Topographic Maps: Image Processing and Path-Finding
2018
- 99Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage99
- Downloads65
- Abstract Views34
Thesis / Dissertation Description
Topographic maps are an invaluable tool for planning routes through unfamiliar terrain. However, accurately planning routes on topographic maps is a time- consuming and error-prone task. One factor is the difficulty of interpreting the map itself, which requires prior knowledge and practice. Another factor is the difficulty of making choices between possible routes that have different trade-offs between length and the terrain they traverse.To alleviate these difficulties, this thesis presents a system to automate the process of finding routes on scanned images of topographic maps. The system allows users to select any two points on a topographic map and identify their specific preferences for their route. This system extracts terrain and contour line data from topographic map images using image processing techniques and then uses the A* Search algorithm to find a route between the specified points. This system can be used as a starting point for hand-drawn routes, as a means of considering alternative routes, or to entirely replace drawing routes by hand. This thesis also presents a user study which shows that this system produces routes in a significantly shorter time than hand-drawn routes, and with a similar level of accuracy.
Bibliographic Details
Robert E. Kennedy Library, Cal Poly
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know