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E.C. Tsipa
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This thesis explores methods to enhance the usability of vario-scale maps, focusing on user interaction, cognitive load, and overall satisfaction. Vario-scale maps, based on a continuous zooming approach introduced by Van Oosterom and Meijers, aim to reduce visual disruptions by allowing smooth generalisation of geographic data in real time. The research highlights their potential to merge precision and aesthetic clarity wxhile advancing beyond the conventional snapping behaviour inherent in multi-scale interfaces.
A mixed-method approach was adopted to investigate whether vario-scale maps could improve navigation and user satisfaction. Data were collected through a pilot web-based usability study, followed by a laboratory eye-tracking study designed to capture detailed behavioural and cognitive processes. Quantitative metrics, such as fixation counts and scanpath lengths, were analysed to determine efficiency in map-use tasks, while think-aloud protocols and questionnaires provided qualitative insights into participant preferences and frustrations.
Findings indicate that vario-scale and multi-scale maps offer similar levels of efficiency based on objective eye-tracking metrics. However, participants generally reported higher satisfaction with vario-scale maps, citing smoother transitions, less visual interruption, and a more intuitive zooming experience. The pilot study underscored the importance of user familiarity with Cartography, the careful placement of icons, and task complexity as influential factors in map usability. These insights informed the final study, which showed that vario-scale maps align more closely with user expectations for modern digital interfaces.
By emphasising controlled task design, participant comfort, and iterative refinement through pilot testing, this thesis demonstrates how vario-scale maps can be optimised for enhanced usability. The results further suggest that leveraging cartographic principles—such as appropriate symbol density-plays an essential role in maintaining clarity and facilitating user orientation. Through comprehensive analysis of both objective metrics and subjective evaluations, this thesis provides evidence that improving vario-scale usability is both feasible and beneficial. Future research with broader user demographics and extended usage contexts is recommended to validate and refine the proposed design strategies, ultimately supporting a wider adoption of vario-scale technology for interactive and dynamic mapping applications. ...
A mixed-method approach was adopted to investigate whether vario-scale maps could improve navigation and user satisfaction. Data were collected through a pilot web-based usability study, followed by a laboratory eye-tracking study designed to capture detailed behavioural and cognitive processes. Quantitative metrics, such as fixation counts and scanpath lengths, were analysed to determine efficiency in map-use tasks, while think-aloud protocols and questionnaires provided qualitative insights into participant preferences and frustrations.
Findings indicate that vario-scale and multi-scale maps offer similar levels of efficiency based on objective eye-tracking metrics. However, participants generally reported higher satisfaction with vario-scale maps, citing smoother transitions, less visual interruption, and a more intuitive zooming experience. The pilot study underscored the importance of user familiarity with Cartography, the careful placement of icons, and task complexity as influential factors in map usability. These insights informed the final study, which showed that vario-scale maps align more closely with user expectations for modern digital interfaces.
By emphasising controlled task design, participant comfort, and iterative refinement through pilot testing, this thesis demonstrates how vario-scale maps can be optimised for enhanced usability. The results further suggest that leveraging cartographic principles—such as appropriate symbol density-plays an essential role in maintaining clarity and facilitating user orientation. Through comprehensive analysis of both objective metrics and subjective evaluations, this thesis provides evidence that improving vario-scale usability is both feasible and beneficial. Future research with broader user demographics and extended usage contexts is recommended to validate and refine the proposed design strategies, ultimately supporting a wider adoption of vario-scale technology for interactive and dynamic mapping applications. ...
This thesis explores methods to enhance the usability of vario-scale maps, focusing on user interaction, cognitive load, and overall satisfaction. Vario-scale maps, based on a continuous zooming approach introduced by Van Oosterom and Meijers, aim to reduce visual disruptions by allowing smooth generalisation of geographic data in real time. The research highlights their potential to merge precision and aesthetic clarity wxhile advancing beyond the conventional snapping behaviour inherent in multi-scale interfaces.
A mixed-method approach was adopted to investigate whether vario-scale maps could improve navigation and user satisfaction. Data were collected through a pilot web-based usability study, followed by a laboratory eye-tracking study designed to capture detailed behavioural and cognitive processes. Quantitative metrics, such as fixation counts and scanpath lengths, were analysed to determine efficiency in map-use tasks, while think-aloud protocols and questionnaires provided qualitative insights into participant preferences and frustrations.
Findings indicate that vario-scale and multi-scale maps offer similar levels of efficiency based on objective eye-tracking metrics. However, participants generally reported higher satisfaction with vario-scale maps, citing smoother transitions, less visual interruption, and a more intuitive zooming experience. The pilot study underscored the importance of user familiarity with Cartography, the careful placement of icons, and task complexity as influential factors in map usability. These insights informed the final study, which showed that vario-scale maps align more closely with user expectations for modern digital interfaces.
By emphasising controlled task design, participant comfort, and iterative refinement through pilot testing, this thesis demonstrates how vario-scale maps can be optimised for enhanced usability. The results further suggest that leveraging cartographic principles—such as appropriate symbol density-plays an essential role in maintaining clarity and facilitating user orientation. Through comprehensive analysis of both objective metrics and subjective evaluations, this thesis provides evidence that improving vario-scale usability is both feasible and beneficial. Future research with broader user demographics and extended usage contexts is recommended to validate and refine the proposed design strategies, ultimately supporting a wider adoption of vario-scale technology for interactive and dynamic mapping applications.
A mixed-method approach was adopted to investigate whether vario-scale maps could improve navigation and user satisfaction. Data were collected through a pilot web-based usability study, followed by a laboratory eye-tracking study designed to capture detailed behavioural and cognitive processes. Quantitative metrics, such as fixation counts and scanpath lengths, were analysed to determine efficiency in map-use tasks, while think-aloud protocols and questionnaires provided qualitative insights into participant preferences and frustrations.
Findings indicate that vario-scale and multi-scale maps offer similar levels of efficiency based on objective eye-tracking metrics. However, participants generally reported higher satisfaction with vario-scale maps, citing smoother transitions, less visual interruption, and a more intuitive zooming experience. The pilot study underscored the importance of user familiarity with Cartography, the careful placement of icons, and task complexity as influential factors in map usability. These insights informed the final study, which showed that vario-scale maps align more closely with user expectations for modern digital interfaces.
By emphasising controlled task design, participant comfort, and iterative refinement through pilot testing, this thesis demonstrates how vario-scale maps can be optimised for enhanced usability. The results further suggest that leveraging cartographic principles—such as appropriate symbol density-plays an essential role in maintaining clarity and facilitating user orientation. Through comprehensive analysis of both objective metrics and subjective evaluations, this thesis provides evidence that improving vario-scale usability is both feasible and beneficial. Future research with broader user demographics and extended usage contexts is recommended to validate and refine the proposed design strategies, ultimately supporting a wider adoption of vario-scale technology for interactive and dynamic mapping applications.
Student report
(2023)
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E.C. Tsipa, G. Iliopoulos, O.J. Post, R.M. Aalders, E. Verbree, J.A. Schoonman, B.M. Meijers
The present report is the end result of the project that was carried out as part of the Geomatics Synthesis Project in cooperation with AllMaps, an open-source platform dedicated to the viewing and georeferencing of historic maps. The main objective of the project was to automatically georeference historic map series curated and digitised by the Dutch National Archive. This was based on the corner coordinates of the map sheets. The first issue that had to be tackled was the reprojection of the original coordinates which were in Bonne projection
to WGS84 coordinates. To determine the corners of the map content within the sheets two methods were implemented. The first one detects the lines based on HoughLines Probabilistic Transformation and the second one detects lines based on the distribution of black pixels in the rows and columns of the images. In addition to map sheets with corner coordinates, there are two other sets of images which were georeferenced utilising a convolution neural network that performs feature matching. The feature matching was performed by running the two sets of images against the georeferenced sheets with known corner coordinates. To minimise the search space for this process a geocoder was used to determine the approximate location of the image. The implemented methods appear to hold the potential for georeferencing old map series. It is worth noting that the developed algorithms, while effective in many cases, may encounter challenges when dealing with irregularities on map sheets caused by the passage
of time, such as damage. Consequently, there is a great opportunity to further enhance the algorithms to ensure they can consistently and accurately georeference images, even when faced with such irregularities. This ongoing development will lead to improved georeferencing accuracy and user confidence. ...
to WGS84 coordinates. To determine the corners of the map content within the sheets two methods were implemented. The first one detects the lines based on HoughLines Probabilistic Transformation and the second one detects lines based on the distribution of black pixels in the rows and columns of the images. In addition to map sheets with corner coordinates, there are two other sets of images which were georeferenced utilising a convolution neural network that performs feature matching. The feature matching was performed by running the two sets of images against the georeferenced sheets with known corner coordinates. To minimise the search space for this process a geocoder was used to determine the approximate location of the image. The implemented methods appear to hold the potential for georeferencing old map series. It is worth noting that the developed algorithms, while effective in many cases, may encounter challenges when dealing with irregularities on map sheets caused by the passage
of time, such as damage. Consequently, there is a great opportunity to further enhance the algorithms to ensure they can consistently and accurately georeference images, even when faced with such irregularities. This ongoing development will lead to improved georeferencing accuracy and user confidence. ...
The present report is the end result of the project that was carried out as part of the Geomatics Synthesis Project in cooperation with AllMaps, an open-source platform dedicated to the viewing and georeferencing of historic maps. The main objective of the project was to automatically georeference historic map series curated and digitised by the Dutch National Archive. This was based on the corner coordinates of the map sheets. The first issue that had to be tackled was the reprojection of the original coordinates which were in Bonne projection
to WGS84 coordinates. To determine the corners of the map content within the sheets two methods were implemented. The first one detects the lines based on HoughLines Probabilistic Transformation and the second one detects lines based on the distribution of black pixels in the rows and columns of the images. In addition to map sheets with corner coordinates, there are two other sets of images which were georeferenced utilising a convolution neural network that performs feature matching. The feature matching was performed by running the two sets of images against the georeferenced sheets with known corner coordinates. To minimise the search space for this process a geocoder was used to determine the approximate location of the image. The implemented methods appear to hold the potential for georeferencing old map series. It is worth noting that the developed algorithms, while effective in many cases, may encounter challenges when dealing with irregularities on map sheets caused by the passage
of time, such as damage. Consequently, there is a great opportunity to further enhance the algorithms to ensure they can consistently and accurately georeference images, even when faced with such irregularities. This ongoing development will lead to improved georeferencing accuracy and user confidence.
to WGS84 coordinates. To determine the corners of the map content within the sheets two methods were implemented. The first one detects the lines based on HoughLines Probabilistic Transformation and the second one detects lines based on the distribution of black pixels in the rows and columns of the images. In addition to map sheets with corner coordinates, there are two other sets of images which were georeferenced utilising a convolution neural network that performs feature matching. The feature matching was performed by running the two sets of images against the georeferenced sheets with known corner coordinates. To minimise the search space for this process a geocoder was used to determine the approximate location of the image. The implemented methods appear to hold the potential for georeferencing old map series. It is worth noting that the developed algorithms, while effective in many cases, may encounter challenges when dealing with irregularities on map sheets caused by the passage
of time, such as damage. Consequently, there is a great opportunity to further enhance the algorithms to ensure they can consistently and accurately georeference images, even when faced with such irregularities. This ongoing development will lead to improved georeferencing accuracy and user confidence.