|Wylie, B -|
|Gilmanov, T -|
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 19, 2011
Publication Date: April 18, 2011
Citation: Skinner, R.H., Wylie, B.K., Gilmanov, T.G. 2011. Using NDVI to estimate carbon fluxes from small rotationally grazed pastures. Agronomy Journal. 103:972-979. Interpretive Summary: Vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), derived from satellite imagery have been used for many years to predict the growth and productivity of forest, crop and grasslands. However, grazed pastures in the northeastern USA are often subdivided into multiple paddocks that are smaller than the resolution limits of many satellite images. Thus, while the total pasture area may be large enough for satellite monitoring, the individual management units might be too small, making it questionable as to whether or not vegetation indices calculated from these images can be used to monitor the productivity of northeastern pastures. The objective of this research was to determine if NDVI calculated from 250-m satellite images could predict the gross primary productivity (GPP) of grazed paddocks in central Pennsylvania that were considerably smaller than the resolution limits of the images. Estimates of GPP, based primarily on NDVI and available solar radiation were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed by 11 to 13%. The satellite images were limited in their ability to capture short-term grazing management effects on GPP. However, they appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term, management induced changes in GPP at individual sites.
Technical Abstract: Satellite-based Normalized Difference Vegetation Index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern US might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (sub-meter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007 and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on eMODIS 7-day NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term, management induced changes in GPP at individual sites.