What if you could find the best place to view the fall leaf colors without having to drive to several locations to find that best one? Remote sensing is creating the ability to do just that with the use of Normalized Difference Vegetation Index (NDVI). NDVI is calculated based on the amount of light reflected by the leaves in the near Infrared (NIR) and red regions. The experiment performed used a cottonwood tree that is located between the Education Building and the Half Acre Gym on the University of Wyoming campus (Figure 1).
|Figure 1: Cottonwood tree (close to the light pole)|
monitored by our team.
Leaf collection and reflectance measurement began prior to the onset of a fall temperature event (freezing) to trigger stress and change in leaf reflectance on September 19, 2013. Leaf reflectance values were collected every other day from the onset until the leaves were brown and falling off the tree.
The hypothesis is that reflectance values of the red and NIR will change and the NDVI (NIR - Red) / (NIR + Red) calculations will enable the ability to identify areas of stress or the optimum color viewing time of leaves in the fall.
We now know that most of the stress inducing factors are the lack of water and the slow decrease of the fall season temperatures. Leaves begin to change from a bright and dark green to a yellowish green, to a yellowish brown and finally the brown color we all know as the leaves fall on the ground. The data collected and analyzed supports this hypothesis (Figure 2).
We learned how a cottonwood leaves start to change reflectance and the values we measured across ten wavelengths can be used to determine stress or even color viewing times. We now have a better understanding of the effects that these stressors create on plants.
The graph (Figure 2) showing the NDVI values and the trend line associated with the values (R² = 56%) helps to clarify that the trend line for the cottonwood tree starts high of reflectance and then slowly starts to trend down. This is common among trees and plants coming into the fall months. It shows how the leaves turn from the color green to yellow and then brown as they started to fall off.