An Information System for Brownfield Regeneration: providing customised information according to stakeholders' characteristics and needs. (1st July 2018)
- Record Type:
- Journal Article
- Title:
- An Information System for Brownfield Regeneration: providing customised information according to stakeholders' characteristics and needs. (1st July 2018)
- Main Title:
- An Information System for Brownfield Regeneration: providing customised information according to stakeholders' characteristics and needs
- Authors:
- Rizzo, Erika
Pizzol, Lisa
Zabeo, Alex
Giubilato, Elisa
Critto, Andrea
Cosmo, Luca
Marcomini, Antonio - Abstract:
- Abstract: In the EU brownfield presence is still considered a widespread problem. Even though, in the last decades, many research projects and initiatives developed a wealth of methods, guidelines, tools and technologies aimed at supporting brownfield regeneration. However, this variety of products had and still has a limited practical impact on brownfield revitalisation success, because they are not used in their entire potential due to their scarce visibility. Also, another problem that stakeholders face is finding customised information. To overcome this non-visibility and not-sufficient customisation of information, the Information System for Brownfield Regeneration (ISBR) has been developed, based on Artificial Neural Networks, which allows understanding stakeholders' information needs by providing tailored information. The ISBR has been tested by stakeholders from the EU project TIMBRE case studies, located in the Czech Republic, Germany, Poland and Romania. Data gained during tests allowed to understand stakeholders' information needs. Overall, stakeholders showed to be concerned first on remediation aspects, then on benchmarking information, which are valuable to improve practices in the complex field of brownfield regeneration, and then on the relatively new issue of sustainability applied to brownfield regeneration and remediation. Mature markets confirmed their interest for remediation-related aspects, highlighting the central role that risk assessment plays inAbstract: In the EU brownfield presence is still considered a widespread problem. Even though, in the last decades, many research projects and initiatives developed a wealth of methods, guidelines, tools and technologies aimed at supporting brownfield regeneration. However, this variety of products had and still has a limited practical impact on brownfield revitalisation success, because they are not used in their entire potential due to their scarce visibility. Also, another problem that stakeholders face is finding customised information. To overcome this non-visibility and not-sufficient customisation of information, the Information System for Brownfield Regeneration (ISBR) has been developed, based on Artificial Neural Networks, which allows understanding stakeholders' information needs by providing tailored information. The ISBR has been tested by stakeholders from the EU project TIMBRE case studies, located in the Czech Republic, Germany, Poland and Romania. Data gained during tests allowed to understand stakeholders' information needs. Overall, stakeholders showed to be concerned first on remediation aspects, then on benchmarking information, which are valuable to improve practices in the complex field of brownfield regeneration, and then on the relatively new issue of sustainability applied to brownfield regeneration and remediation. Mature markets confirmed their interest for remediation-related aspects, highlighting the central role that risk assessment plays in the process. Emerging markets showed to seek information and tools for strategic and planning issues, like brownfield inventories and georeferenced data sets. Results led to conclude that a new improved platform, combining the ISBR functionalities with geo-referenced ones, would be useful and could represent a further research application. Graphical abstract: Image 1 Highlights: An Information System for Brownfield Regeneration has been developed for stakeholders. The system relies on Artificial Neural Networks to answer to users' information needs. The tool has been tailored according to stakeholders' inputs from different countries. … (more)
- Is Part Of:
- Journal of environmental management. Volume 217(2018)
- Journal:
- Journal of environmental management
- Issue:
- Volume 217(2018)
- Issue Display:
- Volume 217, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 217
- Issue:
- 2018
- Issue Sort Value:
- 2018-0217-2018-0000
- Page Start:
- 144
- Page End:
- 156
- Publication Date:
- 2018-07-01
- Subjects:
- Brownfield regeneration -- Information system -- Artificial neural networks -- Information needs -- Customised information -- Stakeholders
Environmental policy -- Periodicals
Environmental management -- Periodicals
Environment -- Periodicals
Ecology -- Periodicals
363.705 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03014797 ↗
http://www.elsevier.com/journals ↗
http://www.idealibrary.com ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1016/j.jenvman.2018.03.059 ↗
- Languages:
- English
- ISSNs:
- 0301-4797
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4979.383000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11600.xml