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Poster Session
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A study of Remote Sensing Information model of soil moisture
Computer mapping of soil moisture
From the theory of soil moisture remote sensing information model mentioned above, the flowchart of computer mapping is designed (Fig.1)
Fig. Technical flowchart of computer mapping
- Calculation of ATI
ATI is (1-A)/Td-Tn) , where real value of A and Td-Tn are
A= 0.4230 chl + 0.5770 ch2-----------------------------------(4)
Td- Tn =ch4 (D) - ch4(N)-----------------------(5)
Where D represents noon, N represents midnight.
- Calculation of RTI (P)
In formula (2), So=1360 J/m-s; Ct=0.76; B=9.66 J/m.s° C; w= 7.3x101-5 1/s .And,
Ai= (2/3.14) sin (h) sin(q) sin(t)+(3.14/2)cos(h)cos(q)(sin(2t)+2t)
where solar declination h= -4°35'24"(1989.3.9), t=arcos(tg(h)tg(q)); Latitute q = N36°-----N41°
From the parameters above, RTI is ascertained.
- The Establishment of Lookup Table
From formula (3), ds is obtained by false color composition with soil map on the basis of soil texture. The lookup table was built (Fig.2)
Fig.2 Lookup Table of Apparent Soil Moisture (Wm%), ds(g/cm 3) and P(Jm.s.° C)
| (Wm%P)ds |
2.71 |
2.68 |
2.57 |
2.50 |
2.55 |
2.60 |
2.65 |
| 5.0 |
254.46 |
246.58 |
218.92 |
202.36 |
214.11 |
226.26 |
238.84 |
| 10.0 |
500.84 |
489.87 |
450.38 |
425.73 |
443.30 |
461.05 |
478.99 |
| 15.0 |
660.86 |
639.37 |
567.14 |
526.33 |
555.08 |
585.83 |
618.66 |
| 20.0 |
993.23 |
955.58 |
827.70 |
754.14 |
806.09 |
861.05 |
919.15 |
| 25.0 |
1421.05 |
1363.07 |
1167.71 |
1056.61 |
1135.04 |
1218.47 |
1307.18 |
| 30.0 |
1951.90 |
1866.68 |
1582.06 |
1421.80 |
1534.71 |
1655.55 |
1784.83 |
- Soil Moisture Mapping
The composition image of Hebei province plain according to ch4(D),Ch2,ch1, (R, G, B,) circled mountain, sea and cities with visual
interpretation , proceeding according to steps mentioned above, we gained soil moisture map (fig. 3)
Theoretically, this soil moisture represents average soil moisture of the definite depth in soil this depth is unlimited if the soil is
homogeneous. In general, this soil moisture is weighted means of real soil moisture of different depth during tilling depth (20cm----40cm) . This soil moisture can be called Apparent Soil Moisture (ASM) and it can be used for monitoring drought better than we think.
- To compare with field Measurement of soil moisture
The remote sensing data is NOAA gigital type of March 9, 1989 . The field measurement
data are provided by dydrogist of Hebei pprovince . It is pity there is only one point data . The location was marked roughly in Fig. 1 with a cross "+" . It shows no difference with the result which the computer yielded . The remote sensing data are one pixel information, but, the field measurement data are one point information . Then, the predicted result by the models would be tested to monitor drought with remote sensing soil moisture information model mentioned above. But it is required to be verified by a large amount of work.
References
- Bartholie, J.F., L.N. Namken and C.L.Wiegand, Water Stress Agronomg Journasl,64(1972), 603-608.
- Idso, S.B.etal. , J.Geophy Res., 80(1975), 3044-3049
Idso,S.B.et al. , American Scientist,63 (1975, 549-577)
- Zhang Xiang Qian, Ma Ai Nai , Remote Sensing Information, 2 (1986), 17-22. (In Chinese)
- Ma Ai Nai , Procedingsof ISPRS Commission IV,ID=8 1/6-6/6, the Tsukuba Symmposium (1990)
- idso, S.B. and W.L. Ehrler,Geophy, Res.Letters 3(1976), 23-25.
- Kahle,A.B.etal., Geophy. Res.Lett. 3(1976), 26-28.
- Commitee of soil Physical Properties Mesurement of Japan, Measurement of soil Physics , Science and Technology Literatures Press(1979) . (In Chinese)
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