Disaster Management GIS in Action: Leveraging Open-Source Software for Rapid Response
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00:00
DISMADependent and independent variablesOperations researchBitGoodness of fitInformationData managementLecture/ConferenceComputer animation
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Operations researchTotal S.A.Event horizonSource codeVirtual memoryNatural numberBitDenial-of-service attackExtreme programmingNumberComputer animationMeeting/InterviewLecture/Conference
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Information managementGroup actionMappingComputing platformInformation managementReal-time operating systemOpen setOnline helpDecision theoryMappingLevel (video gaming)Projective planeHome pageComputer animation
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SkewnessData managementAnalytic setProjective planeTask (computing)Different (Kate Ryan album)MappingComputer animation
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Perturbation theoryMaxima and minimaTask (computing)Projective planeData management
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Event horizonCNNTotal S.A.Perturbation theoryEvent horizonNeuroinformatikMultiplication signInformationOpen setNatural numberMereologyOnline helpDecision theoryComputer animation
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Pressure volume diagramExecution unitBuildingComplete metric spaceForestCovering spaceCellular automatonImage resolutionFacebookIntegerView (database)Total S.A.Texture mappingStress (mechanics)Heat waveHexagonNumberState of matterComplete metric spaceHeat waveDecision theoryMultiplication signPopulation densityBuildingImage resolutionInformationAreaLevel (video gaming)MappingDegree (graph theory)Texture mappingOpen setDialectMereologyBitFacebookUniform resource locatorPrice indexOnline helpProcess (computing)Set (mathematics)Active contour modelRevision controlObject (grammar)Local ringDifferent (Kate Ryan album)MetreComputer animationLecture/Conference
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MappingInternet service providerProcess (computing)InformationForestComputer animation
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Boundary value problemWebsiteDecision theoryCartesian coordinate systemObject (grammar)Level (video gaming)State of matterMereologyPresentation of a groupInformation2 (number)Traffic reportingPlanningSet (mathematics)Moment (mathematics)Heat wavePredictabilityDependent and independent variablesWordSystem administratorConsistencyDifferent (Kate Ryan album)AreaCollaborationismBoundary value problemFeedbackEndliche ModelltheorieMappingReal-time operating systemOnline helpMultiplication signWebsiteBitActive contour modelAttribute grammarProper mapRight angleComputer animationLecture/Conference
23:32
Computer-assisted translationComputer animation
Transcript: English(auto-generated)
00:00
Good morning everybody, or it's bad to say. So let's talk a little bit about disasters. And so this is me. Like this is my contact information here. Oh, managed, just playing.
00:22
And so let's talk a little bit about disasters. So why? Why it is important not only to talk about disasters, but also to be somehow prepared and somehow influence the situation?
00:40
Just because we have a lot of them. As you can see here, we face rather quite drastic growth since the end of 1990s till 2023. As you can see, 2024 has just, like, not just, but began.
01:02
That's why we don't have full data. And as you can see, so the main, typically, we face floods, extreme weather conditions, droughts.
01:21
It's a little bit difficult to decide what is drought in general. And so we face not only the growth in natural disasters number, but also, as you can see,
01:41
we have a lot of people influenced by this disaster. And sometimes even more than 600 million people may be during the year, may face problems or affected
02:01
by natural disasters. I guess it's a quite huge number. And so the next question, who? And the answer is we. So Quanto is a geospatial data real-time risk management
02:24
company, helps many, many companies. But with this very, very product, we work with commentarian OpenStreetMap team to create, and now I will try to answer the last very
02:51
important questions, how? With help of disaster in India. And what is disaster in India?
03:02
So when a disaster occurs, for a humanitarian open street team, it's important to make a decision.
03:23
Is it necessary to ask the community to help with maps, or we have enough maps to make a decision on the local level? And so to answer this question, not in hours,
03:45
but in minutes, helps disaster in India. So this is the home page of disaster in India. You can see, like, oh, sorry.
04:01
Analytical panel disasters, our layers, and hot task manager projects. So on the map, you can see different task hot manager
04:32
projects, where people mapping in general. And so, first of all, to make this decision,
04:47
you have to know what has happened. And our event feed with disaster panel helps to answer this question.
05:02
So you can find information about what kind of natural disaster happened in this very part of the world in, like, today, yesterday, or even up to two years ago.
05:22
And then you also probably want to get a notification, because not every time you are near the computer with opened disaster in India. So you can get your notifications through Slack.
05:41
And then open disaster in India, and check what has happened and where. And so how many people, for example, affected by this disaster, and get some more information. So this information about disaster, and one more thing.
06:07
Yeah, so with this analytical panel, you can get an answer for your question. So how many people affected? And populated area which is affected by this disaster.
06:24
And the state, so to say, the state of the map. So what is the state of OpenStreetMap in this region? How many buildings are mapped, or how many roads
06:43
are mapped, and so on? And so to answer all these questions, help to answer the questions we prepared, be varied layers. So it helps to look at two indicators at the same time,
07:03
and to make a decision. So this Konta OpenStreet building completeness map. So on one side, we have population density. On the other side, we have a number of buildings
07:25
in this very area. And if there are a lot of population, but not many buildings on the map, so you get red hexagon.
07:45
And if everything is OK, and you have a lot of buildings, so you have green hexagon. So this is about, in general, the state of the map.
08:03
So I would say number of buildings and other objects that is mapped in OSM. Here, so OSM building completeness and OSM road
08:21
completeness. Sometimes it's not so when you make a decision, so how this disaster affect how many people affected with this disaster, you have to know where is this people.
08:41
And it's better to look for people when buildings are. And if you have buildings, probably you will have roads. And it's very important to know how many roads are mapped and how many buildings are mapped. And with the help of these two bivariate layers,
09:00
you can find the answer. So from the other side, it's very important to know how many people live on this very area. And to answer this question, we prepare counterpopulation data set.
09:22
It is based on different data sets from Facebook, from European Union, from Microsoft. We process them, prepare them, and get
09:43
counterpopulation data set. And now we have version five. Actually, the last release was on November 1, 2023. And we tried to update it at least once a year.
10:03
But sometimes we can do it a little bit faster. So this time, we know the issues with total population. It was funny because, for example, in Estonia, we get 1.5 million people.
10:20
But actually, in Estonia, we live a little bit less people, so to say, 1.3. And add a new location this time. And we have a resolution, 400 meters resolution for our counterpopulation data set.
10:43
Actually, when you ask people to start mapping, you probably want to know if there are a lot of people
11:00
and a strong local OSM community, which can help you map as fast as possible. And if they're local, obviously, they know more about the situation in the region. So OSM mapping activity, also our Bavaria player,
11:21
which can help to find out whether you have a lot of local mappers or not. Local mappers are marked with green hexagons here.
11:47
Also, sometimes, it's very important to know least edited and most viewed areas at the same time. So for example, if we have it, we
12:09
find out how many people visit this very part of the map during the last 30 days and show how long ago it
12:26
was updated. So there are a lot of people who visit this very map, and it was updated a long time ago.
12:41
It will mark with green. So probably, you need to update this map. And we can also talk a little bit about not only about disasters, but for example, nighttime heat wave risks. So this map shows that if there
13:04
are a lot of people living in a place where nighttime temperature stay above 25 degrees of Celsius, so they marked with green.
13:26
And it is considered to be difficult to live without air conditioning when you have nighttime temperature above 25 centigrade.
13:40
Also, we have, for example, counter sea level rise exposure. So it means we just count what will happen if, for example, all the ice in the world melt down. And so from, as you can see, Estonia also under risk.
14:09
Some Lithuania, Netherlands, Black Sea regions also. Also, we can help to find out whether fires happen somewhere
14:36
in the world. So actually, as far as I know, it
14:41
was quite difficult to find out if you are providers of such information in the world. But it's important, we have to perceive this data
15:02
because we need to find out if it's normal or not. This hot temperature is normal or not. For example, plants can produce a lot of heat, and it will be shown on the map as a fire.
15:23
But actually, it's not, just normal working process. And you also shall, for example, if it's wildfire, you shall know more information about whether it's like a forest or not. Also, we have such kind of administrative boundaries.
15:48
So you can choose, for example, a country or any part or region of this country and find out how many people live here, territory,
16:01
and this populated area, which has no OSM objects, and some more information, like state of the map, I should say.
16:23
Also, we work hard to improve our data sets. And you also can contribute to it. We have disaster ninja reports.
16:42
And for example, it would be good if you go to population inconsistencies, for example, and check your country or check your local community, whether it has proper data or not, and make correction by yourself with the help of data.
17:17
And so, actually, this is it.
17:23
Please visit our site, Contour.io. Please visit our disaster ninja. You will have probably some insights. And it would be great if you send us some feedback, because feedback makes us work better.
17:46
Thank you. Thanks so much, Vasily. I wanted to show something, actually, when I was seeing the presentation. I am following up the hurricane right now happening in Mexico.
18:01
This is in real time in the application with Finder. So what you are doing is really helpful to plan in advance also and how institutions can help their local communities to see how they can protect better. So this is hitting right now, Cozumel Island, and it will be hitting all the area in the Yucatan Peninsula. So thanks for the presentation.
18:21
Questions? I think he went first. You mentioned nighttime heatwave risk. Where do you get your weather or weather prediction data from?
18:45
And this is our GIS engineer who works actually with all these layers, and he will help me to answer the question. Yeah, maybe. Maybe I can answer this question. We have a collaboration with Probable Future. This is a company who developed models
19:02
to predict climate change and different weather situation. And we build our nighttime heatwave risk layer based on their prediction. Thank you for this nice presentation.
19:22
I was wondering about the population that you, so you have built this population based on the data that you mentioned. But is it even, because if I understand correctly, you covered globally. So is it even from one country to the other,
19:44
or there are differences in coverage? Because data might be different from one country to the other. And then also, which attributes do you have of this population?
20:00
Do you know where they work? So that, for example, if a disaster happens during the night or during the day, it's different. Thank you. So we have a population that is for the entire world, and sometimes it has inconsistencies. So we take also, for example, census for,
20:24
but census happened once in 10 years. And sometimes this data may be, let's say, not fully correct. But it's enough to make a decision on the global level,
20:44
not on the level of every community. And one, the second part, OK, just, Andrei, please.
21:23
One second. At this moment, there is no different version for daytime and nighttime. We have it in plants, and we made some investigation about how we can build it with existing data and which kind of data we should achieve to build it.
21:43
Now we use approach when we collect day population. For example, if you have some venue where people work at the day and there is no people at night, we collect it when you wish people.
22:04
Because when disaster happens, better to say that there is people that say there is no people, and they actually will be there. Thank you. We have time for one last question.
22:25
I know that ICRC is quite active on hot OSM, right? So like Red Cross and Red Crescent societies. And oftentimes, it's a bit hard to get financing in this kind of disaster response. So I was wondering how you managed to finance your work
22:45
and whether it's difficult or it's actually, is it partly based on donations, or how does it work? So we create this disaster in India for hot and support it.
23:02
So as a tool for them to make this decision. So actually, we do not make any decisions. But we provide this tool to help them and to manage local and world community
23:21
to contribute for OSM. All right. One quick question, and then we can go for lunch. OK. Thanks. Everybody wants.