We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Mapping Mt. Ushba – How to create a high-quality topographic map from open data using free software

00:00

Formal Metadata

Title
Mapping Mt. Ushba – How to create a high-quality topographic map from open data using free software
Title of Series
Number of Parts
351
Author
License
CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Identifiers
Publisher
Release Date
Language
Production Year2022

Content Metadata

Subject Area
Genre
Abstract
Mapping Mt. Ushba – How to create a high-quality topographic map from open data using free software Mt. Ushba is situated in the Greater Caucasus in Georgia, next to the Russian border. With its nearly symmetrical double peak appearance, it is iconic and a symbol of the historic Svaneti region in Georgia, famous for its mountains, botany, and century-old defense towers. Svaneti is becoming an increasingly popular tourist destination in summer and winter. Therefore, the German Alpine Club is interested in providing a new map for this region, which will be produced by the Institute of Cartography of the TU Dresden. In the age of open data, it is consequential that OpenStreetMap will be an essential source of the new map. It should make the project more sustainable and inspire people to use free and open-source software for map production. One basis of each topographic or touristic map is fieldwork, which means organized mapping and editing with OpenStreetMap aiming to verify and to complement map content and coverage[1], carried out by the Institute of Cartography in Mestia (Georgia) in the summer of 2021. Preparing for this work, a comparison with older maps was conducted to identify possible shortcomings and errors in the data. A draft was created using OpenStreetMap and the SRTM elevation model, preparing for the fieldwork. It helped to evaluate the current state of the data, gave a first impression of the mapping area, and was an ostensive basis for data capturing in field. A field book was produced for each participant, containing the map draft as an atlas and information on which data should be collected and which the specific attributes were required. Finally, the data was contributed to OpenStreetMap, and from there, the draft was updated again. In the case of land cover, creating an own classification seemed beneficial in distinguishing between typical vegetation classes in a high mountain area. Showing the vegetation in detail is a feature of Alpine Club map, but using OpenStreetMap data would not detailed enough. In addition, a land cover classification based on remote sensing data is more reliable and ensures better consistent results compared to individual contributions from users with different previous knowledge. Open remote sensing data from the Landsat and Sentinel programs offer good sources for such a task and are also used to monitor the glaciers in this area[II]. R is used as an analysis platform. It is possible to classify rock, glaciers, and specific vegetation types such as alpine rose or open birch stands. For identifying the vegetation, representative examples were collected during the fieldwork by entering them in the atlas and taking sample photographs. Another essential part of a topographic map for a high mountain area map is a good terrain visualization. The SRTM model is beneficial but not detailed enough to create rock depictions, which will be automatically derived by the Piotr tool[iii]. Planet Labs Inc provided high-resolution Rapid Eye and their Dove satellites imagery, suitable for creating a digital elevation model with a spatial resolution of approximately ten meters by applying stereo photogrammetry methods using the AMES Stereo Pipeline[iv]. The result enables a much more precise and understandable representation of the terrain. The terrain points were recorded with special standard GPS devices, the Garmin GPSMAP 66sr, which stores the raw observations for two frequencies. Accuracies in the range of around 0.1 meters[v] can be achieved using professional GNSS software. In order to produce the final topographic map, it is necessary to combine all data components to represent the area around Mt. Ushba. In a first step, the updated OpenStreetMap data is imported into a PostgreSQL database with PostGIS extension. In a second step, an automated generalization is carried out for the selected target scale of 1:33,000, particularly schema transformation, aggregation, and simplification. For the visualization, QGIS is utilized: one project containing all layers with their visualizations served as WMS. It enables team members to view the current map and access all the data without storing it individually locally on their computer. Additional web mapping services were set up to provide georeferenced scans of other available maps of the region to enable a comparison and evaluation of the new derived topographic map product. Because of the wide range of tasks, the work is split into several work packages and ongoing subprojects. Students' master theses within the International Cartography Master program – a cooperate offer of TU Dresden, TU München, TU Wien, and University Twente contributed significantly to the project by implementing and evaluating selected methods required for the map derivation.
Keywords
Open sourceProduct (business)MappingOpen setTexture mappingSoftwareTexture mappingProduct (business)MappingOpen sourceStandard deviation
Universe (mathematics)Latent heatComputer animation
TowerHypermediaSlide ruleTowerMappingArea
Digital signalData modelAudiovisualisierungAirfoilAreaElectronic program guideInformationMappingOpen setSweep line algorithmTexture mappingServer (computing)Proxy serverMotion captureArithmetic progressionSource codeTrailData storage deviceProduct (business)Transformation (genetics)Visualization (computer graphics)BlogQuantum stateComputer animation
Texture mappingField (computer science)MappingInformationComputer animation
MeasurementPoint (geometry)Web pageTotal S.A.Storage area networkComputer-generated imageryDigital signalFrequencyDuality (mathematics)Source codeSlide ruleActive contour modelLine (geometry)Plug-in (computing)Hill differential equationMetreOnline helpRaw image formatSpline (mathematics)Medical imagingFrequencyState observerPresentation of a groupAreaProcess (computing)Computer animation
MappingMultiplication signStudent's t-testFreewareComputer animation
Transcript: English(auto-generated)
Thanks for introducing me. So I will try to give you the most important things from the paper I wrote with my colleagues together about mapping this big mountain that you see here with the iconic double peak. It's an Alpine Club map. It's something like a gold standard in a map production. So we try to do the best with open source software.
So where we are? We are in Georgia, not in the US. We are in the Georgia country next to Russia between the Black Sea and the Caspian Sea. So red is here. And we are in a specific region called Svaneti, situated in the greater Caucasus, in the middle of nowhere in the mountains.
So what's specific about this region? Yeah, it's about mountains, medieval villages, it's UNESCO heritage, because of these old villages, quite medieval, and the medieval towers. So still special, tourists like to come here, hikers, so there's a demand for a great map for the area. So what we did? Yeah, we tried to do this with Open Sweep Map. What's the new thing?
What was interesting for us? We do this on a daily updated map preview that we built for ourselves. A preview that we saw the progress of mapping, and also like a style preview for us that we're not having a final map in the end. We see already now how it can be looked.
So we do this by mapping, improving Open Sweep Map, we have a workflow for map production, generalization, the working map that you can see here in background, capture data on ground, give it back to Open Sweep Map, and we see on the next day, or the next day, the updated map preview for us.
What's behind? It's awesome to PGL SQL behind for the data transformation, PostGIS as data storage, and the generalization through GIS, a server or desktop visualization, and the map proxy keeps us as cached map. The other thing, how to find missing ways. Just go into nowhere in the mountains how to search it. We try to look
on old maps, other maps, and collect it as for us, there are probably missing ways and also names for Open Sweep Map. And then we went in place and try to check this. So our old maps, hiking maps, topographic maps, guidebooks, blocks, GPS tracks,
and sometimes Open Sweep Map itself with some hidden features and GPS tracks is the source of information we try to check in place. So we're in place this year and last year and try to improve Open Sweep Map. Yeah, another great idea of what has helped us, we make from our map review a field book, we have something like an atlas where
you can see the map already, you can see it overall if there is often bad weather, don't worry, it will get wet. Yeah, it's hard. But we built an atlas so we can go out with this, with the GPS devices and collect our information, taking notes, and there's also documentation for mapping in it, everything together.
Another thing we have to do because we need a customized digital elevation model, we need control points. How to measure this? We have these great things that professionals do. No, not practical on these mountains. We go for a better GPS device, it's the Garmin GPS Map 66 SR, it measures on dual frequency and you get raw observations out of it.
You can do post-processing and then you get below one meter. That's quite enough for us. So we don't need centimeter or millimeters, decimeters, and meters are fine.
We have the NASA Ames Stereo Pipeline like in the last presentation used. We have got images from planet just as a grant that we can make our own digital surface model and we are going for our own digital elevation model for this area. Which we will visualize with the help of QGIS, with the Carica plug-in, and also as a tool for making rock edges, which is called Piotr.
So, that's about all this behind, but you need people. You need motivated people. We found students, colleagues, and their friends who helped us, and also these nice t-shirts.
So, we went out and thanks for everyone helping us to make this map in their free time. Thank you very much, you're just on time.