Rapid Response Crop Maps in Data Sparse Regions

by   Hannah Kerner, et al.
University of Maryland

Spatial information on cropland distribution, often called cropland or crop maps, are critical inputs for a wide range of agriculture and food security analyses and decisions. However, high-resolution cropland maps are not readily available for most countries, especially in regions dominated by smallholder farming (e.g., sub-Saharan Africa). These maps are especially critical in times of crisis when decision makers need to rapidly design and enact agriculture-related policies and mitigation strategies, including providing humanitarian assistance, dispersing targeted aid, or boosting productivity for farmers. 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. We present a method for rapid mapping of croplands in regions where little to no ground data is available. We present results for this method in Togo, where we delivered a high-resolution (10 m) cropland map in under 10 days to facilitate rapid response to the COVID-19 pandemic by the Togolese government. This demonstrated a successful transition of machine learning applications research to operational rapid response in a real humanitarian crisis. All maps, data, and code are publicly available to enable future research and operational systems in data-sparse regions.


page 3

page 4


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

Satellite Earth observations (EO) can provide affordable and timely info...

Satellite-based high-resolution maps of cocoa planted area for Côte d'Ivoire and Ghana

Côte d'Ivoire and Ghana, the world's largest producers of cocoa, account...

Q-RBSA: High-Resolution 3D EBSD Map Generation Using An Efficient Quaternion Transformer Network

Gathering 3D material microstructural information is time-consuming, exp...

Data science on industrial data – Today's challenges in brown field applications

Much research is done on data analytics and machine learning. In industr...

Micro-Estimates of Wealth for all Low- and Middle-Income Countries

Many critical policy decisions, from strategic investments to the alloca...

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 s...

Please sign up or login with your details

Forgot password? Click here to reset