Remote sensing, field survey, and long-term forecasting: an efficient combination for local assessments of forest fuels

This article describes and evaluates a method for assessing local biofuel potentials. Such assessments are important, for example, in connection with the establishment of heating plants for local communities. A sparse grid of field sample plots from an existing national forest inventory (NFI) is use...

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Bibliographic Details
Published in:	Biomass & bioenergy Vol. 22; no. 3; pp. 145 - 157
Main Authors:	Bååth, Härje, Gällerspång, Andreas, Hallsby, Göran, Lundström, Anders, Löfgren, Per, Nilsson, Mats, Ståhl, Göran
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01-01-2002
Subjects:	Forest fuel kNN Satellite image Satellite image kNN Forest fuel
Online Access:	Get full text
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Summary:	This article describes and evaluates a method for assessing local biofuel potentials. Such assessments are important, for example, in connection with the establishment of heating plants for local communities. A sparse grid of field sample plots from an existing national forest inventory (NFI) is used as reference data for satellite image based estimates of forest condition. The data thus obtained will be in a format that makes them readily available for existing forestry scenario models, in this case the Swedish Hugin system. Thus, forecasts of future harvesting levels and the corresponding amounts of forest fuels—mainly from branches and tops—can be derived in a straightforward manner. The proposed method was evaluated in two test areas in northern Sweden, the communes of Vindeln and Älvsbyn. Besides a base-line scenario for the forecasts, a scenario with geographical restrictions as to the extraction of forest fuels was tested. With a maximum transportation distance of 300 m to road, the available forest fuel potential was shown to decrease by more than 50%. With the proposed method, this kind of geographical restriction is easily implemented.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0961-9534 1873-2909
DOI:	10.1016/S0961-9534(01)00065-4