Emily A Heaton
Biographic Data
| ID | 7995760 |
|---|---|
| NAME | Emily A Heaton |
| GIVEN NAMES | Emily A |
| FAMILY NAME | Heaton |
| SIGNATURE | HEATON E A |
| AFFILIATIONS | University of Illinois Urbana-Champaign |
| ORCID | 0000-0003-4521-7273 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching
Process-based agroecosystem models are powerful tools to assess performance of managed landscapes, but their ability to accurately represent reality is limited by the types of input data they can use. Ensuring these models can represent cropping field heterogeneity and environmental impact is important, especially given the growing interest in using agroecosystem models to quantify ecosystem services from best management practices and land use ch…
Farm-scale costs and returns for second generation bioenergy cropping systems in the US Corn Belt
While grain crops are meeting much of the initial need for biofuels in the US, cellulosic or second generation (2G) materials are mandated to provide a growing portion of biofuel feedstocks. We sought to inform development of a 2G crop portfolio by assessing the profitability of novel cropping systems that potentially mitigate the negative effects of grain-based biofuel crops on food supply and environmental quality. We analyzed farm-gate costs a…
No prominent works on this page.
Farm-scale costs and returns for second generation bioenergy cropping systems in the US Corn Belt
While grain crops are meeting much of the initial need for biofuels in the US, cellulosic or second generation (2G) materials are mandated to provide a growing portion of biofuel feedstocks. We sought to inform development of a 2G crop portfolio by assessing the profitability of novel cropping systems that potentially mitigate the negative effects of grain-based biofuel crops on food supply and environmental quality. We analyzed farm-gate costs a…
Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching
Process-based agroecosystem models are powerful tools to assess performance of managed landscapes, but their ability to accurately represent reality is limited by the types of input data they can use. Ensuring these models can represent cropping field heterogeneity and environmental impact is important, especially given the growing interest in using agroecosystem models to quantify ecosystem services from best management practices and land use ch…
Agriculture (2 works) · Geography (2 works) · Agricultural economics (1 work) · Agroecosystem (1 work) · Agronomy (1 work) · Algorithm (1 work) · Archaeology (1 work) · Artificial Intelligence (1 work) · Bioenergy (1 work) · Bioenergy crop production and management (1 work)