding and damage. Coastal managers seek to place such extremes in relation to the anticipated standards of flood protection, and the long-term recovery of the natural system. In this context, return periods are often used as a form of guidance. This paper provides these levels for the winter storms, and discusses their application to the given data sets for two UK case study sites: Sefton, northwest England, and Suffolk, east England. Tide gauge records and wave buoy data were used to compare the 2013/14 storms with return periods from a national data set, and also joint probabilities of sea level and wave heights were generated, incorporating the recent events. The 2013/14 high waters and waves were extreme due to the number of events, as well as the extremity of the 5 December 2013 "Xaver" storm, which had a high return period at both case study sites. The national-scale impact of this event was due to its coincidence with spring high tide at multiple locations. Given that this event is such an outlier in the joint probability analyses of these observed data sets, and that the season saw several events in close succession, coastal defences appear to have provided a good level of protection. This type of assessment could in the future be recorded alongside defence performance and upgrade. Ideally other variables (e.g. river levels at estuarine locations) would also be included, and with appropriate offsetting for local trends (e.g. mean sea-level rise) so that the storm-driven component of coastal flood events can be determined. This could allow long-term comparison of storm severity, and an assessment of how sea-level rise influences return levels over time, which is important for consideration of coastal resilience in strategic management plans.

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