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The measurement and model construction of complex permittivity of corn leaves at the main frequency

points of L/S/C/X-band

Zeng Jiangyuan

Institute of Remote Sensing and Digital Earth

Chinese Academy of Sciences

35th International Symposium on Remote Sensing of EnvironmentApril 23, 2013

Outline

Outline

Background and Motivation

Complex permittivity of the targetsSoil, Vegetation, Snow, et al

The complex permittivity, shapes, and orientations of the vegetation elements together determine the scattering and emission by the canopy. (Ulaby, 1987,TGRS)

Background and Motivation

The complex permittivity of the target can be expressed as:

' j a complex number

The real part The imaginary part

Dielectric constant Dielectric loss factor

Therefore, the establishment of the relationship between the specific physical parameters of the vegetation and its complex permittivity is very important.

Outline

Materials and methods

Collecting location: Zhangye City——the largest breeding base of hybrid corn seeds in China Corn types: Zhengdan 985, Jundan 20 and Xianyu 335Corn heights: range from 0.95m to 2.05m

Corn leaves collection from various corn types and different corn heights

Materials and methodslettuce leaves potato leaves

apple-pear leaves winter apple leaves green poplar leaves

Collection of the other five types of

vegetation

Materials and methods

Instrument: the vector network analyzer E8362B

Method: coaxial probe technique

Materials: six types of vegetation samples

Frequency range: 0.2~20GHz

Temperature: 22℃

The vector network analyzer E8362B

High temperature probe

Materials and methodsVerification of the instrument accuracy after calibration

at room temperature

Reference: Li Liying et al "Laboratory measurement of the dielectric constant of frozen soil" Journal of Beijing Normal University(Natural Science), 2007

Materials and methods

The measurement of the complex permittivity of white bond papers combines copper and Teflon

(a) laboratory equipment (b) experimental results

(a) (b)

Methodological points—1.Determination of the thickness threshold

Thickness threshold is 3 mm

Materials and methodsMethodological points—2. Appropriate pressure

①.Overlay the leaves neatly

②.Apply appropriate pressure on the probe to measure the samples for the purpose of insuring no air gaps among them and avoiding excess pressure to alter the structure of the tissues

③.In order to reduce human errors and systematic errors,10 complex permittivity measurements of vegetation samples were averaged to represent the complex permittivity of the sample.

Materials and methodsAcquisition of the vegetation gravimetric moisture

How to obtain different gravimetric moisture?1. Samples were dried by the automatic drying oven for different time ranging

from 20 minutes to 2 hours after every measurement2. After the drying finished, samples were placed for 30 minutes to allow their

temperature to be equilibrate to room temperature and then measure their complex permittivity

3. Finally, the dry weights of samples were recorded after drying them in the oven for 48 h at 70 until their weights do not change any more

gravimetric moisture Dry weight

Fresh weight

Why obtain the gravimetric moisture?1. The gravimetric moisture is the dominant factor which influences the complex permittivity of vegetation; (Nelson S O et al,J Microw Power Electromagn Energy,2012)2. For the purpose of facilitating the practical application.

Finally, we get:The total number of measured data of the corn leaves with different gravimetric moisture is 26 and the water content ranges from 1.34% to 72.09%. While the number of the other five types of vegetation samples data is 6 or 7 and the water content ranges from 10.31% to 91.70%.

Outline

Measurement results and model constructionPart of the measurement results

(the percentages in the figure represent the gravimetric moisture of the samples)

Measurement results and model constructionGoal of model construction

Purpose: Establish empirical models of different vegetation types for describing the relationship between the gravimetric moisture and both the real and imaginary parts of complex permittivity of all vegetation types at the commonly used frequency points of microwave sensors.

These microwave sensors include SAR, scatterometers and radiometers and the commonly used frequency points are as follow:

L=1.26GHz (ALOS PALSAR sensor) L=1.4GHz (SMOS satellite)

S=3.2GHz (Chinese HJ-1C radar satellite)

C=5.3GHz (ERS-1/2 satellite) C=6.9GHz (Aqua AMSR-E sensor)

X=9.6GHz (TerraSAR-X satellite and Cosmo-SkyMed satellite)

Measurement results and model constructionTake f=5.3 GHz as an example (the results of remaining frequency points are similar)

Measurement results and model construction

Thus, the empirical model used for describing the relationship between the gravimetric moisture and both the real and imaginary parts of complex permittivity at a specific frequency can be expressed as:

2

2

1

1

'

''

a Mg

b Mg

a e

b e

Where a1,a2,b1,b2 are the coefficients which need to be calibrated

The look-up table of the empirical model of corn leaves at the main frequency points of L/S/C/X-band

Outline

Comparisons and validations

The comparison between the empirical models and the Debye-Cole modelat f=5.3GHz (the results of remaining frequency points are similar)

Colpitts and Coleman also found that the Debye-Cole model cannot fit the complex permittivity of potato leaves well, and the model overestimates the real and imaginary parts of complex permittivity of potato leaves (Colpitts and Coleman, TGRS,1997)

Comparisons and validations

The corn leaves samples used for validation were collected from Huailai county in Hebei province, China

Finally, the number of measured data with different gravimetric moisture is 30 and the moisture content ranges from 1.34% to 72.09%

Comparisons and validationsThe comparisons and validations between the empirical model of corn

leaves and the Debye-Cole model by using measured data

at f=5.3GHz (the results of remaining frequency points are similar)

Comparisons and validationsThe comparisons between the empirical model of corn leaves and the

Debye-Cole model by using measured data at the main frequency points of the L/S/C/X-band

Outline

Conclusions and Discussions①. the variation of the complex permittivity of all the vegetation with frequency follows the same rules: the real part of the complex permittivity decreases monotonically as the frequency increases, while the imaginary part decreases as the frequency increases in the low frequency range, after reaching the minimum value, it increases as the frequency increases and finally tends to be stable;

②. At a specific frequency, the relationship between both the real and imaginary parts of the complex permittivity of all vegetation and their gravimetric moisture can fit well with a simple base e exponential function;

③. Debye-Cole model will overestimate the value of both the real and imaginary parts of the complex permittivity of all six types of vegetation in high water content (i.e. >30%);

④. By using the measured data for the comparison and validation between the empirical model of corn leaves and the Debye-Cole model, it was found that the empirical model of corn leaves has higher accuracy and is more practical than the Debye-Cole model.