Search Results for author: Inbal Becker-Reshef

Found 3 papers, 2 papers with code

Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization

1 code implementation21 Sep 2020 Hannah Kerner, Ritvik Sahajpal, Sergii Skakun, Inbal Becker-Reshef, Brian Barker, Mehdi Hosseini, Estefania Puricelli, Patrick Gray

Crop type classification using satellite observations is an important tool for providing insights about planted area and enabling estimates of crop condition and yield, especially within the growing season when uncertainties around these quantities are highest.

General Classification Time Series

Rapid Response Crop Maps in Data Sparse Regions

1 code implementation23 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.

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.

General Classification

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