{"id":6257,"date":"2026-05-29T21:39:10","date_gmt":"2026-05-29T16:39:10","guid":{"rendered":"https:\/\/cifrum.kz\/sputnik-nisar-maisovyy-treugolnik-yuar-2026-en\/"},"modified":"2026-05-29T21:39:12","modified_gmt":"2026-05-29T16:39:12","slug":"sputnik-nisar-maisovyy-treugolnik-yuar-2026-en","status":"publish","type":"post","link":"https:\/\/cifrum.kz\/en\/sputnik-nisar-maisovyy-treugolnik-yuar-2026-en\/","title":{"rendered":"NISAR Satellite Images South Africa’s Maize Triangle"},"content":{"rendered":"
The NISAR satellite \u2014 a joint project of NASA and the Indian Space Research Organisation (ISRO) \u2014 has captured radar imagery of an agricultural area in the northern part of South Africa’s Free State province, covering a full growing season from November 2025 through March 2026. The data obtained were used to create a multicolor visualization reflecting the condition and dynamics of crops throughout the entire season. This was reported in a NASA Earth Observatory feature.<\/p>\n
The “Maize Triangle” and Its Agricultural Significance<\/h2>\n\n Illustrative photo. Source: science.nasa.gov<\/figcaption><\/figure>\n
The imaged area is located approximately 110 kilometers north of Bloemfontein, along the Vet River. Here, in the semi-arid part of Free State province, river water irrigates fields planted with a variety of crops. The region is part of what is known as the “Maize Triangle” \u2014 a zone encompassing the North West, Free State, Gauteng, and Mpumalanga provinces, which accounts for the bulk of the country’s maize production.<\/p>\n
The imagery clearly shows the circular fields characteristic of irrigated farming \u2014 the result of center-pivot irrigation systems \u2014 interspersed with rectangular plots. The combination of geometric shapes and a rich color palette gives the image a resemblance to abstract painting, yet each color carries specific physical information.<\/p>\n
How the NISAR Satellite Works and What the Colors Mean<\/h2>\n\n Illustrative photo. Source: science.nasa.gov<\/figcaption><\/figure>\n
The data for the visualization were collected during 10 passes of the NISAR satellite over the area between November 2025 and March 2026. The spacecraft uses an L-band radar capable of “seeing” the structure of vegetation rather than its color. The radar signal is directed toward Earth’s surface, and the character of its reflection is then measured \u2014 including the polarization of the returning waves, which carries information about plant and surface structure.<\/p>\n
Statistical indicators for each pixel, calculated from multiple observation dates, were combined into a single composite image. The resulting false-color visualization uses the following color coding:<\/p>\n
\n
Green<\/strong> \u2014 presence of vegetation cover;<\/li>\n
Red<\/strong> \u2014 absence of vegetation (bare surface);<\/li>\n
Blue<\/strong> \u2014 rate of change in vegetation cover throughout the season.<\/li>\n<\/ul>\n
Since most pixels contain a mixture of these characteristics, the resulting palette is rich and varied. For example, stable vegetation \u2014 such as forested areas \u2014 produces a light blue hue. Crops that change structure during the season, such as wheat and maize, appear as a darker blue. Fields where plants rapidly accumulate green biomass and are then harvested early take on an orange color \u2014 behavior characteristic of sunflowers in this region, although, as the feature notes, ground-truth verification is required to confirm specific crops on individual fields.<\/p>\n
Scientist’s Commentary: What the Data Reveal<\/h2>\n\n Illustrative photo. Source: science.nasa.gov<\/figcaption><\/figure>\n
“It’s a beautiful image, but it’s also telling us important things,” NASA quotes Paul Siqueira, a scientist at the University of Massachusetts Amherst and ecosystems lead for the NISAR science team. According to him, crops such as maize and sunflowers look different in NISAR imagery than forests do \u2014 owing to differences in plant size and growth periods.<\/p>\n
The data processing method itself is described in the feature as relatively straightforward, yet it is underpinned by a substantial body of information accumulated over several months of observations.<\/p>\n
NISAR: Objectives and Monitoring Prospects<\/h2>\n\n Illustrative photo. Source: science.nasa.gov<\/figcaption><\/figure>\n
The methodology developed makes it possible to track crop development, the effects of irrigation, and land-use changes across large areas in a reproducible manner. As the NISAR satellite continues to accumulate data, researchers plan to compare indicators across different seasons, document differences in growth dynamics between individual fields, and study how agricultural systems respond to water availability and climate variability. Similar approaches to agricultural data analysis are already being applied in other regions \u2014 for instance, AI in agriculture<\/a> is helping to determine optimal harvest timing.<\/p>\n
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