Issues of geographic context variable calculation methods applied at different geographic levels in spatial historical demographic research : a case study over four parishes in Southern Sweden
(2016) In Student thesis series INES NGEM01 20161Dept of Physical Geography and Ecosystem Science
- Abstract
- Spatial analysis is dependent on the geo-referencing quality of the spatial data, as well as on the definition of the geographic context variables used. However, these facts are rarely taken into consideration in historical demographic research where the geographic factor is considered. An important obstacle in this kind of research is the availability of historical data (spatial and non-spatial), sufficient timeframes, and financial resources to employ qualified scientists to perform the geo-coding and the linking of population to specific geographic levels according to the existent historical sources. Since these are essential issues, it is important to determine if and how much the choice of different geographic context variable... (More)
- Spatial analysis is dependent on the geo-referencing quality of the spatial data, as well as on the definition of the geographic context variables used. However, these facts are rarely taken into consideration in historical demographic research where the geographic factor is considered. An important obstacle in this kind of research is the availability of historical data (spatial and non-spatial), sufficient timeframes, and financial resources to employ qualified scientists to perform the geo-coding and the linking of population to specific geographic levels according to the existent historical sources. Since these are essential issues, it is important to determine if and how much the choice of different geographic context variable definitions calculated over different geographic levels could affect the research outcome. This thesis project attempts to address this problem, by examining how much the results of geographic context variables differ when different definitions of the variables are used or when the variables are calculated over different geographic levels. For this purpose, geographic and demographic data from four rural parishes set in the 19th century southern Sweden is used to define geographic context variables that might affect mortality in historical demographic research (e.g. soil types, proximity to water, proximity to wetlands, proximity to gathering places, and population density). The results show that different definitions of distance might produce contradictory results, depending on the geography of the research location and the shape or size of the geographical units. Similarly, results tend to differ when different geographic levels are used. Though the suitability of what geographic level is chosen is highly dependent upon the research hypothesis, additional research is needed to determine when a geographic level is deemed suitable enough. (Less)
- Popular Abstract
- In recent years, the rapid development of Geographical Information Systems (GIS) has resulted in an ever growing list of new application areas. Historical demography is one of the more recent scientific fields to be benefited by the usage of these systems. GIS have provided the tools necessary for historical demographers to explore new and old data sources including detailed geographical information. As a result, data from national censuses containing geographical identifiers at the scale of the individual or at other levels of aggregation (i.e. municipalities, counties or other administrative areas) as well as detailed historical maps of cities and sites have been digitized and therefore become available for further processing.
The... (More) - In recent years, the rapid development of Geographical Information Systems (GIS) has resulted in an ever growing list of new application areas. Historical demography is one of the more recent scientific fields to be benefited by the usage of these systems. GIS have provided the tools necessary for historical demographers to explore new and old data sources including detailed geographical information. As a result, data from national censuses containing geographical identifiers at the scale of the individual or at other levels of aggregation (i.e. municipalities, counties or other administrative areas) as well as detailed historical maps of cities and sites have been digitized and therefore become available for further processing.
The integration of contextual geo-spatial information with socioeconomic and demographic data enables historical demographers to search for patterns and map the population behaviors of the past. Further studies regarding the interaction between climatic, environmental, socioeconomic and demographic processes and how they affect different aspects of society such as public health, mortality, fertility and migration are now feasible. This study includes information regarding the definition of certain geographic context variables (e.g. population density, soil types, proximity to water, proximity to wetlands, and proximity to gathering places) that are suspected to affect mortality. The definition of geographic variables and the choice of suitable methods of computation are not trivial and should always be made considering the objective of the demographic research as well as the special characteristics of the research area. This study provides proof of how different results can be produced over the same area of implementation, depending on the definition of a geographic context variable and the choice of suitable computation method.
Another problem when dealing with the integration of historical geographic and demographic information, is the choice of suitable geographic level. Cities, counties and countries are examples of different geographic levels. The higher the resolution of a geographic level (i.e. the smaller the geographic unit of a geographic level) the more representative the results of the geographic context variable computations. Depending on the circumstances, high resolution historic data may be hard to find, especially when the research objective is to study the population of larger areas for a long period in time. Even if this kind of information was made available, it may come from a variety of sources and, therefore, be in need of excessive processing before it can be used. This can be a very expensive procedure as it often demands the employment of skilled professionals to conduct a set of very time-demanding tasks. Limited financial resources and timeframes might force researchers to focus on smaller areas for shorter time periods or on larger areas of coarser geographical level. When attempting to link demographic data to geographical data it is important to be aware of the fact that depending on the choice of geographic level the linkage is performed over, there is a possibility of associations between demographic and geographic data being lost. This study attempts to examine if and how much the computed results of geographic context variables might vary, when computed over different geographical levels. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8870289
- author
- Pantazatou, Karolina Despoina LU
- supervisor
-
- Lars Harrie LU
- Finn Hedefalk LU
- organization
- course
- NGEM01 20161
- year
- 2016
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- geographic context variables, spatial demography, historic demography, spatial longitudinal demographic research, geography, physical geography, distance calculation methods, geographic levels, GIS
- publication/series
- Student thesis series INES
- report number
- 371
- language
- English
- id
- 8870289
- date added to LUP
- 2016-03-30 11:48:41
- date last changed
- 2016-06-13 09:36:36
@misc{8870289,
abstract = {{Spatial analysis is dependent on the geo-referencing quality of the spatial data, as well as on the definition of the geographic context variables used. However, these facts are rarely taken into consideration in historical demographic research where the geographic factor is considered. An important obstacle in this kind of research is the availability of historical data (spatial and non-spatial), sufficient timeframes, and financial resources to employ qualified scientists to perform the geo-coding and the linking of population to specific geographic levels according to the existent historical sources. Since these are essential issues, it is important to determine if and how much the choice of different geographic context variable definitions calculated over different geographic levels could affect the research outcome. This thesis project attempts to address this problem, by examining how much the results of geographic context variables differ when different definitions of the variables are used or when the variables are calculated over different geographic levels. For this purpose, geographic and demographic data from four rural parishes set in the 19th century southern Sweden is used to define geographic context variables that might affect mortality in historical demographic research (e.g. soil types, proximity to water, proximity to wetlands, proximity to gathering places, and population density). The results show that different definitions of distance might produce contradictory results, depending on the geography of the research location and the shape or size of the geographical units. Similarly, results tend to differ when different geographic levels are used. Though the suitability of what geographic level is chosen is highly dependent upon the research hypothesis, additional research is needed to determine when a geographic level is deemed suitable enough.}},
author = {{Pantazatou, Karolina Despoina}},
language = {{eng}},
note = {{Student Paper}},
series = {{Student thesis series INES}},
title = {{Issues of geographic context variable calculation methods applied at different geographic levels in spatial historical demographic research : a case study over four parishes in Southern Sweden}},
year = {{2016}},
}