Vegetation Classification and Mapping Project Report - USGS
Vegetation Classification and Mapping Project Report - USGS
Vegetation Classification and Mapping Project Report - USGS
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Accuracy Assessment <strong>and</strong> Additional Map Classes<br />
assessment crew, who sampled in the<br />
fall following a drier summer monsoon<br />
season, often found these skeletons on<br />
s<strong>and</strong> dunes <strong>and</strong> were instructed to assess<br />
the underlying vegetation. Summer<br />
monsoon rainfall in 2005, the year before<br />
accuracy assessment, had resulted in<br />
prolific growth of Russian thistle where it<br />
occurred in the seed bank. The skeletons<br />
that the accuracy assessment crew viewed<br />
probably remained from that infestation<br />
event. Half of the polygons mapped as<br />
Russian Thistle S<strong>and</strong> Dune <strong>Vegetation</strong><br />
were assessed in the field as another<br />
map class; however, Russian thistle was<br />
commonly found at these sites. Conversely,<br />
polygons in the field identified as Russian<br />
Thistle S<strong>and</strong> Dune <strong>Vegetation</strong> in the<br />
photointerpretation frequently supported<br />
native vegetation <strong>and</strong> were field identified<br />
as Rubber Rabbitbrush / Blue Grama<br />
Shrub Herbaceous <strong>Vegetation</strong> or Fourwing<br />
Saltbush / Galleta Shrubl<strong>and</strong>.<br />
The vegetation at PEFO has few distinct<br />
boundaries between types, particularly<br />
those types that are composed of grasses<br />
with shrubs. There is a gradient in grass<br />
cover as well as shrub cover. The grass<br />
species <strong>and</strong> the shrub species are not<br />
readily distinguishable using aerial<br />
photography; in fact, some species are not<br />
even readily distinguishable even when<br />
you are beside the species in the field.<br />
Compounding this is the mosaic pattern<br />
that often occurs with shrub distribution.<br />
The cover of shrubs can vary at a grain<br />
finer than the minimum-mapping unit<br />
(.5 ha). These mosaics of varying shrub<br />
density make the assignment of map<br />
classes diffcult between the field <strong>and</strong> a<br />
photo-interpretation assessment. This<br />
results in field assessments that may be<br />
based on dominant species cover whereas<br />
the photo-interpretation assessments<br />
might be based on diagnostic or indicator<br />
species as the only distinguishable<br />
community characteristic on the aerial<br />
photo.<br />
Sparse vegetation at PEFO is often so<br />
sparse that indicator species used to<br />
distinguish the community may not be<br />
apparent during accuracy assessment but<br />
may still be present in the map polygon.<br />
Frequently vegetation at PEFO, even<br />
in the more densely vegetated areas,<br />
has less than 25% cover. This makes it<br />
diffcult to determine on the ground as<br />
well as from the aerial photo when a<br />
species is co-dominant or dominant since<br />
the determination relies on assessing<br />
relative differences of less than 5%<br />
cover. Patchiness in vegetation cover, as<br />
discussed above, further confounds the<br />
determination. The accuracy-assessment<br />
field team assessed a minimum mapping<br />
unit within the polygon whereas the<br />
photointerpreter delineated the entire<br />
polygon.<br />
The vegetation at PEFO displays a<br />
surprising amount of variability in<br />
appearance, considering that it is largely<br />
composed of perennial shrubs <strong>and</strong> grasses.<br />
When dormant, grasses are brown <strong>and</strong><br />
diminished in volume compared to their<br />
non-dormant aspect. Shrubs also can lose<br />
leaves <strong>and</strong> fade in color during drought.<br />
Variation in annual rainfall <strong>and</strong> variation in<br />
the seasonal timing <strong>and</strong> amounts of winter,<br />
spring <strong>and</strong> summer monsoonal rains<br />
greatly influence the visual aspect of the<br />
PEFO vegetation. These climatic factors<br />
influenced the ground appearance of the<br />
plant communities during the fieldwork<br />
of 1996 <strong>and</strong> 2003, the photointerpretation<br />
data collection in 2004-2006, <strong>and</strong> the<br />
accuracy-assessment data collection in<br />
2006. Additionally, the photointerpretation<br />
team was mapping conditions present on<br />
aerial photography acquired earlier than<br />
the field observations, which introduces<br />
some potential of a mismatch between<br />
ground conditions <strong>and</strong> the imagery. These<br />
changes are diffcult to account for in the<br />
development of the map <strong>and</strong> in assessing<br />
the map accuracy.<br />
The photosignatures of some map<br />
classes, such as in the badl<strong>and</strong>s, were<br />
masked by the strong spectral signature<br />
of bare soil. Where this happened, the<br />
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