Analysing methods for visualizing time-series datasets in open-source web mapping
(2022) In Master Thesis in Geographical Information Science GISM01 20222Dept of Physical Geography and Ecosystem Science
- Abstract
- Geography is the study of knowledge in a given location, and history is the study of knowledge over time. The combination of changes over time has always been challenging to visualize in maps. The main aim of this thesis was to analyze differences between various methods used to visualize spatio-temporal data with open-source web mapping technology.
The methodology of this thesis has been split into three main parts: (1) data collection and preparation; (2) application development; and (3) performance testing and statistical analysis. Through a comparative study between four technology solutions/methods to visualize spatio-temporal data, this work has tried to document if there are differences in loading times and efficiency results... (More) - Geography is the study of knowledge in a given location, and history is the study of knowledge over time. The combination of changes over time has always been challenging to visualize in maps. The main aim of this thesis was to analyze differences between various methods used to visualize spatio-temporal data with open-source web mapping technology.
The methodology of this thesis has been split into three main parts: (1) data collection and preparation; (2) application development; and (3) performance testing and statistical analysis. Through a comparative study between four technology solutions/methods to visualize spatio-temporal data, this work has tried to document if there are differences in loading times and efficiency results evaluated based on performance tests.
Four time series datasets ranging in sizes were utilized as the test data for the four different techniques, GeoJSON, WMS, D3 and Cesium. The performance time results shows that the WMS technology was the fastest for data loading in terms of the display time and total loading time. Cesium, GeoJSON and D3/TopoJSON were also usable for small datasets but failed the large data tasks. The results regarding animation efficiency were that WMS was the only technology that was able to display all four datasets.
Conclutions
The overall conclusion is that only one of the four technologies handled all datasets and that was the WMS application. WMS was the fastest method for data loading and had the smallest display times and total loading times, for all four datasets. And for efficiency and animation the conclusion was that WMS was the only technology that was able to display all datasets.
What of four open-source-based methods are most optimal for visualizing spatio-temporal data are the contribution of this work. Future work should use more simular data with different sizes and find a better way to take the time measurements. (Less) - Popular Abstract
- Geography is the study of places, and history is the study of change over time. The changes over time have always been difficult to show in maps. The main aim of this study was to find differences between some methods used to show time series data with open-source maps on internet.
The methods used in this study has been split in three main parts: (1) collecting data and preparation; (2) make a map solution for internet; and (3) measure performance and analysis. Four different technologies to visualize time series data has been compared, this work has showed if there are differences in loading times and efficiency of animations based on time measures.
Four time series datasets in different sizes were used as the test data for the four... (More) - Geography is the study of places, and history is the study of change over time. The changes over time have always been difficult to show in maps. The main aim of this study was to find differences between some methods used to show time series data with open-source maps on internet.
The methods used in this study has been split in three main parts: (1) collecting data and preparation; (2) make a map solution for internet; and (3) measure performance and analysis. Four different technologies to visualize time series data has been compared, this work has showed if there are differences in loading times and efficiency of animations based on time measures.
Four time series datasets in different sizes were used as the test data for the four different methods, GeoJSON, WebMapServises (WMS), vectordata (D3) and Cesium (3D). The time measure results shows that the WMS technology was the fastest for data loading. Cesium, GeoJSON and vectordata were also usable for small datasets but failed with the large data. The results regarding animation efficiency were that WMS was the only method that was able to display all four datasets.
Conclutions
The conclusion is that only one of the four technologies handled all datasets and that was the WMS application. WMS was the fastest method for data loading and had the smallest display times and total loading times, for all four datasets. And for efficiency and animation the conclusion was that WMS was the only technology that was able to display all datasets.
What of four open-source-based methods are best for showing time-series data are the result of this work. Future work should use more simular data with different sizes and find a better way to take the time measurements. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9102046
- author
- Lunde, Viggo LU
- supervisor
- organization
- alternative title
- Showing time-series data in open-source web mapping
- course
- GISM01 20222
- year
- 2022
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Geography, GIS, spatio-temporal, time-series open source, webmap
- publication/series
- Master Thesis in Geographical Information Science
- report number
- 150
- language
- English
- additional info
- Technical Supervisor: PhD. Mattia Natali, Senior Engineer, NIBIO (Norwegian Institute of Bioeconomy Research)
- id
- 9102046
- date added to LUP
- 2022-10-20 13:56:48
- date last changed
- 2022-10-24 17:39:22
@misc{9102046,
abstract = {{Geography is the study of knowledge in a given location, and history is the study of knowledge over time. The combination of changes over time has always been challenging to visualize in maps. The main aim of this thesis was to analyze differences between various methods used to visualize spatio-temporal data with open-source web mapping technology.
The methodology of this thesis has been split into three main parts: (1) data collection and preparation; (2) application development; and (3) performance testing and statistical analysis. Through a comparative study between four technology solutions/methods to visualize spatio-temporal data, this work has tried to document if there are differences in loading times and efficiency results evaluated based on performance tests.
Four time series datasets ranging in sizes were utilized as the test data for the four different techniques, GeoJSON, WMS, D3 and Cesium. The performance time results shows that the WMS technology was the fastest for data loading in terms of the display time and total loading time. Cesium, GeoJSON and D3/TopoJSON were also usable for small datasets but failed the large data tasks. The results regarding animation efficiency were that WMS was the only technology that was able to display all four datasets.
Conclutions
The overall conclusion is that only one of the four technologies handled all datasets and that was the WMS application. WMS was the fastest method for data loading and had the smallest display times and total loading times, for all four datasets. And for efficiency and animation the conclusion was that WMS was the only technology that was able to display all datasets.
What of four open-source-based methods are most optimal for visualizing spatio-temporal data are the contribution of this work. Future work should use more simular data with different sizes and find a better way to take the time measurements.}},
author = {{Lunde, Viggo}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master Thesis in Geographical Information Science}},
title = {{Analysing methods for visualizing time-series datasets in open-source web mapping}},
year = {{2022}},
}