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INSPIRE Knowledge Base

INSPIRE Policy Background

A significant part of all information used by public authorities and exchanged with the public refers to specific locations. Its quality depends on the availability of 'spatial data', which is collected and linked (geo-referenced) to location, and then processed to derive the information. Most environmental data, such as emission measurements, biodiversity observations, or environmental quality data is of a spatial nature.

Policy-relevant assessments and analyses are often based on a combination of different types of environmental and geographical data, e.g. on land -use, administrative boundaries, elevation, hydrology, transport networks, production facilities, protected sites etc.  Geophysical data on meteorology, geology, soils, etc. is also relevant in the environment policy context, as well as socio-economic data, such as population density or data on human health and safety.

The programmes and measures laid down in thematic environmental legislation and policies having an impact on the environment (such as agriculture, transport, energy, spatial development, etc.) generally entail the mitigation of risks arising from societal pressures on the environment or those related to natural or man-made hazards potentially leading to disasters (with climate change a driving factor).

For example, data on air quality and meteorological conditions, combined with data on transport, the location of industrial, urban and agricultural sources of emission, population and epidemiology is needed to assess the health impacts of air pollution. Such data allows identifying the sources of pollution and calibrate emission reductions targets in policies having an impact on air quality.

Extensive fact-finding and public consultations undertaken in the course of the preparation of the INSPIRE directive (2001-2004), identified a number of important obstacles preventing the widespread use of spatial data needed for environmental policies and policies having an impact on the environment. For example, 97% of the participants in a public consultation agreed that at all levels, from local to European:

  1. Spatial data is often missing or incomplete.
  2. The description (documentation) of available spatial data is often incomplete.
  3. Spatial datasets can often not be combined with other spatial datasets.
  4. The systems to find, access and use spatial data often function in isolation only and are not compatible with each other.
  5. Cultural, institutional, financial and legal barriers prevent or delay the sharing and re-use of existing spatial data.