Volume II-4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4, 9-14, 2014
https://doi.org/10.5194/isprsannals-II-4-9-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-4, 9-14, 2014
https://doi.org/10.5194/isprsannals-II-4-9-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  23 Apr 2014

23 Apr 2014

Geospatial web services for limnological data: a case study of sensor observation service for ecological observations

C. Arias Muñoz1, A. Oggioni2, and M. A. Brovelli1 C. Arias Muñoz et al.
  • 1Department of Civil and Environmental Engineering DICA Milan Polytechnic, Como Campus, Italy
  • 2Post-Doc Researcher National Research Council – CNR, Institute for Electromagnetic Sensing of the Environment – IREA, Italy

Keywords: Sensor Observation Service, limnological data, Lake Maggiore, Geospatial Web Services, long time data series

Abstract. The present work aims at designing and implementing a spatial data infrastructure for storing and sharing ecological data through geospatial web services. As case study, we concentrated on limnological data coming from the drainage basin of Lake Maggiore in the Northern of Italy. In order to establish the infrastructure, we started with two basic questions: (1) What type of data is the ecological dataset? (2) Which are the geospatial web services standards most suitable to store and share ecological data? In this paper we describe the possibilities for sharing ecological data using geospatial web services and the difficulties that can be encountered in this task. In order to test actual technological solutions, we use real data of a limnological published study.We concluded that limnological data can be considered observational data, composed by biological (species) data and environmental data, and it can be modeled using Observation and Measurement (O&M) specification. With the actual web service implementation the geospatial web services that could potentially be used to publish limnological data are Sensor Observation Services (SOS) and Web Feature Services (WFS). SOS holds the essential components to represent time series observations, while WFS is a simple model that requires profiling. Both, SOS and WFS are not perfectly suitable to publish biological data, so other alternatives must be considered, as linked data.