Improving forest field inventories by using remote sensing data in novel sampling designs

Abstract

It is becoming more common that auxiliary information from remote sensing is available at the planning stage of a forest field inventory. Recent developments in sampling theory allows the inclusion of such information in the sampling design to obtain better samples and, hence, improve estimates of common forest attributes. We explain the methodology and evaluate the possibility of including data from airborne laser scanning in the sampling design. The novel designs that we use can select samples that are balanced on a set of auxiliary variables and (or) well spread in a set of auxiliary variables. The results from a simulation study with real data indicate that significant improvement is achieved.

Published in

Canadian Journal of Forest Research
2013, volume: 43, number: 11, pages: 1015-1022
Publisher: NRC Research Press (Canadian Science Publishing)

SLU Authors

• Grafström, Anton

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Hedström Ringvall, Anna

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science
Probability Theory and Statistics

Publication identifier

• DOI: https://doi.org/10.1139/cjfr-2013-0123

Permanent link to this page (URI)

https://res.slu.se/id/publ/51569