Pre and Post Processing ALOS PALSAR in NEST

7/22/2019 Pre and Post Processing ALOS PALSAR in NEST

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Datasets downloaded from ALOS website

Fine Beam Single Polarimetry (FBS) - HH Fine Beam Dual Polarimetry (FBD)HH, HV Full Polarimetry Mode (PLR)HH, HV, VV, VH

The full polarimetric Level 1.1 data, the HH phase intensity

Deriving a RGB colour image of the HH, HV and VV Intensities respectively.


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Processing PLR

Full Polarimetry; HH. HV. VV. VH Acquired on 16.11.2008 Orbit14988 Track99999 PassAscending pass Location: Hiroshima Incident Angle: 25.647 Frame: Range spacing (Original): 9.3685143 (9.37 m) Azimuth spacing (Original): 3.792048 (3.79 m) Pixel before processing: (Radar Geometry; Rg x Az in m: 9.37 x 3.79 m) Wavelength 23.6 cm *SR pixel spacing (SR to first pixel) = 761575 ma) Multilooking: Azimuth look6.0 Range looks1.0 Mean ground square pixel: 22.1946 Geographic Reference : GRS80 Calibration Factor: -83dB Range spacing: 9.3685143 (9.37 m) Azimuth Spacing: 22.7522928 (22.75 m) Pixel (multilooking step): (Radar Geometry; Rg X Az in m: 9.37 x 22.75 m) i.e. 1 look Rg x 6

look Az in m. Why 6 looks? I have chosen GR Square pixel and not Independent Looks option.

Mode Location

PLR Hiroshima


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FBS

FBD

Only the bands that are used for the analysis are the Intensity bands: HH, HV, VH, VV SAR Tools > Multilooking

Notice the number of range (1) and azimuth looks (6), and the mean GR square pixels(22.1946) are automatically loaded.


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The result of the multilook proessing

The RGB from Multilook

b) Radiometric Calibration SAR Tools > Radiometric correction > Calibrate We dont Save in Decibel because Terrain Correction uses Linear units (and not dB)


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c) Speckle Filter Using Median Filter, with x=3 by y=3 Filter size Other Filtering methods include Mean, Frost, Gamma Map, Lee and Refined Lee


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Below is the RGB of the Speckle Filtered SAR

d) SAR Simulation Geometry > Terrain Correction > SAR Simulation DEM: SRTM 3 sec DEM Resamling: Bilinear Interpolation


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Simulated SAR Intensity

e) SAR Simulation Terrain Correction Geometry > Terrain Correction > SAR-Simulation Terrain Correction

DEM: SRTM 3Secautomatically downloaded DEM Resampling: Bilinear Interpolation Number of GCP: 200?


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Resultant SAR-Simulation Terrain Correction in RGB


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f) Developing a Graph for Batch Processing of the above stepsg) Polarimetric Decomposition Definition: Radar target detection, feature extraction and feature classification. Feature detection using SAR is achieved through Polarimetric SAR (PolSAR). PolSAR allows for

identification and separation of scattering mechanisms in the polarization signatures for

purposes of classification and parameter estimation. It is sensitive to the character and

orientation of object and polarimetry could yield several descriptive new radar target


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detection parameters and lead to the improvement of radar detection algorithms (Lamei Z.

et al, 2008).

The polarimetric information of target echo can reflect the geometry structure and physicalcharacteristic of target, and polarimetric target decomposition theorem expresses the

average mechanism as the sum of independent elements in order to associate a physical

mechanism with each component. Unlike method using SAR for information process, targetdecomposition explores phase message contained in PolSAR data. Polarimetric target

decomposition theorems can be used for target classification or recognition.

Polarimetric SAR data are coherent by nature of the principle of operation, however, mostoften incoherent approaches are chosen for the post-processing in order to apply

conventional averaging and statistical method. At present, two main classes of

decomposition can be identified. One, called coherency decomposition, deals with

decomposition of the scattering matrix, while another, called incoherent decomposition,

deals with decomposition of coherency or covariance matrices.

POLSAR is sensitive to the orientation and character of objects from which the radar signalreturns and has been extensively used for terrain classification. Target decomposition theory

is one approach that has been widely used to extract information from POLSAR imagery bydecomposing the radar returns in terms of different components such as surface or single-

bounce scattering, double-bounce scattering, and volume scattering. Using such target

decomposition concepts it is possible to classify objects within POLSAR imagery as being due

to natural targets such as vegetation and water, and man-made targets such as buildings

(CPI, 2014)

h) Using PolSARPro v4.2 for SAR Data Analysis Select the Sensor and Platform, eg ALOS PALSAR

Select the Processing Level, eg L1.1 (this needs further processing to level 1.5) or L1.5 (in thiscase), and Polarimetric phase: Dual (HH or HV or VV or VH) or Quard (HH, HV, VV, VH).

The selected option, platform, turns yellowish (activated).

Setting up the Environment: Click Environment, the dialog box opens with prompts to specifythe Main Input Directory. Change this as appropriate to reference the folder with data.

Click Save & Exit

Import Data: Import > Input Data File.
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The ALOS PALSAR Input data file dialog box opens with various fields to be specified; Input

and Output Directories, and the SAR Leader File (beginning with LED-.)

After specifying the LED-file, click the Check Files Button. This automatically reads theSAR images and loads all the Phases and also updates the metadata; Scene ID, SAR Mode

(Quad or Dual), Data Level (1.1, 1.4 or 1.5), Node (Ascending or Descending passes), SAR Map

Projection, SAR Trailer File and SAR Image Files (all available Modes: HH, HV, VV, VH)

Click Read Header and it lists whether it is a GEOREFERENCED SAR IMAGE or not, InitialNumber of Rows and Columns.

Click ok, then an advise to Extract Data before Analysis shows

Click OK Data Extraction: Import > Extract > Full Resolution?


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Click Run Now, all the MENU Functionalities are Active: Environment, Input, Process and

Display

Displaying Polarization Data in PolSARPro v4.2

Click Display. The Display Dialog tab opens, with several options:

However, it is not possible to Create HSL File based on Quad Polarimetric Mode. Click Run


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Use BMP viewer to view the RGB Map: BMP Viewer, then Navigate to the SinclairRGB.bmp

Types of Coherent Interferometric Decompositions

Reference

1.

Lamei Zhang, Junping Zhang, Bin Zou and Ye Zhang, 2008: Comparison of Methods forTarget Detection and Applications using Polarimetric SAR Image. Habin Institute of

Technology, China. In PIERS ONLINE Vol. 4, No. 1, Pg 140-145.


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2. Computational Physics Inc. (2014) Synthetic Perture RADAR:http://www.cpi.com/capabilities/psar.html

Pre and Post Processing ALOS PALSAR in NEST

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