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ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Publications at this Location » Publication #108559
Title: RANGELAND VEGETATION COVER ESTIMATING FROM REMOTELY SENSED DATA 1288

Author
item QI, J. - MICHIGAN STATE UNIV.
item MARSETT, R. - USDA-ARS
item Heilman, Philip - Phil

Submitted to: Geospatial Information in Agriculture and Forestry International Conference
Publication Type: Proceedings
Publication Acceptance Date: 10/8/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: Remotely sensed images are often processed to assess vegetation. The most common approach is to calculate a Normalized Difference Vegetation Index (NDVI). This index provides a useful indicator of the amount of green vegetation at a particular time across broad areas. However, the NDVI is not as useful when vegetation is senescent, as is the case during most of the year on rangelands. In the bands used to calculate the NDVI, senescent vegetation appears very similar to soil. This paper presents a method of calculating a vegetation index that includes brown vegetation by using the short-wave infrared band instead of the near infrared band, as is used in the NDVI. With this new vegetation index a better estimate of the percentage of the soil that is covered by both green and brown vegetation can then be calculated. Future research is needed to apply this improved index to make better estimates of standing biomass, forage and other variables of interest to the rangeland manager.

Technical Abstract: Rangelands occupy one half of the United States. They are a major source of food production and are a vital part of the environment. Maximizing rangeland production while preventing land degradation is a challenging task for range managers for several reasons: 1) rangelands are often vast and spatial information is often difficult to obtain in a timely manner; 2) )variable annual weather patterns make the prediction of forage production difficult, if not impossible; and 3) traditional field surveys of rangeland condition and production are labor intensive, time consuming, and expensive. Although remote-sensing technology has been demonstrated to have potential for rangeland applications, operational use of recent remote sensing technology has not been practiced. In this study, we present some examples of remote sensing products, including temporal thematic maps of green vegetative cover, brown vegetative cover, and biomass indicators using the Landsat TM imagery, that could address production and degradatio issues on rangeland.