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Identify man-made & natural material, using high resolution SWIR imagery

by Rohit Kumar

SWIR (Shortwave Infrared) refers to a non-visible range of light falling between 1400-3000 nm in wavelength. SWIR light is same as visible light which reflects from minerals, man-made and natural structures due to the unique nature of the object, the resultant SWIR light shows shadow and contrast in its imagery (contrast depends upon the radiometric resolution of a sensor). Unlike visible light imagery, SWIR light image is not in colour, makes objects easily recognizable and yields one of the tactical advantages of the SWIR, namely, object or individual identification.

Applications of SWIR Sensors:

  • Mineral exploration.
  • Wildfire response(can penetrate through smoke).
  • Minerals and mining.
  • Identification of urban features.
  • Oil spill identification.
  • Soil moisture estimation.
  • Snow and ice discrimination.
  • Detect heat.

Identifying man-made materials
In SWIR wavelength, man-made materials reflect differently and show unique nature which is not possible in visible light spectrum, helps to distinguish materials that look similar to the naked eye. There are many reasons to understand the different types of man-made materials that are present in a particular area. Other examples of using SWIR to accurately classify man-made materials include an urban planner who needs to know building roof types to plan for fire mitigation, a transportation/logistics manager who needs to know road types to plan for material deliveries to job sites, or an analyst who needs to understand materials being used in new construction to determine the purpose of the construction. SWIR can answer these questions with satellite data that has not been available until now.

Figure1. Shows features distinguished in SWIR imagery.

                                                                                    Fig.1: ©DigitalGlobe

Fighting Fires

Whether called a forest fire, bush fire, or wildfire, uncontrolled fires have a devastating impact on communities and natural resources. Fast and effective detection is a key to protecting infrastructure and ensuring communities’ safety. While it seems that fires should be easy to see, there are often obstacles that get in the way. First, smoke obscures what the fire-fighters can see – both on the ground and from the air. Also, aerial imagery can see only the tops of trees and can give a false impression of how large a fire is on the ground. 

                                                                             Fig. 2: ©DigitalGlobe

Minerals and Mining

WorldView-3’s spectral bands allow for precise mineral identification and chemical measurements. Energy from light is either transferred to molecules of matter or reflected away from them. Based on the mineral content, different materials absorb specific wavelengths of light and reflect others.

The SWIR imagery available from WorldView-3 was designed with geological applications in mind. Electronic absorptions in the SWIR wavelengths can be used for detecting materials containing anion groups such as Al-OH, Mg-OH, Fe-OH, Si-OH, carbonates, ammonium, and sulphates – many of which are indicator minerals in the mining industry. Exposed outcrops are manifestations of potential mineral ores or sub-surface deposits. While the geological and mining industries spend millions of dollars to identify potential mining sites during their exploration phase, WorldView-3 SWIR data can cut costs and increase efficiency by narrowing the potential area before field verification is planned.


Detect heat

SWIR can be used for heat detection which may results from wildfire, volcanic eruptions, heat produced by factory machinery or anthropogenic activity.

                                                                              Fig. 3: ©DigitalGlobe


SATPALDA is a privately owned company and a leading provider of satellite imagery and GeoSpatial services to the user community. Established in 2002, SATPALDA has successfully completed wide range of photogrammetric and Remote Sensing Projects.

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