remote sensing lecture slides

Nirmal Chaudhary 25/08/2011

1

Satellite Imagery and Digital Image Processing

Nirmal Chaudhary, M.Sc.

………………………………

Course content:

• (V) introduction, satellite navigation system, types of RS satellite,

introduction to photo interpretation and photogrammetry, satellite imagery

and digital image processing.

• (Vi) radiometric and geometric corrections, image enhancement and

interpretation, spatial filtering, feature extraction, classification methods,

maximum likelihood classifier.

• (vii) GIS/RS applications: for assessment, monitoring and conservation of

biodiversity.

• Practical assignment will follow after each lecture.

Satellite imagery and digital image processing: Introduction

The first photograph: taken in 1839

………………………………


2

………………………………

Object

SensorProcessing

………………………………

Physical Components of RS:

1. Source

2. Atmospheric interaction

3. Interaction with object

4. Sensor

5. Processor

Remote Sensing: The use of Electronic Radiation Sensors to record images of the

environment, which can be interpreted to yield useful information (Curran, 1985)

1. The Source: Target illumination

Electro-Magnetic Radiation

С = λ ν (Wave model of light )

Q= h ν = h (c/ λ) (Particle model of light)

C= velocity of light ( 3 X 10 8 m/s)

λ = Wavelength (m)

ν = frequency (cycles per second; Hz)

h= Planck’s constant (6.6262 X 10-34 Js

nm= 10-9 m

µm= 10-6 m

cm= 10-2 m

1. The Source: Radiation and Emissivity

All energy above 0 0K emits radiation due to molecular agitation. Not only

the sun but the Earth too, emits energy.

Energy radiated by any body depends upon its absolute temperature and

emissivity and is function of wavelengths: Stefan-Boltzmann’ s law


3

1. The Source: EM Spectrum

Primary

Colours

2. Atmospheric Interaction

• Particles and Gases of Atmosphere affects

the radiation via absorption and scattering.

• Scattering by molecules of size smaller than

the wavelength of EM waves cause

Rayleigh scattering. O2, NO2, CO2 etc are

the cause. These cause smaller wavelengths

of light to scatter more than longer

wavelengths. Sky is blue in a clear midday.

• Scattering by aerosols with size larger than

EM waves is Mie Scattering. Water drops,

haze, dusts, Pollens etc are the cause.

• Non-selective scattering are caused by

much larger particles than wavelength. This

distribution of all the wavelength is nearly

equally scattered. E.g. clouds.

• Ozone, Water Vapours, CO2 absorb radiation

of particular wavelengths.

2. Atmospheric Interaction………………………………

• Atmospheric Transmission windows are the region of the spectrum which are

not influenced by the atmospheric absorbents.

• For remote sensing the windows in range of 0.35 to 2.5 μm in visible and

reflected IR region (Optical region) , narrow windows in range of 3 to 5 μm

and a broad window from 8 to 14 are of interest.

3. Interaction with the Target

1. Radiation that is left after atmospheric interaction reaches the Earth skin. Surface

roughness determines the reflection: Specular (smooth surface) and Diffuse

(Irregular surface) Reflection.

2. Incident energy on target interact in one or more ways: Absorption, Transmission

and Reflection: Reflection from targets are of particular interest, in Remote

sensing.

3. Reflectance is ratio of the incident energy flux to the reflected energy flux of a

surface. It range from 0 - 1. Spectrometer measures the Reflectance.

4. Reflectance with respect to wavelength are called spectral reflectance.


4

Question hour:

1. What are the advantage/disadvantage of air-borne (aerial) remote sensing and

space-borne remote sensing?

2. What is electromagnetic spectrum?

3. Why clouds appear white?

4. Define atmospheric window.

5. What time of the year, remote sensing for forest area of Nepal will be most

suitable and why?

Satellite Navigation Systems………………………………

Satellite Navigation Systems ………………………………

1. Definition: System of artificial satellites for positioning, navigation and timing (PNT

technology).

2. Features:

a. High position accuracy from ‘m’ to ‘mm’

b. Capability of determining velocity and time in relation to the accuracy of

position (PVT).

c. Position location is in 3D: Latitude, Longitude and Altitude.

d. Available 24 hours a day and all weather system

e. Wide application: Environmental, Cadastral, Engineering, GIS, Planning,

Navigation-land, sea, air

3. Global Navigation Satellite System (GNSS) is an umbrella term for all the present

and future global, satellite based, radio-navigation system.

a. Global Positioning System (GPS) of US Department of Defence

b. GLONASS of Russian Federation

c. GALILEO of European Union:2013

d. COMPASS /Beidou of China: 2020

e. Indian Regional Navigation Satellite System (IRNSS): 2014

Components of GPS technology

1. Space segment: Satellites and transmitted signals

2. Control Segment: ground facility controlling satellite tracking, orbit computation,

satellite clock behaviour, system monitoring etc.

3. User segment: application, equipment and computational techniques for users

1. At an altitude of 20,200 km, 24 satellites located in 6 orbital planes inclined at

630 to the equator is sufficient to ensure that there will be at least 4 satellites

visible, anytime anywhere on the earth

2. At present there are 31 GPS satellites since 1978.

3. The orbital period is 11 h 58 min so that each satellite make 2 revolution in

one sidereal day. In solar day, the satellites will be in same position in sky

about 4 min earlier each day.


5

Basic of GPS

• GPS satellite signals have following

components:• Carrier waves: L1 (1575,42 MHz) and

L2(1227.60MHz)

• Ranging codes in the carrier waves using Code

division multiple access (CDMA) scheme:

determines the transit time of signal.

• Navigation message: orbital information

(ephemeris), satellite clock error parameter

etc (Almanac)

• The transit time when multiplied by speed of

light, gives the distance of satellite and the

receiver. With 4 satellites, the distance of the

receiver is in 3D on Trilateration basis,

because the accuracy will be high with at

least 4 satellites.

• Errors:

• Ionosphere and Troposphere delay

• Orbital and Transit time error

• Less satellites and position

• Signal multipath

Remote Sensing Satellites

• Satellites may be Polar or Geo-stationary. Polar satellites travel north

eastward at angle between 800 to 1000. They are placed at 600-1000 km from

earth and most of them are sun-synchronous-meaning they pass overhead at

the same time. Most of them pass the equator at 10:30 hour local solar time

and may take 2 weeks to repeat scan of the same location. Landsat, SPOT and

IRS are examples. Sun-Synchronous satellites have polar orbit with

inclination angle between 980-990.

Geo-stationary satellites are fixed at 3600 km above earth and are always at

same position on earth. They are generally meteorological and

communication purpose.

• Based on sensors on satellite, it could be Active or Passive.

• Passive sensor depends on energy from sun or from earth itself. After

reflection from the target, this energy is recorded by sensors on platform. E.g.

Photographic camera.

• Active sensors emit their own energy to the target and receives the reflected

energy. Radio detection and Ranging (radar) and light detection and ranging

(Lidar), Sound navigation ranging (SONAR) are the passive sensors.

………………………………

Fundamental sensor types are Across-track scanning sensor (Whiskbroom

scanner) and Along-track scanning sensor (Pushbroom scanner).

Whiskbroom scans the earth surface perpendicular to the direction of

satellite movement. Eg. NOAA/AVHRR, Landsat/TM.

Pushbroom scans parallel to the direction of motion. Eg. SPOT-1, IKONOS

Remote Sensing Satellites:

Meteosat-8:

Owned by: European organization: Eumetsat.

Sensor: SEVIRI (Spinning Enhanced VIS and IR Imager)

Orbit: Geo-stationary, 00 longitude

Swath: Full earth disc (FOV=180)

Revisit time: 15 mins

Spectral band (μm): o.5-09 (PAN), 0.6, 0.8 (VIS), 1.6, 3.9 (IR), 6.2,7.3 (IR

for WV), 8.7,9.7,10.8,12.0,13.4 (TIR)

Ground pixel: 1 km (PAN), 3 km (all other band)

Data Archive: www.eumetsat.de

NOAA -17: National Oceanic and Atmospheric Administration

(When the sun acts up, NOAA knows why.)

Owned by: US Department of Commerce.

Sensor: Advanced Very High Resolution Radiometer (AVHRR-3)

Orbit: 812 km, Sun-Synchronous, 98.70 inclination

Swath: 2800 km (FOV=1100)

Revisit time; 2-14 times /day

Spectral bands (μm): 0.58-0.68 (1), 0.73-1.00(2),1.58-1.64(3A day),3.55-

3.93 (3B night), 10.3-11.3 (4), 11.5-12.5 (5)

Spatial resolution: 1 km (at Nadir) , 6 kmX2 km (at limb)

Data Archive: www.sa.noaa.gov


6

………………………………

Landsat-5 and 7: NASA and US Geological Survey (USGS)

Sensor: TM and ETM+



Revisit time; 16 days

Spectral bands (μm): 0.45-0.52 (1), 0.52-0.6 (2),0.63-0.69 (3),0.76-

0.90 (4), 1.55-1.75 (5), 10.4-12.5 (6), 2.08-2.34(7),0.50-0.90 (PAN)

Spatial resolution: 15m (PAN), 30m (band 1-5,7), 60m (band 6)

Data Archive: http://landsat.gsfc.nasa.gov/images/

Envisat: Environmental Satellite; European Space Agency

Sensors: Advanced SAR(ASAR), Medium Resolution Imaging Spectrometer (MERIS),

GOMOS (Global Ozone Monitoring by Occultation of Stars), RA -2 (Radar

Altimeter),MWR (Microwave Radiometer), MIPAS(Michelson Interferometer for

Passive Atmospheric Sounding) along with other complementary instruments.


Swath: 56 to 405 km (ASAR), 1150 km (MERIS)

Revisit time; 35 days

Spectral bands (μm): C-band (ASAR), 15 bands in 0.39-1.04 μm EM Spectrum

(MERIS; programmable)

Spatial resolution: 30m or 150m (ASAR), 300m land and 1200m Ocean (MERIS)

Data Archive: http://earth.esa.int/dataproducts/

………………………………

Resourcesat-1: Indian Space Research Agency

Sensor: Linear Imaging Self-Scanning Sensor (LISS-4)



Revisit time: 24 days

Spectral bands (μm): 0.52- 0.59, 0.62- 0.68 , 0.77- 0.86

Spatial resolution: 6m

Data Archive: http://landsat.gsfc.nasa.gov/images/

TerraSAR-X: German Aerospace Center and EADS Astrium GmbH

Source: 965GHz.

Sensor: X-band SAR antenna

Orbit: 514 km sun synchronous, 97.440

Swath: width (10km – 100km) length (5 km to 1650 km)

Revisit time: 2.5 days at maximum.

CALIPSO: Cloud-Aerosol Lidar with Orthogonal Polarization

Owner: NASA (US) and Centre National d’Etudes Spatiales (CNES, France)

Source: 532 nm and 1064 nm with pulse repetition of 20.16 Hz.

Spatial Resolution: 125m, 333m,1km,5km,

Swath: 1km X 70 km

……………………………… Introduction to Photo interpretation and photogrammetry…………

•Photo Interpretation involves:

•Photo Reading : to recognize features

such as trees, rivers in a photo

•Photo measuring (Photo-grammetry)

:crown diameter? Altitude? Distance?

•Information Extraction: Status of

tree/forest/land/soil ?

•What is Photo-Interpretation?

• It is an act of examining photographic images for the purpose of identifying

objects and judging their significance. ( Colwell, 1997)

Photogrammetry is the science or art of obtaining reliable measurement by means

of photographs (McGlone et al., 2004)

Photogrammetry and photo-interpretation are more common words for Aerial

photographs than Satellite imageries. Nowadays, the advances of satellite remote

sensing has blurred the distinction among them.


7

………………………………

Image or Photo Interpretation is meant for information extraction. Information

extraction can be Human method (Image interpretation) and Computer method

(Digital Image processing)

Photogrammetry is concentrated to modelling of 3D images from 2D images using

“Stereoscopic viewing”.

………………………………

Scale: is the ratio of distance between two points in photo/image to the distance

between same points on ground. This ratio is also called Representative Fraction (RF).

distance in photograph

RF =

distance on ground

If the distance width of a road is 0.2 mm on map and its width on ground is 5m,

calculate the scale of the map.

Soln = RF = 0.2 /(5 X 1000 )= 1/25000 = 1:25000

Problem: If the distance between two trees on a map is 0.2 inch, which has scale of

1:2400 then the distance on ground will be ?

0.2 inch = 0.2X2.4= 0.48 cm = 0.0048 m

distance on ground = distance in photograph /RF

= 0.0048 X (1/2400)

= 0.0048 X 2400

=11.52 m

RF can be also calculated as ratio of focal length of camera to the height of the

camera from ground.

Aerial survey planning:

Specification:

Scale: 1:2400

Size of Photograph: 23X23 cm (9 X 9 inch)

Overlap along line of flight (endlap): 60%

Overlap across adjacent lines of flight (sidelap) : 20%

Length of Area along lines: 30 km

Width of Area across lines of flight: 20 km


8

………………………………

Kinds of photographs:

Vertical: camera axis vertical 900: Nadir view

Oblique: Off Nadir view

………………………………

For any point (pixel) in at least two images we calculate the 3rd dimension (terrain

coordinates) and this is the principle task in Photogrammetry.

•We need all the geometric parameters

in the situations of when we take

photos/images.

•Using the geometric parameters, we

set the equation of rays [P’ P] and

[P” P] and calculating their

intersection.

•Once the 3D coordinates are known,

we can digitize maps, calculate

distance, volume, slopes etc in

Photogrammetry.

………………………………

Films and Filters

Photogrammetry can be considered as a

traditional approach to remote sensing.

Because, all the calculation process achieved

from photogrammetry can be easily developed

as algorithm in computers and are available in

remote sensing/GIS softwares.

Satellite imageries and digital image processing

• Satellite images are digital images of electro-magnetic energy received by sensors on

satellite. A digital image has individual cells of uniform value.

• These individual cells are called picture cell (Pixel) and are generally square in shape.

• Digital image has coordinates of pixel number (sample) counted from left to right and

line number counted from top to bottom.

Satellite imageries record reflected rays form target across several wavelengths in

UV-Radio waves, hence are called: Multi-Channel, Multi-band or Multi-Spectral data.


9

………………………………

•Multi-band images are stored/represented by combination of spatial position (pixel

number and line number)

•Satellite images may be in BSQ, BIL or BIP format.

•Band squential (BSQ) the spatial position for each band is separately arranged

•Band interleaved by line (BIL) data are arranged in the order of band number and

repeated with respect to line number

•Band interleaved by pixel (BIP) stores data with first line of first band, first line of

second band and so on.

Auxiliary data are supplementary to image

data that describe image file, sensor,

processing method etc.

Resolution of Image:

• Spatial Resolution (objects on ground)

• Spectral Resolution (portion of EMR)

• Radiometric Resolution (level of signal)

• Temporal Resolution (Sensor re-visit time)

Spatial Resolution is the smallest size of the object that can be

picked from the ground.

It is mainly determined by the Instantaneous field of view (IFOV)

and the height of sensor/camera from ground.

Diameter on ground (D) = Height (H) X IFOV (Radians; β)

………………………………

Spectral Resolution is the number and dimension of specific wavelength interval of

EMR that a sensor is capable of measuring.

Smaller the width of band, higher is the spectral resolution.

Resolution A < Res. C < Res. B

Panchromatic image consist of large width

band often entire Visual Spectrum.

Multispectral image have relatively large

narrower several bands.

Hyperspectral image has large number of

narrower bands.

Landsat TM Spectral resolutions

………………………………

Radiometric Resolution is the number of unique values the sensor can record for

sensed EM waves. It is expressed in bits.

Bits are expressed as power of 2 and number starts from 0.

1 bit = 21= 2: sensor can record 0 and 1

2 bit =22 = 4: sensor can record 0,1,2 and 3

8 bit = 28 = 256: sensor records 0,1,2,…….255


10

………………………………

Temporal resolution: Shortest period of time the sensor will pass over a same spot

on the earth surface.

Landsat makes 14 orbital revolution in

a day to cover whole earth. Landsat revisits the same spot in 16 days,

thus has temporal resolution of 16 days.

AVHRR on NOAA satellite has 12 hrs of temporal resolution.

You cannot have all the resolutions higher, in same image.

High Spatial Resolution= Low IFOV= Low energy sensed= Less value= Low Radiometry

Digital Image processing

Radiometric calibration/correction

There are chances the sensor’s recording of reflected EM energy from target does not

coincide with the energy reflected form the object due to path disturbances

(atmospheric, sun position and elevation, fog, haze etc). This gives radiometric distortion

in image. To obtain real irradiance or reflectance, radiometric calibration is needed.

Out of several methods for radiometric correction, Dark Object subtraction is one of

them.

It assumes that dark objects on earth surface does not reflect energy thus any value of

the pixel from sensor that contains the dark object is due to atmospheric scattering. This

value should be subtracted from the entire pixels of the image to get radiometrically

correct image.

Spectral radiance at sensor (L) for 8 bit image is

obtained as:

Geometric calibration/correction

Geometric correction or Georeferencing: The process of transforming the x-y dimension

of a image so that it has the same scale and project properties of a selected map

projection.

Ground Control Point (GCP) are needed to process the matching of points on an image

with corresponding map (image) co-ordnates from which GCP is obtained.

A good number of GCPs is 20 at minimum, distributed homogeneously over the image

extent.

The two data sets are then used for coordinate transformation matrix, one using linear

transformation.

The result of Georeferencing is to produce new output grids aligned with northing and

easting of reference map/image. The values of the newly acquired pixels of the output

image is determined by sampling: Nearest Neighbour, Bi-linear, Cubic convolution.

remote sensing lecture slides

Documents