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What is NDVI (Normalized Vegetation Index)?

Updated: Oct 28

Simply seeing how much "green" a field actually is isn't always enough. Especially when we're talking about large areas, some technology is essential. Did you know we can measure the health of plants remotely, and even numerically? NDVI does exactly that. It helps us understand the condition of soil, fields, and forests by looking at satellite imagery. Without further ado, let's take a detailed look at what NDVI is and where it's used.


Contents


What is NDVI?

The Normalized Difference Vegetation Index (NDVI) is an indicator of plant health by quantifying the "greenness" of vegetation in an area. NDVI is calculated using reflectance data from the near-infrared (NIR) and red bands of satellite imagery. Healthy plants absorb red light due to chlorophyll and strongly reflect near-infrared light. The NDVI formula is obtained by normalizing this difference:

NDVI = (NIR - Red) / (NIR + Red)
NDVI plant health
NDVI ile Bitki Sağlığı Analizi

This formula gives the NDVI a value between -1 and +1 . On surfaces devoid of vegetation, such as water surfaces or thick clouds, the NDVI value is generally 0 or negative because the red and NIR reflectances are similar; on bare ground with very sparse or no vegetation, the value is generally close to zero . On the other hand, dense and healthy vegetation (for example, forested areas or fertile agricultural land) can increase the NDVI to values as high as +0.6–+0.8 . In short, a high NDVI value is directly proportional to the amount and vibrancy of green vegetation in the area, while a low NDVI indicates areas devoid of vegetation or under stress.

Interpretation of NDVI Values

Land types and vegetation density according to the NDVI range can be interpreted as follows (approximate value ranges):

NDVI plant value range
NDVI Değer Aralığı

  • NDVI ≤ 0 : Typically water bodies or thick cloud scenes (e.g. lakes, seas).

  • NDVI 0 – 0.1 : Clear soil, rocks, desertified areas or snow-covered surfaces.

  • NDVI 0.1 – 0.3 : Areas with grass, shrubs or sparse vegetation.

  • NDVI 0.6 – 0.8 and above: Densely forested areas and strong vegetation.

For example, according to NASA observations, very low NDVI values below 0.1 correspond to bare surfaces such as rock, sand, or snow, while high values between 0.6 and 0.8 indicate dense, healthy vegetation such as tropical rainforests. Furthermore, on satellite NDVI maps, dark green colors indicate high vegetation density (high NDVI), while light brown/pale shades indicate bare land.

NDVI Formula Explanation

The variables in the NDVI formula are defined as NIR (near-infrared reflectance) and Red (red reflectance). Chlorophyll in plants absorbs a high amount of red light (hence low red reflectance) and strongly reflects near-infrared light. Due to this biochemical property, living vegetation increases NIR reflectance and decreases Red reflectance . The NDVI formula normalizes this difference:

  • In case of high NDVI: NIR >> Red, i.e. if there is green and living vegetation, the result of the formula approaches +1.

  • Low NDVI: When Red >> NIR, i.e. if there are no plants or they are stressed, the formula result approaches -1.

Let's consider Landsat satellite data as an example use of the formula: On Landsat 8–9, the NIR band is Band 5, the red band is Band 4, and NDVI is calculated as:

NDVI = (Band5 - Band4) / (Band5 + Band4).

In Landsat 4–7, NIR is Band 4 and red is Band 3. Similarly, in Sentinel-2 satellite, NDVI is calculated using B8 (NIR) and B4 (red).

Application Areas of NDVI

The plant health indicator provided by NDVI is used as a decision-support tool in many areas. Key application examples include:

  • Agriculture (Precision Agriculture and Yield Estimation): Farmers use NDVI maps to monitor plant health and yields in their fields. Plant stress, lack of irrigation, or nutrient deficiencies can be identified by decreases in NDVI. For example, wheat and sunflower producers in Tekirdağ, Turkey, monitor their fields using NDVI maps derived from satellite imagery. The data shows that fields with higher NDVI values also have relatively higher yields (one field with an NDVI of ~0.7 yielded ~6.5–7 tons/ha, while another field with an NDVI of ~0.4 yielded ~3.5–4 tons/ha). This allows interventions in unproductive areas and optimization of fertilizer and water distribution.

    NDVI vegetation sentinel2
    Sentinel-2 Verileriyle Konya Bölgesi NDVI Haritası

  • Forestry and Ecosystem Monitoring: In forest ecosystems, NDVI is used to estimate forest canopy health, leaf area index (LAI), and biomass. For example, forest degradation or growth rate in a region can be monitored using NDVI data calculated at regular intervals. A high NDVI indicates dense leaf cover and high photosynthetic activity, while a low NDVI indicates declining or thinning forest areas.

  • Drought and Desertification Monitoring: NASA and other organizations use NDVI as a drought indicator. Prolonged water scarcity results in decreased chlorophyll in plants, lowering NDVI values. Agricultural engineering and meteorological organizations use NDVI declines below certain thresholds to issue drought warnings. NDVI analysis is also used to monitor vegetation damage in post-fire areas or as early warnings for forest fires.

    NDVI drought map
    Kuraklık Analizinde NDVI Haritaları

  • Environmental and Climate Research: NDVI data are used for environmental studies such as global vegetation change, the impacts of climate change, and soil erosion. Long-term satellite-based NDVI datasets are used to examine trends in deforestation and desertification, changes in biodiversity zones, and the carbon cycle.

NDVI Satellite and Data Sources

Imagery from remote sensing satellites is used to calculate NDVI. The most common sources today include satellite systems such as Landsat (NASA/USGS), Sentinel-2 (ESA), and MODIS (NASA). NDVI maps can be created using the red and near-infrared bands of these satellites. For example, NDVI is calculated by combining the NIR and red bands with data from Landsat 8. Other satellites such as SPOT and NOAA also offer similar band combinations. Additionally, up-to-date NDVI data is available in freely available archives (e.g., Sentinel-2, Landsat, and AVHRR-based datasets) accessible through platforms like Google Earth Engine.

As a result, the NDVI index is used as a universal indicator for monitoring vegetative cover density and health. In Turkey, NDVI analyses are becoming increasingly common in precision agriculture, drought monitoring, and ecosystem assessments in agriculture and forestry. The resulting NDVI maps objectively reveal changes in natural areas and agricultural performance, particularly through seasonal and annual comparisons.

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