Search Results for author: Catherine Nakalembe

Found 4 papers, 2 papers with code

How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?

1 code implementation5 Jul 2023 Hannah Kerner, Catherine Nakalembe, Adam Yang, Ivan Zvonkov, Ryan McWeeny, Gabriel Tseng, Inbal Becker-Reshef

Satellite Earth observations (EO) can provide affordable and timely information for assessing crop conditions and food production.

Using transfer learning to study burned area dynamics: A case study of refugee settlements in West Nile, Northern Uganda

no code implementations29 Jul 2021 Robert Huppertz, Catherine Nakalembe, Hannah Kerner, Ramani Lachyan, Maxime Rischard

By comparing the district-level BA dynamic with the wider West Nile region, we aim to add understanding of the land management impacts of refugee settlements on their surrounding environments.

Management Transfer Learning

Rapid Response Crop Maps in Data Sparse Regions

2 code implementations23 Jun 2020 Hannah Kerner, Gabriel Tseng, Inbal Becker-Reshef, Catherine Nakalembe, Brian Barker, Blake Munshell, Madhava Paliyam, Mehdi Hosseini

A major challenge for developing crop maps is that many regions do not have readily accessible ground truth data on croplands necessary for training and validating predictive models, and field campaigns are not feasible for collecting labels for rapid response.

Humanitarian

Field-Level Crop Type Classification with k Nearest Neighbors: A Baseline for a New Kenya Smallholder Dataset

no code implementations6 Apr 2020 Hannah Kerner, Catherine Nakalembe, Inbal Becker-Reshef

Accurate crop type maps provide critical information for ensuring food security, yet there has been limited research on crop type classification for smallholder agriculture, particularly in sub-Saharan Africa where risk of food insecurity is highest.

Classification General Classification

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