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Found 5 papers, 3 papers with code
How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?
Satellite Earth observations (EO) can provide affordable and timely information for assessing crop conditions and food production.
Rapid Response Crop Maps in Data Sparse Regions
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.
Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization
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.
Field-Level Crop Type Classification with k Nearest Neighbors: A Baseline for a New Kenya Smallholder Dataset
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.
Improve State-Level Wheat Yield Forecasts in Kazakhstan on GEOGLAM's EO Data by Leveraging A Simple Spatial-Aware Technique
Accurate yield forecasting is essential for making informed policies and long-term decisions for food security.
