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00:00
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01:01
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01:24
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04:05
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10:25
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11:40
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14:43
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15:01
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16:33
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23:20
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23:56
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Transcript: English(auto-generated)
00:07
OK, so I think I will start. It's the right time. Welcome to this presentation. My name is Michel Duchamp. I work for the Threeliz company in France.
00:20
And basically, we had people to use QGIS, PostgreSQL. And we have a web map publication app, which is called LizMap. And today, I will show you feedback on a solution based on the offline special server, which
00:45
is called Geopoppy, in the context of the forest fire defense. So let's talk about the stakeholders, data, and software used today. Vallabra is a French public institution. Their main mission is to help actors
01:04
to prevent and fight natural risks, like fires, floods. And so they test new technologies. They do some trainings, research. They share services and hardwares. And they work with partners in the French Mediterranean areas.
01:24
So that's some pictures. You can see firefighters and so on. A bit of history of the project. We will speak about a small topic in their missions.
01:42
But it's about the firefighting infrastructures, like water tankers, tracks, road tracks or forest tracks, watchtowers, and so on. And they have also standardized grids to be able to know where some actions must be taken.
02:04
So they share standardized grids. And they have, obviously, base layers, like photographic IL photos and digital television models and so on. They have done a lot of work to harmonize and centralize
02:21
the data between all the stakeholders, which means they have set up a list of layers to share. What are the names, the metadata, the ontology? What is it about? They agree on the data structure, like the fields, constraints, the types, everything.
02:42
You need to agree on your attribute tables and the geometry type. They have created common glossaries. They share the same way to describe the data. And they agreed also on the data styling, which
03:05
means symbology, the colors used. Because when you're in the field against the fire, you really need, if you work on an area in the frontier between two different administrative areas,
03:22
you really need to be quick to see in the map what is this object, this object. So you need to share how you will render the data in a map. The extent is the French Mediterranean areas. It's about around 100,000 square kilometers.
03:44
And it represents 200, but it depends on the data. Four vectors and 30 gigabytes for our stores. That's a print screen of the data.
04:01
So you can see some water tanks. You can see the tracks here. And the weird grid they use in the field to locate the different structures and to see where they have some codes with that.
04:22
Sorry. This is the main area, so the special extent of the project. They already use some software since some times. QGIS is the main GIS used in Vallabh, which is the organization I talked about.
04:43
But some actors also use different GIS solutions, like MapInfo, S3, or GeoConcept, which is a French GIS, very old one. And they use PostgreSQL to store and process data. They have an hosted server.
05:03
And they also use the application LizMap Web Client, which is made to publish web maps from QGIS. So I will really focus this presentation on this triptych. It's QGIS, PostgreSQL, and web publication with LizMap.
05:26
What is LizMap? Basically, you take your QGIS project. You send that to the server. And you have a web application which render a map based on the project properties and layers.
05:40
And it respects a lot of QGIS features, like attribute tables and so on. One of the key features for the Vallabh is the authentication and group rights management. So you can tell this map can be seen by these groups of users or not. These kind of users can edit the data or not and so on.
06:07
Some print screen about the solution. So that's the main page. You have a map in QGIS. You get it in LizMap. You can have more complex data.
06:22
This is one of the key features. You can edit data with forms based on QGIS forms. So you don't have to code your form. You just describe it in QGIS in the vector dialogue with combo boxes, check boxes. And you get that back inside LizMap.
06:41
So they use this kind of maps since three years. So they are very used to this web map solution. And they also have organized a PostgreSQL database to be able to share data and to do
07:06
some processing in the server. For example, they use Triggers Python services to send emails when somebody has modified data to the admin. And then when the data is validated,
07:22
you get an email back to tell you, OK, your data has been validated by the admin user. So they have a complete, it's not just a storage PostgreSQL. They use it with all the features you can expect from this kind of database.
07:44
The project objectives, they wanted to use this web map solutions, but offline. Because sometimes you have no internet connections when you go to the field, for example. And they ask us to help us to test
08:05
this solution in the field. So they needed GIS features like the same we talked about, like data editing, base layers, attributable visualizations. And they needed the tool to be based on QGIS projects
08:21
to simplify the workflow. They didn't want to do some more styling for another tool. They did not want to recreate web forms from XML. I don't know what. And they also needed to have some PostgreSQL views offline
08:41
to be able to see some buffers or some data special analyses that you can do with SQL views or triggers and things like that. They have no internet connections in the field. In France, you can have internet connection.
09:02
But when you're a firefighter, you really need to have a tool which can work without internet. So one of the other expectations was
09:22
they needed to be able to synchronize the data when they get back from the field. So they didn't want to use the copy-paste and manual checking of the data afterwards.
09:40
They asked us to try to help them to synchronize it easily. So they have studied some solutions, like Windows tablets or Android tablets. Can they use a simple but powerful data collection tool,
10:03
like Open Data Kit or QGIS-based mobile solutions? They preferred the latter. And then they tried Qfield, but did not like it for some reason. And I haven't spoken enough with them for that. But they told me, we want to try Geopoppy.
10:23
So what is Geopoppy? Geopoppy has been around since, I think, three years. Basically, it's a special server in the box. Like you take a Raspberry Pi with battery,
10:40
and you put a LISMAP web client, QGIS server, PostgreSQL, and an FTP server inside a Raspberry Pi. Then you can have an offline web server solution. The main concept of that is Julien Anselin from a research center in France.
11:01
And he based the work on Docker, how do you update the softwares, and how do you package all the different softwares inside this box. It is already used by researchers,
11:21
like in France, and also for some projects in Africa, in Africa, to collect rain deforestation data, and in Madagascar, too, for another project.
11:41
So this is a Raspberry Pi, very naked one. And when you use it, so you put QGIS server, you put PostgreSQL and LISMAP, and then you connect with Wi-Fi, with your smartphone, tablet, or computer, you connect to it.
12:02
So that's a bit of another picture, which shows it's not very packaged. So you need a bag to put that. I think it's a little bit like do it yourself, look and feel. So that's some disadvantages of this tool.
12:24
It's tied to web browser capabilities, because you use a web browser like Firefox or another one to see the map. So you need to use the geolocation API. You cannot really save files locally, et cetera.
12:42
And the LISMAP web client application is responsive, but it's not dedicated to field data collection. So you have some improvements that can be made. And one of the problems in Android OS is you cannot connect to 3G, 4G, or 5G, and to the Wi-Fi
13:07
at the same time. So it's offline with the geolocation, and you will use the LISMAP and the PostgreSQL. And you cannot do that and be connected to another network to gather some external data.
13:24
But you have some advantages for them. It's open source. It's affordable, because the Raspberry Pi is not very expensive. You work offline, and you have no new software. So you use QGIS, QGIS server, LISMAP, and PostgreSQL.
13:42
For them, it's a known workflow, because they used that before to publish the web maps and data to the central server. It's PostgreSQL powered, so you can use all the good stuff in PostgreSQL. You can use all the features of QGIS to style your layers
14:02
and to show some data. And you can also use the authentication and other LISMAP features. Some pictures of the LISMAP interface.
14:22
So you can see data on objects. You can start editing data in the field. And so for them, it was OK, because they use LISMAP in the desktop when they're working, and they can use the same tool in the field.
14:45
They needed, when you work in the field offline, you need to package the data to be able to go to the field. And then you need to go back and synchronize the data. So for that, they asked us to develop some synchronization
15:05
meter. So we wanted a very, very small PostgreSQL-based solution. So we just used unique IDs in every table. And we developed some tools based on QGIS processing
15:23
to run the queries to be able to synchronize the data. I won't spend time to present this, because it will be a bit long. But the main goal is to have a log with audit of every actions made in the PostgreSQL
15:43
server for every tables. And then you can replay this log, because you know which device has created or updated the data. And you have all the synchronization data,
16:01
metadata in the central server. So basically, in QGIS desktop, you have a processing algorithm. And you can find the same algorithm in the LISMAP WPS module. So you can use it in QGIS and in LISMAP
16:22
with your smartphone or a tablet in the field. It's the same algorithm which does the job. And as a conclusion, I will give some feedback. It works. So some people are very excited about this solution,
16:43
because it's low cost. It's a full powered special server based on open source software, QGIS, PostgreSQL, LISMAP. But I think it's also a bit complicated for users, compared to some other solution based on QGIS, like Qfield.
17:03
Or the last one is input, which is a great tool, too. But I think the main problem here is the fact that you have others to carry, like the Raspberry Pi and the battery. And if we want to make it more user friendly,
17:23
there is a solution ongoing, developed by Julien Anselin. You just take all the features. You put that on your Android, which means you don't need your Raspberry Pi. All the servers are packaged to run on your phone,
17:43
on your tablet. So you just need your smartphone, your tablet, and you will be able to have the same thing, PostgreSQL, which is running on Android now. And so I think that can be a great solution. But you really need to evaluate
18:01
the balance to balance between the complexity of your needs. Do you need complex PostgreSQL, QGIS features, or not to choose to use that solution? But with PostgreSQL running on Android, you can also use Qfield or input
18:20
to speak with this data storage. Some links on Geopopy and PostgreSQL audit tool, PQGIS server based on QGIS processing algorithm, and how do you on LISMAP web client.
18:44
I will thank you for your attention. I think he is right on time. If you have some questions.
19:09
Only one. Does it work? Only one question, actually. Basically, as I understand, the first thing you had to do in this project was to make some kind of atlas of fire equipment
19:22
in the field. Then you can, and you could, your first step was probably to get the, so all the shareholders agreed on this at some level about the science and everything. And I'm asking, is this atlas also possible
19:41
to get in some kind of paper form or PDF or something like that? Sure. I talked about it in the history. They have already make all this stuff. They have paper atlases. They don't rely on Geopopy for emergency situations.
20:05
It's only to go to the field, see if the water tanks is OK or not, change some attributes. So it's not the only solution they use. They really reuse QGIs in desktop and PostgreSQL
20:22
to centralize and share all the data. But they have paper. They have other tools, like proprietary tools also to deal with the data. Geopopy is like a proof of concept. They really want to know if they can use it in the field or not. And they were able to use it, but we
20:42
have some progress to make. Did you test how many clients can hang off the Raspberry Pi and maintain performance? I have some feedback by Julien Slant.
21:04
He told me like five people can use the Raspberry Pi. So that's OK because you have the Raspberry Pi in the backpack and you have different people in the same area that can gather some data. So for deforestation data, for biology observation,
21:22
like if you see a bird or you see something, you can work together with the same database. But really, it won't scale.
21:41
If you're 10 or 20 people in the same Raspberry Pi, it won't. But if you have an Android solution, you can have as many server as you have devices. That will be the solution.
22:02
Hi. Sorry. Just one question. I didn't get it. Did you sell that? Or is it open source? And how do you sell it like with the Raspberry Pi and the software? And what is the education of that users? How do you educate the users for that?
22:24
OK, so we do open source. So everything is open source. The synchronization, PostgreSQL scripts is not yet published, but there will be. What we did for this project is just
22:42
buy the job, the Raspberry Pi, and all the tablets for Valab, because it was easier for them. But we just sell them the same price. So we don't earn money with this project. It's a side project of Thrillies. But it's mainly used by researchers and by NGO,
23:06
because you can just grab all the sources, the documentation. You have the link at the end of the presentation. And you have a good documentation
23:21
of how to get the image, put that on your Raspberry Pi, and then use it. So you can test it with no problem. You can already test it on Android. There is a GitHub describing how to do that. So I will just try to.
23:45
So that's data of flower, like poppy sites in the field. So it's open source. Of course, it's open source. There is nothing closed.
24:08
No more questions? OK, so thank you very much. Thank you very much.