Conference Paper

Handling Heterogeneous EO Datasets via the Web Coverage Processing Service


The deluge of EO imagery available for the scientific community, empowered by increasingly advanced cloud and grid computing capabilities, is giving rise to new paradigms for manipulating and exploring massive
datasets [HTT+ 09].
While new techniques for data segmentation and mining are getting more and more sophisticated [CVTBB14], at the very backend of the researcher’s workflow lies the extraction of the data from services. The Open Geospatial Consortium (OGC) provides a variety of open standards for serving data of different nature and source [Ree14].
For a proper scientific analysis, the coverage concept is fundamental for the researcher, in contrast with the concept of map for mere visual purposes. It provides HTTP access to lossless geospatial data to the user, with room for rich metadata determination [Bau10a], and n-dimensional spatio-temporal agglomerates [CMBB13].
The Web Coverage Service (WCS) and its companion Web Coverage Processing Service (WCPS) are the OGC standards for the access and control of coverages from a web service. While the former is essentially used to access the Big data to a specified region of interest, the latter offers a thorough syntax for some basic algebra and processing on a number of different data [Bau10b][CBMB14].
The WCPS can be a key tool for the management of heterogeneous but related coverages: data products show different spatial, temporal and spectral signatures; data analysts want to cross-compare different products for validation; modellers want to minimize the data download to retrieve meaningful predictors pushing all the possible preliminary data operations to the server side, preferably co-locating them onto a common grid.
Finally, thanks to the transactional extension of the WCS (WCS-T), a user can upload its own dataset and either share it with other co-researcher or refine its model via further analysis, all in the open web.
The presentation will analyze the potential of WCPS for the described scenario by means of a use case that will use MODIS MOD08, Copernicus MACC and ESA CCI aerosol total-column optical products to be presented at the NASA World Wind Europa Challenge.

[Bau10a] P. Baumann. GML application schema for coverages. OGC document, pages 09–146, 2010.
[Bau10b] Peter Baumann. The OGC web coverage processing service (WCPS) standard. Geoinformatica, 14(4):447–479, October 2010.
[CBMB14] P. Campalani, A. Beccati, S. Mantovani, and P. Baumann. Temporal analysis of atmospheric data using open standards. In 4th Symposium on Geospatial Databases And Location Based Services. ISPRS Technical Commission, May 2014. (accepted).
[CMBB13] P. Campalani, D. Misev, A. Beccati, and P. Baumann. Making time just another axis in geospatial services. In 20th International Symposium on Temporal Representation and Reasoning (TIME), Sep 2013.
[CVTBB14] Gustavo Camps-Valls, Devis Tuia, Lorenzo Bruzzone, and J Benediktsson. Advances in hyperspectral image classification: Earth monitoring with statistical learning methods. Signal Processing Magazine, IEEE, 31(1):45–54, 2014.
[HTT+ 09] Anthony JG Hey, Stewart Tansley, Kristin Michele Tolle, et al. The fourth paradigm: data-intensive scientific discovery. 2009.
[Ree14] Carl Reed. 14 ogc standards and geospatial big data. Big Data: Techniques and Technologies in Geoinformatics, page 279, 2014.


Piero Campalani, Simone Mantovani, Alan Beccati, Peter Baumann

Presenter Biography: 

2007/2009 : BSc/MSc in Electronic and Telecommunications Engineering at UNIFE (IT).
2012 : PhD in Engineering Sciences at UNIFE (IT) with the thesis "Geostatistical modelling of PM10 mass concentrations with satellite imagery from MODIS sensor".
[current] : PostDoc at the Large-scale Scientific Information Service (L-SIS) group at Jacobs University Bremen on the design and implementation of OGC services for spatio-temporal coverages with rasdaman Array DBMS.

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