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Volume 14 Issue 5
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Article Navigation >  Forest Research  > 2001 >  14(5): 479-483

Citation:
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Classification of Damage Level for Italian Coast Forestry Using Remote Sensing Data

  • 1.

    Research Institute of Forest Resource Information Techniques, CAF, Beijing　100091, China

  • 2.

    IATA-CN R, P.ledelle Cascine 18, 50144 Firenze, Italy

  • 3.

    LaMMA Regione Toscana, Via Einstein 35/B, 50013 Campi Bisenzio(FI), Italy

  • Received Date: 2000-04-17
  • The potential of applying Landsat TM and ERS 1 SAR data to classify the damage levels of Italian coast forestry was analyzed. The result indicates that TM data acquired in summer is more effective than that obtained in winter and ERS 1 SAR data on forestry damage mapping. But the contribution of ERS 1 SAR data for this study is not neglected. The B P (Back propagation) model of artificial neural network was applied to identify different levels of forestry damage. The evaluation for the classified precision with FINDKAPPA program is provided and the map of forestry damage levels for study area is also provided.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Classification of Damage Level for Italian Coast Forestry Using Remote Sensing Data

  • 1. Research Institute of Forest Resource Information Techniques, CAF, Beijing　100091, China
  • 2. IATA-CN R, P.ledelle Cascine 18, 50144 Firenze, Italy
  • 3. LaMMA Regione Toscana, Via Einstein 35/B, 50013 Campi Bisenzio(FI), Italy
  • Received Date: 2000-04-17

Abstract: The potential of applying Landsat TM and ERS 1 SAR data to classify the damage levels of Italian coast forestry was analyzed. The result indicates that TM data acquired in summer is more effective than that obtained in winter and ERS 1 SAR data on forestry damage mapping. But the contribution of ERS 1 SAR data for this study is not neglected. The B P (Back propagation) model of artificial neural network was applied to identify different levels of forestry damage. The evaluation for the classified precision with FINDKAPPA program is provided and the map of forestry damage levels for study area is also provided.

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