NDVI

Also called: Normalised Difference Vegetation Index · Topic: Remote Sensing, GIS and GNSS · NCERT: Beyond NCERT

Meaning

NDVI (Normalised Difference Vegetation Index) is a number that shows how green and healthy plants are. It is worked out from two bands: red light and near infrared (NIR). The formula is NDVI = (NIR − Red) ÷ (NIR + Red), and the value always lies between −1 and +1.

It matters because satellites can use it to watch crops, forests and drought over very large areas, again and again. In India it is the main index behind national agricultural drought monitoring [1].

Explanation

How it works: why healthy plants give high NDVI

• Plants absorb red light.
• Chlorophyll (the green pigment in leaves) uses red light (0.6–0.7 µm) for photosynthesis.

• So very little red light is reflected back to the satellite.

• Plants reflect near infrared (NIR) strongly.

• NIR (0.7–1.1 µm) is the band just beyond visible red. The human eye cannot see it.

• A healthy leaf has many internal layers of cells and air spaces. NIR light bounces many times inside these layers and is sent back out.

• Result: a healthy plant shows high NIR and low red. NIR minus red is a large number, so NDVI is high.

• Stressed plants show it early.
• A stressed or dying leaf loses its layered structure, so it reflects less NIR.
• NDVI therefore falls before the leaf looks brown to the eye.

The formula and how to read the values

• NDVI = (NIR − Red) ÷ (NIR + Red)
• The top part (difference) measures how far apart the two bands are.
• The bottom part (sum) "normalises" the result. Dividing by the sum turns it into a ratio, so it always stays between −1 and +1. This also lets you compare places that look brighter or darker overall.

Surface	NIR vs red	NDVI value
Dense, healthy forest or crops	NIR much higher than red	High, close to +1
Bare soil	NIR and red roughly equal	Near 0
Water and clouds	Red equal to or higher than NIR (clear water absorbs NIR)	Negative

• This follows from the spectral signature (an object's pattern of reflectance across wavelengths, unique like a fingerprint). NDVI turns the vegetation "fingerprint" into one simple number.

Conditions it needs

• Sunlight: red and NIR record reflected sunlight. So NDVI cannot be measured at night. Thermal infrared is different because it records heat the surface gives off.
• Clear skies: red and NIR are optical bands, which means clouds block them. During the Indian monsoon (June–September), cloud cover can hide the ground.
• A multispectral sensor: a sensor that records several bands at once, including red and NIR.

Using NDVI over time

• A single NDVI image shows how green an area is on one date.
• For drought, experts compare this season's NDVI curve with the normal NDVI for the same place [1].
• If the current curve stays well below normal, crops are under stress, which signals agricultural drought.

Where it occurs

• India: NADAMS (National Agricultural Drought Assessment and Monitoring System)
• Started: at the end of 1986. Operational: in 1990 [1].
• Who runs it: the National Remote Sensing Agency (now NRSC) under the Department of Space, supported by IMD and state agriculture departments [1].
• What it reports: how widespread, how severe and how long-lasting agricultural drought is, at state, district and sub-district level [1].
• Early method: NDVI combined with IMD rainfall data [1].

• Current method: NDVI plus NDWI, SASI, and ground data on rainfall and crop-sown area. NRSC produces fortnightly NDVI products [1].

• Satellites and sensors used [1]:

• Indian: Resourcesat AWiFS and Oceansat-2 OCM.

• Foreign: NOAA AVHRR (USA) and Terra MODIS (NASA).

• Wider use: resource managers use multispectral red, green, blue and infrared data to monitor fragile lands, wetlands and forests [2]. NDVI is one of the main tools for this.

Don't confuse with

• NDWI (Normalised Difference Wetness Index): NDWI measures moisture. NDVI measures greenness and plant health. NADAMS uses both together [1].
• Thermal infrared sensing (e.g. TRISHNA): thermal infrared records heat given off by the surface (about 8–14 µm), so it works at night. NDVI uses reflected sunlight in red and NIR, so it works only in daylight.
• Standard false-colour composite: this is an image, where healthy vegetation looks red because NIR is shown in red. NDVI is a calculated number for each pixel, not a colour picture.
• Green band (0.5–0.6 µm): leaves look green to the eye, but NDVI does not use the green band. It uses red (0.6–0.7 µm) and NIR (0.7–1.1 µm).

Prelims Hooks

• NDVI = (NIR − Red) ÷ (NIR + Red). Range: −1 to +1.
• Reading the values: dense healthy vegetation gives a high value, bare soil gives about 0, and water and clouds give negative values.
• Why it works: healthy leaves absorb red (photosynthesis) and strongly reflect NIR (many-layered leaf structure).
• NADAMS: started at the end of 1986, operational in 1990, run by NRSC with IMD support. It reports drought down to sub-district level [1].
• Sensors for NDVI in NADAMS: Resourcesat AWiFS, Oceansat-2 OCM, NOAA AVHRR, Terra MODIS. NRSC gives fortnightly NDVI products [1].
• Trap: NDVI needs sunlight and clear skies, because visible and NIR are reflected sunlight. It does not work at night or through thick cloud. Thermal infrared and microwave radar are the sensors that get past those limits.

Mains Points

• Drought governance and farm support (GS-III): NADAMS reads NDVI from Resourcesat AWiFS and MODIS together with IMD rainfall data and produces fortnightly drought reports down to sub-district level [1].
• These reports guide drought declarations and contingency crop plans.

• They also help check crop insurance claims.

• Limits of NDVI and how to handle them:

• Optical bands cannot see through monsoon cloud, which is when kharif crops grow. Microwave radar, which passes through cloud, can fill these gaps [2].
• Different surfaces can have similar spectral signatures. So satellite readings must be checked against ground truth (field data).

• This is why NADAMS now combines NDVI with NDWI, SASI, rainfall and crop-sown-area data [1].

• Early warning instead of late relief: NDVI falls when leaves lose their internal structure, before crops look brown. By comparing the current NDVI curve with the normal curve [1], states can act early with irrigation advice, seed for alternate crops and fodder planning.

Related concepts

• Electromagnetic radiation
• Electromagnetic spectrum
• Spectral band
• Near infrared
• Atmospheric absorption and scattering
• Thermal infrared remote sensing
• Reflectance
• Absorptance
• Spectral signature

Read more

• Electromagnetic energy, the spectrum and spectral signatures