Skip Navigation

Forestry 2004 77(5):383-396; doi:10.1093/forestry/77.5.383
© 2004 by Institute of Chartered Foresters
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (6)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Donoghue, D.N.M.
Right arrow Articles by Smith, S.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

An evaluation of the use of satellite data for monitoring early development of young Sitka spruce plantation forest growth

D.N.M. Donoghue1 *, P.J. Watt1, N.J. Cox1, R.W. Dunford1, J. Wilson2, S. Stables2 and S. Smith3

1 Department of Geography, University of Durham, South Road, Durham DH1 3LE, England, 2 Forest Enterprise Scotland, Galloway Forest District, Newton Stewart, Dumfries and Galloway DG8 6AJ, Scotland, 3 Forest Research Agency, Woodland Survey Branch, Northern Research Station, Roslin, Midlothian EH25 9SY, Scotland

This paper describes an evaluation of the potential of medium resolution (20–30 m pixel size) satellite data to monitor the growth of Sitka spruce (Picea sitchensis Bong. Carr.) plantations in the UK. The aim is to develop a cost-effective methodology to allow crops to be monitored by remote sensing and, in particular, to provide a mechanism to identify compartments that fail to establish as commercially viable crops. The method used involves predicting forest variables from optical reflectance imagery and field observations using generalized linear modelling. The first stage of this process is to establish the quantitative relationship between forest structure and reflectance data from the Landsat ETM+ and SPOT 4 HRVIR sensors. This was investigated for 25 compartments of Sitka spruce ranging in age from 2 to 17 years. The generalized linear models used showed that mean height is most strongly correlated with reflectance data. There is, however, no relationship between tree density and reflectance data. Interestingly, despite the differences in spatial resolution between Landsat and SPOT data, the predictive models derived were almost identical. Independent field checking of these models indicates that the root mean square error of crop height predictions is 1.5 m. The study suggests that by using repeated satellite surveys, tree growth can be monitored for very low cost per unit area and data can easily be integrated into a GIS (Geographical Information System) allowing foresters to interrogate and visualize the predictions over large areas.

* Corresponding author. E-mail: danny.donoghue{at}durham.ac.uk


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.