Infrastructures de données spatiales Évaluations économiques : concepts, méthodes et retours d'expérience
Materialtyp:
ArtikelUtgivningsinformation: éditions Quae 2022Beskrivning: 1 electronic resource (120 p.)Innehållstyp: - text
- computer
- online resource
- 9782759235148
- 9782759235155
- 9782759235162
- Earth Sciences, Geography, Environment, Planning
- Geography
- Geographical information systems, geodata and remote sensing
- Environment
- Geography
- Planning
- R Earth Sciences
- RG Geography
- RGW Geographical information systems
- biodiversity
- economy
- geodata and remote sensing
- geography
- information system
- migration
- sociology
- soil
- technology
- thema EDItEUR
Open Access Unrestricted online access star
The demands and uses of satellite spatial data are developing and diversifying significantly, in line with the precision, frequency of shooting and size of the images. It is therefore necessary to understand and report on the impact of this growing production on the organisation and rationalisation of the structures that use them, but also on the effectiveness and transparency of public policies that use this information. Spatial data infrastructures (SDIs) are essential devices: they facilitate access to images (acquisition, processing, archiving), as well as the processes of sharing and methodological innovation. They constitute public information goods and mobilise increasing resources, which requires us to question the types of "economic models" to which they belong. This guide, which is both educational and operational, is intended for all those involved in the production or use of spatial information. It allows for an à la carte reading according to centres of interest and disciplines, through multiple boxes and examples. It presents the concepts and methods of economic evaluation applied to spatial information, detailing three types of approach depending on whether one wants to estimate the value of spatial information, measure the economic spin-offs of an SDI or characterise its impacts using multi-criteria approaches.
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