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Vegetation Mapping

Most land surfaces on the earth have some type of plant cover, and identification of vegetation is a common component in modeling habitat and ecosystems.  AggieAir's high-resolution, multi-spectral, multi-temporal imagery provides a tool that can be used to map and classify the characteristics of vegetation in various environments and create models that can reveal biological identity, landscape changes, and species habitat.

The AggieAir remote sensing system captures imagery in various environments such as wetlands, fields, and river corridors, which can then be applied in the science of vegetation mapping to represent a single moment in a season or detect changes between multiple moments in time. Classification studies can calculate vegetation indices using color visual and near-infrared spectral bands.

AggieAir was flown as part of a wetlands classification effort, and the Utah State University RS/GIS Laboratory [] used eCognition Trimble Software, an object-based image analysis software, to classified the AggieAir imagery and map wetland species.

Wetlands managers have initiated a long-term effort to control the spread of Phragmites australis, an invasive non-native grass species that crowds out native plants and diminishes critical habitat for valuable waterfowl species.  AggieAir's high-resolution, multi-spectral remote sensing capabilities is helping wetlands managers to identify where Phragmites is growing and track its spread at a very fine scale over the course of the growing season, which in turn helps them them to assess the effectiveness of their management actions.


AggieAir imagery can assist with a variety of vegetation mapping and classification applications, including the following:

  • Establish baseline maps for monitoring studies
  • Analyze changes in vegetation / ground cover over time
  • Identify wildlife habitat and corridors
  • Identify plant and animal species distributions
  • Develop conservation planning measures
  • Manage invasive species
  • Estimate vegetation mass and productivity

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