DETERMINING SURFACE SOIL MOISTURE STATUS USING DIGITAL IMAGE ANALYSIS | ||||
| Misr Journal of Agricultural Engineering | ||||
| Article 18, Volume 29, Issue 4, October 2012, Page 1545-1566 PDF (625.9 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjae.2012.101378 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| D. M. El Shikha1; A. M. El-Ghamry2; A. M. El Shikha3 | ||||
| 1Associate Professor, Agricultural Engineering Department, Fac. of Agric, Mansoura University, Egypt | ||||
| 2Associate Professor, Soils Department, Fac. of Agric., Mansoura University, Egypt | ||||
| 3Assistant Professor, Agricultural Engineering Department, Fac. of Agric, Damietta branch, Mansoura University, Egypt | ||||
| Abstract | ||||
| Estimating surface soil moisture from soil color using image analysis is evaluated in this paper. The experiment consisted of five samples of natural soil [sandy clay loam (1), clay loam (2), silty clay loam (3), sandy (4) and clayey (5)] with four levels of moisture [applying 0 (a- air dried soils), 100 (b), 150 (c), 200% (d) of field capacity (FC)]. Soil samples were spread in wooden trays (1x1x0.15 m). Soil was wetted to full saturation twice and let to dry before the experiment started. In each tray, the soil surface was leveled and soil depth was measured to be 15 cm. All soil samples (trays) were wetted to the moisture contents mentioned above then they were photographed. The variations in soil color (red, green, and blue values and their standard deviations) with moisture content were investigated. Results indicated that all the tested soils had an inverse relation between moisture content and the average of the standard deviation of the green and red values (). The average of the green and red values was not as consistent as the ASDRG in separating the soil moisture treatments. Also, the ASDRG was clearer than the average of the blue, green or red values in indicating the presence of standing water. Some examples of practical applications of the method used in this study are estimating the runoff, the advance and recession of the water over the field surface, the water ponding on the soil surface, and estimating the application uniformity. | ||||
| References | ||||
|
Aston, A. R. and C. H. M. Van Bavel. 1972. Surface Soil Water Depletion and Leaf Temperatures. Agron Journal 64, 368-373.
Chen, F.; D.E. Kissel; L.T. West, and W. Adkins. 2000. Field-scale mapping of surface soil organic carbon using remotely sensed imagery. Soil Sci. Soc. Am. J. 64:746-753.
Dewis, J. and F. Fertias. 1970. Physical and Chemical Methods of Soil and Water Analysis. Soils Bulletin No. 10. Rome, FAO.
Ehrler, W. L. 1972. Cotton leaf temperatures as related to soil water depletion and meteorological factors. Agron. J. 65: 404-409.
Ehrler, W.L.; S.B. Idso; R.D. Jackson; and R.J. Reginato. 1978. Wheat canopy temperature: Relation to plant water potential. Agron. J.70: 251-256.
Gardner, B.R. and B. L. Blad. 1981. Relationships between Crop Temperature, Grain Yield, Evapotranspiration and Phenological Development in two Hybrids of Moisture Stressed Sorghum. Irrigation Science, 2: 213-224.
Hesse, P.R., 1971. A Text Book of Soil Chemical Analysis. Juan Murry (Publisher) Ltd., London.
Jackson, M.L., 1967. Soil Chemical Analysis. Printice-Hall of India, New Delhi.
Kostrzewski, M.; P. Waller; P. Guertin; J. Haberland; P. Colaizzi; E. Barnes; T. Thompson; T. Clarke; E. Riley, and C Choi. 2002. Ground-based remote sensing of water and nitrogen stress. Transactions of the ASAE 46(1): 29-38.
Persson, M. 2005. Estimating surface soil moisture from soil color using image analysis. Vadose Zone J., 4 (November), 1119-1122.
Richards, L.A., 1954. Diagnosis and Improving of Saline and Alkaline Soils. U.S., Salinity Laboratory Staff. Agric. Handbook, No. 60. | ||||
|
Statistics Article View: 198 PDF Download: 252 |
||||
