To conserve the Earth's most extraordinary expressions of temperate
biodiversity in the Pacific Northwest (PNW), USA, the mapping of late
seral (old and mature) conifer forests plays a critical role. For this
paper, we define old conifer forests as >150 years and mature conifer
forest between 50 and 150 years. We offer a new Optimal Iterative
Unsupervised Classification (OIUC) procedure for mapping late seral
conifer forests over an eight-ecoregion area. The key steps of the OIUC
classification were: (1) fully using the Landsat 7 Enhanced Thematic
Mapper Plus (ETM+) 15 m panchromatic channel merged with other 30 m
bands 3 and 5 to make a pan-sharpened false color composite for high
resolution image interpretation; (2) splitting the ETM+ scene by
ecologically distinct areas, or ecoregions, to create relatively
homologous images for classification; (3) using a procedure similar to
cluster busting where multiple iterative manipulation of the ISODATA
clusters was employed; and (4) edge matching of sub-scenes to form
ecoregions, then later merged together to form a map for the entire PNW.
Supporting data and information included ancillary spatial GIS data
layers, aerial photos, Digital Ortho Quad images (DOQs), field
investigations, and previously reported forest age results.
Classification accuracy was assessed using 2081 stratified random
locations on 105 individual DOQs covering the entire region.
Approximately 4.7 million ha (not, vert, similar19%) of the PNW was
classified as old conifer forest (>150 years). Another 4.8 million ha
(not, vert, similar19%) was classified as mature conifer forest (50150
years). Over 9.48 million ha (not, vert, similar38%) of the PNW was late
seral conifer forest. The extent of late seral forests (old and mature
conifer cover classes) varied greatly between the eight ecoregions. The
Central and Southern Cascades and KlamathSiskiyou ecoregions contained
the highest amount of late seral forest in the region. The results
showed high accuracy of the late seral forest classification for the PNW
with an overall accuracy of 90.72% and KAPPA test K value 0.8534.
Producer's (Omission) accuracy for old and mature forests were 91.36%
and 80.40%, User's (Commission) accuracy were 89.42% and 80.59%,
respectively. Accuracy levels differed for the different ecoregions
examined. In general, mature conifer forests exhibited higher levels of
confusion than did old conifer forests, due to the spectral influences
of high-density young conifer stands and terrain shadow effects. The
results fill an important data gap needed for ongoing conservation
planning purposes throughout the region. We found that for relatively
large geographic areas the OIUC method is an efficient and
cost-effective alternative that yields high quality results.