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NRG (NIR-Red-Green)
The primary purpose of this false-color image is to reflect the vegetation productivity of a given area. The abbreviation NRG provides a hint about the spectral bands included in the image. It combines reflected near-infrared radiation (NIR), red light (Red), and green light (Green). Information from the near-infrared spectrum is mapped to the red channel, red visible light is mapped to the green channel, and green visible light is mapped to the blue channel. In simpler terms, this means you see the information from these spectral bands in the respective colors assigned to each channel.
The NRG false-color image is particularly well-suited for monitoring changes in vegetation. Chlorophyll in plants reflects near-infrared radiation and green light effectively. Plants reflect near-infrared radiation most intensely, and since this is displayed through the red channel, photosynthesizing vegetation appears red in the image.
This map layer is both viewable and informative year-round. The seasonal color variations are visualized in Image 1. Generally, we observe that in early spring, the map layer features green tones. As summer progresses, it shifts to vibrant reds and pinks. In autumn, as temperatures drop and vegetation withers, the red tones fade back to greenish-gray (Image 1). During winter, when the ground is bare, the background remains greenish-gray. However, when snow covers the ground, the map layer becomes whiter and dimmer. Snow appears in familiar white tones on this false-color layer, while unfrozen water bodies without snow cover are shown in light blue tones.
When observing forest masses on summer satellite images, in the NRG color scheme, deciduous trees appear brighter red, while coniferous trees, which reflect less near-infrared radiation, appear darker (see an example of tree types in summer at Satilao here). As deciduous trees lose their green foliage and shed their leaves in early autumn, this difference becomes visible on satellite images. Evergreen coniferous trees remain cherry red in the satellite false-color images, while areas with leafless trees appear (brownish) green (observe the color changes between summer and late autumn conditions by clicking the comparison button <> below).
When a photosynthesizing plant reflects near-infrared radiation, green, and a small amount of red light, the reflection of green and near-infrared radiation is significantly reduced or absent in leafless or damaged trees, and the proportion of reflected red light increases significantly. Since this false-color image combination displays red light through the green channel, areas without foliage or with sparse vegetation appear green (Image 2).
To better distinguish deciduous forest masses from bare areas on winter satellite images, you can use the forest mask in the left menu of Satilao. In general, it is more suitable to use another color scheme—NGR—for differentiating forest types in summer. NRG is more appropriate for distinguishing forest types during the winter period.
In the NRG false-color combination, the shadows of trees and other taller objects are more prominently and contrastively visible (Images 3 and 4). These shadows provide insights into the three-dimensional properties of the terrain and objects, allowing a better understanding of their structure and profile. The length of shadows displayed on satellite images directly reflects the angle of sunlight. Therefore, in winter, when the sun's elevation is lower (daily maximum height) and light falls at a sharper angle, the shadows are longer and more clearly visible.
An interesting observation for forest masses is that with a high NDVI (Normalized Difference Vegetation Index), healthy photosynthesizing vegetation becomes a relatively uniform deep green. However, in the NRG scheme, the masses where photosynthesis is more intense (with a well-defined gradient of red tones) are slightly more distinguishable to the naked eye (Image 5). When using false-color images, it’s always worth experimenting a bit, as different derivatives or index layers may be more suitable under different conditions.
Bright red or pink tones also represent photosynthesizing agricultural fields and grasslands with taller or denser vegetation. Areas without vegetation, such as bare soil, appear green. While soil does reflect near-infrared radiation, the proportion of red light is greater, making bare ground appear light green in this color scheme. For this reason, mown grasslands and peat fields also appear light green on NRG false-color images.
While RGB satellite images can appear relatively muted during winter, the NRG color combination highlights features with strong contrast. For example, winter crops show up as vibrant, intense pink when the crops are more vigorous and dense. You can observe agricultural fields in various growth stages during winter in the diagram below (Image 5).
To visually and quickly identify and filter agricultural fields on a satellite image, we recommend using the bare area mask available in Satilao’s left menu (Image 7). Additionally, you can apply the PRIA agricultural field vector layer from the Boundaries button in the left menu if desired.
NRG generally enables the distinction of vegetated areas from other surfaces and environments, making it useful for highlighting green spaces. This allows urban planners and environmental specialists to assess the condition of green areas and networks, plan new green corridors, or enhance existing ones.
The animated example below demonstrates how ESTHub services can be integrated into various systems. In the X-GIS2 map application, ESTHub base maps are included, and the Muhu green network (outlined in green from comprehensive planning data) is visualized along with alternating Sentinel-2 imagery and NRG base maps. This comparison showcases planning vector data alongside satellite-derived information (the actual state of vegetation and the connectivity of green corridors).
Within the green outline areas, NRG highlights issues and potential opportunities to improve or better monitor vegetation conditions.
Clear and clean water bodies appear black on NRG false-color images because all radiation in the given spectral range is absorbed (Image 7). However, if a water body is overgrowing, green light may also be reflected. In the NRG false-color scheme, green light is displayed through the blue channel, which makes such eutrophic water bodies appear blue on the image (Image 8).
The color of water bodies is also influenced by sediments or turbidity, where light scattering increases. It can be said that such overgrown water bodies blend relatively well into the surrounding greenery on summer RGB images, whereas in NRG images, these water bodies stand out prominently with their blue hue.
Image 7. Comparison of Parika Lake in RGB (left) and NRG (right) images (reference to Satilattu for closer examination).
Image 8. Distinction of an overgrown water body in the comparison of RGB (left) and NRG (right) images (reference to Satilattu for closer examination).
For observing water bodies, a dedicated water body mask is available in the left menu of Satilao (Image 9). However, we note that in the case of narrow flowing water bodies, a so-called shoreline effect may occur. This happens when a single pixel covers more than one landscape type, such as both water and land. As a result, the river's contour may appear blurry or imprecise on the image.
If the goal is to accurately assess water quality, lower-resolution satellite images may not be suitable or are better suited for preliminary or indicative results. For detailed analysis and precision, higher-resolution data should be used. Alternatively, the water body mask can be useful for highlighting ditches or smaller water bodies in an area that may not clearly stand out due to their small size and the satellite image's limited resolution.
Image 9. Applying the water body mask (reference to Satilattu for closer examination).
Certain vegetation anomalies, such as wildfires, are well-highlighted in the NRG spectral combination (Image 10). By comparing satellite images and vegetation indices or other false-color images available in Satilao across different time periods, it is possible to assess how quickly and to what extent vegetation recovers after a fire.
Satilao provides an archive of Sentinel-2 images dating back to 2015, enabling the analysis and comparison of land cover changes over an extended period.
Image 10. Area damaged by fire near Aegviidu, comparison of RGB (top) and NRG (bottom) images (reference to Satilattu for closer examination).
Artificial surfaces and various man-made structures appear in the NRG image with a greenish-light blue hue (Image 11). For example, roads, bridges, larger solar panel structures, port facilities (Image 12), mining areas (Image 13), larger buildings, parking areas, and much more can be distinguished. Due to the relatively small dimensions of these man-made structures, satellite imagery is primarily useful for detecting initial changes. For instance, in Satiladu, it is possible to compare satellite images from two different dates. An illustrative example of port facility construction in a comparison between 2015 and 2024 is shown in illustration 12 (Image 12).
Image 11. Visualization of urban infrastructure in an NRG false-color image using the example of the city of Tartu.
Image 12. Construction of port facilities in a comparison between 2015 and 2024.
Image 13. Mines appear in NRG color tones with a bluish-green hue (illustrated by the Estonia mine).
Wetlands often appear brown rather than green in RGB images, primarily due to their unique vegetation and environmental conditions. While the chlorophyll in typical green vegetation reflects green light, wetland vegetation consists of plants adapted to nutrient-poor and water-saturated conditions. These plants often exhibit brownish or reddish tones, as their pigments, such as tannins or anthocyanins, absorb more red and blue light and reflect less green light. Additionally, the accumulation of organic material in waterlogged conditions, including partially decomposed plant matter, also contributes to the brownish tones.
Thus, wetlands have lower values in the green spectrum and higher proportions of red light. In an NRG false-color image, red light information is displayed through the green channel, causing wetlands to primarily appear in green tones, while areas with more green photosynthetic vegetation, such as coniferous forests, are displayed in red tones (Image 14).
Image 14. In the NRG false-color image (right), wetlands primarily appear in green tones. For comparison, the regular RGB photograph is on the left.
Note! Cloud shadows generally appear in a relatively contrasting black color on NRG satellite images (Image 15). This is the case when the clouds are opaque or only slightly transparent. Cloud veils are quite visually identifiable, but it's important to note that near the cloud, there can also be a shadow that, in the case of a veil, might be subtly faint (Image 16). Such faint shadows, if not noticed, can lead to incorrect interpretation of the information, as it may seem like a color gradient change in the vegetation.
Image 15. In the NRG false-color image, clouds appear in the usual white tone, and cloud shadows are contrasted in black.
Image 16. Example of a cloud haze in the NRG false-color image that requires attention.