Research Methodology - Historical Land Use/Land Cover Classification Using Remote Sensing - page 71

Fig. 5.5 A simplified model
of the atmospheric effects on
the reflection on a target
object (Source modified from
Kaufman 1985 )

Satellite

Sunlight

Sunlight

Atmosphere

A

EarthSurface

Schematic of the atmospheric influence on the recorded radiation at the sensor. The
Sunlight is broken into three compenents:
: Air light.
: Diffuse lighting. Distracted Radiation and Reflection/Emission.
: Direct Reflection/Emission + Reflection/Emission by neighborhood effects.
A : Target

atmospheric conditions; and the wavelengths. Hence, energy recorded by the
sensor is a constructed process of: (1) incident energy (irradiance); (2) target
reflectance; (3) atmospherically scattered energy (path radiance); and (4) atmo-
spheric absorption (ERDAS 1999 ; Liang 2004 ). Figure 5.5 illustrates this process.
A large amount of optical remote sensing data is affected by the impact of the
atmosphere. This impact is called atmosphere effects (Liang 2004 ). It includes
''molecular and aerosol scattering and absorption by gases, such as water vapor,
ozone, oxygen and aerosols'' (Liang 2004 ). These effects are note measured as
''error'', because they are a component of the entire recorded signal by a receiver
or sensor (Bernstein 1983 ). To deal with these effects in optical remote sensing,
there is a procedure known as Atmospheric Correction. It corrects for surface
reflectance from remotely sensed images. However, it is not always simple to
remove or enhance these effects. The procedure of atmospheric correction
includes: assessment of the parameter of the atmosphere; and regain of the surface
reflectance. To correctly regain the surface reflectance based on converting of
sensor measurements to actual reflectance values on the ground using radio
transfer codes, may be need a well knowledge about the atmospheric conditions at
the time of image acquisition by a remote sensing sensor (e.g., humidity and
temperature).
The assumptions that the reflectance values recorded on the remotely sensed
data (optical remote sensing) are equal to the real reflectance of the different
features on the ground surface, and that there is representative relation between the
recorded values on the images and between the three properties of the ground
surface (physical, chemical and biological), is not acceptable unless atmospheric
corrections are applied (Liang 2004 ). Smith and Milton ( 1999 ) had presented the
next more radical principle: ''to collect remotely sensed data of lasting quantitative
value then data must be calibrated to physical units such as reflectance''.