Digital Earth Pacific
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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. | |
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00:00
CubeOpen setDigital signalSpeech synthesisDigitizingGeometryDivision (mathematics)Projective planeWeb 2.0Computer animation
00:27
Self-organizationPrincipal idealDivision (mathematics)Food energyInternet service providerService (economics)MathematicsNatural numberReduction of orderWater vaporArchaeological field surveyBoundary value problemSelf-organizationDivision (mathematics)AreaFood energyArchaeological field surveyMultiplication signBoundary value problemSoftware developerPhysical systemSpacetimeComputer animation
01:17
Digital signalIntegrated development environmentPhysical systemState of matterContext awarenessInformationDecision theoryInformation securityDependent and independent variablesData recoveryField (computer science)Vector potentialProduct (business)Strategy gameOrder (biology)Digital signalProduct (business)Conservation lawIntegrated development environmentDecision theoryProjective planeSatelliteDependent and independent variablesOperator (mathematics)Information securitySoftware developerMathematicsVector potentialComputer animation
02:26
ImplementationProduct (business)Personal digital assistantPlanningPrototypeChannel capacityService (economics)Digital signalPhase transitionLocal GroupSatelliteGeometryAddress spaceCubeSeries (mathematics)Decision theorySystem identificationFeedbackFunction (mathematics)Computer programmingProduct (business)Subject indexingUniverse (mathematics)Projective planeNumberPrototypeRange (statistics)CASE <Informatik>Template (C++)Instance (computer science)Musical ensembleObject (grammar)Software developerLine (geometry)Data modelChemical equationComputer animation
04:56
Digital signalMathematicsFocus (optics)Water vaporMathematicsChainWater vaporRight angleDenial-of-service attackFocus (optics)Computer animation
05:17
FrequencySatelliteMathematical analysisDecision theoryContinuous functionPoint cloudMotion captureProcess (computing)Scale (map)Band matrixInternetworkingTerm (mathematics)Strategy gameOpen setScripting languageMultiplicationSpectrum (functional analysis)Image resolutionCycle (graph theory)PixelDiscrete element methodWater vaporCubeContext awarenessWärmestrahlungDigital signalMusical ensembleMathematical analysisFormal languageBand matrixMoment (mathematics)Projective planeCentralizer and normalizerInternetworkingLaptopOpen setDirection (geometry)Point cloudContext awarenessTesselationFacebookIntegrated development environmentExistenceRepresentation (politics)Fitness functionComputer animation
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Numerical digitAreaFeld <Mathematik>Point cloudMultiplication signComputer animation
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Mathematical analysisConsistencyDigital signalUsabilityChief information officerLevel (video gaming)Multiplication signComputer animation
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Point cloudCubeAsynchronous Transfer ModeDigital signalMathematical analysisTube (container)Computer animation
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Denial-of-service attackMathematicsDigital signalFrequencySoftware testingLogic gateEquivalence relationConsistencyCartesian coordinate systemSpeciesMereologyQuicksortCovering spaceComputer animation
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MathematicsDigital signalCovering spaceInterior (topology)LengthMultiplication signCovering spaceDenial-of-service attackComputer animation
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MathematicsWater vaporNumerical digitDenial-of-service attackBuildingProduct (business)Extension (kinesiology)AreaGoodness of fitDependent and independent variablesWater vaporDenial-of-service attackComputer animation
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Digital signalGroup actionLimit (category theory)AreaStrategy gameMetreComputer animation
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Mathematical analysisMathematicsDigital signalGoogle EarthMathematical analysisFreezingChainPhysical systemSet (mathematics)Endliche ModelltheorieImage resolutionMultiplication signData acquisitionGauge theoryResultantComputer animation
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Water vaporSubject indexingOrganic computingDigital object identifierSubject indexingVisualization (computer graphics)AreaRhombusProjective planeCountingWater vaporComputer animation
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Digital signalData structureMathematicsProjective planeAreaCubeVaporLocal ringStrategy gameIdentifiabilityComputer animation
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Alpha (investment)Revision controlPrototypeRWE DeaPersonal digital assistantProduct (business)CubeDigital signalOpen setPrice indexVector potentialDenial-of-service attackDivision (mathematics)Food energyFormal languageSoftwareCubeDigitizingProduct (business)Software testingSubject indexingDecision theoryMoment (mathematics)Inductive reasoningNumberRevision controlGoodness of fitCASE <Informatik>Vector potentialLaptopOpen setAlpha (investment)Different (Kate Ryan album)MappingDampingGroup actionPower (physics)Centralizer and normalizerPoint cloudKey (cryptography)SpacetimeComputer animation
13:59
Meeting/Interview
Transcript: English(auto-generated)
00:03
Hello my name is Sachin and I work for the geoscience and geometrical division of the Pacific committee based in the Fiji Islands. Thank you for this opportunity to allow me to talk about our digital lab best speaking initiative which is derived from the existing
00:21
digital lab Africa and digital lab Australia projects. So to start off some background, what is SPC? SPC is the principal scientific and technical organization supporting sustainable development for our green six member countries in the Pacific Islands and the division that I work for the geoscience energy maritime division works in diverse areas
00:45
such as my time transport boundaries also equals to geoscience disaster extraction renewable energy and climate change. And as you would note most of these work areas has the potential to benefit widely from the on this ecosystem because the pandemic we are not
01:08
able to deploy teams on the ground on the day clean surveys so a lot of work can be done remotely using a chemical spatial data. So what is digital lab best week? The best week
01:21
project aims to support the development of operational air conservation infrastructure that will take decades worth of openly accessible satellite data and remote sense data able to inform our member countries around challenges such as climate change, food security and
01:43
disasters. So we hope the solution will help us understand our environment and better prepare us for challenges such as sea level rise, disaster preparedness response, and also look at issues such as crop yield and potential impacts for wildlife change. So we hope that
02:10
this product will empower our leaders and give them ready to use decision-making products in order for them to make better decisions around sustainable development and fulfill their SDG
02:24
requirements. So the project as I said is quite new we just started earlier this year in March and over the last few months we have mostly been engaged in the stakeholder engagement
02:41
and we have engaged a wide range of stakeholders to ensure that the product will be fit for purpose and the solutions and products that are derived from DEP will meet the development goals of our countries. So as of this month we have done a number of workshops with our country stakeholders
03:06
and developing a roadmap based on their needs and on the technical side we also put in some effort into putting up a prototype for ODC for two-part templates
03:21
mostly focused on interesting structural data and making products on that. Going forward based on the output from the prototype we will be developing some early wins demonstrating products for the countries and then based on the feedback we'll be doing a business case
03:42
which will inform how the project goes forward in the future. So the current objectives the last six months have been to understand the needs and priorities of our countries, look at some of the early win cases that we can tackle this year and what are the immediate needs.
04:05
We are also ingesting indexing data at ODC for a couple of countries and building some products and all of this will fit into the business case going forward. So SPC is not working in isolation for this we have engaged with the governments
04:23
and the relevant ministries of four countries. Two of them are welcoming talents such as 3G and Vanuatu. The other two are atoll talents such as muscle support. As you would know the challenges around atolls is different from lines of work in the balance. We have also
04:43
involved academia with our university, University of South Pacific along with the technical agencies and oversight agencies such as CIOs, GA, GEO and more. So the five countries that we're working on right now is Vanuatu and Fiji and the initial focus for them are mostly
05:04
around crop yield, agricultural monitoring, flooding, river extraction, coastal change and radar based deforestation and water change detection. So a common issue that we have in the
05:21
best fit is that people do not understand that we have a lot of open data. We also have data for the best fit. The misconception is that we do not have data for the best fit. So a quick analysis by Central Sec shows that we have terabytes of data over the last decade for the region. However, the challenge that we face is that this data is underutilized for
05:44
the prospects and also for the season making because of lack of computing infrastructure, internet infrastructure. It's not feasible to download gigabytes of tiles and GIS environment and do anything on top of that because of the bandwidth restrictions. And also there's a lot
06:02
of awareness that this data exists. So there's no investment in long-term representation. The other big challenge on the technical side is that we face the issue of cloud cover. We have very high cloud cover, especially for smaller atolls and islands. So
06:23
at the moment we are focused on bench set eight and central two and of course central one. So central one in greater data is of particular interest to us because it will counter the cloud cover that we face. Just to give an example of how much of
06:42
cloud cover is, you can see that for a particular area in Vanuatu, for both central two and land set eight, we usually take them at the same time. There's lots of clouds and how to actually see the roads, how the agriculture feels easily, whereas with central one, we don't have to worry about cloud cover.
07:06
And this is done by Dr Brian Keeler from CIMOS so that for the same country in 2020, there's about six months of data issue for unuseful data for land set eight because of cloud cover and possibly to take up to four months. The issue is compounded when you go
07:23
down to atoll levels for some of the smaller airline islands such as Marsils and Tonga, the data is entirely essential for the year. So our central one is always consistent for us and we can use it. So henceforth, we have received data from CIOs
07:46
from Peron Sabukin, COG optimized radar data for S1, for Fiji and Vanuatu. And these have currently been adjusted to our pilot tubes for which we are tested.
08:05
So what are some of the applications that we can use using the central one data and also the land set central two data? Like I said, one of the major requirements for two part countries are agriculture monitoring. So this is a quick example of Suga Canyon in Fiji,
08:24
it's sort of a primary export and using RDI, we're able to detect the yield of the gate and you can see it's consistent with the harvesting period to October. And we want to extend this methodology to other things such as
08:46
species detection and also monitoring tests. Another quick example would be land cover detection using NPDI and EPI using Li-10S2. So we can look at land cover land use detection
09:06
over a period of time. Another one is water pollution detection and flooding. Flooding is a major issue for our urban areas, especially countries, vocational camps. So this is a very good product for our disaster response team
09:26
to see the extent of flood and the impact they would have on buildings. Illegal fishing, we did some experimentation in Vanuatu of using SAR data for fishing vessel
09:42
detection. The limitation we faced was that we were able to detect vessels easily, less than 40 meters, so more research is required in this area. We use S1 or LS data to have a strategy for detecting illegal fishing boats.
10:06
Again, a common requirement that we get is coastal chain detection. So we're able to do that using the S2 and L8. However, one of the requirements for doing this kind of analysis
10:21
is up-to-date time elevation data. And sometimes it's not possible to have time gauges deployed in all the places we want to be discovered by analysis. And the global models are two high-resolution, of course. Most of them are really good results. So it's another example why in situ deployments of instruments is also important to validate
10:47
some of the acquisition data sets, such as deployment of time gauges. And you can see on the south side of the island, the settlement there of about 80 people
11:02
have been detected by sea level rise over the last five, six years. Water quality is again, as you see, there's atolls and islands, pretty similar in counts. So we want to use the indexes that are available to us via the sea
11:25
to do water quality visualization, to detect nitrates, chlorophyll, water color, and sediments across impacted areas. Another project that we are trying to retrofit into ODC is the illegal vapor gravel extraction monitoring. So we're trying to use
11:47
metallurgy such as NPDI, EVI, and water quality extraction to monitor local areas or unidentified areas to see what the impacts of illegal reflux taxonomies, and then also hopefully implement a long-term work strategy around
12:05
this arching today. So what's the status of the pilot cube at the moment? We have deployed the initial vessel with the Landsat and Central 2 data index from 2014 to 2015. We have received
12:23
the SAR data, S1 data from SEOS. So this is currently the indexing to the cube for Fiji and Vanuatu. That was all of the islands. We have equipped it with the EEA, not books and examples, and we're trying to evolve them for the different use cases for
12:43
Fiji and Vanuatu. So we don't have to start from scratch and we just take the lessons learned and the production will be dropped in two key power needs. We are not expecting our leaders and our decision makers to use the notebooks as is, but we'll just make the products be an interesting space for the infrastructure
13:04
they have deployed within the countries such as Vanuatu, which is on Geonord, and the alpha deployment is being made available online and digital like testing the cloud. So to summarize, we are quite confident that the ODC ecosystem and the Central 1 data in
13:25
particular has very high potential for a number of use cases in the past week. And then it can make, enable our leaders to make really good decisions on forestry, agriculture, fishing, landowner training, urban deformation, and also respond to some of our disasters such as
13:45
coal and gas, and that group. Thank you.