Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables. (January 2015)

• Record Type: Journal Article
• Authors: Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.
• Is Part Of: Ecological indicators. Volume 48(2015)
• Page Start: 472
• Page End: 476
• Publication Date: 2015-01
• Subjects: Cellulosic biofuel -- Switchgrass productivity -- Satellite NDVI -- Environmental variables -- Multiple regression model -- Great Plains; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2014.09.013
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Strong correlation between site environment variables and switchgrass productivity. Sufficient precipitation in the growing season is essential for switchgrass growth. Suitable elevation and temperature are important factors for switchgrass production. The derived switchgrass production model has an overall training accuracy of 95%. Highly productive switchgrass are mainly located in the eastern part of the GP. Abstract: Switchgrass is being evaluated as a potential feedstock source for cellulosic biofuels and is being cultivated in several regions of the United States. The recent availability of switchgrass land cover maps derived from the National Agricultural Statistics Service cropland data layer for the conterminous United States provides an opportunity to assess the environmental conditions of switchgrass over large areas and across different geographic locations. The main goal of this study is to develop a data-driven multiple regression switchgrass productivity model and identify the optimal climate and environment conditions for the highly productive switchgrass in the Great Plains (GP). Environmental and climate variables used in the study include elevation, soil organic carbon, available water capacity, climate, and seasonal weather. Satellite-derived growing season averaged Normalized Difference Vegetation Index (GSN) was used as a proxy for switchgrass productivity. Multiple regression analyses indicate that there are strong correlations between site environmental variables and switchgrass productivity ( r = 0.95). Sufficient precipitation and suitable temperature during the growing season (i.e., not too hot or too cold) are favorable for switchgrass growth. Elevation and soil characteristics (e.g., soil available water capacity) are also an important factor impacting switchgrass productivity. An anticipated switchgrass biomass productivity map for the entire GP based on site environmental and climate conditions and switchgrass productivity model was generated. Highly productive switchgrass areas are mainly located in the eastern part of the GP. Results from this study can help land managers and biofuel plant investors better understand the general environmental and climate conditions influencing switchgrass growth and make optimal land use decisions regarding switchgrass development in the GP.