Project Methods

Overview

With the launch of Landsat 1 in 1972, the ability for scientists to analyze remote sensing data for land resource monitoring became possible. The use of remote sensing data is an increasingly important component of natural resource monitoring, offering resource managers the opportunity to obtain information about the landscape without on-the-ground investigations. Researchers and analysts continue to develop methods of identify changes in vegetation on the landscape using remotely sensed data, such as Landsat imagery. The SouthFACT project is currently using three of these methods to track vegetation changes across the Southern landscape:

 

     Normalized Difference Vegetation Index

     Normalized Difference Moisture Index

     Shortwave Infrared Band Differencing

 

Each of these methods have been used for varying purposes by scientists as indicators of vegetation change, commonly referred to as Vegetation Indices. Each method is derived using relatively simple mathematical formulas that include one or more spectral bands (see Technology Overview for band details). Vegetation change formulas typically use either a ratio or differencing technique. A ratio method includes division, where one or more spectral band values are divided into other values. A differencing method includes a simple subtraction, where an image from one date is subtracted from an image acquired a different day. The SouthFACT project computes the percent change of each vegetation index method used, expressing the change in image values from one date to another as a percentage. A brief explanation of each method used on the project is provided below. A more detailed discussion of methods can be found in the SouthFACT Technical User Guide (see User Guides).

 

Normalized Difference Vegetation Index (NDVI)

The NDVI method is a commonly used vegetation index and is generically referred to as a measure of vegetation "greenness". In general, this method relies on the characteristics of healthy vegetation to absorb red light (for energy / photosynthesis) and reflect near-infrared light. As a result, evaluating the change in NDVI from one image to another roughly equates to evaluating the change in vegetation health / productivity. The U.S. Forest Service's ForWarn and Forest Disturbance Mapper projects both use MODIS satellite imagery and the NDVI method to evaluate vegetation changes across the Nation. Additional information about the NDVI method can be found on NASA’s website, ForWarn’s website, and numerous other sources (e.g., Wikipedia).


The formula for NDVI is:

 

     NDVI = (NIR - Red) / (NIR + Red)

 

Where “NIR” is the value recorded for the near-infrared spectral band and “Red” is the value recorded for the red spectral band.

Specific formulas used for the SouthFACT project are below. Differences in bands are based on Landsat band designations, with only slight variations in wavelength ranges across platforms.

 

     Landsat 5 NDVI = (Band 4 - Band 3) / (Band 4 + Band 3)

     Landsat 7 NDVI = (Band 4 - Band 3) / (Band 4 + Band 3)

     Landsat 8 NDVI = (Band 5 - Band 4) / (Band 5 + Band 4)

 

Normalized Difference Moisture Index (NDMI)

The NDMI method is another relatively common Vegetation Index and is generically referred to as a measure of vegetation moisture. NDMI is more frequently being used in drought monitoring but is also capable of detecting more subtle changes in vegetation moisture conditions. Researchers have also evaluated the use of NDMI to determine fuel moistures for wildfire hazard assessments.


The formula for NDMI is:

 

     NDMI = (NIR - SWIR1) / (NIR + SWIR1)

 

Where “NIR” is the value recorded for the near-infrared spectral band and “SWIR” is the value recorded for the shortwave infrared band (lower wavelength of two Landsat SWIR bands).

Specific formulas used for the SouthFACT project are below. Differences in bands are based on Landsat band designations, with only slight variations in wavelength ranges across platforms.

 

     Landsat 5 NDMI = (Band 4 - Band 5) / (Band 4 + Band 5)

     Landsat 7 NDMI = (Band 4 - Band 5) / (Band 4 + Band 5)

     Landsat 8 NDMI = (Band 5 - Band 6) / (Band 5 + Band 6)

 

Shortwave Infrared Band Differencing

The Shortwave Infrared (SWIR2) Band Differencing method represents the most simplistic of the three current methods used on the SouthFACT project. Utilizing the higher wavelength SWIR2 band (Band 7) provided by Landsat satellites, this method is intended to focus on vegetation moisture while minimizing interference of atmosphere and light cloud cover. State forestry agency personnel have found this method to be simple / quick approach to identify more drastic vegetation changes on the landscape, particularly forest harvesting.


The formula for SWIR2 (Band 7) Differencing is:

 

     Band 7 Differencing = (Band 7 Date 2) - (Band 7 Date 1)