Capability of ETM+ in estimates standing stock in beech stands of mountain forest

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• 作者：Seyed Armin Hashemi (1)
  Mir Mozaffar Fallahchai (1)
  Farahzad Jahan Bakhsh (2)
  
• 关键词：Regression analysis ; Spectral data ; ETM+ ; Growing stock ; Beech
• 刊名：Arabian Journal of Geosciences
• 出版年：2013
• 出版时间：September 2013
• 年：2013
• 卷：6
• 期：9
• 页码：3371-3376
• 全文大小：301KB
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• 作者单位：Seyed Armin Hashemi (1)
  Mir Mozaffar Fallahchai (1)
  Farahzad Jahan Bakhsh (2)
  
  1. Department of Forestry, Lahijan Branch, Islamic Azad University, Lahijan, Iran
  2. Ms Forestry, Department of Forestry, Lahijan Branch, Islamic Azad University, Lahijan, Iran
  

文摘

Stand volume is an important criterion in forest sciences for monitoring status and function of forests, estimation of productivity, prediction and modeling of forest disturbance, economic and environmental issues, and forest planning. The aim of this research is to evaluate the ETM+ sensor of Landsat 7 satellite data ability for forest timber volume estimation. For this purpose, 40 selective sample plots with 60?×-0?m dimension were selected, and in each sample plot, standing volume was calculated. Correspondent digital data to plots were extracted from spectral and considered as independent variables. Original stand volume data, square root, and logarithm of them were considered as dependent potential for stand volume estimation. Variables using stepwise regression, the best model with coefficient of determination, and adjusted coefficient of determination with regard to determining the appropriate model were modified Log?V=-7.546--.85Greenness??-0.564NDWI??-8 0.063Band1. In this model, the coefficient of determination and adjusted coefficient of determination were obtained 0.778 and 0.770, respectively. Result showed that spectral data of the mentioned sensor have a moderate.