We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Validating the European Ground Motion Service: An Assessment of Measurement Point Density

00:00

Formal Metadata

Title
Validating the European Ground Motion Service: An Assessment of Measurement Point Density
Title of Series
Number of Parts
266
Author
License
CC Attribution 3.0 Germany:
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.
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
The European Ground Motion Service (EGMS) is a pioneering project that employs high-resolution ground deformation monitoring using Copernicus Sentinel-1 radar images. It's the first initiative of its kind and offers valuable insights into geohazards and human-induced deformations. This project aims to validate the EGMS product's spatial coverage and density of measurement points across twelve diverse sites in Europe, representing various regions and data processing entities. The validation process evaluates usability criteria such as completeness, consistency, and pointwise quality measures. Ensuring completeness and consistency is crucial for effective use, requiring alignment between data gaps and land cover classes susceptible to landscape variations. Pointwise quality measures, like temporal coherence and root-mean-square error, are essential in assessing the quality of EGMS PSI results. The validation includes twelve selected sites representing different regions, rural and urban areas, and various processing entities, using the Copernicus Land – Urban Atlas 2018 dataset. With 27 different land cover classes defined in Urban Atlas, the results are aggregated and presented for key categories like Artificial Surfaces, Forest, Agricultural Areas, Wetlands, and Water Bodies. Key performance indices (KPIs) are calculated to normalize density values for each service provider, facilitating outlier detection and ensuring consistent and accurate measurements across different land cover types. In conclusion, the EGMS dataset, as an open and freely available resource, holds immense potential for various applications, including geohazard assessment, environmental monitoring, and infrastructure management, particularly when integrated with free and open-source geospatial analysis software. The validation results presented here are crutial in ensuring the accuracy and reliability of the EGMS product, enabling further research and applications in geospatial analysis fields.
Service (economics)Electric dipole momentValidity (statistics)Computer animation
SummierbarkeitPoint (geometry)Programmer (hardware)State of matterSet (mathematics)Service (economics)Point (geometry)Computing platformMembrane keyboardBitRing (mathematics)Computer animation
Form (programming)Core dumpElectric currentProbability density functionTerm (mathematics)Complete metric spaceProduct (business)Formal verificationPopulation densityMeasurementPoint (geometry)Social classTerm (mathematics)Social classSurfaceArithmetic meanForestWebsiteMeasurementPoint (geometry)Product (business)Latent heatPopulation densityValidity (statistics)Artificial neural networkProjective planeAnalytic continuationObject (grammar)Complete metric spaceSet (mathematics)AreaTheoryComputer animation
Pairwise comparisonAlgorithmVector potentialMathematical analysisPopulation densityProduct (business)Image resolutionPolygonProgrammer (hardware)Point (geometry)Population densityAreaFrequencyBitAlgorithmWebsiteResultantMeasurementSolid geometryComputer animation
MeasurementWebsitePoint (geometry)Resultant
Artificial neural networkMIDIGreen's functionProbability density functionPopulation densityLocal GroupSocial classSurfaceOutlierWebsitePoint (geometry)ForestProbability distributionParameter (computer programming)Artificial neural networkSurfaceSocial classError messagePoint (geometry)MeasurementSoftware developerPopulation densityTemporal logicResultantFisher informationSquare numberParameter (computer programming)RootArithmetic meanComputer animationDiagram
Set (mathematics)Traffic reportingResultantPhase transitionWebsiteComputer animation
Programmer (hardware)Computer animation
Transcript: English(auto-generated)
Hi, everyone. My name is Amalia, and I will be presenting the work that we have done for the validation of the eDMS service. So I will start by explaining, first of all, what is eDMS.
It is the new service of Copernicus that it is basically a data set that is covering all the Copernicus membering states with ground deformation data. So basically, it's a huge data set of points that you can see how the ground is moving in all the participating
members of states of Copernicus. So here, for example, I'm showing you an example of the dashboard that has been recently gone live, and it is ready for use by anyone. And I have selected randomly some points in the city of Barcelona, Sagrada Familia,
just to capture your interest, that they have been building for so many years, and we see that it is moving a little bit down. So basically, everyone can enter the platform, the dashboard already, and check maybe their house if it is moving or not. So what we have been doing, we have been participating in a project
that the objective was to validate this huge data set that Copernicus has published. And the validation activity that we have been working on at Six Sense had us a goal to verify the completeness of the product in terms of spatial coverage and density of measurement points.
And to do that, we are using another product of Copernicus, an open product, which is the Urban Atlas classification of 2018. And if you're not aware of it here, so an example that they take sites in Europe, and they are making a classification, they're using 27 different classes, and they are separating it in, for example,
continuous urban fabric. Here again, we saw the example of Barcelona, that where we have green is a forest area, dark warm colors are urban fabric, and green are usually non-artificial surfaces. So what we do in this specific validation activity is to measure how many points fall in each of these classes
to ensure that we get consistent with the theory, meaning that in continuous urban fabric and artificial surfaces in general, we expect to get a lot of measurement points because the technology that is used to calculate those points in CER is working better in these areas. On the other hand, we don't expect to get many points,
for example, in forest areas, or coastal areas, or water bodies. So this has been our validation activity. In the paper that we're publishing, we are also covering a challenge that we faced during our work, which has been the overlapping bursts, because as the Sentinel-1 is scanning the Earth,
we have overlapping swaths that if we measure all the points from there, we might get higher density of points in areas that they have a higher frequency of overlaps. So we are explaining a bit how this algorithm works.
We have selected 12 different sites that include eight urban sites and four rural sites, and those are all representing equally all the member sites, so the result that we get, we can draw solid conclusions
about the coverage of measurement points. So here I show some preliminary results and how we are presenting them in the paper. So what we are doing is that we are calculating the measurement of points, the density of points, both for ascending and descending for each class,
and here we're making a classification between artificial surfaces and non-artificial surfaces, and we see that we get a much higher density of points for the classes of artificial surfaces. We are also using other quality parameters, which are the temporal coherence
and the root mean square error that can provide us even with more information about the quality of the measurement points that we have. And basically, this is only to say that we have been validating this huge dataset that is available for everyone. You can actually visit it here.
And currently, we're in the phase of validating all the results. In the paper, you can see some preliminary results, but soon enough, we're going to have the final reports available for everyone. And yeah, if you have any questions or if you potentially might use it in the future, you can contact me, and this is the website.
Thank you very much.