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Implementation Of Standard Web Services For GOCE Data Exploitation

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Implementation Of Standard Web Services For GOCE Data Exploitation
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The European Space Agency (ESA) with the launch of the GOCE satellite in 2009 made it possible to study the Earth's gravitational field and estimate the geoid with unprecedented accuracy and resolution on a global scale. In the framework of the GOCE mission a group of experts from Politecnico di Milano, led by Professor Fernando Sansò, is also involved in order to collect, process and distribute data. Access to GOCE data, through common procedures and standard, can bring significant improvement in many fields of Earth sciences: for this reason it was decided to distribute the data using standard web services as specified by OGC (Open Geospatial Consortium). In this work first results of the development of a WPS (Web Processing Service) for spatio-temporal exploration and exploitation of GOCE and GEMMA (GOCE Exploitation for Moho Modeling and Applications) data is presented. The download query can be made for both global data and local data; in the latter case data can be dynamically interpolated from the WPS on the area and at the resolution defined by the user, or evaluated in correspondence of a set of sparse points provided by user. The GOCE service is implemented with free and open source software, GRASS GIS and pyWPS for WPS service and OpenLayers for the web interface. Furthermore the development of WMS and WCS services is on going; a WFS service, built using MapServer and to be used for the data distribution, will be added soon to improve the ASCII Grid and GeoTIFF formats that are currently available and also a new interpolation algorit based on spherical harmonics will be added too. The service is continuously updated from the point of view of the available data, the calculation procedures and data distribution.
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Transcript: English(auto-generated)
I'm Marco Negrete from Politecnico di Milano and from campus of Como, someone asked me about this, Politecnico di Milano is organized in like many subsidiaries in different town near Milan and so Como is one of this town, is in Nordo Milano near Swiss border, so
this is about me. About my presentation, the title is implementation of standard web service for ghost data exploitation. So first of all, a brief introduction about the ghost mission.
In 2009, European Space Agency launched the ghost satellite. The mission target was to study gravitational earth field and compute the global geoid. In 2011, started JAMA project, JAMA is for ghost exploitation for more modeling and applications.
The purpose of this project was to estimate the discontinuity surface between earth crust and mantle using ghost data and now the satellite still works but it is nearly at
the end, the fuel is finished so will fall down in two, three weeks I feel. But we have the data and we have to deliver this data from ghost satellite. We have two kinds of different data.
We have data along with different satellite orbits as observed from ghost. And then this data were processed and were organized in global scale grids at a resolution of 0.5 degree. So we have delivery above of this kind of data.
And to do that, we have two built service and this service should provide interpolation data in a new user defined grid. So the user defines extended and resolution and then we have to create a new grid for
the user. And other things, we have to do interpolation data matching with user defined sparse points. So the user have a set of points and then we have to compute the value in this set
of points. For this we use the global grid. And then other thing, we have computing of local grid using the data along the orbit
in a user defined period. So in this case, the user wanted to calculate our grid using the data along the orbit and not the data preprocessed in global grids.
Go ahead. To do this, we build a service. We build the web service following the open geospatial consortium standard. And so all these classical schema, the client, the user make a request to the server
in standard way and then the server says to the data and reply to the user with the results. So we built three different service, a web processing service, WVPS.
And in the service, we made three different process, named Ghost, Gemma, and H-Manipulator.
And then we build also WMS service and WCS service. So here you can see the address of our service and you can access.
Now I will tell about the different service that we have implemented. The Ghost service uses the grid data on a global scale. The data are gravitational potential and second radial derivatives.
These data are related to partial periods and to wall observation period. So we have one grid for each gradiometer recalibration and also we have one grid
data for all the observation period. We have two kinds of data. We have full data. This is the gravitational potential observed. And we have that we named anomalous data. In this case, the data are defined with respect to normal potential.
So you consider the contribution of ellipsoidal earth and then the anomalous data are the difference between the difference with respect to the normal potential.
This service makes that interpolation on a user-defined region. So take the global grid and then create a grid for the user.
The process, Gemma. Also Gemma uses the grid data on a global scale. In this case, we have many kinds of data, but in geometry I changed the upper sediments, medium sediments and so on.
These data are defined from the top of the surface to the bottom. And for each kind of this data, one or more layers are distributed. So for example, for bathymetry, we have a layer that describes the top bathymetry surface, a layer density, a layer for second radial derivatives, and a layer that describes
the bottom bathymetry surface. So when the user asks for bathymetry, we have to deliver both of these four layers.
And then Gemma process made data interpolation on a user-defined region, like Ghost process, and also made data interpolation on a user-defined sparse point.
These are our WPS service. We built the service with PyWPS and GRASS. We used VSURF IDV GRASS command to make grid interpolation, and we used VSURF BISPLINE
GRASS command to make sparse point interpolation. The data are delivered in two different formats, Azure Grid and GridTiff.
But I think it's possible to improve this output format. Then, this is the schema of our service, it's a classic schema for these cases.
The user can access to the service, use the browser, in this case I have to write the correct tool to make the request, or use our client WPS.
So we built also a WPS form to help user make easy requests. And then, one example, in this case if you use the browser, the user has to specify
in the urban address the name of the service, the process identifier, the layer, in this case bathymetry, the resolution, the bounding box.
So I have to type this string, and then the server replies with an XML file, and in this XML file we have a link to a tar file, and in this tar file we have all the layers
that the user requires. In this case we ask for bathymetry, and so we have these four layers that describe the four data for bathymetry, bottom surface, density, second derivatives, and the top surface. In this case the format is the RashiGrid format for the output.
Here you can see the WPS form that we built, and here it's easier for the user to make
a request because they have only to fill the form. So, indicate the process, the layer, the bounding box, the region, and the output format, and then submit the request and download the file.
So it's more easy. We have made also another process, in this case a Spheric Harmonics Interpolation Service.
This method is better for our purpose because the gravity field is an harmonic field, so it's better to interpolate with a Spheric Harmonics Interpolation. This process is built using a Spheric Harmonic Manipulator software.
This software has been developed by Politecnico di Milano Gross Research Group, and this is a command line software. We use this software as core to build our service.
The software is online, you can download it, but you use only your PC, so you use this as core to build our process online.
The service asks the user the coordinates of the region of interest, a time range, so the service tracks all the data in the user-specified range.
We use the PostgreSQL database to store the data, because we have more than 75 million of data, and then the service computes second derivatives from a given gravity model with the H-manipulator software, and then creates a grid using GRASS.
This command is almost finalized, I opted to come here with the service ready, but I have no time, I regret for that.
Now, going to the other two services that we built, we built also our WMS service and WCS service. Now we deliver only a few data, and the core of our project was the WPS service,
so the WMS, WCS was not so developed, it was less important. But also you can use this service to get data at the moment. Online the gravitational potential anomalies,
second radial derivative anomalies, related to the whole period of satellite observation. And the more data. And this is the usual schema for this kind of service,
so the user can assess the data with a browser like I said before, or with our one client, WCS, WMS, and then these two tools make the request to the server.
An example of a WMS service, you can see the address, the web address to our service, to our WMS service. And this is an example
about a request made with a browser. So the user has to specify all this data, bounding box, layers, and so on.
And then the server replies with an image, in this case a PNG image. More easier, if you use a client, WMS, like you did, you can navigate and explore the data in a classical way.
Like WMS, we have a WCS service, these are the addresses to our service, and it's very similar to WMS service, but in this case,
we don't deliver an image as output, but a geophile. Now, they are performance-available, are actually greater than a geotiff. Oh, it is.
This is an example of a query to WCS server, so it's very similar to WMS, but in this case, the server replies as a grid file. And then, now, this brings me to the end of my presentation.
Here you can see some addresses that explain in a general way this project. So, thank you.
Thanks for this presentation. I find it very interesting to use such kind of data and provide them. One particular technical question,
is there any particular reason why you are using the old WCS specification, which is from I believe 2003 or so, instead of the current one, which already has been issued in 2010?
No. Actually, this particular address that you have here would translate pretty much into WCS2 syntax, which is replacing a few keywords, so that wouldn't make a lot of fuss like this.
OK. But, honestly, the W... OK. This project started one year ago.
So, I worked but not full-time, so I made some things 12 months ago and then I improved something about the WPS. And the WCS is not a core, so I made it
so it stays this level. I have to improve. Yes? Yes. Thank you.
And then it runs and then it stays with your elsewhere. But if you want to step up,
we've got 10 minutes, so I hope he turns up. I presume you must have taken that phone to the section and something vanished and I don't know why you did it. Hello.
Hello.
OK.