Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Stefania Di Tommaso

Biographic Data

ID6929699
NAMEStefania Di Tommaso
GIVEN NAMESStefania
FAMILY NAMEDi Tommaso
SIGNATUREDI TOMMASO S
AFFILIATIONSStanford University
ORCID0000-0002-0664-3651
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2025
H-INDEX0
  • Precrop payoffs

    Open Access•Dan M Kluger, Stefania Di Tommaso et al.•ARTICLE•Environmental Research Letters•2025

    Building sustainable food systems that are resilient to climate change will require improved agricultural management and policy. One common practice that is well-known to benefit crop yields is crop rotation, yet there remains limited understanding of how the benefits of crop rotation vary for different crop sequences and for different weather conditions. To address these gaps, we leverage crop type maps, satellite data, and causal machine learni…

  • The mixed effects of recent cover crop adoption on US cropland productivity

    Open Access•David B Lobell, Stefania Di Tommaso et al.•ARTICLE•Nature Sustainability•2025•References: 1

  • Combining Gedi and Sentinel-2 for wall-to-wall mapping of tall and short crops

    Open Access•Stefania Di Tommaso, Sherrie Wang et al.•ARTICLE•Environmental Research Letters•2021

    High resolution crop type maps are an important tool for improving food security, and remote sensing is increasingly used to create such maps in regions that possess ground truth labels for model training. However, these labels are absent in many regions, and models trained on optical satellite features often exhibit low performance when transferred across geographies. Here we explore the use of NASA’s global ecosystem dynamics investigation (GED…

No prominent works on this page.

  • Combining Gedi and Sentinel-2 for wall-to-wall mapping of tall and short crops

    Open Access•Stefania Di Tommaso, Sherrie Wang et al.•ARTICLE•Environmental Research Letters•2021

    High resolution crop type maps are an important tool for improving food security, and remote sensing is increasingly used to create such maps in regions that possess ground truth labels for model training. However, these labels are absent in many regions, and models trained on optical satellite features often exhibit low performance when transferred across geographies. Here we explore the use of NASA’s global ecosystem dynamics investigation (GED…

  • Precrop payoffs

    Open Access•Dan M Kluger, Stefania Di Tommaso et al.•ARTICLE•Environmental Research Letters•2025

    Building sustainable food systems that are resilient to climate change will require improved agricultural management and policy. One common practice that is well-known to benefit crop yields is crop rotation, yet there remains limited understanding of how the benefits of crop rotation vary for different crop sequences and for different weather conditions. To address these gaps, we leverage crop type maps, satellite data, and causal machine learni…

  • The mixed effects of recent cover crop adoption on US cropland productivity

    Open Access•David B Lobell, Stefania Di Tommaso et al.•ARTICLE•Nature Sustainability•2025•References: 1

Crop (3 works) · Agricultural Economics and Policy (2 works) · Environmental Science (2 works) · Agricultural economics (1 works) · Agricultural engineering (1 works) · Agricultural risk and resilience (1 works) · Agriculture (1 works) · Agroforestry (1 works) · Agronomy (1 works) · Artificial Intelligence (1 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae