OACALCATTSAR

Description

From one or more input channels, OACALCATTSAR calculates attributes of objects (polygons) in a vector layer, and then writes the output values to the same or a new segmentation vector layer. Attributes can be statistical, geometrical, textural, or polarimetric.

Parameters

oacalcattsar(fili, dbic, chnalias, filv, dbvs, filo, dbov, ftype, statatt, geoatt, ppixatt, qpatt, texatt, texwinsz)

Name	Type	Caption	Length	Value range
FILI*	str	Input file name	1 -
DBIC	List[int]	Input raster channels	0 -
CHNALIAS	str	Aliases of input channels	0 -
FILV	str	Name of input vector file	0 -
DBVS*	List[int]	Segment number of vector layer	1 - 1
FILO	str	Output vector file name	0 -
DBOV	List[int]	Output vector segment	0 - 1
FTYPE	str	Output file type	0 - 3	PIX \| SHP Default: PIX
STATATT	str	Statistical attributes to calculate	0 -
GEOATT	str	Geometrical attributes to calculate	0 -
PPIXATT	str	Calculate pure pixels	0 - 3	NO \| YES Default: NO
QPATT	str	Polarimetric attributes to calculate	0 -
TEXATT	str	Texture attributes to calculate	0 -
TEXWINSZ	List[int]	Size of texture window	0 - 1	Default: 11

* Required parameter

Parameter descriptions

FILI

The name of the PCIDSK file that contains the SAR-image channels to process.

DBIC

The channel or channels from which to extract attributes.

By default, all channels are processed.

CHNALIAS

Comma-separated aliases, or brief descriptions, of each channel specified as input.

The field names will appear in the attribute table with the aliases you specify.

If you do not specify a value, an alias is generated based on GDB-provided channel metadata, if it exists. If the channel metadata is unavailable, a generic sequence of bands is used; for example, B01, B02, B01, and so on.

Note: Aliases must be in the same order as the input channels, and the channel numbers must correspond.

FILV

The name of the file that contains a vector layer of closed polygons; typically, a segmentation layer generated by OASEGSAR.

If you do not specify a value, the PCIDSK file you specified as input is used.

DBVS

The vector layer to which to write the calculated attributes.

FILO

The file containing the segmentation layer to which to write the calculated attributes.

The file name you specify can be that of the input file or a new output file. When you create a new output file, the objects and attributes you specified are also written to the file.

If you do not specify a value, the segmentation layer is written to the corresponding layer of the input file.

DBOV

The segment number of the vector layer of the output file to which to write the results of the attribute calculation.

When FILO does not exist, DBOV will be ignored. The results will be written to the new file.

FTYPE

The format of the output file.

The following formats are supported:

PIX: PCIDSK
SHP: ArcView shapefile (ESRI)

The default is PIX.

STATATT

The statistical attributes to calculate for each object of the input segmentation vector layer from the input channels.

Specify the attributes you want to calculate as follows:

"" (None): Do not calculate texture attributes
ALL: Calculate all statistical attributes (MIN, MAX, MEAN, STD)
MIN: Minimum
MAX: Maximum
MEAN: Mean
STD: Standard deviation

You can also specify a subset of any statistical attributes. For example, to specify minimum and mean, enter "MIN, MEAN".

GEOATT

The geometrical attributes to calculate for each object of the input segmentation vector layer.

Specify the attributes you want to calculate as follows:

"" (None): Do not calculate geometrical attributes
ALL: Calculate all geometrical attributes (COM, ELO, CIR, REC, FOR, CON, SOL, MJR, MIA)
COM: Compactness
ELO: Elongation
CIR: Circularity
REC: Rectangularity
FOR: Form factor
CON: Convexity
SOL: Solidity
MJR: Major-axis length
MIA: Minor-axis length

By using a comma-separated string, you can define a subset of any geometrical attributes. For example, to specify form factor, solidity, and minor-axis length, enter "FOR, SOL, MIA".

PPIXATT

Calculate pure pixels.

You can specify the value as one of the following:

No: Do not calculate pure pixels.
Yes: Calculate pure pixels.

When you specify Yes, the field name will be appended with _PP_ to indicate it is pure-pixel statistics.

This parameter is optional.

QPATT

The polarimetric attributes to calculate for each object of the input segmentation vector layer.

Specify the attributes you want to calculate as follows:

ALL: Calculate all polarimetric attributes
CLOUDE: Cloude
FREEMAN: Freeman
TOUZI: Touzi
ALP: Alpha angle
BET: Beta angle
ENT: Entropy
ANI: Anisotopy
L1: Lambda 1
L2: Lambda 2
L3: Lambda 3
DB: Double-bounce
VOL: Volume
SUR: Surface
MAXDPOL: Maximum degree polarization
MINDPOL: Minimum degree polarization
MAXRPOW: Maximum receiving power
MINRPOW: Minimum receiving power
MSINT: Maximum scattering intensity
PHHVV: HHVV phase

By using a comma-separated string, you can define a subset of any polarimetric attributes. For example, to specify form Cloude and volume, enter "CLOUDE, VOL".

TEXATT

The texture attributes to calculate for each object of the input segmentation vector layer from the input raster layers.

The attributes are based on second-order statistics calculated from the gray-level cooccurrence matrices.

Specify the attributes you want to calculate as follows:

"" (None): Do not calculate texture attributes
ALL: Calculate all texture attributes (TMEAN, TSTD, TENT, T2ANGM, TCON)
TMEAN: Cooccurrence mean
TSTD: Cooccurrence standard deviation
TENT: Cooccurrence entropy
TANG2M: Cooccurrence angular second moment
TCON: Cooccurrence contrast

You can also specify a subset of any textural attributes. For example, to specify cooccurrence standard deviation and cooccurrence contrast, enter "TSTD, TCON".

TEXWINSZ

The size of the window to use to extract texture attributes.

The value you specify must be an odd integer and a minimum of 5.

The default size is 11.

Details

Supported channels

OACALCATTSAR can calculate attributes of the following channel types:

8U
16U
1S
32R

Statistical attributes

Statistical attributes are calculated based on the image pixels inside an object. Attributes are calculated for each of the selected image bands and added to the attribute table of the vector segment layer as new fields (attributes). The following table provides a description of statistical attributes you can calculate.

Table 1. Statistical attributes
Attribute	Short name	Description
Min.	Min	Minimum value of the pixels beneath an object in a selected band
Max.	Max	Maximum value of the pixels beneath an object in a selected band
Mean	Mean	Mean value of the pixels beneath an object in a selected band
Standard deviation	StdV	Standard-deviation value of the pixels beneath an object in a selected band

Pure-pixel statistics

Imagery and data sets of various resolutions are often used in an object-based image analysis (OBIA) to combine information from (a) high-spatial-resolution panchromatic or wide-band multispectral imagery acquired at a low-temporal resolution with (b) imagery from narrow-band multispectral high-temporal resolution with a low-spatial resolution. This fusion of information of various resolutions is used commonly with multitemporal image analysis.

Pixels along the borders of segments contain information from the adjoining segments and act as mixed pixels. This can have substantial impact on the local mean of a segment. To overcome the mixed-pixels issue, you can opt to calculate statistics by excluding the pixels on the segment boundary. This is referred to as pure-pixel statistics.

Geometrical attributes

The attributes representing geometrical characteristics of an object (polygon segment) make object-based image analysis (OBIA) advantageous over pixel-based measures. The geometrical attributes are calculated by analyzing the polygon boundary created during segmentation, so raster information is not required. Many of the shape descriptors used commonly are calculated. Each is described in the following table.

Note: Geometrical attributes are independent from the channel aliases, because they are calculated from the shape of objects.

Table 2. Geometrical attributes
Attribute	Short name	Description
Compactness	Compact	A measure of closely packed a shape is. A circle is the most compact. `Compactness = √(4 × As ÷ pi) ÷ O` Where `As` is the area of the object, and `O` is the perimeter of the object (outer contour).
Elongation	Elongation	The ratio of the height and width of a rotated, minimal-bounding box; that is, rotate a rectangle so it is the smallest rectangle in which the object fits, and then compare its height with its width. `Elongation = major axis length ÷ minor axis length`
Circularity	Circular	A ratio representing how like is the shape of the object to a circle. Circularity is the ratio of the area of a shape to the perimeter of the square of the shape. `Circularity = A_s ÷ O²` Where `A_s` is the area of the shape, and `O²` is square of the perimeter of the shape.
Rectangularity	Rectangular	How rectangular a shape is; that is, how much it fills its minimum bounding rectangle: `Rectangularity = A_s ÷ A_R` Where `A_s` is the area of a shape, and `A_R` is the area of the minimum bounding rectangle.
Convexity	Convexity	The relative amount that an object differs from a convex object. Convexity is calculated by forming the ratio of the perimeter of the convex hull of an object to the perimeter of the object itself. `Convexity = convex-hull perimeter ÷ object perimeter`
Solidity	Solidity	The density of an object. Solidity is calculated as the ratio of the area of an object to the area of a convex hull of the object. A value of `1` indicates a solid object, and a value less than `1` indicates an object having an irregular boundary or containing holes. `Solidity = area ÷ convex-hull area`
Form factor	FormFactor	The measure that compares the area of a polygon to the square of the perimeter. The form-factor value of a circle is `1`, and the value of a square is `pi` ÷ `4`. `Form factor = 4 × pi × area ÷ sqrt (perimeter)`
Major-axis length	MajorAxis	The length of the major axis of an oriented bounding box enclosing the polygon. Values are map units of the pixel size. If the image is not georeferenced, the values are pixels.
Minor-axis length	MinorAxis	The length of the minor axis of an oriented bounding box enclosing the polygon. Values are map units of the pixel size. If the image is not georeferenced, the values are pixels.

Texture attributes

You can calculate texture measures for a specific direction or directional invariant for all pixels in an input image. The measures are based on second-order statistics calculated from the gray-level cooccurrence matrices.

Table 3. Texture attributes
Attribute	Short name	Description	Algorithm
Mean	Tex_Mean_<ch_alias_name>	Cooccurrence mean	TEX
Standard deviation	Tex_Std_<ch_alias_name>	Cooccurrence standard deviation	TEX
Entropy	Tex_Ent_<ch_alias_name>	Cooccurrence entropy	TEX
Angular second moment	Tex_Ang2m_<ch_alias_name>	Cooccurrence angular second moment	TEX
Contrast	Tex_Cont_<ch_alias_name>	Cooccurrence contrast	TEX

Polarimetric attributes

The predefined polarimetric attributes described in the following table are available for fully polarimetric images only (matrix type = [s4c]). The attributes correspond to a selection of parameters from various polarimetric decompositions that have the potential to discriminate among a diverse set of land-cover classes.

Note: For more information about polarimetric attributes, in the following table, click

to view the help of the algorithm according to the relevant programming environment.

Table 4. Polarimetric attributes
Attribute	Short name in Attribute Manager	Unit (bounds: min., max.)	Algorithm
Scattering type	AlphaAngle	Degrees [`0,90`]	PSEABA
Entropy	Entropy	Unitless [`0,1`]	PSEABA
Anisotropy	Anisotropy	Unitless [`0,1`]	PSEABA
Orientation angle	BetaAngle	Degrees [`0,` ]	PSEABA
First eigenvalue	Lambda1	Intensity [`0,` ]	PSEABA
Second eigenvalue	Lambda2	Intensity [`0,` ]	PSEABA
Third eigenvalue	Lambda3	Intensity [`0,` ]	PSEABA
Double-bounce scattering	DoubleBounce	Intensity [`0,` ]	PSFREDUR
Volume scattering	Volume	Intensity [`0,` ]	PSFREDUR
Surface scattering	Surface	Intensity [`0,` ]	PSFREDUR
HH-VV phase difference	HHVVPhase	Degrees [`-180,180`]	PSPHDIFF
Maximum degree of polarization	MaxDegPol	Unitless [`0,1`]	PSPOLDIS
Minimum degree of polarization	MinDegPol	Unitless [`0,1`]	PSPOLDIS
Maximum of received power	MaxRecPwr	Intensity [`0,` ]	PSPOLDIS
Minimum of received power	MinRecPwr	Intensity [`0,` ]	PSPOLDIS
Maximum of scattered intensity	MaxScatInt	Intensity [`0,` ]	PSPOLDIS

Note: With the polarimetric parameters for PSPOLDIS, the step size for the orientation and ellipticity angles are set to five degrees (5), respectively.

Band aliases

Aliases supplement the organization of the attributes you calculate. With attributes calculated from image layers, corresponding fields are created in the attribute table of segments. To distinguish among the various attributes, the field name is appended with the relevant layer identifier. By using aliases, you can better manage and interpret the information in the attribute table, which you can view in Attribute Manager.

During attribute calculation, the metadata is analyzed for identification of various band names and short names based on the sensor and wavelength range.

Aliases are generated based on the GDB-provided channel-metadata tag, if it is present. With optical data, aliases are generated from the BandDescription tag and, with SAR data, from the Polorization tag. If the metadata is found, a generic short name, such as B01, B02, B03, and so on is applied as an alias. You can, however, modify the aliases to suit.

The following table shows an example of the channel-level metadata tags and aliases for a sample SAR image, RS2_ FQ18_20090818_HH_VV_HV_VH_SLC.pix.

Table 5. Aliases for sample SAR image
Input channel	RS2_ FQ18_20090818_HH_VV_HV_VH_SLC	Channel-metadata tag Polarization	Alias
1	RADARSAT-2 HH Sigma Nought Complex	HH	HH0818
2	RADARSAT-2 HV Sigma Nought Complex	HV	VV0818
3	RADARSAT-2 VH Sigma Nought Complex	VH	VH0818
4	RADARSAT-2 VV Sigma Nought Complex	VV	VV0818

For example, to generate the statistical attributes HH0818_mean, HH0818_min, VV0818_mean, VV0818_min for each object of a segmentation vector layer, specify the input channels and statistical attributes as follows:

DBIC=1,4
CHNALIAS="HH0818, VV0818"
STATTATT="Mean, Min"

Note: If necessary, you can use the same segmentation vector layer to run attribute calculation on several images. If any of the images already have aliases and attributes matching the ones defined herein, they will be overwritten.

Example

from pci.oacalcattsar import oacalcattsar
fili= "RS2_SLC_FQ09subset.pix"
dbic=[1,2,3,4]           
chnalias=""        
filv="RS2_SLC_FQ09subset_seg_35_0.1_0.5.pix"
dbvs=[2]
filo=""                               # Blank, calculated attributes will be to added filv/dbvs
dbov=[2]
ftype="PIX"
statatt="all"                    # Calculate all statistical attributes 
geoatt=""                        # None - do not calculate geometrical attributes
ppixatt="No"
qpatt="all"                      # Calculate all polarimetric attributes
texatt="tmean, tstd"     # Calculate only the mean and standard deviation texture measures
texwinsz=[11]

oacalcattsar ( fili, dbic, chnalias, filv, dbvs, filo, dbov, ftype, statatt, geoatt, ppixatt, qpatt, texatt, texwinsz)

Environments	PYTHON :: EASI
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OACALCATTSAR

Calculate object attributes from SAR imagery

Description

Parameters

Parameter descriptions

Details

Example