Using multi-spectral landsat imagery to examine forest health trends at Fort Benning, GeorgiaThis article is part of a larger document. View the larger document here.
Assessing vegetation health attributes like canopy density or live crown ratio and ecological processes such as growth or succession ultimately requires direct measures of plant communities. However, on-theground sampling is labor and time intensive, effectively limiting the amount of forest that can be evaluated. Radiometric data collected with a variety of sensors from satellite platforms provide a partial solution to this challenge. Because plant function via photosynthesis is directly tied to electromagnetic energy, vegetation function has been successfully related to radiometric data (Lawley and others In press). Various indices have been developed to interpret vegetative functions or conditions including basal area, species composition, moisture stress, and damage from insects or disease (Liew and others 2008; Bannari and others 1995). The normalized difference vegetation index (NDVI), based on reflectance in the red (R) and near infrared (NIR) bands of the electromagnetic spectrum (NDVI = (NIR - R) / (NIR + R); range:-1 to 1), has been shown to be highly correlated with photosynthetic capacity, net primary productivity, leaf area index, and evapotranspiration. Further, time-series of NDVI have proven useful for evaluating such functions as canopy growth rates, and phenological events like the onset of spring (Pettorelli 2013).