Fields of Tomorrow

Watch how the world's leading producers of staple cereal crops—specifically rice (milled), wheat, and coarse grains—have changed from 1961 to 2007. This animated bar chart vividly illustrates the annual rankings of these key crops, showing how national production volumes in million tonnes have grown, declined, or remained stable over the decades.

The visualization highlights the consistent dominance of China, India, and the United States in global cereal production, while also illustrating the steady rise of other countries such as Indonesia and Brazil. These trends help pinpoint regions that have become key players in global food security.

This visualization explores three important aspects of sustainable agriculture: land use, fertilizer usage, and water resource utilization. For each continent, it becomes clear how agricultural land area (% of total land), fertilizer consumption (kilograms per hectare of arable land), and agricultural water withdrawal (% of total renewable water resources) have changed over time. The map's color intensity reflects the magnitude of each indicator—darker colors indicate higher values.

The interactive design allows you to follow the progression of these indicators automatically, or to manually explore specific years for more detailed insights. From these visualizations, you can see regions with intensive land and fertilizer use—often linked to both high productivity and environmental challenges. The water use data reveals areas at risk of over-extracting water for farming, which can threaten future supplies. Together, these indicators paint a clear picture of the balancing act between agricultural output and sustainability.

This section showcases six radar charts comparing key sustainability factors for different regions. We analyzed agricultural production data from 1961 to 2007 and performed polynomial regression on five critical dimensions: land use, fertilizer intensity, cropland stability, agro-economic advancement, and water use efficiency.

Polynomial regression was chosen over linear models because agricultural systems often experience non-linear trends and interactions over time. The resulting coefficients—plotted in the radar charts—capture how strongly each factor influences agricultural production within each region.

By hovering over each radar chart, you can view specific numeric values and accompanying descriptions, offering a more detailed understanding of each region's sustainability profile. This analysis helps us understand the balance and trade-offs in agricultural sustainability. For example, regions with high fertilizer intensity coefficients might be relying more heavily on chemical inputs, while those with higher water use efficiency may have more resilient production systems. By comparing these patterns, we gain insights into how different regions prioritize and manage key resources—highlighting pathways for sustainable intensification and future agricultural development.