Prepared by: Akash Tikhe (akashtk92@gmail.com)

CONCEPTS OF REMOTE SENSING

Natural Remote Sensing

Sensing / Perceiving

Analysis

Information / Knowledge

Boy or Man ?

Name the remote sensing organs in our body?

Artificial Remote Sensing

Sensing / Perceiving

Analysis

Extracting Information /

Knowledge

Output

Subject

Definition of Remote Sensing

Remote sensing is art, science & technology adopted for obtaining reliable

information of the objects on the surface of earth without coming into

physical contact. In fact we are measuring and recording the electro-

magnetic radiations reflected and emitted by the bodies.

Major objective is to Analyze/Understand the Environmental and Natural

resources information.

Components of RS

Energy Source

Radiation

Atmosphere

Target area

Sensor

Ground Acquisition centers/

Receivers

Interpretation/ Analysis

Output to Clients

Electro Magnetic Radiation

Sun is the main source of energy.

Energy propagates in form of Electro Magnetic Radiation

(EMR).

Wavelength (λ)

Frequency (ν)

Velocity (C)c = ν* λ

Electro Magnetic Spectrum

Light energy is explained as EMR and can be classified according to the

length of the wave. All possible energy channels called as Electro Magnetic

Spectrum (EMS).

Human eyes can only measure visible light but sensors can measure other

portions of EMS.

Figure: Electro Magnetic Spectrum (EMS)

Sensors

Sensors are the devices, which gathers energy and converts it

into a signal and presents it in form suitable for obtaining

information about the target under investigation (Aggarwal, S.

2003).

Types of Sensors

ACTIVE

- Creates their own energy

- Work day & night

- Non seasonal

Ex: Radar, LIDAR

PASSIVE

- Depends on External energy, Sun, fire etc

- Work on day

- Seasonal

Ex: Latsat, LISS, Spot & AWIFS

RADARSAT (Active Sensor)

- Canadian Space Agency

- Altitude: 798 KM

- Inclination: 98.6°

- Orbit: Polar

- Orbit period: 100.7’

- Revisit time: 14 days

Write a brief note on at least two active sensors?

Image Credit: http://www.asc-csa.gc.ca

LISS III (Passive Sensor)

- ISRO - NRSC

- Altitude: 817 KM

- Inclination: 98.7°

- Orbit: Polar

- Orbit period: 101.35’

- GSD : 23.5 m

- Revisit time: 24 days

Write a brief note on at least five passive sensors?

Image Credit: NRSC

Platforms

Platforms are the places where the sensors are placed.

Depending upon the working environment they are classified as follow:

Platforms

Fixed Platforms

Cherry based

Tripod based

Moving Platforms

Air Borne

Balloon Based

Aircraft

Space Borne

Geo Stationary

Sun Synchronous

Type of Space Borne Platform

Geo Stationary Platform

• Faces towards particular portion

of earth

• 3600 km altitude

• West to East rotation

• Equatorial Orbit

• Angular Coverage 120°

• Orbital period 24 Hr.

• Ex: INSAT, GSAT, etc …

Sun Synchronous Platform

• Crosses particular place at same local

time

• 600 - 900 km altitude

• North to South rotation

• Polar Orbit

• Inclination 80 °/100 ° to Equa.

• Orbital Period 100’ (Approx.)

• Ex: IRS, LandSat, Spot etc …

Types of Remote Sensing

Type of RS

Depending upon

energy source

(EMR)

Depending upon

Sensor

Depending upon

Platform

Optical MicrowaveIR or ThermalX-Ray

Active Passive

Ground

BaseAir Borne

Optical Remote Sensing

• In Optical Remote Sensing, optical sensors detect solar radiation reflected or scattered from the earth, forming images resembling photographs taken by a camera high up in space.

• The wavelength region usually extends from (300 nm to 3000 nm) the visible and near infrared (commonly abbreviated as VNIR) to the short-wave infrared (SWIR).

• Different materials such as water, soil, vegetation, buildings and roads reflect visible and infrared light in different ways. They have different colours and brightness when seen under the sun.

• The interpretation of optical images require the knowledge of the spectral reflectance signatures of the various materials (natural or man-made) covering the surface of the earth.

Thermal Infrared Remote Sensing

• There are also infrared sensors measuring the thermal infrared radiation

emitted from the earth, from which the land or sea surface temperature can

be derived.

• The middle-wave infrared (MWIR) and long-wave infrared (LWIR) are

within the thermal infrared region.

• The wavelength range of 3000 nm to 5000 nm and 8000 nm to 14000 nm.

These radiations are emitted from warm objects such as the Earth's surface.

• Thermal Infra RS used for measurements of the earth's land and sea surface

temperature and forest fire.

Microwave Remote Sensing

These satellites carry their own "flashlight" emitting microwaves to

illuminate their targets and Analyzes the information collected by the sensor.

The active sensors emit pulses of microwave radiation to illuminate the

areas to be imaged. A microwave remote sensor records the backscattered

microwaves from earth or sea surface.

The Microwave wavelength range of 1 mm to 1 m of electromagnetic

spectrum. So, have an additional advantage as they can penetrate clouds.

Most of the microwave sensors are active sensors, having there own sources

of energy. Thus, images can thus be acquired day and night.

Characteristics of Sensors

Atmospheric Windows

Spectral Resolution

Spatial Resolution

Radiometric Resolution

Temporal Resolution

Atmospheric Windows

The spectral Bands for which the atmosphere is transparent are called

as the Atmospheric windows.

Spectral Resolution

The ability of a sensor to discriminate b/w different wavelengths in the

detected signals.

RS sensors can have spectral resolution from more than 1µm to 1 nm.

Low Resolution Medium

Resolution

High Resolution

Panchromatic Multi-Spectral (MS) Hyper-Spectral

(HS)

Single Band >1, <20 bands >= 20 bands

CartoSat P5 LISS-III, LandSat AVIRIS, Hyperion

Spectral ResolutionSingle Band: PAN

500 - 750 nm

CartoSat 1:

Band F image showing Katraj, Pune

Panchromatic Multi-Spectral

Hyperion:

Image showing Katraj, Pune

Four Band:

0.52-0.59 (green)

0.62-0.68 (red)

0.77-0.86 (near IR)

1.55-1.70 (mid-IR)

Spatial Resolution

A measure of the smallest distance between two objects that can be

distinguished by a sensor.

Source: Rees, 1999

Orbview : BVU (1 metre ) LISS III: BVU (23.5 metre )

Image Credit: USGSImage Credit: NRSC

0.6 m Spatial Resolution Hyper spectral Space Image

Spatial Resolution of Satellites

Satellites Sensors Optical Radar

Spatial resolution

LOW MEDIUM HIGH VERY HIGH

>2KM 2KM-100M 100M -10M <10M

CORONA X X

COSMOSTK-350 X

XKVR-1000 X X

ENVISAT

AATSR X X

ASAR X X X

MERIS X X X

ERS

AMI-SAR

X XATSR X X

GOME X X

GEOEYE GEOEYE-1 X X

IKONOS OSA X X

IRSP6/RESOURCESAT

LISS-III X X

LISS-IV X X

AWIFS X X

Spatial Resolution of Satellites

Satellites Sensors Optical Radar

Spatial resolution

LOW MEDIUM HIGH VERY HIGH

>2KM 2KM-100M 100M -10M <10M

LANDSAT

MSS X X

TM X X X

ETM+ X X

METEOR M-N1 X X X X X

METEOSAT

MVIRI X X

SEVIRI X X

GERB X X

METOP X X

NOAA AVHRR X X

ORBVIEW2 SEAWIFS X X

QUICKBIRD X X

RADARSAT SAR X X X

RESURSESI X

XMSU X X X

SPOT

HRG X X

HRS X X

HRV X X

HRVIR X X X

VGT X

SRTM X X

WORLDVIEW X X

Radiometric Resolution

Radiometric resolution is a measure of sensor sensitivity to the magnitude of

the EMR.

Finer the radiometric resolution greater the ability to detect the small diff. in

reflected/ emitted energy.

Digital resolution is a synonym to Radiometric resolution. It is the number of

bits comprising the each image.

It is also referred as no. of brightness levels available to record the energy.

Radiometric Resolution

1 bit = 21 = 2 = {0, 1}

8 bit = 28 = 256 = {0,1,……….,255}

10 bit = 210 = 1024 = {0,1,……………………..,1023}

Temporal Resolution

Is the revisit time period of sensor to image the same area at the same

viewing angle.

Multi temporal Remote sensing

Kedarnath

Floods

(June 2013)

Pre Post

Image Credit: NRSC

Satellites with their Sensor Characteristics

Spectral Reflectance Curve

Is the plot between the Spectral reflectance (ratio of reflected energy to

incident energy) and wave length.

It depends upon the Chemical composition and Physical conditions.

Image Credit: Dr Robert Sanderson

Typical Spectral reflectance curve for Vegetation, Water & Soil

How the Object is Identified by Sensor?

The Basic principle of Remote Sensing is that each object reflect and emit

energy of particular part of EMR in a unique way. Therefore, the signatures

received from different objects is always different. This is called its Spectral

signature. This is the key for interpretation in RS.

Which image will be suitable?

Consideration factors are:

Purpose – what You are interested in

Scale- what will be the scale of out put

These will decide

Bands – which part of spectrum

Spatial Resolution – Positional accuracy required or minimum size of a

object to be identified Seasons of data acquisition

For Large scale Urban mapping High resolution images are applicable.

Example: IRS 1-D PAN 5.8m

Cartosat 1 2.5 m

Cartosat 2 1m

Ikonos PAN 1m

Quickbird 0.6m

For Display:

For single band panchromatic:

0 is black and 255 is white and in between gray

For RGB:

Three value from three band assigned as R,G & B will produce combination of color

For example: Red=255, Green=255 & Blue=0, will be Yellow

How to display in your Computer?

Image is supplied in a specific format.

Image need to be converted to the S/W specific format.

Most of the S/W provide the interface to import such images.

Once imported it can be displayed and further processing can be carried out.

Blue

Green

Red

NIR

SWIR

Part of

spectrum

Monitor

color guns

Viewing images

Three bands are viewable simultaneously

Band4

Band3

Band2

Band4

Band5

Band3

Band1

Band2

Band3

Applications of

RS

Forestry

Geology

Agriculture

Ocean & coastal

monitoring

Hydrology

Pollution monitoring

Land use pattern

Urban planning

Biodiversity conservation

Surveying and mapping

National Security

Environmental Science

Application of Remote Sensing

Agricultural

Crop type classification.

Crop condition assessment.

Crop yield estimation.

Crop stress monitoring.

Crop production forecasting

Mapping of soil characteristic.

Soil moisture estimation.

Ocean applications:

Storm forecasting.

Water quality monitoring.

Aquaculture inventory and monitoring.

Navigation routing.

Coastal vegetation mapping.

Oil spill.

ForestryForest cover and density mapping

Deforestation mapping

Forest fire mapping.

Grassland mapping

Shifting cultivation

Wetland mapping and monitoring

Biomass estimation

Species inventory

National SecurityTargeting

Disaster mapping and monitoring

Damage assessment

Weapons monitoring

Homeland security

Navigation

Policy

Hydrology:

Watershed mapping and management

Flood delineation and mapping

Ground water targeting

Assessment of land surface water

Assessment of sub surface water

Snow melt run-off

Multipurpose river valley

Land Use/Land Cover mapping:

Natural resource management

Wildlife protection

Encroachment

Application of Remote Sensing

Urban Planning:

Land parcel mapping

Infrastructure mapping

Land use change detection

Future urban expansion planning

Geology:

Lithological mapping

Mineral exploration

Environmental geology

Sedimentation mapping and monitoring

Geo-hazard mapping

Glacier mapping