Inventory, Classification, and Mapping

Classification

For classification of existing vegetation, a set of U.S. Forest Service standards and procedures has been established at the national and regional levels. The R5 CALVEG classification system conforms to the upper levels of the National Vegetation Classification Standard (USNVC) hierarchy as it currently exists. The USNVC sets guidelines for all federal agencies involved in this work. Lowest (floristic) levels of this hierarchy are currently being developed and have not yet been finalized for their applicability to California.

Mapping

The Pacific Southwest Region (R5) Information Management staff is responsible for producing comprehensive spatial and tabular databases for existing vegetation, in addition to other duties. A mapping methodology has been developed to capture vegetation characteristics using automated, systematic procedures that efficiently and cost-effectively map large areas of the state with minimal bias and is supplemented with onsite field visits when appropriate. Map attributes consist of vegetation types using the CALVEG classification system and forest structural characteristics such as tree and shrub canopy cover and tree stem diameters.

Download Existing Vegetation Zones, Keys and Descriptions

Notice:
In the Fall of 2017, these feature classes were migrated to the current Forest Service Existing Vegetation Data Dictionary format for Mid level mapping (Existing Vegetation Classification, Mapping, and Inventory Technical Guide). Regional add-ons to the database will supplement the core attributes for further interpretation of the data. To reduce the size of the database and speed download times, these zone-wide layers have been dissolved into "multi-part" features, where spatially separate polygons sharing the same attributes are stored as a single feature. In its entirety, a "single-part" format of one of these feature classes can potentially be more than 1,000,000 polygons. For analysis purposes, it is wise to select a smaller area of interest and break apart features using tools such as the "Multipart To Singlepart" tool in ArcGIS. Reference to this program does not serve as an endorsement by the USDA Forest Service for a specific product.

Citing Geospatial Data

Database Name [type of medium]. (Year). Producer location, province/state: Producer name. Available: Supplier/Database identifier or number [Access date].

Example using the 'Existing Vegetation - CALVEG layers':

Existing Vegetation - CALVEG, [ESRI personal geodatabase]. (2004). McClellan, CA: USDA-Forest Service, Pacific Southwest Region. EvegTile03B_99_04_v2. [2009].

The R5 vegetation inventory program is part of a national Forest Inventory and Analysis (FIA) program. It uses a quasi-systematic sample design to allocate plots across all forest lands regardless of ownership. This Region has augmented the national program by installing plots on all vegetation growth forms, not just forested types, and also by targeting rarer types. The design is intended to provide a baseline vegetation inventory from which long-term monitoring of change (growth, mortality, species composition, etc.) can be assessed. In addition, post-fire plots have been collected to analyze the effects of fire damages on tree, ground surface cover, understory vegetation and downed woody material.

Calveg System

Hierarchical Classification

The USDA Forest Service Region 5 employs the Calveg system and its standards to classify "existing vegetation" in contrast to the classification of "potential natural vegetation", which employs other classification systems. Calveg is a dynamic system that is updated by R5 and maintains strict standards for classification and naming conventions that are consistent across California.

Historical to Present

The CALVEG ("Classification and Assessment with Landsat of Visible Ecological Groupings") system was initiated in January 1978 by the Region 5 Ecology Group of the U.S. Forest Service with headquarters in San Francisco. The Calveg team's mission was to classify California existing vegetation communities for use in statewide resource planning considerations. This was originally accomplished with the use of color infrared satellite imagery and field verification of types by current soil-vegetation mapping efforts as well as professional guidance through a network of contacts throughout the state. It is a hierarchical classification originally based on "formation" categories: forest, woodland, chaparral, shrubs and herbaceous in addition to non-vegetated units. They were originally identified by distinctions calculated among canopy reflectance values used in the LANDSAT satellite. Since then, the classification has been expanded from an initial 129 types occurring throughout the eight regions of the state to the current 213 occurring in nine regions, and image resolution has been enhanced. Recent Calveg expansions include identifying:

• new types in sites consisting of mixed species, such as mixtures of alkaline shrubs rather than dominants
• combinations of conifer and hardwood mixtures in the canopy that are mapped as two primary Calveg alliances
• types that are not widespread across the state, such as various species of Cupressus or Cercocarpus but are suitable for mapping at the current scale of resolution

Crosswalks to Other Systems

At the state level, the Calveg system crosswalks easily to types in the California Wildlife Habitat Relationships System (Meyer and Laudenslayer, 1988 ¹) and its later versions. Additionally, Calveg crosswalks to MCV vegetation types as defined in A Manual of California Vegetation, Second Edition (Sawyer, Keeler-Wolf and Evens, 2009 ²), can be found using the California Native Plant Society's Classification Conversion tool.

Calveg is also consistent with the non-floristic guidelines of the National Vegetation Classification System (NVCS) supported and approved by the Federal Geographic Data Committee Vegetation Subcommittee since 1997 (Vegetation Classification Standard). The USDA Forest Service is a lead agency on this Subcommittee and has clarified these standards in the Existing Vegetation Classification and Mapping Technical Guide, designed for classification and vegetation community mapping uses in our agency. The "Floristic 1" level of the NVCS equates to Calveg's Alliances. They are considered to be provisional alliances in the sense that, although they have been verified in the field, they are not usually determined by sets of plot data that meet NVCS standards for collection and analysis. Under the current floristic standards, which have not yet been approved by the Federal Geographic Data Committee, the analysis of plot data is required to determine plant associations, the lowest level of the system ("Floristic 2") prior to determining alliances. For many USDA Forest Service projects, this approach to classification is not practical for larger-scale or rapid mapping and classification projects. Calveg Alliances are also defined as "Dominance Types" for the purpose of mapping vegetation in accordance with the Tech. Guide's mapping standards.

Identification of Calveg Types

Types are defined in the field with the aid of a set of descriptions and dichotomous keys, one for each of the Calveg regions of California. The provisional alliance descriptions are based on types that have been mapped in each region, indicating environmental conditions, site locations, and species composition.

¹ Meyer, K. E. and W. F. Laudenslayer. 1988. A guide to wildlife habitats of California. 1988. Sacramento: California Dept. of Fish and Game.
² John O. Sawyer, Todd Keeler-Wolf, and Julie M. Evens. 2009. Revision to Manual of California Vegetation, Second Edition.  2009. Sacramento: California Native Plant Society

Remotely sensed data have played an important role in documenting the condition of our landscape and in monitoring changes and trends in those conditions. Historically, aerial photography was the primary source for characterizing the contiguous landscape and events occurring on that landscape. While photography remains a critical resource, other data captured from a variety of sources are also used to map and monitor vegetation and land cover. These data are captured from a variety of platforms ranging from fixed ground stations to satellite based sensors, and are entirely digital in their format. In assessing land cover with remotely sensed data, it is now common to make use of several types and scales of imagery to achieve the desired product.

The Pacific Southwest Region of the Forest Service relies on several data types and sources in its efforts to map and monitor forestland resources. Hierarchically, these data range in scale from coarse to fine, with widely varying spatial and spectral resolutions. The scale and resolution of the data that are used depends on the scale of the information need balanced by the time and cost necessary to process those data. For example, a landscape scale vegetation map that covers 50,000 hectares is typically derived from mid-resolution satellite imagery while a finer scale vegetation map covering a single small watershed is more appropriately derived from large scale, high resolution satellite imagery or digital photography.

Scale and resolution are two concepts critical to the evaluation and use of digital remotely sensed data. While linked, the two terms are not synonymous. It is possible, if generally inappropriate, to view low resolution imagery at a large scale and, conversely, to view high resolution images at small scales. The result can be inadequate information in the source data or far more information than is necessary, resulting in greater processing costs and time. Balancing the scale and resolution of source data with the information need, while a simple concept, is frequently a challenge to accomplish. In the course of meeting that challenge, the Pacific Southwest Region has acquired and archived a variety of digital remotely sensed data sources. These data represent a broad range of remotely sensed data available, but are only a subset of the many image types and sensors currently available on the commercial market. Detailed descriptions of most digital imagery are easily obtained on the World Wide Web. The following illustrates examples of data that have been and are commonly used by the Pacific Southwest Region to obtain information about various natural resources.