Nearly 70% of the world’s poor live in rural areas and rely on agriculture for their livelihood. Target 2.3 of the Sustainable Development Goals (SDGs) aims to double the agricultural productivity and incomes of small-scale food producers by 2030.

Timely, cost-effective, and high-quality crop statistics play an important role in the formulation of policies targeting poverty reduction, agricultural growth, and the welfare of agricultural households. They are also central to monitor progress on achieving SDG 2.

Traditional methods for estimating crop yield involve collecting field data, through either administrative reporting systems or sample surveys. Both methods are time-consuming, expensive, and results are unlikely to reach policy makers in time for planning purposes.

Remote sensing technology, on the other hand, holds a lot of promise for producing timely and accurate yield data, allowing for crop forecasting across space and time...  — blog.adb.org/blogs