6.0 Data Management and Analysis for Vegetation Mapping

The following section describes how the plot data will be managed,
analyzed, and linked with the photographic signatures to create
vegetation descriptions, field keys, photointerpretation keys, and
vegetation maps. See **Figure 4** for a diagram of the flow of
information from the plot data to the final map product.

The field-collected plot data will be entered and managed in a
standardized relational database management system that will have the
capability to output data into standard vegetation analysis programs
(see **Section 6.1** below). The plot data will be analyzed to
illustrate floristic patterns and to relate these patterns to key
environmental variables (see the National Vegetation Classification
System \[NVCS\] document for a detailed description of this process).

The descriptions of the floristic patterns will then be fit within the
NVCS. The NVCS will be continuously updated as new information becomes
available. The result of this process will be a list of all of the
vegetation types found on the park organized within the NVCS. Each
community occurring in the park will be thoroughly described based on
the data collected on the park and the information available for the
community from the NVCS classification (see **Section 6.3** below and
the Vegetation Classification document). Vegetation field keys will be
produced using the biological and environmental characteristics of the
community identified from the plot data (see **Section 6.4**).

Photointerpretation keys will also be developed which link the patterns
identified on imagery to the vegetation types of the NVCS (see **Section
6.4.1** below). To accomplish this, the photointerpreters will review
the characteristics of the signatures (texture, tone, color, etc.) to
identify which characteristics are diagnostic of the vegetation types
from the NVCS (see the National Vegetation Classification System
document for a detailed discussion of this process). The signatures
initially identified on the imagery will then be documented to provide a
guide for interpreting and mapping vegetation from the aerial
photography.

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height="7.513194444444444in"}

6.1 Plot Data Management

All plot data will be managed using a relational database management
system (RDBMS) with a file structure that is compatible with the
Biological and Conservation Data system (BCD) used by the Natural
Heritage Network. The data fields will have the same (or compatible)
values as that of the fields in the Community Element Occurrence
database in the BCD system, which was developed to manage the
polygon-specific information collected on the field forms (see the
National Vegetation Classification System document for a detailed
description of the fields in this database). A database to manage
plot-specific information is currently being developed and will be
completed for this project. The plot data will be entered into this
system and will be available for export to standard analysis packages.

The RDBMS used to manage plot data will be built using the Structured
Query Language (SQL). SQL is a computer language used to interact with
relational databases. Some major features of SQL, such as software
independence, portability across computer systems, SQL standards, and
client/server architecture, will help overcome the difficulty of data
transformation, file compatibility, and connections with other systems
that are often associated with sharing information. Programming the
RDBMS in SQL will facilitate transfer of information within NPS systems
as well as with other agencies. The RDBMS will provide a powerful tool
to manage vegetation information for individual parks and for National
Park Service (NPS) as a whole system in terms of data standardization,
analysis, and transformation within and across agencies.

Automation of field data collection (field data loggers integrated with
Global Positioning System and Geographical Information System) will be
investigated during the prototype stage of the program (see **Section
7** below). This could eliminate the need to transfer between field data
sheets and the plot RDBMS. The various input/output (I/O) functions and
open file structure of the RDBMS will allow easy linkage and transfer of
data between the RDBMS and standard statistical analysis programs and
GIS. Standard data output functions will be written to facilitate export
of data from the RDBMS to analysis software such as TWINSPAN (Hill
1979), CANOCO (ter Braak 1990), DECORANA (Hill 1980), SAS (1994), and
others.

The aerial photointerpretation can be supported with the plot data by
integrating the plot data with a GIS system. Most GIS systems have
built-in interfaces with RDBMS so the data can be easily transferred
among the systems. A GIS point coverage can be created from the
locational fields in the plot database to display the spatial
distribution of field plots to support the photointerpretation. This
methodology will also be investigated during the prototyping effort.

6.2 Data Analysis

The plot data collected in the field will be used for multiple
objectives, including evaluating the list of vegetation types within the
park, creating vegetation keys, describing the range variation of
vegetation across the mapping area, and creating aerial
photointerpretation keys. All of these tasks will be accomplished
through scientific analyses of the field plot data.

**6.2.1 Park-based Vegetation List**

Identifying the floristic patterns on the park and creating a complete
park-based vegetation list will be based on both the plot data collected
in the field during this project and any suitable existing vegetation
information. Floristic patterns and their general relationship to key
environmental variables in the park will be identified either
quantitatively using analysis programs such as TWINSPAN (Hill 1979),
CANOCO (ter Braak 1990), DECORANA (Hill 1980), SAS (1994), or
qualitatively (see the National Vegetation Classification System
document for a detailed description of the analysis procedure). The
floristic patterns resulting from this analysis will be compared to the
initial list of vegetation types identified for the park and to the
initial signatures identified on the aerial photography.

The recognition of the distribution patterns of vegetation along
environmental gradients will facilitate vegetation mapping based on
remote sensing data and subsequent management of the parks resources.
Because plot data collected at each site contain both environmental and
vegetation information of the sampled plant community, trends in the
relationship between the vegetation and the environment will be
identified. Rigorous statistical analysis of these relationships,
however, is not possible with the current design of the project and is
beyond the scope of this project.

The result of these analysis procedures will be a preliminary
description of the floristic patterns on the park and their broad
relationships to the environmental gradients. These results will be
reviewed by ecologists from The Nature Conservancy, the Natural Heritage
Network, park staff, and other experts, and modified to develop a
complete park-based vegetation list.

**6.2.2 Relating the Floristic Patterns on the Park to the NVCS**

The floristic patterns identified in the park will then be fit within
the NVCS. The types will be placed into the physiognomic hierarchy and
be compared to the corresponding types within the NVCS based on
qualitative analysis of structure, species composition, and
environmental characteristics. There may be interest on the part of the
individual park, the National Park Service or the National Biological
Survey, The Nature Conservancy, or other researchers in gaining a more
rigorous understanding of the relationship between a particular type
which occurs in the park and the characteristics of the types across its
entire range. When this occurs, and funding is available, additional
existing data on the type across its entire range will be quantitatively
analyzed using the methods identified in the National Vegetation
Classification System document. Types identified as new to the NVCS will
be described based on the data collected in the park and assigned an
appropriate confidence level.

The result of this analysis will be a complete list of all the types
from the NVCS that occur in the park. This list will be thoroughly
reviewed by the experts identified above.

6.3 Development of Vegetation Descriptions and Keys

All existing data will be used to develop descriptions and field keys
for the vegetation across each park. These vegetation descriptions and
keys will allow researchers and resource managers to rapidly identify
vegetation types in the field. Detailed descriptions and keys will be
necessary to ensure accurate evaluation of the vegetation in the field
during the map validation and accuracy assessment process (see **Section
7.1.3**).

**6.3.1 Vegetation Descriptions**

Each vegetation type that occurs in the park will be fully described.
The descriptions for each type will draw from the plot data collected in
the park and other available information on the type from across the
entire range of distribution. The descriptions will include a general
characterization of the type based on the range-wide information and
then focus on particular expressions of the type that are specific to
the park. The descriptions will include information on the physiognomic
and biotic traits of the vegetation, as well as environmental
relationships, dynamic processes, community variability and other
relevant factors. The descriptions will follow the format provided in
the Community Characterization Abstract file of the Biological and
Conservation Data System designed by The Nature Conservancy (See the
**Appendix of the National Vegetation Classification System document**).
Examples of the fields in this database file that may be completed in
the description of each community are provided in **Table 3**.

**Table 3. Minimum Set of Fields for Community Descriptions**

+-----------------------------------------------------------------------+
| Scientific name                                                       |
|                                                                       |
| Common name                                                           |
|                                                                       |
| Synonym                                                               |
|                                                                       |
| TNC system                                                            |
|                                                                       |
| Physiognomic class                                                    |
|                                                                       |
| Physiognomic subclass                                                 |
|                                                                       |
| Formation group                                                       |
|                                                                       |
| > Formation                                                           |
| >                                                                     |
| > Alliance                                                            |
|                                                                       |
| Classification confidence level                                       |
|                                                                       |
| Range                                                                 |
|                                                                       |
| Environmental description                                             |
|                                                                       |
| USFWS wetland system                                                  |
|                                                                       |
| Strata                                                                |
|                                                                       |
| Most abundant species                                                 |
|                                                                       |
| Diagnostic species                                                    |
|                                                                       |
| Vegetation description                                                |
|                                                                       |
| Other noteworthy species                                              |
|                                                                       |
| Conservation rank                                                     |
|                                                                       |
| Rank justification                                                    |
|                                                                       |
| Comments                                                              |
|                                                                       |
| References                                                            |
+-----------------------------------------------------------------------+

**6.3.2 Vegetation Keys**

The field keys to the vegetation types will be developed on a park by
park basis using the distinguishing physiognomic characteristics and
species composition of the vegetation, along with the environmental
relationships. These keys will be developed to identify the vegetation
types formally classified in the NVCS as well as any non-homogeneous
mapping units such as community complexes, mosaics and transition zones.
The features that will generally be used to develop keys will be the
structure and cover of the vegetation, along with the dominant and
associated diagnostic species. When the vegetation information alone is
not sufficient to confidently distinguish between closely related types,
key environmental factors will be used to aid the field identification.
The environmental variables that may be used as discriminating features
include topographic position, elevation, slope/aspect, moisture regime,
landform, soils, and surficial geology.

The NVCS hierarchy includes many of the distinguishing characteristics
that can be used to key out the vegetation in the field. The field keys
that will be developed on a park will only use the minimal number of
characteristics that are required to correctly identify the type in the
field. It will rarely be necessary to apply all of the physiognomic
levels in the classification hierarchy in order to key out the
vegetation on a particular park. Because each park will contain a
different subset of the communities in the NVCS, different
characteristics may be used to distinguish the same vegetation type from
one park to another park.

The example below illustrates the minimal characteristics that were
needed to identify the NVCS Deciduous Forest Alliances in the state of
Maine (Maine Natural Heritage Program, 1991). The keys to the vegetation
types for each National Park in the NBS/NPS Vegetation Mapping Program
will follow a similar format.

**Example: Field Key to the Deciduous Forest Alliances of Main**

1a. Trees (woody plants usually over 5m tall) present and forming
10-100% cover.

2a. Trees with their crowns interlocking, forming 60-100% \[FOREST\] 3

3a. Deciduous species contribute \>75% of the total tree cover
**Deciduous Forest**

4a. Upland 5

5a. *Acer saccharum* dominant in the canopy 6

> 6a. Forest of sheltered hillsides or pockets (coves), with moist
> comparatively rich soils, sometimes bouldery; Acer saccharum usually
> strongly dominant; herb layer may contain rare species such as
> *Dryopteris goldiana, Panax quinquefolius, or Impatians pallida*

***Acer saccharum-Fraxinus americana-Tilia americana*** **Forest
Alliance**

6b. Forest of mid-elevation slopes and ridgelines; Acer saccharum
typically co-dominant with *Betula* *alleghaniensis* and/or *Fagus
grandifolia*

***Acer saccharum-Betula alleghaniensis-Tilia americana*** **Forest
Alliance**

5a. *Quercus rubra* dominant in the canopy etc.

4b. Wetland etc.

3b. Deciduous species contribute \<75% of the total tree cover etc.

2b. Trees forming open to very open strands, with crowns not usually
touching etc.

1b. Trees absent, or less than 5m tall, or forming \<10% cover etc.

6.4 Photointerpretation Process

Once the list of the vegetation types in the park has been fit within
the NVCS, the photointerpreters will begin to delineate these
communities on the phot image. The photointerpretation and mapping
process is one of successive approximation (see the National Vegetation
Classification System document for a detailed description of this
process). When in the field with the ecologists collecting the plot
data, the photointerpreters will begin to identify and describe
characteristics of the vegetation (e.g., crown shape and leaf
characteristics of individual species, the composition and density of
species, and the distribution of species) that create visual differences
on the aerial photographs (e.g., differences in texture, tone, contrast,
and color). When the initial floristic patterns are fit within the NVCS,
the photointerpreters will begin to refine the characteristics they use
to identify the vegetation in the field to those that are characteristic
to the types in the NVCS.

The extent to which the photointerpreters can distinguish the diagnostic
characteristics of the vegetation on the imagery will determine the
level of information that can be mapped. For some vegetation types, the
key characteristics of the vegetation will not be identifiable on the
photographs (i.e., understory species composition). In these cases, the
photointerpreters will use other clues to discern the vegetation types
on imagery. For example, the key biological and environmental variables
for vegetation type may also be used to assist the photointerpretation
process. Where there are difficulties in identifying the diagnostic
characteristics on the imagery, the type can be mapped at a higher level
of the hierarchy, or with less accuracy (see the National Vegetation
Classification System document for a detailed description of this
issue).

The photointerpreters will continually refine their understanding of the
characteristics of the vegetation on the imagery to create a set of
decision rules for identifying every vegetation type in the park. These
decision rules (or \"photointerpretation keys\") may represent
vegetation types from different levels of the hierarchy due to the
limitations described above. The decision rules (keys) will be
accompanied by both written description and aerial photo examples.
Throughout the project, the keys will be adjusted and refined to provide
an accurate representation of the vegetation for the final map products.

**6.4.1 Aerial Photointerpretation Keys**

It is planned that photointerpretation keys will be developed as part of
the park vegetation mapping process. Their purpose is to facilitate the
training and orientation of the production staff and users, document the
interpretation process, and help the photointerpreter to evaluate the
photography in an organized and consistent manner.

Ideally, these keys would take the form of a dichotomous key, which
allows the interpreter to find the correct answer through a process of
elimination. However, dichotomous keys for vegetation identification
cannot be developed in as straightforward a manner or as reliably as
those that can be developed for cultural features or plant taxonomies.
The differences in vegetation signatures are often very subtle and can
be quite variable depending on the circumstances under which the photo
was captured. Such things as soil moisture differences, wind conditions,
photo processing, season, and sun angle can introduce considerable range
in the expected signature of a vegetation type. By their nature,
dichotomous keys force decisions. Errors will result when there is
uncertainty about the choices.

The more useful approach is to develop keys based on photo/signature
examples. Some aspects of a dichotomous key can be used to move through
the physiognomic levels but the floristic-based units will be
illustrated by numerous photographic samples with descriptive text. The
descriptive text should include discussions on color, tone, texture, and
pattern of the overall signature, the shapes and form of individual
elements such as tree crown where visible and, just as importantly, the
context in which the signature occurs. The discussion on context should
address items such as drainage, slope, aspect, and other visible
elements of the environment.

**6.4.2 Photointerpretation Quality Assurance**

The most important steps of the quality assurance process will occur at
the field reconnaissance and photointerpretation stages of the effort.
Any errors made at this stage, whether positional or thematic, will
propagate throughout the entire process and will be extremely expensive
to fix. The quality assurance objectives at this stage are to achieve
consistency, accuracy, completeness, and documentation. This can be
accomplished by planning and monitoring for the following:

> \(1\) Selecting and assigning field ecology and photointerpretation
> staff (PIs) with the requisite training and experience is critical.
> Training and orientation of the staff will be required to some degree
> but this cannot be substituted for the in-depth knowledge and
> experience of a professional staff with relevant experience.
> Specifically, the field ecologist should have expertise in the flora
> of the park and its environs. The PIs will require a background in
> natural science or ecology as well as photointerpretation.
>
> \(2\) The field ecology and PI staff must have a high level of
> interaction both in the field and in the office. Both groups bring
> special expertise to the project that must be integrated. It is
> expected that these two groups will provide each other a measure of
> cross training and will assist each other with specific tasks. The
> groups will be directed to check each other\'s work for consistency
> and completeness. It is also an axiom that the more time the PI staff
> spends in the field, the better the work will be.
>
> \(3\) The PI staff must have a high level of interaction and exchange
> of information among themselves. The only way to ensure a consistent
> approach to the photointerpretation is to have the PIs review each
> other\'s work in a systematic fashion. This can be programmed by
> assigning different PIs to work in adjacent areas and to assign
> in-process edits of each other\'s work.
>
> \(4\) Systematic checking of the work and documentation of the process
> at several stages is mandatory. Senior staff will be required to check
> all work against specific checklists at the early and last stages of
> the process and they will provide direct feedback to the assigned
> staff. Field checking of the interpretation work while in the early
> stages of the process must also be part of the quality assurance
> program. Records will be kept of the errors to detect trends or any
> misunderstanding. Any designated corrective actions will be the
> responsibility of the interpreter and must be documented. In summary
> the important element of quality assurance are in-process edits,
> accountability, and coordination between the ecologist, PIs, and
> editors.
>
> \(5\) Consistent work between parks is as important as consistency
> within a park. This is primarily achieved by a uniform set of
> guidelines and procedures, but is also supported by continuity in the
> PI/field teams. It is also recommended that an individual or
> individuals be assigned to the role of national consistency quality
> assurance. This position would have the advantage of a broad overview
> and could overcome the natural tendency to diverge in purpose and
> products.

6.5 Map Generation

The complete vegetation map of the entire park will be created by
applying the decision rules developed from the sampled polygons. The map
scale will be 1:24,000 with a minimum mapping unit of 0.5 hectares. The
vegetation maps will represent every vegetation type that occurs
throughout the mapping area if the polygons are greater than the minimum
mapping unit. As a rule, every polygon will be attributed with one
vegetation type from the NVCS (but see the National Vegetation
Classification System document for a description of exceptions). The
per-class accuracy of the maps will exceed 80 percent.