Forests Sourcebook - HCV Resource Network

Box 7.8
Example of Defining the Sample of Interest
Box 7.10
Map-Based Estimation Methods
If “forests on the edge” are to be included in the
sample, a possible way of defining them would be
to
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choose watersheds (approximately 1,000) with
– at least 10 percent forest cover, and
– at least 50 percent of forest in private ownership;
and
rank watersheds
– by forest contributions,
– by threats to forest contributions, and
– by combination of contributions and threats.
The inventory could be focused on watersheds
with a high rank.
Source: USFS 2007.
Internet map-based estimation methods involve
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selecting a map of forest attribute,
drawing polygon of any shape, and
developing a selection estimation type that
could be
– sample-based estimate and standard error, or
– pixel-based estimate and standard error (for
small or user-defined areas).
Within this process there are two relevant sets
of images: (i) a “reference set,” which is made up of
satellite image pixels with associated plots, and (i)
a “target set,” which is the satellite image pixels
without associated plots.
Source: USFS 2007.
Practical considerations. Considerations to keep in
mind when developing inventories include the following:
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how to link the national inventory with (where available
and relevant) existing stand (management) inventory.
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difficulty of access to plots in large, remote areas;
continuity of estimates when transitioning from a statelevel
inventory to a national level inventory; and
Box 7.9
Initial plot observation and stratification can assist
in identifying the areas that need to be measured
and those that can be excluded. If initial plot
observation indicates an area is obviously a nonforest
area, it does not need to be observed in the
field. This type of information can help classify
satellite imagery into homogeneous strata to
increase the precision of estimates.
When stratifying forests, stratification must be
distinguished from classification. It is possible to
have large numbers of classifications and few stratification,
or vice versa. For example, there may be
21 classifications, stratified into forest and nonforest
land; or the classification can be forest land and
nonforest land, with four stratifications: forest,
forest edge, nonforest edge, nonforest.
Source: USFS 2007.
Plot Stratification
It is helpful to identify regions where different sampling
and attribute intensities can be applied, such as remote or
reserved areas. The same level of precision is not required in
such areas. If such an approach is adopted, it is important to
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decide whether aerial or ground sampling or both are to
be used, by region;
ensure that a core set of compatible results is available
across all regions; and
clarify the responsibilities of all groups involved.
Cost of inventory. Cost is an important consideration in
inventories. It is important when promoting forest inventories
to
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determine the most cost-effective data collection and
processing approaches;
develop needed operational experience in the relevant
department or unit so that the inventory can be scaled up
on a cost-effective and timely basis; and
provide an estimate of the cost for implementing the
inventory.
Use of new technologies can help with cost concerns.
However, cost should not be the sole driving force for
NOTE 7.1: NATIONAL FOREST INVENTORIES 259