The UN Open GIS initiative – Spiral 4 for geospatial data collection
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00:00
WebsiteMultiplication signGroup actionPresentation of a groupBitEvent horizonSpiralOpen setUniverse (mathematics)SpacetimeLecture/Conference
00:49
SpiralOpen setData managementMathematical analysisService (economics)Vector spaceDigital photographyContent (media)VideoconferencingFunction (mathematics)Content management systemField (computer science)GeometryView (database)LengthDirection (geometry)SequenceEinbettung <Mathematik>Directed setComputer-generated imageryPredicate (grammar)Query languageTrajectoryWeb browserMathematicsMultimediaPairwise comparisonLibrary (computing)Computing platformGEDCOMJava appletTomcat <Programm>Temporal logicSanitary sewerComputer configurationImplementationUtility softwareSoftwareObject (grammar)GeometryRevision controlFrame problemComputer fileStreaming mediaMobile appMedical imagingPhysical systemShared memoryLibrary (computing)Cartesian coordinate systemData structureInternet service providerSequenceWeb portalCycle (graph theory)User interfaceDigital photographyField (computer science)Real-time operating systemTrajectoryInformationPresentation of a groupLevel (video gaming)Fundamental theorem of algebraMultimediaMappingView (database)Source codeValidity (statistics)CASE <Informatik>Phase transitionVideoconferencingProduct (business)BitPredicate (grammar)Vector spaceData qualityVideo gameTesselationOpen sourceComputer configurationUniverse (mathematics)SpiralMultiplication signMechanism designHuman migrationMultiplicationSingle-precision floating-point formatTemporal logicMetadataMathematical analysisAngleVertex (graph theory)FamilyContent management systemSampling (statistics)Sinc functionCanadian Mathematical SocietyFunctional (mathematics)WebsiteUniform resource locatorConstructor (object-oriented programming)Software testingPairwise comparisonData managementQuery languageOpen setGroup actionResultantCondition numberOrder (biology)Water vaporProcess (computing)Web crawlerRight angleService (economics)SpacetimeTotal S.A.Centralizer and normalizerChief information officerDemosceneFocus (optics)Conservation lawComplete metric spaceSummierbarkeitSpeech synthesisShooting methodMassPlanningLie groupRule of inference2 (number)Lattice (order)HypermediaRow (database)Computer animation
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Computer-generated imageryOpen setProcess (computing)Total S.A.Server (computing)Local GroupForceComputer configurationModule (mathematics)Software testingSample (statistics)Military operationParameter (computer programming)Performance appraisalComputer fileEstimationHuman migrationWebsitePairwise comparisonMathematical analysisAttribute grammarCodePolygonPoint (geometry)Type theoryError messagePhysical lawCondition numberConditional probabilityPower (physics)Object (grammar)Shape (magazine)Entire functionFrequencySimilarity (geometry)ExplosionLatent heatInformation and communications technologyChannel capacityMobile WebGame controllerLine (geometry)Parameter (computer programming)Office suiteValidity (statistics)Error messagePerformance appraisalPairwise comparisonProcess (computing)DistanceMaxima and minimaAdditionTraffic reportingSource codeMedical imagingWeb 2.0Procedural programmingSoftwareFunctional (mathematics)ResultantCircleGeometryOrder (biology)Open sourceWeb applicationSoftware developerComputer configurationStreaming mediaField (computer science)Software testingLevel (video gaming)Correspondence (mathematics)Mobile appComputer fileWeb browserPresentation of a groupRight angleStapeldateiMappingFile formatDifferent (Kate Ryan album)DatabaseOpen setPhysical systemClient (computing)BuildingEndliche ModelltheorieConnected spaceDynamical systemProduct (business)Projective planeServer (computing)PasswordAreaBoundary value problemHuman migrationFlow separationAbsolute valueArithmetic meanHypermediaEntropie <Informationstheorie>Task (computing)Form (programming)Wechselseitige InformationChief information officerHeegaard splittingForestSpecial unitary groupSummierbarkeitMathematicsMusical ensembleDemosceneForcing (mathematics)Multiplication signCASE <Informatik>Design by contractComputer animation
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Channel capacityMobile WebInformation and communications technologyMultiplication signGame theorySet (mathematics)VideoconferencingSoftware testingSmartphoneBuildingArchaeological field surveyInformationPhysical systemFormal languageWorkstation <Musikinstrument>Direction (geometry)Wave packetLimit (category theory)CASE <Informatik>Musical ensemblePosition operatorCore dumpComputer programmingDigital photographyNumberSocial classRow (database)CNNMedical imagingCanadian Mathematical SocietyPlastikkarteFilm editingMobile WeboutputAndroid (robot)Endliche ModelltheorieWeb serviceWeb pageSource codeComputer animationMeeting/Interview
Transcript: English(auto-generated)
00:07
Okay, thank you So I was told that I have a little bit more time because after that this is a lunch time But I have no intention to take the lunch time. Okay, so first of all, I'd like to show my teachers
00:20
Which was given Four or five years ago at post 4g in Seoul So this is the same color, but it's a different event. All right okay, and For this time, I'd like to give the presentation on the spiral for that means the working group for of
00:40
UN Open GIS initiative So this is for the geospatial data collection so there are many courses most of them are from South Korea from my university and I'd like to also introduce Ananda Velkanon who is working at the minuscule minuscule. What is ten for minuscule exactly?
01:01
Yeah, so but so So multi so every time I hear that Every time I hear that I forget it
01:20
Sorry, but it is so it is based on the Central Africa Republic of Central Africa so where there are many missions over there and some of the courses like to GIT GIT is the geospatial company in Korea who has been working for the
01:40
validation of a national mapping agency and then Who's at the professor? Kwangwonam who is where is? Okay, so he is one of the leader of the product for spiral for I will give an explanation and in Pyeong Lee He is working at University of Seoul for the solution of called the live drone map. All right
02:03
These are the also of the the this presentation and we are working together So I'd like to to explain or what is the goal of spiral for or walking group for walking So this is a life cycle of a geospatial system starting from other data construction
02:22
so data construction is Very beginning work and most fundamental things of geospatial system Of course after that we have the management and the sharing of data and application and analysis so everything start from this geospatial data collection, so the
02:44
the activity of spiral for focused on the data collection Of course as you know If you look at the spatial data instructs structure of a single country or United Nation There is not one single way to collect the data. There are many many ways
03:04
If you look at the mission field in Africa, so sometimes the the The situation of the data the availability availability of a geospatial data is very bad So we have to to struggle To find out the proper data any kind of geospatial data
03:24
So there is not only one single solution, but there are many many solutions like for example migration of legacy data if there is from proprietary software to open source solution or the of course the open stream app is one of the big source of
03:43
geospatial data for the United Nation and so these are one of the important these are the some activity within the spiral for and But I do like to focus on the next three Activity first is a live-draw map and the second one is
04:01
Georeference to multimedia data called the geo CMS and the final one is Geospatial data quality so called the open geodt and of course we include vector tile map service, but which is led by Hidden Ori so so over there
04:21
But he will give another presentation and this afternoon about that activity Alright, so I will give the presentation of these three activity so first one is a geo CMS The geo CMS is led by professor Nam over there So the goal of this geo CMS is to provide
04:41
Geo reference to multimedia that means geo reference to photo and geo reference to video so for example we install a dashboard camera on the Convoy vehicle or the utility vehicle of the United Nation Then they capture every video every frame of the video files
05:01
So when they move to the mission field so then we need a kind of a geo reference that means the trajectory of The video file to analyze or and to to find some information and so on so these the goal are to provide the solution for Collecting and managing the geo reference to multimedia
05:24
right so in order to keep the geo reference the data of a photo or the Video what is very important is to keep the information about the field of view so as you know if we take a picture we have a location and we have the bearing we have the heading and
05:45
The depths and the angle of vertical angle and horizontal angle, so we have to keep the metadata What the information about this FOB for every picture or every single frame of the video file? So that is something that we have to
06:02
manage in the system of open geo CMS, so we have two version of geo CMS the first one is just Managing the data from the field of a geo reference to video and geo reference to photo So this is a case of geo reference to photo and also if you look at the geo reference to video
06:24
You we have not only one single FOB But the sequence of FOB which correspond to the trajectory where you are moving with the camera So we have to handle this kind of information so this is the first version of geo CMS then
06:42
After after developing geo CMS one of course we deliver it to the mission field of minuscule and then we Have been working for geo CMS version 2 which is With some new feature like a little bit modified user interface
07:00
But the most importantly the image detection mechanism function for example when you take a picture Then we can detect the person and the vehicle on the picture So this is additional a new new function of geo CMS version 2 and of course We implemented a little bit more complicated sophisticated the predicate so called the geospatial
07:25
temporal predicate Alright, so This is a comparison between the version 1 and version 2 so we introduced for example the deep learning engine For the the the Detection of the object using a tensorflow or M geometry like M means mobile moving object library
07:47
So there are many libraries for handling Spatial temporal or moving object so we included these two things into the new version of geo CMS
08:01
Okay, so this is a sample image of the image the feature detection using deep learning So as you see here, it is not very clear from you from you But we detected the every every person's here and the vehicle if there is So this is the feature detection function and also we can give the query based on
08:24
spatial-temporal condition All right, so and as a result of this this system. We return the data with the JSON file All right, so you can test this open geo CMS version 2 via this
08:41
Website. All right, and the second one is a live room map. The main contributor is a Professor the team of professor Lee There are many leads in Korea Anyway, the Lee is one of the biggest family in the world Since okay, it's nothing to do with my presentation
09:04
So university professor Lee in Pyeong he is working at University of Seoul and they are working together with the Gaia 3d the goal and of course a minuscule is Is they are working for? Testing there's a solution. The goal is to deliver a solution for collecting geo rectified image
09:25
Captured from drone and sharing via a web portal. So there are two approaches the first phase From 2016 and 2017 we focused on the option a which is to collect the data
09:43
almost in real time from drone and we process it almost in real time to produce a geo rectified image map and Stitch it together and provide it immediately via web portal So one very good very nice thing and the option a is of course
10:03
The quality is not that good, but we can see what's happening on the on the image map Not only in the mission field But for example in the UN headquarter almost in real time in for example every five a second So this is very good thing But the quality is not that good. So we
10:23
Have an option B which is a post-processing because there are many very nice Solution like open draw map. So we we use open draw map to produce a better quality image map and The share via a web portal through a Margo 3d Margo 3d is a very nice engine to share
10:45
Dynamic data. So this is a two approaches. So I will give a very short explanation of each So first one is okay. This is the requirement of the the live-draw map solution. So there are many requirements from the United Nations, but anyway, so
11:04
This explained the whole process of the first option the live-draw map So once you have you prepare the the region where you want to capture the data Then you launch the live-draw map Then they send the the the image from the each drone then it is processed
11:26
In a ground. Oh, sorry so And then They generated you rectify the data and it is a send to Geo portal called Margo 3d then this Margo 3d data is shared by everywhere in the world
11:47
We are only a web browser. So this is very nice solution, but the problem was the quality was not that good anyway, we can see what's going on in the field and Then so this is the comparison. So this is some test
12:05
Using this solution, but I will skip it. Yep All right so and for for option two Because there is already the very nice open source software called the open draw map
12:21
So we use this one for testing five different region provided by minuscule and then we tested it using a web Web open draw map solution probably some of you are already aware of that So this is the the result of this product
12:42
If you see this is not very clear But you see the boundary of the the image that we captured from the drone and the other area So this is very accurate and we can get not only the the geo rectified image But also the 3d modeling, of course, the 3d modeling is not very far perfect
13:04
But anyway, we can get the idea of the terrain or the building and so on This is a very nice solution and then after produced this solution that can be shared by by every client in the world of the United Nation almost in
13:22
All right. Okay, so we install this solution within the minuscule But we have some connection problem. But anyway, we are Trying to install this one within minuscule Okay, the next one is Open geo DT which is a quality control solution for
13:43
for for geospatial data this company geodt GIT They have been working to validate the map produced by National Mapping Agency of Korea So they have a lot of experience to validate the data
14:01
So they applied this technique and they release the source code as an open source of software So the goal is to to call it to to provide the quality control like validation and if you find some errors, then you can Correct it immediately and you provide as a result of the validation of evaluation report
14:25
okay, so this is the goal of this activity and web-based solution so but what they they have done is They implemented this solution as a plug-in of QGIS. So this is quite a nice things
14:43
so and in order to so in order to run this Quality control tool or validation tool you have to set up some parameters For example, if you want to check if you want to detect the sliver line You have to you have to set the the maximum distance one minimum distance between two lines, etc
15:06
So you can set the parameters through their website. So these are the Password anyway, so and I'm sorry that document is is available in in Korean So if you learn Korean you can see that but anyway, this is very understandable
15:24
Without any knowledge on Korean, but anyway, we we have to translate to to English but okay, so and This is explanation of the solution as a geo QGIS plug-in This is the comparison. So and the one very interesting thing with the geo DT is the solution open geo DTS
15:47
We we provided the quality control not only for general data, but also open stream map data All right. Okay, so we we first of all compared the validation Items of Joseph Joseph me. It's very nice to to editing open stream app data
16:04
So we compared the functions or validation item from Joseph and the solution from geo DT So, of course, there are common functions. But anyway, there are many many very nice solutes many items for the validation and
16:21
We tested to compare the our solution with the Justin so we downloaded the data of South Sudan Open-stream app of South Sudan and we tested So these are the result of the the comparison so of course the the testing item of just Sam and our solution a little bit different because the
16:44
function the Justin the Function for the validation are based on the Justin format But the geo DT or we convert to the open stream app data into the the post GIS So these are based on the the database on post GIS
17:01
so the validation item are slightly different, but there are almost some correspondence between this function and this function and So this is a result of the the test so this is original file of open stream app and the circle here did indicate the region of the errors
17:22
alright, these are the So comparison of the result from Joseph and the open geo DT So there are some almost these are very similar except for example the tagging system Which are in only in the open stream app data, and we don't have any tagging system in and post GIS
17:42
So the the checking the tagging in post GIS is meaningless, so we don't have that item But anyway these are almost the same As a summary the for the open geo DT the contribution is so if you look at the the process of Joseph It is quite interactive checking. It is not a batch processing, but for example
18:05
You are supposed that you are The the national mapping agency and you are subcontractor with the the data collection company Then once they provide their the data to nation mapping agency Then we have to check whether it satisfy the evaluation criteria
18:24
So these are such kind of purpose so once we have open cinema data Probably Diego explained it the previous presentation. They have to migrate this data periodically to UN basement data so during this data the migration we need
18:45
Validate whether there are some errors in open stream app data or not so these are for this process Okay All right the summary of this presentation we Achievement we develop several solution for geospatial data collection
19:03
And we delivered we and we are delivering as well the the thing That we have to do is we have to not install we have to install within a UN ICT infrastructure because in order to install every software within
19:22
UN infrastructure we have to follow a very rigorous procedure so we need to follow that procedure and The data collection process should be coupled very tightly coupled with the workflow of United nation so they have their own procedure so that should be
19:43
integrated or harmonized with the UN a workflow and We have to Strength the community so this solution are very first step of the development So we have to work together with the community from OS geo and so on so for example
20:02
We are planning to set up an incubation project not all by some VR OS geo and What we need as well is we don't have yet the validation for field That means suppose that you are the the field officer Then you have some work to do but in addition to your own mission
20:25
You may carry your mobile solution, and you may check whether the data on the server Well in the basemap is correct or not so if it is not correct Then you can very quickly make a report so that we may complete the data
20:40
All right, that's it. Thank you. Thank you very much We are again very well in time time for questions, please the first
21:00
So the people Which worry this one all right?
21:21
Okay, yeah, so to take picture so there is a the leader of the developing team so professor now So if you have a question then the technical question, so please do not ask me the technical question about that solution He's the next All right anyway, okay?
21:41
Regarding this tool Is it for only for which kind of? mobile system is and in which Language is it developed so there is no limitation of the mobile devices so once you get the FOB data the position and the heading then you can get the
22:04
iOS so professional so it is for iOS and Android Some pages are available, but the system is not for the mobile system
22:21
Just that is for the only web service in this time Oh Thank you. Yes, this is I think every smile smart ponies of it, okay, okay, I modern smartphone have magnetic sensors and
22:41
GPS so you can take a pictures that that pictures have direction Including GPS. Okay, so that is we are using that information so in the when you take a Video, okay, we there is no magnetic sensor So so we are guessing that information from the direction moving direction. Okay, that is we
23:08
We can extract the information from the GPS it information. Okay. Yes. Yes, okay
23:30
Yes, yes, it's possible we you can extract that information from the Jpz or all other pictures that is okay, but that is in our bed over in the smartphone pictures
23:43
smartphone features and Android or IOS okay, this is okay Yeah, hi just one question are you doing any automatic feature extraction from the drone data like Like 3d buildings building outlines. Yeah, so that is very good question. So could you answer to this?
24:06
So the the automatic detection not only from smartphone photo, but also the drone photo Running problem, so we we have adjusted to Dataset one is a ms. Cocoa. Can you show that?
24:26
this one Ms. Cocoa Ms. Cocoa Ms. Cocoa is further just the of front Generally easy the front is a Front way that is not for the drone. So but we can make a new data set
24:44
by the drones and we can we can learning my our system and we can attach the This system in our two CMS that is available. All right, but this time, okay So so so far you you you train the the system with the front image
25:01
Yeah, but if you have enough learning training data setter then that could be also possible to realize for the the drone Image, am I right? Our system is a cut to cut to your system so we can add a
25:21
MSCO core running data set for the front imaging if you want to do data set do running detection, okay So you can you can make a new learning model and added the system that is available But we have we have very flexible system But in this time that is just to support that ms. Cocoa and mascara CNN
25:43
Okay, so it's okay and okay. There was another one here, maybe Okay, okay. Okay, so assault other questions So I do like to say that for data collection
26:01
We also need your contribution So this is very that that's clear in this If there are no more questions, I will stop the session here