Monitoring Rangeland Health: A Comparative Analysis of NDVI and SAVI Spectral Indices

Presenter: Sage Wright, University of Wyoming

Presenter’s Bio:

As a current student at the University of Wyoming and a recent graduate of Casper College, I bring a fresh perspective to Geographic Information Science and Technology field. In 2023 I was recognized as the recipient for WYGEO 2023 student scholarship, for my ESRI story map detailing research on mountain pine beetles with the use of remote sensing. I’ve applied my GIS expertise to various sectors, from municipal management to energy development and ecology. Currently, I’m dedicated to exploring GIS applications in natural resource management and conservation, with a focus on leveraging remote sensing techniques to enhance habitat improvement strategies.

Session Time:

May 10, 2024, from 9:30 AM to 10:00 AM

Location:

White room

Session Abstract:

With increasing threats to all ecosystems, the habitat management decisions we make have become essential for conservation efforts. To sustain these efforts, innovative techniques such as, using satellite spectral indices to monitor vegetation health are imperative. It is important to understand the interaction these indices have with habitats, specifically disturbed rangeland habitats. In this research we analyzed the data from the following spectral indices: Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI). NDVI uses near-infrared and red spectral bands to calculate a numerical indicator of vegetation health. SAVI uses an additional soil reflectance adjustment factor. We aimed to learn if NDVI and SAVI show the same spectral trend to disturbances in rangeland habitats. To conduct the research a Wyoming Bureau of Land Management habitat improvement area was selected. The area in 2020 had undergone a removal treatment of encroaching junipers. Landsat imagery from 2019-2023 was processed to reflect the NDVI and SAVI indices values. To compare the imagery, random points were displayed across the study area and spectral values were recorded. The initial analysis of the data suggested, the NDVI spectral trend to be as predicted, and the SAVI index trend varied. Further analysis aims to illuminate how environmental factors influence spectral trends, statistical disparities between indices, and their applicability in management decisions.