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Development of a neural network model to update forest distribution data for managed alpine stands

Author

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  • Scrinzi, Gianfranco
  • Marzullo, Laura
  • Galvagni, David

Abstract

Forest inventories support resource managers to define the extent, size distribution, and species composition of forested and non-forested lands, and after re-measurement, the changes in such resources [Armitage, I., 1998. Guidelines for the management of tropical forests 1. The production of wood. FAO forestry paper 135].

Suggested Citation

  • Scrinzi, Gianfranco & Marzullo, Laura & Galvagni, David, 2007. "Development of a neural network model to update forest distribution data for managed alpine stands," Ecological Modelling, Elsevier, vol. 206(3), pages 331-346.
    • Handle: RePEc:eee:ecomod:v:206:y:2007:i:3:p:331-346
    DOI: 10.1016/j.ecolmodel.2007.04.001
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    Cited by:

    1. Wen, Xuding & Zhao, Zhonghui & Deng, Xiangwen & Xiang, Wenhua & Tian, Dalun & Yan, Wende & Zhou, Xiaolu & Peng, Changhui, 2014. "Applying an artificial neural network to simulate and predict Chinese fir (Cunninghamia lanceolata) plantation carbon flux in subtropical China," Ecological Modelling, Elsevier, vol. 294(C), pages 19-26.
    2. Haywood, Andrew & Stone, Christine, 2011. "Mapping eucalypt forest susceptible to dieback associated with bell miners (Manorina melanophys) using laser scanning, SPOT 5 and ancillary topographical data," Ecological Modelling, Elsevier, vol. 222(5), pages 1174-1184.
    3. Ito, Eriko & Ono, Kenji & Ito, Yoichi M. & Araki, Makoto, 2008. "A neural network approach to simple prediction of soil nitrification potential: A case study in Japanese temperate forests," Ecological Modelling, Elsevier, vol. 219(1), pages 200-211.

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