Thematic Accuracy Assessment Procedures. Version 2 - USGS

the Literature Cited section). It is likely that travel costs per observation could be quite high for
those observations in less accessible strata in very large parks. On the other hand, it would allow
the less accessible areas to be represented in the accuracy assessment.
2.3.4 Adjustments to Achieve Sample Data Homogeneity in Observations
In a digital vegetation map, vegetation data will be classified into nonoverlapping polygons with
discrete boundaries that imply a fixed line along which there will be a distinct change from one
vegetation class to another. On the ground, these delineations often appear more as transitional
zones (ecotones) between individual vegetation types of varying width. Some accuracy
assessment sampling designs have avoided potential sites of ambiguous (transitional between
types) vegetation, often by locating field observation sites away from map class boundaries with
other map classes. However, the purpose of employing an ecological and mapping classification
for an inventory implies a clear class membership for any site within the study area, and the
purpose of a thematic accuracy assessment is to evaluate the “goodness of fit” between the
discrete (classified) model and the more continuous real condition. Thus, the term “ecotone” has
no real meaning in the context of discrete classes because nearly any site will have more affinity
for one class than for others, depending on the classification rules. The possibility of transitional
or otherwise atypical vegetation should not be a factor in selecting sites for thematic accuracy
assessment.
However, in order to define the sample data value of a site in order to determine the degree of
match with the site’s corresponding reference data value, it is usually necessary to identify
individual observation sites as unambiguously belonging to a single map class (i.e., they have a
single possible sample data value). In order to do this efficiently the site must be located
sufficiently far from (or, in a Geographic Information System context, buffered from) the map
class boundary to eliminate the possibility that the observed area was of mixed sample data
values due to (1) confusion as to whether the observation area is wholly contained within the
map class, (2) positional error due to site location (GPS) error and (3) allowable positional error
in the map data. To calculate the buffer distance that would be required to eliminate this
uncertainty, the square root of the sum squares of these error sources can be calculated using the
following equation.
2 2
Buffer Distance = R +F + M
2
In this equation, R is the radius distance of the observation area (from Table 3), F is the expected
(e.g., 90 th percentile field positioning (GPS) error distance, and M is the expected maximum
positional error distance in the map. The value for the term M may be generalized to 12 meters
for all NPS Vegetation Inventory projects that meet National Map Accuracy Standard (NMAS)
requirements for positional accuracy of 1:24,000 scale products.
For example, if the observation area is a circular area the size of a 0.5 hectare minimum mapping
unit (40 meters radius), the expected maximum field positioning error is 15 meters, and 12
meters is the allowable positional error in the map data for 90% of all map positions, the sample
site should be positioned at least the root sum square of these three quantities from the polygon
boundary (in this case, approximately 44 meters). Site positioning can be accomplished in a
sampling scheme that is generated in a Geographic Information System (GIS) by creating a
buffer of 44 meters on the interior of all polygons within the inference area, for this scenario.
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