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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 />

57

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