Spectral signature

Also called: Spectral reflectance curve · Topic: Remote Sensing, GIS and GNSS · NCERT: Class 11, Ch 6 "Introduction to Remote Sensing"

Meaning

A spectral signature is the pattern of how much energy an object reflects at different wavelengths. When this pattern is drawn as a graph, it is called a spectral reflectance curve. Each material has its own pattern, so it works like a fingerprint (NCERT Fig. 6.4). Satellites use these patterns to tell vegetation, soil and water apart in multispectral images. That is how land use, crop health and water quality are mapped from space.

Explanation

How a signature forms (cause → process → result)

• Cause: energy hits an object.
• Sunlight (electromagnetic radiation, or EMR) falls on a surface.

• The surface can absorb, transmit (let it pass through), reflect or emit this energy.

• Process: the share changes with wavelength.

• Reflectance is the share of incoming energy that a surface reflects.
• Absorptance is the share of incoming energy that a surface absorbs.

• The same surface may reflect a lot at one wavelength and very little at another.

• Result: a unique curve.

• If you plot reflectance against wavelength, you get a curve with its own peaks and dips.
• For example, sand reflects more than green vegetation at some wavelengths and less at others [4].
• Because of these differences, grasslands, pinewoods, red sand and silty water can each be told apart by their reflectance curves [4].

How a sensor reads the signature: spectral bands

• Spectral band: one chosen wavelength range in which a sensor records energy.
• A multispectral sensor records several bands at the same time. Together, these readings give a rough picture of the signature.
• Key NCERT bands:
• Green: 0.5–0.6 µm
• Red: 0.6–0.7 µm

• Near infrared (NIR): 0.7–1.1 µm. This band lies just past visible red, and the eye cannot see it.

• Multispectral sensors record reflected energy in the red, green, blue and infrared bands [4].

• NIR is the best band for separating vegetation, land and water. Healthy leaves reflect NIR strongly, while clear water absorbs it.

Signatures of the main surfaces

Surface	Blue / green	Red	NIR	How it looks
Healthy vegetation	Moderate (green peak)	Absorbed (used for photosynthesis)	Strongly reflected	Bright in NIR; red in standard false-colour images
Fresh, clear water	Some reflection	Absorbed	Absorbed	Dark
Turbid (muddy) water	Reflects more	—	—	Light, because suspended silt reflects light

• Why healthy leaves reflect NIR:
• 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.

• Why a stressed leaf shows up early:

• A stressed or dying leaf loses this layered structure, so its NIR reflectance drops.
• A satellite can detect this drop before the leaf looks brown to the eye.

Conditions and limits

• The atmosphere must let the energy through.
• Carbon dioxide, hydrogen and water vapour absorb middle infrared. These blocked ranges are called absorption bands [5].
• Dust and other particles scatter blue light (send it off in all directions).

• So sensors are tuned to atmospheric windows. These are wavelength ranges where the atmosphere is transparent, so energy passes through easily [4][5].

• Reflected signatures (visible and NIR) need sunlight. Thermal infrared (about 8–14 µm) is different. It records heat that the surface gives off (emits), so it works at night too.

• Signatures can look alike. Turbid water and wet soil, for example, can have similar patterns. Readings must therefore be checked against ground truth (data collected in the field).
• NDVI turns a signature into a single number.
• Formula: NDVI = (NIR − Red) ÷ (NIR + Red). The range is −1 to +1.
• Dense forest or healthy crops give a high value.
• Bare soil gives a value near 0.
• Water and clouds give negative values.

Where it occurs

• Sambhar Lake, Rajasthan (India's largest inland salt lake), NCERT Fig. 6.5:
• Its clear, deep parts look dark, because water absorbs red and NIR.

• Its shallow, muddy or salty parts look light, because they reflect more blue and green.

• Drought monitoring across India: NADAMS (National Agricultural Drought Assessment and Monitoring System):

• Started: end of 1986. Operational: 1990 [3].
• Run by: the National Remote Sensing Agency (now NRSC) under the Department of Space. It is supported by IMD and state agriculture departments [3].
• Method: this season's NDVI curve is compared with the normal NDVI for that place [3]. Today it also uses NDWI (Normalised Difference Wetness Index, which shows moisture), SASI (Shortwave Angle Slope Index), rainfall and crop-sown area. NRSC gives fortnightly NDVI products [3].
• Coverage: state, district and sub-district level [3].

• Sensors: Resourcesat AWiFS, Oceansat-2 OCM, NOAA AVHRR and Terra MODIS [3].

• TRISHNA (ISRO–CNES, France): this planned thermal infrared satellite will read heat signatures. It carries a 7-band VNIR-SWIR (visible, near infrared and short-wave infrared) sensor from ISRO [2]. It aims to detect water stress in crops, map urban heat islands and check water quality in coastal and inland waters [2].

• Worldwide: resource managers use multispectral signatures to monitor fragile lands, wetlands and forests [4].

Don't confuse with

• Spectral band vs spectral signature: a spectral band is one wavelength range that a sensor records, such as red at 0.6–0.7 µm. A spectral signature is the object's whole reflectance pattern across many wavelengths.
• Thermal (emitted) signature: thermal infrared (~8–14 µm) records heat that the surface gives off, so it works at night. A reflectance signature in the visible and NIR bands needs sunlight.
• Atmospheric window vs absorption band: an atmospheric window is a wavelength range that passes through the air easily, so sensors are placed there. An absorption band is a range blocked by gases such as water vapour, CO₂ and ozone [5]. The signature belongs to the ground object. Windows and absorption bands are properties of the air.
• NDVI: NDVI is a single number calculated from just two points on the signature (red and NIR). It is not the full curve.

Prelims Hooks

• Healthy vegetation: it absorbs red (for photosynthesis) and strongly reflects NIR (because of its many-layered leaf structure). It appears red in standard false-colour images.
• Clear water looks dark because it absorbs red and NIR. Turbid water looks light because silt reflects more blue and green. The NCERT example is Sambhar Lake, Rajasthan.
• Band ranges (NCERT): green 0.5–0.6 µm, red 0.6–0.7 µm, NIR 0.7–1.1 µm. Visible light as a whole is 0.4–0.7 µm [4].
• NDVI = (NIR − Red)/(NIR + Red), with a range of −1 to +1. Dense vegetation is high, bare soil is near 0, and water and clouds are negative.
• Trap: remote sensing uses visible, infrared and microwave. X-rays are NOT used (NCERT Class 11, Ch 6).
• Trap: a stressed plant's NIR reflectance falls before it looks brown. Satellites catch crop stress early.

Mains Points

• Drought and farm management (GS-III):
• Under NADAMS, NDVI from Resourcesat AWiFS and MODIS is read together with IMD rainfall. This gives fortnightly drought reports down to sub-district level [3].

• These reports guide drought declarations, contingency crop plans and crop insurance checks.

• Water security and climate adaptation:

• TRISHNA's thermal and VNIR-SWIR sensors are designed to measure crop water stress at 57 m and to map urban heat islands [2].

• This helps irrigation scheduling in water-scarce states and heat action plans for cities.

• Limits and how to fix them:

• Similar signatures, such as turbid water and wet soil, can confuse the reading. Monsoon clouds (June–September) also block optical sensors.
• So satellite signatures must be checked against ground truth. They should also be combined with microwave radar, which passes through cloud [4]. This is why NADAMS joins satellite indices with sown-area and rainfall data [3].

Related concepts

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

Read more

• Electromagnetic energy, the spectrum and spectral signatures