Remotely Sensed Data

Acquisition of Remotely Sensed Data• As discussed there are two types of sensor based on their

energy source for illumination.

• Passive Sensors• Active Sensors

Passive Sensors rely on the Sun’s energy reflected by objects on the ground. These reflected energy is measured and stored in the satellite storage unit and downloaded by the ground control station of the satellite

Active Sensors emit their own elecatromagnetic signals and these signals are reflected by objects on the ground. These energy of the reflected signal is measured and stored in the satellite storage unit and downloaded by the ground control station of the satellite

Data PreprocessingRemotely sensed data downloaded from the satellite is just a series of numbers that represent the measurement of the sensors which contains errors. Preprocessing eliminates these data registration errors. To be able to use this data for base maps, GIS and digital image processing, there are certain preprocessing steps that need to be executed.

Types PreprocessingGeometric CorrectionRadiometric CorrectionNoise RemovalGeoreferencing / Orthorectification

Geometric CorrectionThis correction eliminates geometric distortions due to :

Earth RotationEarth CurvatureInstability of the Platform

- Altitude- Velocity- Pitch- Roll- Yaw

Geometric Correction

Radiometric Correction• This correction minimizes distortions due to:

• changes in scene illumination• atmospheric conditions• viewing geometry• instrument response characteristics

• Depending on the application, some or all of these corrections need to be applied to produce desirable results

Radiometric CorrectionExamples

Sun elevation correction:accounts for the seasonal position of the sun relative to the

earth image data acquired under different illumination angles are normalized by calculating pixel brightness values assuming the sun was at the zenith on each date of sensing

Haze compensation:procedures designed to minimize the influence of path

radiance effects

Noise RemovalNoise

- unwanted disturbance in image data due to limitations in the sensing, signal digitization, or data recording process.

Sources of noise• periodic drift or malfunction of a detector• electronic interference between sensor components• intermitted “hiccups” in the data transmission and

recording sequence

Georeferencing• The process of associating geographic information to

image pixels

• Georeferenced image contain information on geographic location, pixel size and scale.

• For mapping and GIS application, images need to be properly georeferenced to avoid errors in data extraction

Orthorectification• The process of simultaneously georeferencing an image

and correcting geometric errors.

• This process require ground control points that are indentified in the image to aid in solving unknowns in the geometric parameters of the sensor.

Composition of Remotely Sensed Image File

Bands – These are the different layers in an image file. A band represent a range of wavelength in the electromagnetic spectrum from which the sensor measures reflected energy. A sensor may measure from different ranges of wavelengths which result into multiple layers or bands of data

Bands are often associated with color but there are some bands not visible to the naked eye like those in the microwave region of the spectrum. False color images are made to represent these bands

Composition of Remotely Sensed Image File

Digital Number – the value recorded by the sensor by converting the energy measured into digitally quantized numbers.

Digital numbers are arranged in columns and rows.

Composition of Remotely Sensed Image File

Properties of Remotely Sensed DataProperties are remotely sensed data are commonly

described as resolution. There are four properties of RS data.

SpatialSpectralRadiometricTemporal

Spatial ResolutionSpatial resolution of an imaging system can be measured

in a number of different ways. It is the size of the smallest object that can be discriminated by the sensor. The greater the sensor's resolution, the greater the data volume and smaller the area covered. In fact, area coverage and resolution are interdependent and these two factors determine the scale of an imagery. Alternatively, spatial resolution can be said to be the length of the size of the area on the ground represented by a pixel on an image.

Spectral ResolutionIt is the width of the spectral band and the number of

spectral bands in which the image is taken. Narrow band widths in certain regions of the electromagnetic spectrum allow us to discriminate between the various features more easily. Consequently, we need to have more number of spectral bands, each having a narrow bandwidth, and these bands should together cover the entire spectral range of interest.

Radiometric ResolutionIt is the capability to differentiate the spectral reflectance/

emittance between various targets. This depends on the number of quantisation levels within the spectral band. In other words, the number of bits of digital data in the spectral band or the number of gray level values, will decide the sensitivity of the sensor. It is the smallest difference in exposure that can be detected in a given film analysis.

Temporal ResolutionTemporal resolution refers to the minimum duration of an

event that is discernible. It is affected by the interaction between the duration of the recording interval and the rate of change in the event. A shorter recording interval implies higher temporal resolution, just as a faster film has given us the ability to photograph quickly-moving objects. For geospatial data, the situation is more complicated because interactions between spatial and thematic resolutions must also' be considered.

Basic Image Manipulation• Layer Stacking• Resizing Images

• Spectral• Spatial

• Resampling• Compute Image Statistics• Band Math