A GIS-based model for multiscale forest insurance analysis: The Italian case study
| Autor: | Sandro Sacchelli, Maria Cipollaro, Sara Fabbrizzi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
040101 forestry
Mediterranean climate Economics and Econometrics Geographic information system 010504 meteorology & atmospheric sciences Sociology and Political Science business.industry Environmental resource management Forestry Subsidy 04 agricultural and veterinary sciences Woodland Management Monitoring Policy and Law 01 natural sciences Geography High forest Scale (social sciences) Damages 0401 agriculture forestry and fisheries business Risk management 0105 earth and related environmental sciences |
| Zdroj: | Forest Policy and Economics. 92:106-118 |
| ISSN: | 1389-9341 |
| Popis: | The increasing probability of natural and human-induced extreme events in forests calls for innovative forms of risk management. Insuring timber is one possible way to cope with possible financial damages incurred by forest owners. This study developed a Geographic Information System (GIS) for identifying optimal insurance schemes in the forestry sector. The model comprises three modules used to calculate: i) potential financial damage (temporary or permanent), ii) the annual probability of extreme events (fires and storms), iii) the insurance premium for each site. Research focused on a multiscale approach able to provide outputs at a regional (NUTS-2) and national scale in Italy. Results reveal the high variability of forests in the case study area from the standpoint of both the value of woodlands and the probability of extreme meteorological events. In general, premiums seem to be consistent in the southern regions, in high forest and in Mediterranean forest typologies. The model can be used to analyse different scenarios and variables related to forest characteristics/management as well as financial options. Additional analysis can reveal where and how public subsidy of insurance premiums could favour the diffusion of this form of risk management. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect