Effects of vegetation cover on soil moisture sensing with x-band radar
Zhao Changling, Hao Weixing, Li Shengping, Li Xiaohong
Institute of Remote Sensing Applications, Academia Sinica
Beijing, China
Ji Jiankang, Li Guikui
China Research Institute of Radiowave Prodagation
Xingxiang, Henan, China
Abstract
In this paper, the relationship between backscattering coefficient and soil moisture is studies for bare and vegetation (sweet potato, soyabean and peanut) - covered fields. Backscattering measurement carried out by means of sensing soil moisture with X-band radar image is affirmed. The results estimated by a simple model indicate that the sensitivity and accuracy of X-band are lower than that of C-band for vegetation-covered fields, but there will still be certain sensitivity and accuracy wit proper parameters. And the prediction error is about
±25% at X-band. As for bare soil fields, C-and C-band are quite similar accuracy.
Introduction
The use of microwave remote sensing in soil moisture measurements has caused very close attention over the past years. Significant progress in finding out about the relationship between backscattering coefficient and soil moisture has been achieved (1) - (10). Theoretical model and experiments have shown that, backscattering coefficient and soil moisture are closely related. In fact, the relationship is quire complicated. Ti s concerned in the factor as random roughness, soil texture (type), and vegetation cover as well as microwave frequency, incidence angel and polarization. Most of the research in this area was done at C-band in the past. Ulaby, et al. (9), think that C-band (freq. 4.25-4.75 GHz), HH polarization and small incidence angle (q = 10°) are optimum parameters in sensing soil moisture by radar.
In Asia, SAR and SLAR and X-band have been widely used. Someone is attending to study soil moisture by X-band radar image. Then whether or not could the X-band imaging radar be used to predict the soil moisture under vegetation cover? In this study, experimental data were summarized. We have analyzed the relationship between backscattering coefficient at X-band and bare soil moisture, and especially the effects of vegetation cover in detail. The ability of sensing soil moisture with X-band radar image is affirmed.
General Situation of Experiment
Bare soil field measurements were carried out at Xingxiang, Henan province of China, during May 10- June 8, 1989. And some vegetation covered field measurements were carried out at Pandian, near Xingxiang, China, during August 4 - September 27, 1989, crops observed were sweet potato, soyabean and peanut. The measurement system used in the experiments is X-band microwave scatterometer (fre: 9375 MHz) made by Shanghai institute of electron physics. The incidence angel can be changed (0° - 48°, step 6°). The azimuth can be changed continuously.
In the experiments we have noted the effects of soil texture composition, random roughness of the soil surface to microwave response of soil moisture. To minimize the influence of soil texture we used mf the percent of field capacity to represent the soil moisture. Considering that microwave penetration of soil is limited, thus we only collected the soil samples of a fixed layer, 5 cm depth, to measure soil moisture.
Some researchers reported that when the incidence angle is between 5° to 7°, the effect of the roughness of soil surface is smaller to the measurements. The optimum incidence angle is different to various bands. Generally the smaller angle is better. In this study, we mainly discuss the case of 60 the incidence angle.
Bare Soil
Fig.1 shows the response of backscattering coefficient
s° for bare soil as a function of mf the soil water content of the top 5-cm soil layer expressed in percent of field capacity at three incidence angles (q=6°, 12° and 18°).
mj = (100mf / FCg)% ----------------------(1)
Where m
f is the weight soil water content of top 5-cm layer in g water/g drysoil, and FC
g is the weight soil water content at 1/3 bar tension (commonly known as field capacity). Through the analysis of soil texture composition we can get the sand an clay content. And FCg can be calculated using the empirical relation derived by Schmugge (11).
FCg = 25.1 - 0.21S + 0.22C ---------------------------(2)
Where S and C are percent of sand and clay content, respectively. Application of a least squares linear regression fit yields.
s° g(dB) = 0.261 mmj - 25.83 dB, q= 6, r = 0.81 --------------------(3)
where r is the correlation coefficient.
Now we can further express (3) in natural units of m
2 m
-2
s°g= 0.003exp(0.06mj)m2. m-2, q = 6°, r = 0.81 -----------------(4)
