Methods to Create a Longitudinal Integrated Demographic and Geographic Database on the Micro-Level

Hedefalk, Finn; Harrie, Lars; Svensson, Patrik

doi:10.1080/01615440.2015.1016645

Cited by 6 publications

(20 citation statements)

References 55 publications

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“…A common method of creating such reference data is to scan, georeference and digitize historical maps that contain sufficient geometric and address information that can be used in the geocoding process (cf. Hedefalk et al 2015).…”

Section: Geocoding Of Demographic Databasesmentioning

confidence: 99%

“…By including accurate digital representations of historical city street centrelines, these authors created the tools necessary to link the ward-level dataset to city blocks. Moreover, Hedefalk et al (2015) geocoded approximately 53,000 individuals to their rural property units in the SEDD database for the time period 1813-1914. Two main challenges arose in this geocoding process.…”

Section: Geocoding Of Demographic Databasesmentioning

confidence: 99%

“…Studies that analyse micro-level geographic factors are also becoming more common (e.g., Ekamper 2010), although they are seldom longitudinal because there are few historical longitudinal demographic databases that geocode individuals to a more precise location, such as the property unit/parcel boundary or building, over long time periods. Recently, however, certain longitudinal demographic databases have been geocoded on a detailed level (e.g., Villarreal et al 2014;Hedefalk et al 2015Hedefalk et al , 2017b, which enables the inclusion of micro-level geographic context in longitudinal historical analyses. In this study, we use the geocoded Scanian Economic Demographic Database (SEDD) to perform our analyses for the period from 1850 to 1914 (Hedefalk et al 2017b).…”

Section: Introductionmentioning

confidence: 99%

“…Efficient methods are required to perform both of these processes (cf. e.g., Hedefalk et al 2015). An important issue in this context is to determine the geographic level at which the geocoding should be performed.…”

Section: Introductionmentioning

confidence: 99%

“…We use individual-level longitudinal data from the Scanian Economic Demographic Database (SEDD) (Bengtsson et al 2014), which has recently been geocoded (Hedefalk et al 2015(Hedefalk et al , 2017b. In this geocoding, approximately 53,000 individuals have been linked to the property units 1 at which they lived.…”

Section: Introductionmentioning

confidence: 99%

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Importance of the Geocoding Level for Historical Demographic Analyses: A Case Study of Rural Parishes in Sweden, 1850–1914

et al. 2017

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Geocoding longitudinal and individual-level historical demographic databases enables novel analyses of how micro-level geographic factors affected demographic outcomes over long periods. However, such detailed geocoding involves high costs. Additionally, the high spatial resolution cannot be properly utilized if inappropriate methods are used to quantify the geographic factors. We assess how different geocoding levels and methods used to define geographic variables affects the outcome of detailed spatial and historical demographic analyses. Using a longitudinal and individual-level demographic database geocoded at the property unit level, we analyse the effects of population density and proximity to wetlands on all-cause mortality for individuals who lived in five Swedish parishes, 1850-1914. We compare the results from analyses on three detailed geocoding levels using two common quantification methods for each geographic variable. Together with the method selected for quantifying the geographic factors, even small differences in positional accuracy (20-50 m) between the property units and slightly coarser geographic levels heavily affected the results of the demographic analyses. The results also show the importance of accounting for geographic changes over time. Finally, proximity to wetlands and population density affected the mortality of women and children, respectively. However, all possible determinants of mortality were not evaluated in the analyses. In conclusion, for rural historical areas, geocoding to property units is likely necessary for fine-scale analyses at distances within a few hundred metres. We must also carefully consider

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Section: Geocoding Of Demographic Databasesmentioning

confidence: 99%

Section: Geocoding Of Demographic Databasesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Importance of the Geocoding Level for Historical Demographic Analyses: A Case Study of Rural Parishes in Sweden, 1850–1914

et al. 2017

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Spatiotemporal historical datasets at micro-level for geocoded individuals in five Swedish parishes, 1813–1914

2017

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This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database, we obtain a geocoded population (at the property unit level) for this area for the period 1813–1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored in object-lifeline time representations (information about creation, changes and ends of objects are recorded in time), whereas the other feature types are stored as snapshots in time. Thus, the datasets present one of the first opportunities to study historical spatio-temporal patterns at the micro-level.

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Unequal lands: Soil type, nutrition, and child mortality in southern Sweden, 1850-1914

Hedefalk¹,

Quaranta²,

Bengtsson³

2017

DemRes

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Methods to Create a Longitudinal Integrated Demographic and Geographic Database on the Micro-Level

Cited by 6 publications

References 55 publications

Importance of the Geocoding Level for Historical Demographic Analyses: A Case Study of Rural Parishes in Sweden, 1850–1914

Importance of the Geocoding Level for Historical Demographic Analyses: A Case Study of Rural Parishes in Sweden, 1850–1914

Spatiotemporal historical datasets at micro-level for geocoded individuals in five Swedish parishes, 1813–1914

Unequal lands: Soil type, nutrition, and child mortality in southern Sweden, 1850-1914

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