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Forest Parameters Estimation in a European Mediterranean Landscape Using Remotely Sensed Data

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Satellite remote sensing provides new possibilities and challenges to forest managers for monitoring and managing forest ecosystems. The value/use of high-resolution satellite data of Landsat Thematic Mapper (TM) to estimate tree density, basal area, basal volume, and forest biomass was investigated under an operational perspective in a spatially heterogeneous Mediterranean landscape in northern Greece. Digital classification using Fisher's linear discriminant functions produced an overall accuracy of 82%. A series of multispectral transformations were also performed, and the derivative synthetic channels were used along with the original ones as explanatory variables in the model developed. The forest stand parameters that were investigated in the study presented a similar but weak correlation with the Landsat-5 TM spectral channels. Among them, TM4 and TM7 presented the highest correlation with forest stand parameters, while the integration of the derivative synthetic channels increased the correlation coefficients and resulted in statistically significant predictive models. FOR. SCI. 50(4):450–460.
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Keywords: Forest stand parameters; Landsat TM; abrupt relief; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; regression models

Document Type: Regular Article

Affiliations: 1: MSc, Remote Sensing and GISLab of Forest Management and Remote Sensing, Department of Forestry and Natural Environment Aristotle University of Thessaloniki Box 248 Thessaloniki Greece 540 06 Phone: 30310472815;, Fax: 30310992701, Email: [email protected] 2: Dr Geographic Information Systems Division (GIS), Department of Geography University of Zurich Winterthurerstr. 190 Zurich Switzerland CH-8057 Phone: 41 1635 52 57, Email: [email protected] 3: Ph.D. Student Lab of Forest Management and Remote Sensing, Department of Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece Phone: 30310992701, Email: [email protected] 4: Professor Lab of Forest Management and Remote Sensing, Deparment of Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece Phone: 30310992700, Email: [email protected]

Publication date: 2004-08-01

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    Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
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