Azizi, Z., Najafi, A., Fatehi, P., Pirbavaghar, M. (2010). Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon). , 18(1), 151-143.
Zahra Azizi; Akbar Najafi; Parviz Fatehi; Mahtab Pirbavaghar. "Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon)". , 18, 1, 2010, 151-143.
Azizi, Z., Najafi, A., Fatehi, P., Pirbavaghar, M. (2010). 'Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon)', , 18(1), pp. 151-143.
Azizi, Z., Najafi, A., Fatehi, P., Pirbavaghar, M. Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon). , 2010; 18(1): 151-143.

Forest stand volume estimation using satellite IRS_P6 (LISS_IV) data (Case study: Lirehsar, Tonekabon)

تحقیقات جنگل و صنوبر ایران
Article 14, Volume 18, Issue 1 - Serial Number 39, March 2010, Pages 151-143    PDF (324.15 K)
Document Type: Research article
Authors
Zahra Azizi1; Akbar Najafi* 2; Parviz Fatehi3; Mahtab Pirbavaghar4
1M.Sc. student of Forestry, faculty of Natural Resources, Tarbiat Modares University
2Assistance Prof., Department of forestry, Faculty of Natural Resources, Tarbiat Modares University
3Research expert, Research Center of Agriculture and Natural Resources of Kurdistan province
4Assistant Prof., Department of forestry, Faculty of Natural Resources, Kurdistan University
Abstract
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 evaluation of the LISS_IV sensor of IRS_P6 satellite data ability for forest timber volume estimation. The study area (1240 ha) is located in watershed No. 35 (Lirehsar) of Mazandaran province. Using systematic random method, 87 circular plots with 0.1 ha area were measured to study the relationship between forest stand volume and satellite data. 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 variables. Using stepwise regression, the best model (LogV= 8.64 – 0.19Mb3 – 0.044Rb3) respect to some criteria including RMSE, bias and correlation coefficient was chosen, while the value of criteria were 32.5%, 12.6% and 0.83%, respectively. Result showed that spectral data of the mentioned sensor have a moderate potential for stand volume estimation.
Keywords
LISS-IV; growing stock; regression analysis; spectral data; Lirehsar
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