Part 2 LN

• Thermal, Hyperspectral and Microwave Remote Sensing
• GEM104: Thermal, Hyperspectral and Microwave Remote Sensing
• In this module we will learn about the gamut of thermal imaging. First we are going to learn about the across-track thermal scanning mechanism. Then we are going to learn about the thermal radiation principles, interpret thermal scanner imagery, analyse the geometric characteristics of across-track scanner imagery, temperature mapping with thermal scanner data, FLIR systems, and thermal scanners. We will know the radiant temperature, kinetic temperature, real body and black body radiations. We will learn about the geometric distortions found in thermal imagery. Then we will learn about thermal remote sensing, Planck Radiation Law, diurnal-heating effects, thermal properties of water, various thermal sensors. We will discuss heat capacity mapping mission and other weather satellites. Next we will learn what is hyperspectral remote sensing or understand the main concept of hyperspectral remote sensing, why it is necessary to find out certain subtle mineral composition of rocks, vegetation. We will discuss the usefulness of hyperspectral sensing in forestry applications and to understand the crown features and also we will learn some satellites carrying hyperspectral sensors. Finally the last topic we will study is the concept, fundamentals or principals of microwave remote sensing, the radar altimeter and microwave radiometer.
• The approach of study or learning will be section by section or sub-topic by sub-topic until we will complete all mode of study.
• Rationale for interpretation of Thermal Scanner Imagery

  Potential applications
• Thermal Scanner


  Many Multi-Spectral Systems (MSS) sense radiation in the thermal infrared as well as the visible and reflected infrared portions of the spectrum
• FLIR Systems


  Thermal imagers are typically across-track scanners that detect emitted radiation in only the thermal portion of the spectrum
• The Warm Earth: Thermal Remote Sensing


  Thermal sensors essentially measure the surface temperature and thermal properties of targets
• Heat Capacity, Thermal Conductivity, Thermal Inertia


  Some Problems and Solutions - Stuff for Critical thinking
• Diurnal Heating Effects


  Some Problems and Solutions - Stuff for Critical thinking
• Thermal Properties of Water


  Some Problems and Solutions - Stuff for Critical thinking
• The Heat Capacity Mapping Mission (HCMM)


  Weather Satellites
• Hyperspectral Remote Sensing


  Concept, meaning and utility
• Satellites carrying hyperspectral sensors

  ARIES-1, ORBIMAGE's OrbView-4, NASA's QuikTOMS
• Microwave Remote Sensing


  Concept, fundamentals and principles
• Radar concept and principles
• Microwave radiometer
• Self Assessment Exercises
• Thermal sensors


  • Detect emitted radiation in the thermal portion of the spectrum
  • Employ one or more internal temperature references for comparison with the detected radiation
  • Can relate detected radiation to absolute radiant temperature
  • Data generally recorded on film and/or magnetic tape
  • Temperature resolution can reach 0.1°C

  
• Thermogram


  Image of relative radiant temperatures depicted in grey levels, with warmer temperatures shown in light tones and cooler temperatures in dark tones

  
• Atmospheric scattering is minimal for thermal radiation due to the relatively long wavelength (compared to visible radiation)
• Atmospheric absorption normally restricts thermal sensing to two specific regions - 3 to 5 μm and 8 to 14 μm

  
• Thermal sensors generally have large IFOVs to ensure enough energy reaches the detector to make a reliable measurement, so the spatial resolution is usually fairly coarse
• Thermal imagery can be acquired during the day or night as the radiation is emitted, not reflected

  
• Thermal imagery is used for applications such as military reconnaissance, disaster management, and heat loss monitoring
• The Earth's surface and atmosphere radiate thermal energy outward due to heating by solar irradiation and internal heat flow
• FLIR (Forward-Looking Infrared) systems


  • Acquire oblique views of the terrain ahead of an aircraft
  • Operate on the same basic principles as an across-track line scanning system but with the mirror pointing forward
• Modern FLIR systems are extremely portable and can be operated on a variety of platforms
• Civilian use of FLIR is increasing in applications such as firefighting, electrical transmission line maintenance, law enforcement, and nighttime vision for automobiles
• Thermal imagery can show contrasting tones between dawn and day scenes of the same features

  
• There are two prominent atmospheric windows for thermal mapping where absorption is minimum
• Peak wavelength


  The wavelength at which the maximum radiant energy is emitted by a body at a given temperature

  
• Radiant flux (FB)


  The rate of flow of electromagnetic energy, commonly measured in Watts per square meter, emanating from a blackbody and related to its internal (kinetic) temperature Tk by the Stefan-Boltzmann Law
• Radiant flux (FR)


  The radiant flux of a real (or 'greybody') material, which is always less than the blackbody flux FB, as calculated by FR = εσTk4, where ε is the emissivity
• For real bodies, the radiant temperature TR differs from the kinetic temperature Tk according to the relation TR = ε^(1/4) Tk
• Heat Capacity (C)


  The measure of the increase in thermal energy content per degree of temperature rise, denoting the capacity of a material to store heat
• Thermal Conductivity (K)


  The rate at which heat passes through a specific thickness of a substance
• Thermal Inertia (P)


  The resistance of a material to temperature change, indicated by the time dependent variations in temperature during a full heating/cooling cycle, defined as P = (Kcρ)^(1/2) = cρ(k)^(1/2)
• Interpreting thermal data and images is complex due to factors like material composition, insolation angle, emissivity, geothermal heat flux, topography, soil moisture, and vegetation
• The distribution of temperature over an area is complex. In many instances, we must look for patterns of relative temperature differences rather than the absolute values, because of the many complex factors that make quantitative determinations difficult