Painting the Growing Season in the Maize Triangle

A visualization of agricultural land in South Africa shows geometric fields in an array of colors that combine red, green, and blue.

A false-color composite derived from NISAR data highlights vegetated areas (green), unvegetated surfaces (red), and how rapidly vegetated areas changed (blue) during the 2025-2026 growing season in an agricultural region of South Africa. Most pixels contain a mix of these colors, producing the visualization’s rich and varied color palette.

Along the Vetrivier (Vet River) in South Africa, a patchwork of circular and rectangular fields spreads across what is otherwise a semi-arid part of the Free State province. The water brings life to an array of crops, contributing to the agricultural productivity of the wider Maize Triangle.

The agricultural area shown in this image lies about 110 kilometers (70 miles) north of Bloemfontein. The scene is reminiscent of a modern abstract painting. Colorful circles mingle with straight-edged fields in combinations of red, green, and blue. But each color carries physical meaning, providing clues about crop types and revealing how they changed over the course of the Southern Hemisphere’s growing season.

Data for the visualization were acquired by the NISAR (NASA-ISRO Synthetic Aperture Radar) satellite during 10 passes over the area between November 2025 and March 2026. L-band radar observations, which can “see” vegetation’s structure instead of its color, were analyzed to produce per-pixel statistical measures across the scene. By combining radar scattering behaviors observed across multiple dates into a single composite, scientists built a compact summary of seasonal agricultural activity and change.

“It’s a pretty picture, but there are also important things that it communicates to us,” said Paul Siqueira, a scientist at the University of Massachusetts Amherst, and ecosystems lead of the NISAR science team. “With NISAR, crops like maize and sunflower appear differently than forests because of their size differences and period of growth.”

In this false-color composite, green indicates a vegetated area; red represents an unvegetated surface; and blue indicates how rapidly a vegetated area changed over the season. For instance, stable vegetation—such as forested areas—display a light blue component. Plants that change structure throughout the season, such as wheat and maize (corn), have a darker blue component.

In practice, most pixels contain a mix of these colors, producing the visualization’s rich and varied palette. For example, plants that grow rapidly (contributing some green) and are harvested early (contributing a large red component) make fields appear orange. Sunflowers are known to exhibit this pattern in the region, though ground validation would be needed to confirm their presence in any given field.

The processing behind the visualization is relatively straightforward, but it is based on a large amount of data. NISAR sends radar signals to Earth and measures how they bounce back; the orientation of the returned radar waves (cross-polarized or co-polarized) carries information about the structure of vegetation and surfaces. By combining radar measurements from multiple satellite passes and calculating statistics for each pixel, scientists built the detailed map of the landscape’s characteristics throughout the growing season.

The technique provides a repeatable way to monitor crop development, the impacts of irrigation, and land-use change across large regions. As NISAR collects more data, researchers will be able to compare seasons, track field-to-field differences in growth patterns, and better understand how agricultural systems respond to water availability and climate variability.

Image by Paul Siqueira (UMass Amherst) of the NISAR science team using data from the NISAR GCOV product, and prepared for NASA Earth Observatory by Michala Garrison. Story by Kathryn Hansen.