Date of this Version
Remote Sensing of Environment 171 (2015) 291–298
Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) andmay result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystemservices is preferred. The 30-mLandsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. Themain goal of this study is to develop a 30-mgrassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based onMODIS and Landsat (r=0.91)was developed, and a 30-mMODIS equivalent GSN mapwas generated. Finally, a 30-mgrassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass productionmap andwill be useful for regional ecosystemstudy and local land management practices.