Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic

Abstract

Understanding the plant community is vital in grasping the effects of climate change. Functional type, which divides vegetation into vascular plants, lichens, and mosses, aids in this understanding by representing a system of classification capable of predicting vegetation responses to, and on, ecological processes (Chapin et al., 1996). Traditional ecology offers a relatively simple strategy of using visual cover estimates to detect plant functional type, representing an effective yet subjective method. Remote sensing presents a more objective technique of vegetation analysis through the use of electromagnetic radiation (Gamon and Qiu, 1999). Just like traditional methods, hyperspectral remote sensing, which is on the scale of the landscape, differentiates between plant functional type (Gamon and Qui, 1999). This study compares the results of traditional and hyperspectral vegetation analysis to ensure that the hyperspectral method of remote sensing describes the plant community in a meaningful and helpful way.