Computer-generated map, based upon data used by GAP staff at
INHS, showing vegetation alliances in Calhoun County, Illinois.
The main agenda of the Illinois Gap Analysis Project (IL-GAP), part of a nationwide project funded by the U.S. Geographical Survey, is to locate unprotected land that has or is predicted to have high biodiversity. Vertebrate species and vegetation are mapped as part of this process.
The Illinois Natural History Survey (INHS) is using Landsat Thematic Mapper (TM) satellite imagery as the primary means of mapping the state's vegetation. By combining satellite imagery data analysis with other forms of ancillary data, the INHS is able to classify the vegetation to the alliance, or species association, level in most cases. In some areas vegetation is extremely mixed, in which case the vegetation is mapped at more of a natural community level.
Satellite imagery is collected from two dates, spring and fall, to account for seasonal variations such as agriculture, tree leaf-on and leaf-off, wetness, and so forth. Landsat TM imagery has a resolution of 30 meters by 30 meters. Digital elevation models (DEMs), also with 30-meter resolution, are used to create a slope/aspect index (SAI) to represent topological differences across the landscape. The imagery is combined with the SAI and statistically analyzed for clusters of similarity, accounting for spectral and topological variables. These clusters of similarity are then classified using ancillary data and expert knowledge.
Computer-generated map, based upon data used by GAP staff at
INHS,
showing
vegetation alliances in Calhoun
County,
Illinois.
Ancillary data is found in many forms and may vary across different regions of the state. Some common types of ancillary data include black-and-white aerial photography, color infrared aerial photography, updated wetlands inventories, county soil surveys, local vegetation maps, U.S. Forest Service Forest Inventory Analysis (FIA) points, Illinois Natural Areas Inventory, and hydrography.
The vegetation alliances used to name the classes are taken from An Alliance Level Classification of the Vegetation of the Midwestern United States, (Drake and Faber-Langendoen, The Nature Conservancy (TNC), 1997), following the National Gap Analysis protocol. The TNC document lists detailed descriptions of vegetation alliances, their natural community type, and similar Society of American Foresters (SAF) forest types, where applicable.
One of the major challenges of classifying the vegetation of Illinois is that the landscape has been disturbed many times over the past 150 years. The result is fragmented forests with mixed and invasive vegetation and few natural-state communities. Even vegetation distribution reports from the 1960s are dated in some areas as invasive, successional, and opportunistic species have moved into areas previously thought to be unsuitable. This makes it difficult to follow TNC vegetation alliance naming schemes in their pure forms. As a result, the IL-GAP project will rely heavily on the observations and knowledge of district foresters and forest preserve professionals to accurately classify the vegetation on the Illinois landscape as it is seen today.
When a "rough" classification of a satellite scene is finished, maps are sent to the district forester offices of the Illinois Department of Natural Resources where they will be checked for content and general correctness. This will allow for minor changes to be made, such as breaking out more classes, combining classes, or even renaming classes to better reflect the actual composition. Once the classification for the entire state is completed, an official accuracy assessment will be performed on each class that has been mapped. The goal of this project is to reach 80% accuracy for each class.
The final analysis and end products of the IL-GAP project will inevitably allow us to map and locate areas where habitat conservation and management is needed most in order to maintain high biodiversity for all species of flora and fauna.
Linda Schwab, Center for Wildlife Ecology
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