Introduction to RS Lecture 2. NR401 Dr. Avik Bhattacharya 1

Transcription

1 Introduction to RS Lecture 2 NR401 Dr. Avik Bhattacharya 1

2 This course is about electromagnetic energy sensors other types of remote sensing such as geophysical will be disregarded. For proper analysis and interpretation of remote sensing data, it is important to understand the source of electromagnetic energy, its nature, its propagation, and its interaction with atmosphere and other matter. NR401 Dr. Avik Bhattacharya 2

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5 Passive system: EM Energy source- the SUN NR401 Dr. Avik Bhattacharya 5

6 The Sun is the most important source of EM radiation used in passive optical remote sensing. The Sun s radiation covers Ultraviolet Visible Infrared Microwave Radio waves Maximum radiation occurs around 0.55 µm Visible region of the EM spectra. NR401 Dr. Avik Bhattacharya 6

7 Surface regions of the Sun - the photosphere, the chromosphere, and the corona. The photosphere corresponds to the bright region normally visible to the naked eye. (`Temperature ~ 6000 K) The chromosphere lies ~5,000 km above the photosphere. Short-lived, projections may extend for several thousands of kms from the chromosphere. (Temperature ~ 20,000 K) The corona is the outermost layer of the Sun; this region extends into the region of the planets. NR401 Dr. Avik Bhattacharya 7

8 Solar radiation reaching the Earth s surface is modified by the atmospheric effects All bodies at temperature above absolute zero degree emit EM radiation at different wavelengths Planck s Law Earth as blackbody at 300 K emits radiation at around 9.5 µm NR401 Dr. Avik Bhattacharya 8

9 Solar radiation has to pass through the atmosphere before it interacts with Earth s surface. Radiation is scattered/absorbed by gases and particulates. The strongest absorption occurs at wavelength < 0.3 µm Ozone Layer NR401 Dr. Avik Bhattacharya 9

10 Certain spectral regions of the EM radiation pass through the atmosphere without much attenuation Atmospheric Windows In the region of atmospheric windows Scattering by atmospheric molecules and aerosols produces spatial redistribution of energy The scattered/diffused radiance entering the field of view of a remote sensor other than that from the target Path Radiance NR401 Dr. Avik Bhattacharya 10

11 Atmospheric haze/cloud is much more transparent to microwave than optical and Infrared region of the EM spectrum Microwave remote sensing Side Looking Airborne Radar (SLAR) Synthetic Aperture Radar (SAR) Active and Passive Microwave RS NR401 Dr. Avik Bhattacharya 11

12 (Concept of Signatures) Incident EM on a surface either gets Reflected/Absorbed/Re-radiated/Transmitted Dependence upon the nature of the object and wavelength of the incident radiation Study of interaction understanding of the object under observation NR401 Dr. Avik Bhattacharya 12

13 (Concept of Signatures) The basic property which allows identification of an object Signature Spectral/Spatial/Temporal/Polarization 4 major characteristics of the target which facilitates discrimination. NR401 Dr. Avik Bhattacharya 13

14 Spectral Signatures NR401 Dr. Avik Bhattacharya 14

15 Spectral variation are changes in the reflectance/emittance of an object R f E f ( f ) Colour of an object is a manifestation of spectral variance in reflectance in the visible region NR401 Dr. Avik Bhattacharya 15

16 Spatial variation Spatial arrangement of terrain features providing attributes such as shape/size/texture of objects Temporal variation Changes in reflectivity/emissivity with time. They can be diurnal/seasonal NR401 Dr. Avik Bhattacharya 16

17 Polarization variation Changes in polarization of the EM radiation reflected/emitted by an object. The degree of polarization is a characteristic of the object and hence can be used to distinguished the object. Useful in the microwave region NR401 Dr. Avik Bhattacharya 17

18 Signatures are not completely deterministic Statistical in nature with certain mean value with some dispersion around it Spectral variation is the most often used signature in the Optical/IR region NR401 Dr. Avik Bhattacharya 18

19 Not impossible to generate continuous spectra for identifying objects. Practical solution Observation in discrete spectral region Spectral bands NR401 Dr. Avik Bhattacharya 19