Analysis of the spatiotemporal accumulation process of Mapillary data and its relationship with OSM road data: A case study in Japan
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Number of Parts | 351 | |
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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 | 10.5446/68914 (DOI) | |
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Production Year | 2022 |
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00:00
Mathematical analysisProcess (computing)Integral domainObservational studyQR codeResultantOpen setRight angleLevel (video gaming)Computer animation
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PolygonTotal S.A.Process (computing)Mathematical analysisRadiusMaxima and minimaData conversionSpatial joinDatabaseFunction (mathematics)Computer-generated imageryUniqueness quantificationNumberDigital photographyExecution unitCurvatureLevel (video gaming)Medical imagingStructural loadUniqueness quantificationFunction (mathematics)Process (computing)Multiplication signOpen setConstructor (object-oriented programming)DatabaseRelational databaseFile formatArithmetic progressionDomain nameResultantWebsiteLocal ringOnline helpComputer animation
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Computer-generated imageryExecution unitWebsiteMathematical analysisComputer animation
Transcript: English(auto-generated)
00:01
Okay, I will start my presentation. So thank you so much to the chair. So this short is a lightening talk, right? So I'm regarding to some short result, only for result. But you are interested in my talk.
00:23
Please visit our papers below the QR code. So anyway, I will talk about research for not only using OpenStreetMap, but also using Mapillary for the tokens of data.
00:41
So anyway, so anyway, I will prepare an overview of the six years, so long times in Mapillary data for Japan. So this is a summary of Mapillary's data.
01:04
So about 41 millions, some large, huge data set here is shown. So anyway, in Japanese situation, Mapillary will start at 2014.
01:20
So anyway, for Japan, a low-corrected user, only the 1,000, anyway, about 1,000 users. So this time series in Mapillary taken photo,
01:42
and also the user participate with Mapillary projects. So this graph is shown, the time series discussions. So anyway, I will, so data correcting and some database constructions,
02:04
very important things in the very few data set. So anyway, we will go through the four steps database construction. So maybe, so 41 million data is very huge,
02:23
and also maybe our first time to use the PostGIS, however, the main hangover in data set. So I will switch to the, this is for 4G conference,
02:42
so related with flat geobuff format. So this is very quickly and very wonderful to use this database. So anyway, leading times, it's very shortly and quickly processing,
03:01
also very quickly, was maybe about three times faster than local domain of the PostGIS. But the output data size is very huge in FGB format.
03:20
This is a, so issues in my opinion. So anyway, our research result is the partially to output of the GitHub. Please access to the GitHub site.
03:45
So this is research of the, our research in relation Maperi and the OpenStreetMap coverage. So anyway, about 15,000 unique Maperi contributors
04:04
during the six years. So anyway, the top 10 users only contributed about 90% of the image taken of Japan. So anyway, about 40 of Maperi related
04:23
OpenStreetMap loads have been update since the Maperi image were taken, which can help update OpenStreetMap load data progress in Japan. So anyway, last update of OpenStreetMap load
04:45
before and after Maperi image taken by one kilometer grid sites. So these, oh sorry, these data will be now,
05:03
now calculate with more locally, local sites. So we are try to, so any other contribution and any other analysis, please suggestion and opinion for our research.
05:23
Thank you so much.