Remote Sensing Using the Thermal Infrared Spectrum Range

Introduction:

After the development of remote sensing technology, the study of the earth’s natural resources become easy. The term remote sensing stands for observing something from the distance. The sensing of some things can be done by using a remote sensor that is mounted on a suitable platform such as a ground-based, air-based, and satellite-based platform. The first remote sensing satellite was Landsat 1 which was launched in the late 1970s era. After the success of Landsat 1 the actual development of remote sensing technology takes off and several other satellites were launched for studying the natural resources of the earth (The Basic Concept of Remote Sensing).

Nowadays it is one of the important branches of remote sensing which can be used by the scientist for the new researches. The thermal remote sensing sensor measures the radiation of the thermal infrared region in the electromagnetic spectrum. Primarily the sensors detect the emitted energy from the targeted surface.

Process of Thermal Remote Sensing

Source of energy:

A first, most important element of any type of remote sensing. The source of energy can be natural (earth’s terrestrial longwave radiation, volcanic eruption, forest fire, and emitted energy from different geological features) and mam made (Industries, Road traffic, built-up land, etc).

Sensor:

A well-mounted sensor is also a very important key element of well working thermal remote sensing. A sensor may be mounted on the ground like a tower, building, etc, or air like a plane, helicopter, drone, etc, or a satellite platform which is situated at an average elevation of above 300km mean sea level.

1. Landsat.
2. Sentinel 5.
3. Modis (Moderate-resolution Imaging Spectroradiometer).
4. Thermal Infrared Multispectral Scanner (TIMS).
5. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER).

Fig. 1

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Fig. 4

All the four images from fir. 1 to fig. 4 is the satellite image of MOD11A1.006 Terra Land Surface Temperature and Emissivity Daily Global 1km captured on January 2020. (The MOD11A1 V6 product provides daily land surface temperature (LST) and emissivity values in a 1200 x 1200 kilometer grid. The temperature value is derived from the MOD11_L2 swath product. Above 30 degrees latitude, some pixels may have multiple observations where the criteria for clear-sky are met. When this occurs, the pixel value is the average of all qualifying observations. Provided along with both the day-time and night-time surface temperature bands and their quality indicator layers are MODIS bands 31 and 32 and six observation layers.)Images are collected by using the google earth engine platform. Google earth engine platform is a newly introduced platform for the Geographic information system users which available freely. There are different types of data present there which can access by free data such as Landsat time-series data, sentinel data sets, Modis NDVI, NDSI, Temperature data, Aster’s DEM data, and a lot more.

Convert data into Information:

data sets that are collected by using a remote sensing sensor have come in the form of binary. After that, it will convert it into a raster format which can access by the scientist and the society for application purposes.

Interpretation of Thermal imagery:

Interpretation of thermal imagery is not an easy task. For interpretating thermal imagery, an expert GEOGRAPHIC INFORMATION SYSTEM analysist uses some of the interpretation keys such as shape, size, pattern, tone color, etc. Based on these key elements of interpretation, the User of thermal imagery can able to interpretate thermal imagery.” Major application areas are discussed below”.

Wavelength and the spectral range of thermal remote sensing

The infrared portion of EMS is considered being from 0.7 – 1,000 μm. The infrared portion is divided majorly into three parts first near-infrared, the second one is mid-infrared and the last one is far-infrared. In general, for the terrestrial remote sensing purpose, the region of EMS is from 3 – 35 μm which is called thermal – infrared.

As in all other remote sensing missions, data acquisitions are made only in regions of least spectral absorption known as the atmospheric windows. Within the thermal infrared, an excellent atmospheric window lies between 8-14 μm wavelength. Poorer windows lie in 3-5 μm and 17-25 μm.

The thermal infrared region (TIR from 8 to 14 μm). This is the emitted energy from the Earth’s surface that is commonly used to map surface temperatures. The thermal region has been widely used in detecting vegetation evapotranspiration (ET), ice and cloud properties, urban heat effects, and rock discrimination (Fundamentals_of_satellite_remote sensing An environmental approach by [Chuvieco,_Emilio]).

Application of Thermal Remote Sensing

1. For the study of the urban environment
2. Volcanic study
3. Forest fire trend, monitoring
4. Coal Fires monitoring
5. Studies of hydrologic aspects
6. A better study of geological units and structures
7. Soil moisture content studies
8. Coastal change study
9. Environment monitoring
10. Heat loss from the building
11. Military application

Some important terms used for understanding the concept of Thermal Remote Sensing:

Thermal Capacity:

the capacity of the cover to store heat. The thermal capacity per mass unit is known as the specific heat (c).

Thermal diffusivity:

the measure of how well the temperature of the surface changes through heat conduction. For example, the dry surface show low-temperature changes in comparison to the wet surface with higher conductivity.

Thermal Inertia:

represents the resistance of a material to temperature changes. Directly related to thermal conductivity (K), the heat capacity (C), the density of material(D), described by the formula: –

Example of Thermal properties of vegetation which can be studied by Remote Sensing Sensor:

The plants absorb a high amount of incident coming solar heat to drive photosynthesis. Same the energy will reemitted during the night to maintain the balance of energy. Vegetation has a high content of water and would also have high thermal inertia. Another Eassinal factor of controlling the thermal pattern of vegetation is evapotranspiration (ET), which regulates the water and temperature of plants. The extra energy involved in releasing water vapor means a drop inappropriate heat and a parallel decline in plant surface temperature as vegetation transpires. For that reason, the plants showed to be cooler during the day than their surroundings. Most of the studied related plant health is based on the solar spectrum. Thermal images have also been extensively used to look at vegetation changes resulting from deforestation processes, desertification, or water stress (Curran 1985; Jackson et al. 1981; Moran et al. 1994; Nieto et al. 2011; Sandholt et al. 2002).

Fig. 5: Thermal inertia response curve of different land features classes. (Adapted from Short, N.M. and Stuart, L.M., The Heat Capacity Mapping Mission (HCMM) Anthology, NASA, Washington, DC, 1982.)