Anupma Prakash 
  
3.1.1 Active versus passive mode: Most of the thermal sensors acquire data passively, i.e. they measure the radiations 
emitted naturally by the target/ground. Data can also be acquired in the TIR actively deploying laser beams (LIDAR). 
However, these techniques are not well researched and are only in the infancy. 
3.1.2 Broad band versus multispectral mode: For the broad band thermal sensing, in general the 8 to 14 um 
atmospheric window is utilised. However, some spaceborne thermal sensors such as Landsat Thematic Mapper Band 6 
operate in the wavelength range of 10.4 to 12.6 jum to avoid the ozone absorption peak which is located at 9.6 um. The 
multispectral thermal channels, such as those in the ASTER platform, are targeted specially for geological applications. 
3.1.3 Daytime versus night-time acquisition: Thermal data can be acquired during the day and during the night. For 
some applications it is useful to have data from both the times. However, for many applications night-time or more 
specifically pre-dawn images are preferred as during this time the effect of differential solar heating is the minimal. 
The platforms for such data acquisitions range from satellites, aircrafts to ground based scanners. 
32 Spatial resolution and geometric correction 
Most thermal sensors have onboard recording and calibration systems. Two black bodies (BB) commonly known as 
BB1 and BB2 are setup which control the radiometric calibration of the acquired data. As the sensors measure emitted 
radiations, there is also a heating effect and constant cooling of the sensors is required. This poses a physical limit to the 
measuring capability of the sensors and therefore the spatial resolution of the acquired data. The coarse spatial 
resolution, specially of satellite borne broad band thermal data poses some additional problems in geometrically 
registering it to other data, specially when the latter have much higher spatial resolution. Identification of corresponding 
reliable control points on data sets with such wide differences in spatial resolution is not only difficult but when tried 
may result in unacceptable transformation results. Alternate approaches of co-registration must be thought of. This may 
be done by first registering the thermal image to another image with intermediate spatial resolution and in the next step 
to the target high resolution image. For details on this two step transformation the readers are referred to the paper by 
Prakash et al. 1999. 
4 APPLICATIONS 
Thermal property of a material is representative of upper several centimetres of the surface. As in thermal remote 
sensing we measure the emitted radiations, it proves to be complementary to other remote sensing data and even unique 
in helping to identify surface materials and features such as rock types, soil moisture, geothermal anomalies etc. The 
ability to record variations in infrared radiation has advantage in extending our observation of many types of 
phenomena in which minor temperature variations may be significant in understanding our environment. Thermal 
remote sensing reserves immense potential for various applications. The following is a list of some of the areas in which 
thermal data is put to use 
Identification of geological units and structures 
Soil moisture studies 
Hydrology 
Coastal zones 
Volcanology 
Forest fires 
Coal fires 
Seismology 
Environmental modelling 
Meteorology 
Medical sciences 
Vetenary sciences 
Intelligence / military applications 
Heat loss from buildings 
Others 
  
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