Demand for biofuel products is expected to increase as the world seeks alternatives to fossil fuels. Currently, ethanol produced from Midwest corn is the most common biofuel product in the United States. The negative environmental effects caused by corn-based biofuel development include soil erosion, water quality impairment from pesticides and fertilizer, and demand for water for irrigation. The feedbacks of these environmental effects may cause local ecosystem changes. Biofuels produced from cellulosic feedstocks such as grasses, forest woody biomass, and agricultural and municipal wastes have lagged behind corn-based ethanol because the biochemistry of conversion is more complex. As the technical challenges are anticipated/predicted to be met in the near future, demand is expected to increase for cellulosic feedstocks as inputs to the refineries that produce biofuels. Our goal is to identify grasslands and marginal croplands that are suitable for growing cellulosic feedstock crops such as switchgrass (Panicum virgatum) while minimizing impacts on food production.
Our initial study area is the grasslands of the Greater Platte River Basin (GPRB). We identify grasslands suitable for conversion to a switchgrass crop by selecting areas 1) that have consistent grassland productivity that is high or fairly high and 2) that have not had severe ecological disturbance (e.g., wildfire, floods, insects, and overgrazing). Our method, known as "dynamic monitoring of ecosystem performance" (Wylie et al., 2008), is able to separate the influence of year-to-year weather changes (e.g., drought) from disturbance changes (e.g., fire or overgrazing) to identify and map suitable areas. Our analysis uses satellite-derived growing season normalized difference vegetation index (GSN) data, weather data, biophysical and geophysical data, and ecosystem or land cover performance models. We make maps of areas that may be suitable for conversion from grassland to biofuel feedstocks. Results from this study provide information to assist land managers and decision makers make optimal land use decisions for cellulosic biofuel development and sustainability. We have done preliminary work to evaluate the potential conversion of marginal croplands to switchgrass. Future work will extend the study area to the Northern Great Plains.
Below are publications associated with this project.
Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA
Mapping cropland waterway buffers for switchgrass development in the eastern Great Plains, USA
Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA
An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data
Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States
Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations
Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA
Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches
Estimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables
Projecting future grassland productivity to assess thesustainability of potential biofuel feedstock areas in theGreater Platte River Basin
Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA
Identifying grasslands suitable for cellulosic feedstock crops in the Greater Platte River Basin: dynamic modeling of ecosystem performance with 250 m eMODIS
- Overview
Demand for biofuel products is expected to increase as the world seeks alternatives to fossil fuels. Currently, ethanol produced from Midwest corn is the most common biofuel product in the United States. The negative environmental effects caused by corn-based biofuel development include soil erosion, water quality impairment from pesticides and fertilizer, and demand for water for irrigation. The feedbacks of these environmental effects may cause local ecosystem changes. Biofuels produced from cellulosic feedstocks such as grasses, forest woody biomass, and agricultural and municipal wastes have lagged behind corn-based ethanol because the biochemistry of conversion is more complex. As the technical challenges are anticipated/predicted to be met in the near future, demand is expected to increase for cellulosic feedstocks as inputs to the refineries that produce biofuels. Our goal is to identify grasslands and marginal croplands that are suitable for growing cellulosic feedstock crops such as switchgrass (Panicum virgatum) while minimizing impacts on food production.
Our initial study area is the grasslands of the Greater Platte River Basin (GPRB). We identify grasslands suitable for conversion to a switchgrass crop by selecting areas 1) that have consistent grassland productivity that is high or fairly high and 2) that have not had severe ecological disturbance (e.g., wildfire, floods, insects, and overgrazing). Our method, known as "dynamic monitoring of ecosystem performance" (Wylie et al., 2008), is able to separate the influence of year-to-year weather changes (e.g., drought) from disturbance changes (e.g., fire or overgrazing) to identify and map suitable areas. Our analysis uses satellite-derived growing season normalized difference vegetation index (GSN) data, weather data, biophysical and geophysical data, and ecosystem or land cover performance models. We make maps of areas that may be suitable for conversion from grassland to biofuel feedstocks. Results from this study provide information to assist land managers and decision makers make optimal land use decisions for cellulosic biofuel development and sustainability. We have done preliminary work to evaluate the potential conversion of marginal croplands to switchgrass. Future work will extend the study area to the Northern Great Plains.
Location of the Greater Platte River Basin (inside the blue outline) and the land cover types as identified in the National Land Cover Database (NLCD) 2001. Grasslands are shown in light yellow and cultivated crops are shown in brown (Homer et al., 2004).(Public domain.) - Publications
Below are publications associated with this project.
Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA
Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffeFilter Total Items: 16Mapping cropland waterway buffers for switchgrass development in the eastern Great Plains, USA
Switchgrass (Panicum virgatum L.), a highly productive perennial grass, has been recommended as one potential source for cellulosic biofuel feedstocks. Previous studies indicate that planting perennial grasses (e.g., switchgrass) in high‐topographic‐relief cropland waterway buffers can improve local environmental conditions and sustainability. The main advantages of this land management practice iIntegrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA
Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffeAn optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improveMapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States
Growing cellulosic feedstock crops (e.g., switchgrass) for biofuel is more environmentally sustainable than corn-based ethanol. Specifically, this practice can reduce soil erosion and water quality impairment from pesticides and fertilizer, improve ecosystem services and sustainability (e.g., serve as carbon sinks), and minimize impacts on global food supplies. The main goal of this study was to iDeveloping a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations
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 baUsing satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA
Cultivating annual row crops in high topographic relief waterway buffers has negative environmental effects and can be environmentally unsustainable. Growing perennial grasses such as switchgrass (Panicum virgatum L.) for biomass (e.g., cellulosic biofuel feedstocks) instead of annual row crops in these high relief waterway buffers can improve local environmental conditions (e.g., reduce soil erosSpatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composDownscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches
The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS lEstimating switchgrass productivity in the Great Plains using satellite vegetation index and site environmental variables
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 ovProjecting future grassland productivity to assess thesustainability of potential biofuel feedstock areas in theGreater Platte River Basin
This study projects future (e.g., 2050 and 2099) grassland productivities in the Greater Platte River Basin (GPRB) using ecosystem performance (EP, a surrogate for measuring ecosystem productivity) models and future climate projections. The EP models developed from a previous study were based on the satellite vegetation index, site geophysical and biophysical features, and weather and climate drivMapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA
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 ProdIdentifying grasslands suitable for cellulosic feedstock crops in the Greater Platte River Basin: dynamic modeling of ecosystem performance with 250 m eMODIS
This study dynamically monitors ecosystem performance (EP) to identify grasslands potentially suitable for cellulosic feedstock crops (e.g., switchgrass) within the Greater Platte River Basin (GPRB). We computed grassland site potential and EP anomalies using 9-year (2000–2008) time series of 250 m expedited moderate resolution imaging spectroradiometer Normalized Difference Vegetation Index data,