Canadian Forest Service Publications
Biomass mapping using forest type and structure derived from Landsat TM imagery. 2006. Luther, J.E.; Fournier, R.A.; Piercey, D.E.; Guindon, L.; Hall, R.J. International Journal of Applied Earth Observation and Geoinformation 8: 173-187.
Issued by: Atlantic Forestry Centre
Catalog ID: 26349
CFS Availability: Order paper copy (free)
A method for mapping forest biomass was developed and tested on a study area in western Newfoundland, Canada. The method, BIOmass from Cluster Labeling Using Structure and Type (BioCLUST), involves: (i) hyperclustering a Landsat TM image, (ii) automatically labeling the clusters with information about forest type and structure, and (iii) applying stand-level equations that estimate biomass as a function of height and crown closure within forest species-type classes. BioCLUST was validated with biomass values measured at geo-referenced field plots and mapped across the study area using an existing forest management photo-inventory. Root mean square error (RMSE) values ranged from 43 to 79 tonnes/ha, and were lowest for intermediate height classes when validated with field plots. Overall bias was negative at 10 tonnes/ha compared with a negative bias of 3 tonnes/ha estimated for the photo-inventory. Validation of the biomass map gave RMSE values of 37-47 tonnes/ha and overall landscape biomass estiamtes within 0.4% of biomass mapped by the photo-inventory. BioCLUST offers an alternative to other biomass mapping methods when scene-specific plot data are limited and a photo-inventory is available for a representaive portion of a Landsat scene.