scholarly journals Challenges and limitations of modelling historical spatial data on nature: 19th century flora and fauna of Peloponnese, Greece

2021 ◽  
Vol 2 ◽  
pp. 1-5
Author(s):  
Eleni Gkadolou ◽  
Katerina Koutsovoulou ◽  
Georgios Tolias ◽  
Vassilis Detsis
Keyword(s):  
19Th Century ◽  
Species Distribution ◽  
Spatial Data ◽  
Valid Species ◽  
Historical Sources ◽  
Grid Mapping ◽  
Administrative Area ◽  
Administrative Units

Abstract. The aim of the study is the consolidation of a methodology suitable for organizing, utilizing and visualizing information regarding species distribution provided as text in historical sources. The work of the French Scientific Expedition in 1829 in Peloponnese, Greece, was used as a case study. We propose a system organized in three geographical levels: for information referring to a certain locality the form of a grid is appropriate, otherwise polygons depicting historical administrative areas or the whole region of Peloponnese should be preferred. There are three important caveats to avoid. First, species presence referring to an administrative area or region does not equal with presence in every locality and should not be transferred to the level of grid mapping, respectively reference of presence in the region should not be transferred to the administrative units’ level. Second, historical sources refer to species names that often are no longer valid; this kind of data must be referred to currently valid species names. Third, absence of reference of species presence should not be misinterpreted as absence of the species.

scholarly journals Multimedia integration of cartographic source materials for researching and presenting phenomena from economic history

2016 ◽  
Vol 65 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Dariusz Lorek
Keyword(s):  
19Th Century ◽  
Spatial Data ◽  
Economic History ◽  
Texture Mapping ◽  
Topographic Map ◽  
Historical Sources ◽  
Distinctive Character ◽  
Industrial Landscape ◽  
Multimedia Integration ◽  
The 19Th Century

Abstract The article presents a framework for integrating historical sources with elements of the geographical space recorded in unique cartographic materials. The aim of the project was to elaborate a method of integrating spatial data sources that would facilitate studying and presenting the phenomena of economic history. The proposed methodology for multimedia integration of old materials made it possible to demonstrate the successive stages of the transformation which was characteristic of the 19th-century space. The point of reference for this process of integrating information was topographic maps from the first half of the 19th century, while the research area comprised the castle complex in Kórnik together with the small town – the pre-industrial landscape in Wielkopolska (Greater Poland). On the basis of map and plan transformation, graphic processing of the scans of old drawings, texture mapping of the facades of historic buildings, and a 360° panorama, the source material collected was integrated. The final product was a few-minute-long video, composed of nine sequences. It captures the changing form of the castle building together with its facades, the castle park, and its further topographic and urban surroundings, since the beginning of the 19th century till the present day. For a topographic map sheet dating back to the first half of the 19th century, in which the hachuring method had been used to present land relief, a terrain model was generated. The transition from parallel to bird’s-eye-view perspective served to demonstrate the distinctive character of the pre-industrial landscape.

scholarly journals Visualization of spatiotemporal data with different topology

2020 ◽  
Vol 2 ◽  
pp. 1-2
Author(s):  
Alena Vondráková ◽  
Vít Pászto
Keyword(s):  
Spatial Data ◽  
Spatiotemporal Analysis ◽  
Spatiotemporal Data ◽  
Identification Code ◽  
The Czech Republic ◽  
Advanced Technologies ◽  
Long Term Trends ◽  
Administrative Units

Abstract. The availability of advanced technologies, the time of information society, and also the development of geographic information systems, have brought a lot of spatial data in most disciplines, which are carefully stored in recent decades and allow us spatiotemporal analysis and visualization. However, for long-term analyses and the synthesis of analysed data, including cartographic synthesis processes, it is a big problem when spatiotemporal data have different topologies at different times. And this does not only mean the correction of borders in the sense of clarification or other distinction. The problem is when, for example, the small administrative units is subject to significant temporal changes. Municipalities are divided and merged, while data are always stored for the topology of a particular year or period.The contribution presents a way to solve such a situation on the example of the Czech Republic. Data from 25 years’ period are adjusted so that it is possible to calculate and visualize long-term trends and analyses. In the case of the case study, these are spatial data of more than 6,000 municipalities, with changes in more than 200 cases during the observed period. In addition to the spatial component, there were also changes in identifiers, which are a common means of joining data. For example, when the name of the municipality was changed and the newly "created" municipality also received new identification code. All these problems are solved by the so-called "super layer", which represents aggregation to the smallest possible extent so that the analyses performed are carried out on the most detailed possible scale without missing data in partial periods.The project goal is to explore various geodemographic processes at a very detailed level, specifically at NUTS (Nomenclature of Territorial Units for Statistics) local administrative units 2 (LAU2) commonly used in European Union for statistical purposes. Our presented dataset/approach unified municipal administrative units allowing analyses of data as they change over time. We used a principle of "common spatial denominator", i.e. we used data aggregation into larger units with stable boundary.

Application of PCA with georeferenced data in the tourism industry: A case study in the province of Córdoba, Argentina

2021 ◽  
pp. 135481662098768
Author(s):  
Laura I Luna
Keyword(s):  
Decision Making ◽  
Principal Components ◽  
Spatial Data ◽  
Local Development ◽  
Value Added ◽  
Tourism Industry ◽  
Methodological Innovation ◽  
Spatial Principal Components ◽  
Components Analysis

The spatial analysis of tourism industries provides information about their structure, which is necessary for decision-making. In this work, tourism industries in the departments of Córdoba province, Argentina, for the 2001–2014 period were mapped. Multivariate methods with and without spatial restrictions (spatial principal components (sPCs) analysis, MULTISPATI-PCA, and principal components analysis (PCA), respectively) were applied and their performance was compared. MULTISPATI-PCA yielded a higher degree of spatial structuring of the components that summarize tourism activities than PCA. The methodological innovation lies in the generation of statistics for multidimensional spatial data. The departments were classified according to the participation of tourism activities in the value added of tourism using the sPCs obtained as input of the cluster fuzzy k-means analysis. This information provides elements necessary for appropriately defining local development strategies and, therefore, is useful to improve decision-making.

Case study: Characterization of 19th century candles from maritime archaeological environments with FTIR, NMR, and GC–MS

2021 ◽  
Vol 35 ◽  
pp. 102711
Author(s):  
Lisa Kasprzok ◽  
Stéphanie Boussert ◽  
Johanna Rivera ◽  
Stéphanie Cretté
Keyword(s):  
19Th Century

scholarly journals Constructing Damage Indices Based on Publicly Available Spatial Data: Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

2021 ◽  
Author(s):  
Emmanuel Skoufias ◽  
Eric Strobl ◽  
Thomas Tveit
Keyword(s):  
Spatial Data ◽  
Volcanic Ash ◽  
Satellite Images ◽  
Fragility Curves ◽  
Volcanic Eruptions ◽  
Damage Indices ◽  
Damage Indicator ◽  
Time Period ◽  
Peak Ground Motion

AbstractThis article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events. For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator. For volcanoes we employ volcanic ash data as a proxy for local damages. Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images. We demonstrate the use of these indices with a case study of Indonesia, a country frequently exposed to earthquakes and volcanic eruptions. The results show that the indices capture the areas with the highest damage, and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014. The indices were constructed using a combination of software programs—ArcGIS/Python, Matlab, and Stata. We also outline what potential freeware alternatives exist. Finally, for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.

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