Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA

• Published in: Ecological indicators Vol. 24; pp. 31 - 36
• Main Authors: Gu, Yingxin, Wylie, Bruce K., Bliss, Norman B.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.01.2013; Elsevier
• Subjects: Animal, plant and microbial ecology; Biological and medical sciences; climate change; eMODIS; equations; Flux tower gross primary productivity; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Grassland productivity; grasslands; Greater Platte River Basin; growing season; Growing season averaged NDVI; managers; moderate resolution imaging spectroradiometer; normalized difference vegetation index; primary productivity; rangelands; scientists; soil surveys; SSURGO database; Teledetection and vegetation maps; United States; watersheds; United States; North America; America; Grassland productivity; Greater Platte River Basin; Growing season averaged NDVI; SSURGO database; eMODIS; Flux tower gross primary productivity; Grassland; Primary productivity; Vegetation index; Growing season; Platte River basin; Remote sensing; Database; Environmental monitoring
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2012.05.024

► We assess relationship between growing season NDVI (GSN) and grassland productivity. ► Strong correlation between 9-year mean GSN (MGSN) and SSURGO productivity. ► We develop an empirical equation to estimate grassland productivity using MGSN. ► We generate a regional consistency improved grassland productivity map in the GPRB. This study assessed and described a relationship between satellite-derived growing season averaged Normalized Difference Vegetation Index (NDVI) and annual productivity for grasslands within the Greater Platte River Basin (GPRB) of the United States. We compared growing season averaged NDVI (GSN) with Soil Survey Geographic (SSURGO) database rangeland productivity and flux tower Gross Primary Productivity (GPP) for grassland areas. The GSN was calculated for each of nine years (2000–2008) using the 7-day composite 250-m eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. Strong correlations exist between the nine-year mean GSN (MGSN) and SSURGO annual productivity for grasslands (R2=0.74 for approximately 8000pixels randomly selected from eight homogeneous regions within the GPRB; R2=0.96 for the 14 cluster-averaged points). Results also reveal a strong correlation between GSN and flux tower growing season averaged GPP (R2=0.71). Finally, we developed an empirical equation to estimate grassland productivity based on the MGSN. Spatially explicit estimates of grassland productivity over the GPRB were generated, which improved the regional consistency of SSURGO grassland productivity data and can help scientists and land managers to better understand the actual biophysical and ecological characteristics of grassland systems in the GPRB. This final estimated grassland production map can also be used as an input for biogeochemical, ecological, and climate change models.