Modelling of stand volume and tree density using Spot-4 satellite image: a case study in Devrez planning unit
by Alkan Günlü; İlker Ercanlı; Sedat Keleş; Hüseyin Cihad Anlar
International Journal of Global Warming (IJGW), Vol. 7, No. 4, 2015

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.

Online publication date: Fri, 26-Jun-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Global Warming (IJGW):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com