Technical assessment of GeoSUR and comparison with INSPIRE experience in the context of an environmental vulnerability analysis

Abstract: The use of spatial information has become an important resource for decision support making at national and regional levels. In this respect, several private and public organizations are continuously collecting and producing geospatial data. However, there are still problems that affect the usage of spatial information. As a response to these problems, several spatial data sharing initiatives have been implemented at national, regional and global level. This is also the case of the Infrastructure for Spatial Information in the European Community (INSPIRE) and the Integrated Geospatial Information Network for South America (GeoSUR), both created in 2007. GeoSUR works together with the PAIGH, the Geocentric Reference System for the Americas (SIRGAS) and the Permanent Committee on Geospatial Data Infrastructure for the Americas (PC-IDEA) to consolidate the Spatial Data Infrastructure of the Americas. In this context, the role of GeoSUR is to provide the distribution platform for the SDI and develop geoservices and applications based on institutional spatial databases. This research performs a technical assessment of GeoSUR to identify the extent to which the spatial resources provided by the network area accessible, applicable and usable for decision making processes at regional (multinational) level. In order to do so, this study is conducted in the context of a real case study that implements Spatial Multicriteria Evaluation to assess the environmental vulnerability of the Amazon IIRSA region. Results show strengths at finding spatial resources, and regarding the accessibility to regional datasets in GeoSUR. However several obstacles still limit accessibility, applicability and usability of spatial data to perform regional analysis. In this respect, elements considered by INSPIRE such as common implementing rules and technical guidelines are identified as useful to tackle these obstacles and make the spatial services and datasets of the participant institutions compatible to perform regional analysis.