Title: Modelling of stand volume and tree density using Spot-4 satellite image: a case study in Devrez planning unit

Authors: Alkan Günlü; İlker Ercanlı; Sedat Keleş; Hüseyin Cihad Anlar

Addresses: Department of Forest Engineering, Faculty of Forestry, Çankırı Karatekin University, 18200, Çankırı, Turkey ' Department of Forest Engineering, Faculty of Forestry, Çankırı Karatekin University, 18200, Çankırı, Turkey ' Department of Forest Engineering, Faculty of Forestry, Çankırı Karatekin University, 18200, Çankırı, Turkey ' Forest Management and Planning Department, The Ministry of Forestry and Water Affairs, General Directorate of Forestry, 06530, Ankara, Turkey

Abstract: Estimation of forest stand attributes such as stand volume, basal area, tree density and stand crown closure are required for forest management planning. However, the measurement of these attributes is expensive and time consuming. To solve this problem, remote sensing data can be utilised to predict these stand attributes in forest inventory. The aim of this research was to evaluate the possibility of using Spot-4 satellite image for estimating stand volume and tree density in Devrez planning unit, northwestern part of Turkey. Based on a single Spot-4 satellite data, reflectance values and eight vegetation indices (VIs) were connected to the stand volume and tree density using multiple regression analysis to develop the stand volume and tree density models. Our results showed that a linear combination of Band 1, Band 3, SR, DVI, SAVI, EVI and IPVI were better predictors of stand volume (adjusted R² = 67%; root mean square error (RMSE) = 8.93 m³ ha⁻¹). In addition, the regression model with Band 1, Band 3, SR, DVI, NLI and IPVI as independent variables was a better predictor of tree density (adjusted R² = 62%; RMSE = 6.03 n ha⁻¹). In conclusion, forest stand attributes including the stand volume and tree density can be estimated and modelled using the reflectance values and VIs obtained from Spot-4 satellite image.

Keywords: ground data; Spot-4 satellite data; stand volume; tree density; modelling; satellite images; case study; forest stand; forest management; forest planning; forestry; remote sensing; forest inventory; Turkey.

DOI: 10.1504/IJGW.2015.070047

International Journal of Global Warming, 2015 Vol.7 No.4, pp.454 - 465

Received: 03 Jun 2013
Accepted: 29 Dec 2013
Published online: 26 Jun 2015 *

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