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A GIS decision support system for regional forest management to assess biomass availability for renewable energy production
Journal article   Peer reviewed

A GIS decision support system for regional forest management to assess biomass availability for renewable energy production

Pietro Zambelli, Chiara Lora, Raffaele Spinelli, Clara Tattoni, Alfonso Vitti, Paolo Zatelli and Marco Ciolli
Environmental Modelling and Software, Vol.38, pp.203-213
2012
DOI: https://doi.org/10.1016/j.envsoft.2012.05.016
url
https://doi.org/10.1016/j.envsoft.2012.05.016View
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Abstract

harvesting techniques modelling bioenergy forest residues environmental sustainability renewable energy decision support system GIS
Currently, the use of a mix of renewable and traditional energy sources is deemed to help in solving increasing energy demands and environmental issues, thus making it particularly important to assess the availability of renewable energy sources. In a heavily forested region, such as the Italian Alps, one of the main renewable energy sources is woody biomass. A reliable evaluation of biomass availability must take into account the local management of forest resources and the ability to reach forest areas, which is related to existing road networks, and the characteristics and morphology of the terrain. We have developed a new methodology to estimate forest biomass availability for energy production in the Alpine area and to support management decisions, combining the morphological features of the mountain landscape with the current capabilities of forest technology. The approach has been implemented in a tool for forest biomass evaluation based on the Free and Open Source Software for Geospatial (FOSS4G) framework and to refine the current estimates made by the local government. The methodology was tested on the forests of Trentino province (Italy), providing an accurate evaluation of biomass availability, which can be effectively used to identify possible locations for biomass power plants and to suggest new forest management guidelines. The methodology, combining GRASS, PostgreSQL and PostGIS, can be applied to a wide area and can also be executed as a new GRASS module. Being open source it is already available for testing and development.

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