Land of 60000 zoning plans - QGIS to the rescue!
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| Lizenz | CC-Namensnennung 3.0 Deutschland: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen. | |
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00:00
SoftwareKanalkapazitätOpen SourceGebäude <Mathematik>SpeicherabzugProgrammierumgebungInformationProzessautomationAnalysisRandwertStrom <Mathematik>ElementargeometrieFehlermeldungAttributierte GrammatikStreuungFormation <Mathematik>DifferenteMaßerweiterungSelbst organisierendes SystemStandardabweichungTopologieBildgebendes VerfahrenElement <Gruppentheorie>Open SourceBeobachtungsstudieSystemplattformInterface <Schaltung>BenutzerbeteiligungKartesische KoordinatenStreuungSpezielle unitäre GruppeGruppenoperationRechenschieberValiditätZentralisatorFehlermeldungProzessautomationEnergiedichteDatenbankFamilie <Mathematik>Nichtlinearer OperatorKlasse <Mathematik>Basis <Mathematik>MereologieMAPVollständiger VerbandAnalysisWhiteboardProjektive GeometrieIntegriertes InformationssystemHardwareEin-AusgabeMinkowski-MetrikTelekommunikationOrdnung <Mathematik>Service providerServerProgrammierumgebungElementargeometrieSoftwareGebäude <Mathematik>WellenpaketTypentheorieGenerizitätCASE <Informatik>CADZweiRelativitätstheorieStrategisches SpielInformationMigration <Informatik>DatenfeldDienst <Informatik>LastSpeicherabzugElektronisches ForumProgrammierungStellenringPolygonFontPixelShape <Informatik>CachingEndliche ModelltheorieBitComputeranimation
09:39
Singuläres IntegralElementargeometrieMengentheoretische TopologieLoopPolygonKategorie <Mathematik>DigitalisierungValiditätMittelwertGruppenoperationFormation <Mathematik>ElementargeometrieProjektive GeometrieResultanteMultiplikationsoperatorKlasse <Mathematik>VorhersagbarkeitFehlermeldungTypentheorieSchlussregelDifferenteAttributierte GrammatikEinfügungsdämpfungFortsetzung <Mathematik>Dreiecksfreier GraphSpeicherabzugTopologieDelisches ProblemRechter WinkelTotal <Mathematik>MAPProgrammbibliothekDienst <Informatik>VideokonferenzBitCASE <Informatik>Arithmetische FolgeMereologieZeiger <Informatik>RechenwerkDatenbankInverser LimesEntscheidungstheorieSoftwareentwicklerDiophantische GeometrieStreuungDatenfeldInformationPolygonTermTrennschärfe <Statistik>Produkt <Mathematik>TabelleGenerizitätPhasenumwandlungSpielkonsoleComputeranimation
Transkript: Englisch(automatisch erzeugt)
00:23
Can you get the microphone? Can you get the microphone? Yes. Okay, let's get the microphone. Just a little bit of an overview for LZD.
00:40
We were founded on 2012. And we are now working with some of the companies. And what we do, we are consulting for the post-4G issues for different companies. And we also build software, QGIS Bunnies, and also QGIS Core.
01:09
We also train training companies, and we have over 100 customers, and we host over 1000 people. We do QGIS, PostGIS, GeoServer, GeoGIS Python, and so forth, all kinds of other trainings.
01:32
We also support our customers who use Post4G. We have online support service for our customers.
01:43
And what we are talking about today is regarding to this kind of a public project that we executed at FIELDS. It was funded by the Ministry of Employment and made all of it by the FIELDS Environment Institute.
02:02
And the aim of this project is to build an environment information system that collects, we try to collect, all land use and building data provided to different municipalities in the industry.
02:21
And this project is for both of us. We are working with the pilot, Scott Lasker, who is here. And he is now continuing for all years until 2013. What we did on this other project, or the aim of this project was to collect the external
02:46
data for our labs in this South Southern region, in Finland, from their municipalities. And also that's a kind of reference to all of this GIS data.
03:05
And it was quite an operation because in this region we have over 20 different municipalities, and the data was quite scattered all over.
03:22
And how it was scattered, follow the next slide. There was a big migration process for the data collection and analysis, and putting the data together. It was mostly done by the industry.
03:41
And now we are done with another project, and the second group of people continues with the next season in Finland, and now the next season is down for a whole year or so. So I think that's going to be the second group, and now we continue with the second group of people for the next season.
04:08
So, when we started to collect the data from the municipalities, we already knew that the data would be quite scattered. There were quite a lot of challenges to tackle.
04:21
The first, when we went through the data, it was in quite many forms. Quite a few, yet some of the first 14 applications, can't go away. So we have the geobags type of points, also shape file,
04:44
ENG, different kind of cache platforms, DOG, DXF, also cloud points, EF, image sheets with that, and also web fonts like VNS.
05:04
And, like you can see from the images we got from the data, it was quite a problem overall. A lot of the data, I think, matters quite a lot in the data. Also, it's important that it's being managed.
05:24
And also, there were quite a lot of supporters here, mostly related to the CAD programs, all the data that was done in the CAD programs.
05:41
And they mostly included the forum design. Even though the topic said that a few GIS came to rest, we had quite a big process of automation. The whole processing data first, and then it came to the few GIS for manual work.
06:07
And we had quite a complicated, easy algorithm, which started as a notepad for the OS X-RAC transport and load process. And now, because I try to include as much as possible in GIS,
06:26
I also use most of the local transport process for the automation process we did. And there was a program called geobags, which we used as an extension in Python, and we include and process the geobags, so that's another problem.
06:46
Couple of strings, although our operators released a third strategy with the validity, we'll check with voice error relatives for the data.
07:05
Also, how do we actually evaluate the percentage that is matching the data with the other regional databases?
07:21
And we try to match at least 98% accuracy with that. And it gave us some percentage with automation code, in the worst case it was close to 50% that speaks, and in the most best cases 99% some percentages.
07:45
And, for example, the main value is the operation that, if we have a lot of overlaps, or database resources, or data with generic errors,
08:01
it tries to make data to a simple multiple layer, or if there are a lot of overlapping layers, it tries to create a generic information that you can choose of which layer or if you want to go all the way to layers, you can do that.
08:24
And the other thing that came as a problem was tolerance, how to match the order values, that we had a reference data, that we tried to validate the percentage of correct data,
08:46
and we used the different tolerance values, which is usually in the layers, or we can use the pixel values, we can try to match the model size, we can use the tolerance, we can match the pixel, one pixel per size.
09:04
But we faced that, because the data from the different user values was quite scattered, the data was in the tolerance systems, we couldn't use the same tolerance, so we had to private the tolerance values from the different data sources,
09:21
from different use values, so it wasn't that seething to the tolerance value. Also, these other sources created quite a lot of these remove pain claims, that if you had a data source called Polygon for one week's time, it might have had smaller polygon nodes, like the one with the values of those,
09:47
we thought pain claims had to be removed. And there's an example on using housing, that when we did the geometry,
10:01
there were 852 polygons in total, and we gave 300 of these to 2002 layers, so the data was quite corrupted that way, and had to be fixed. Okay then, I'm changing the plot, I guess the main part was the UTIS,
10:23
which was mainly to process the quality experiences, and I wrote that what the ICE can see, some UTIS tool will probably do, and from the left side we have the data from one utility,
10:45
which doesn't have a field code, it all shows the coordinates, and on the right side, it's created one simple geometry check, I think I put it on the check,
11:01
just to check if the polygons next to each other or not, so it usually gives quite a lot of geometry errors in this regard. So, a couple of ways,
11:22
in the ETL process, you can try to automate, and you can try to do solutions, but in that way also, when you move your tool, and we actually developed an ETL process to give you the use of the data separately, and then it's the quality console on the UTIS side,
11:47
and the results were quite scattered, the error values, most of them, and obviously there are all UTIS tools,
12:01
something might be familiar to you, and I think that, you know, they probably have used all these tools we have, congratulations, and I hope that from this, somebody can pick up some tools to check out that,
12:22
to test your data from the topology of the checker pairs. A couple of very interesting tools, technology, knowledge entity, generic checker, topology checker, and you can fix your case, and you have the,
12:42
if you have real networks, and I would say that there are a couple of practical differences that you can, you can turn to try to fix the data. Also, I tried to find suitable,
13:01
suitable tools from the compress, and also from the GDA library, and that was quite a fun skill, so if somebody has some other suggestions for their problems, who is going to have some of these? Just give me a note of that.
13:22
Would like to try those out. And eventually I would say that after the ETL process, and we had quite a lot of work,
13:43
or had to try to find a lot of different tools to check out what, or how well these tools, these leaders, finalize these geometry errors,
14:02
which means that's desirable, 98% of the way it's possible. And to conclude, with also the introduction of all the leaders within these projects, would be the general assumption that there should be multiple of all of these processes,
14:26
because they don't always apply to all of them. And in these kind of processes, because now it's,
14:40
even though I said in the beginning that the process will be executed during the next seven years, so as in 2030, then there might be some, it just inspires other governments to go almost on on recent design. So we find that there's quite a lot of scattered information
15:03
and the lack of data within the different municipalities that we can't establish, we can't build any part of this process within the ETL, and for the following different regions,
15:20
we are more mature about that, a little bit in terms of region, we face similar problems, we can't believe in something else also. So the question came to my mind, and it gets grasped mentally, let's say, now we are dealing with,
15:40
we are dealing with one municipality, and municipalities vary from the size of someone else, and in Finland, I would say the average number of a municipality would be something between 100,000 and 500,000 people,
16:02
different volunteers to go through, and I think that's, even though it could be 1,000, there could be quite a lot of work to go through for all the two persons, and many of these classes, either QG, I guess.
16:22
So in this class, the other person would be the accuracy, that the other person's process is always a compromise process, that would be the reasonable accuracy for this final launch,
16:41
or the final legacy, and in our case, I think it would be quite a high, I guess we want to communicate the person's accuracy with the data, and if we just put it a little down, then I would say that it's more simple, or a lot of the processes,
17:00
you can tweak the little bits, you've got a couple of people who are used to those, so you try to try to prove them, check if the quality check would be close to 90, 90% or something like that, and then see if you have still money left, or a workforce to do, to go through a manual way for the final check phase.
17:28
For the following year, so now for the normal process, we start with the next reason, that's going on the product for the following year, we're going to do a little bit of tweak for the install process,
17:44
and try to find a couple of these compromised ways to try to find the good way, or try to find the mistakes that are going to be, or handful of the processes that we're trying to hold in the group, would be to reach the desirable accuracy with the final data.
18:05
And when it comes to money, my work table will be the UGIS process, so I have planned, or I will probably do this kind of work for the booth, for the experience selection of the tools,
18:21
or for the previous dimensions, these are the tools to build up the work for the booths, to go through the database of these different tools, and if there's a desirable percentage value
18:43
of all the data that it wants, then it goes through the value, it's not desirable, then it goes back to the booth, and you just take the tool, and then you run it through it, you run all the process throughout, so it's a desirable percentage of the data accuracy.