Validation of Automatically Generated Global and Regional Cropland Data Sets: The Case of Tanzania. - Juan Carlos Laso Bayas; Linda See; Christoph Perger; Christina Justice; Catherine Nakalembe; Jan Dempewolf; Steffen Fritz (Remote. Sens., 2017)

Field-Level Crop Type Classification with k Nearest Neighbors: A Baseline for a New Kenya Smallholder Dataset. - Hannah Kerner; Catherine Nakalembe; Inbal Becker-Reshef (CoRR, 2020)

Rapid Response Crop Maps in Data Sparse Regions. - Hannah Kerner; Gabriel Tseng; Inbal Becker-Reshef; Catherine Nakalembe; Brian Barker; Blake Munshell; Madhava Paliyam; Mehdi Hosseini (CoRR, 2020)

Learning To Predict Crop Type From Heterogeneous Sparse Labels Using Meta-Learning. - Gabriel Tseng; Hannah Kerner; Catherine Nakalembe; Inbal Becker-Reshef (CVPR Workshops, 2021)

CropHarvest: A global dataset for crop-type classification. - Gabriel Tseng; Ivan Zvonkov; Catherine Nakalembe; Hannah Kerner (NeurIPS Datasets and Benchmarks, 2021)

Using transfer learning to study burned area dynamics: A case study of refugee settlements in West Nile, Northern Uganda. - Robert Huppertz; Catherine Nakalembe; Hannah Kerner; Ramani Lachyan; Maxime Rischard (CoRR, 2021)

OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data. - Ivan Zvonkov; Gabriel Tseng; Catherine Nakalembe; Hannah Kerner (AAAI, 2023)

How accurate are existing land cover maps for agriculture in Sub-Saharan Africa? - Hannah Kerner; Catherine Nakalembe; Adam Yang 003; Ivan Zvonkov; Ryan McWeeny; Gabriel Tseng; Inbal Becker-Reshef (CoRR, 2023)

Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War. - Hannah Kerner; Catherine Nakalembe; Benjamin Yeh; Ivan Zvonkov; Sergii Skakun; Inbal Becker-Reshef; Amy McNally (CoRR, 2023)

Field-Scale Yield Estimation Using Remote Sensing Time-Aggregate Variables. - Isha Asalla; Diana Botchway Frimpong; Catherine Nakalembe (IGARSS, 2024)