期刊
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
卷 8, 期 3, 页码 173-187出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jag.2005.09.002
关键词
boreal environment; classification; forest biomass; forest inventory; geographical information systems; Landsat TM
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 photoinventory. 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 estimates 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 representative portion of a Landsat scene. (c) 2005 Elsevier B.V. All rights reserved.
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