7.principles of remote sensing overview

Principles of Satellite Principles of Satellite Remote SensingRemote Sensing

Sundar A. ChristopherDepartment of Atmospheric ScienceUAHuntsville, AL

DefinitionDefinition

Remote sensing is the measurement of an object by a device that is not in physical contact with the object.

Types of Remote SensingTypes of Remote Sensing

Passive Sensors: Satellites

Active Sensors: Radar

Electromagnetic energyElectromagnetic energy

The frequency of EM radiation is directly proportional to the speed of light and Inversely proportional to the wavelength

Commonly used satellite sensors sense EM radiation from visible to infrared part of the spectrum

Why Satellite Remote Sensing?Why Satellite Remote Sensing?

Advantages: Repeated reliable measurements

Disadvantages: Expensive and need expertise to convert measurements to geophysical values such as temperature.

Numerous satellites are now in orbit

NASA Observing Spacecraft for Earth System Research

Moderate Resolution Imaging Spectroradiometer (MODIS)

Common types of orbitsCommon types of orbits

Geostationary orbitAn orbit that has the same Earth’s rotational periodAppears ‘fixed’ above earth Satellite on equator at ~36,000km

Polar orbiting orbitfixed circular orbit above the earth, ~1000km in sun synchronous orbit with orbital pass at about same local time each day

Example of satellite imageryExample of satellite imagery

Shortwave and Longwave RadiationShortwave and Longwave Radiation

Shortwave radiation from the sun is reflected from earth atmosphere that is seen by satellite (< 4 micron)

Longwave radiation is earth emitted radiation (> 4 um)

Fate of EM RadiationFate of EM Radiation

Incident solar energy can either be reflected, transmitted or absorbed

Satellite imagerySatellite imagery

In visible imagery water is dark because it absorbs most of the energy.

Clouds are white because most of the incoming energy is reflected

Pollution is hazy depending upon its absorptive properties

Atmospheric WindowsAtmospheric Windows

Portions of EM spectrum where absorption and scattering is minimal is called Atmospheric Windows

Remote Sensing - ResolutionsRemote Sensing - Resolutions

4 major resolutions

– Spatial resolution

– Spectral resolution

– Temporal resolution

– Radiometric resolution

Spatial ResolutionsSpatial Resolutions

Spatial Resolution : A simple definition is the pixel size that satellite images cover.

Satellite images are organized in rows and column called raster imagery and each pixel has a certain spatial resolution.

Nadirpixel sizeOff-nadir

pixel size

FOVFOV IFOVIFOV

SatelliteSatelliteheightheight

Spectral ResolutionSpectral Resolution

The number of bands is sometimes referred to as spectral resolution

A better definition is the width is the spectral band

Temporal ResolutionTemporal Resolution

How often is data obtained for the same area

Twice daily for polar orbiting satellites

Hourly or sub hourly for geostationary satellites

Radiometric ResolutionRadiometric Resolution

The ability to separate small differences in energy striking a sensor

For example 8 bits per pixel means the image is quantized as 256 gray levels.

Examples, AVHRR : 10 bit, MODIS : 12 bit

Trade Off’sTrade Off’s

A sensor cannot extremely high spectral, spatial and radiometric resolutions.

We discuss this in the Critical Thinking module.

Spectral SignaturesSpectral Signatures

The unique signature of various classes (e.g. Vegetation, Water, bare Soil) in the exam

above allows multi-spectral satellite imagery for identification

What does satellite see?What does satellite see?

Visible spectrum-Satellite measure radiance and not geophysical quantities such as temperature these radiance values must be converted to parameters of interest.

Radiance - DefinitionRadiance - Definition

RadianceI =flux per unit area

per unit solid angle normal to the direction of propagation

[Wm-2sr-1]

The concept ofStera-radian (sr)

From pretty pictures to numbersFrom pretty pictures to numbers

Radiance is converted to reflectance and temperature

Multi-spectral Image must be separated into various features (clouds, aerosols, ocean, land etc.)

This must now be converted to geophysical parameter

For example: Cloud top

temperature

For a known satelliteMeasured radiance theCloud top temperature Can be calculated if theWavelength is given. H, c, and k are all constants