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Accurate soil moisture content measurements are vital to precision irrigation management. Remotesensing using the microwave spectrum such as GPS signals has been used for measuringlarge area soil moisture contents. In our previous work, we estimated surface soil moisture contentsfor bare soil using a GPS Delay Mapping Receiver DMR developed by NASA. However, theeffect of vegetation was not considered in these studies. Hence the objectives of this study were to:1 investigate the feasibility of using DMR to determine soil moisture content in cotton productionfields; 2 evaluate the attenuation effect of vegetation cotton on reflected GPS signal. Field experimentswere conducted during the 2013 and 2014 growing seasons in South Carolina. GPS antennaswere mounted at three heights 1.6, 2.7, and 4.2 m over cotton fields to measure reflectedGPS signals DMR readings. DMR readings, soil core samples, and plant measurements were collectedabout once a week and attenuation effect of plant canopy was calculated. Results showedthat DMR was able to detect soil moisture changes within one week after precipitation events thatwere larger than 25 mm per day. However, the DMR readings were poorly correlated with soil volumetricwater content during dry periods. Attenuation effect of plant canopy was not significant.For irrigation purpose, the results suggested that the sensitivity of reflected GPS signals to soilmoisture changes needed to be further studied before this technology could be utilized for irrigationscheduling in cotton production. Refinement of this technology will expand the use of advancedremote sensing technology for site-specific and timely irrigation scheduling. This wouldeliminate the need to install moisture sensors in production fields, which can interfere with farmingoperations and increase production costs.


Remote Sensing, GPS, Soil Volumetric Water Content, Cotton, Irrigation

Cite this paper

Qiao, X. , Khalilian, A. , O. Payero, J. , Mari Maja, J. , V. Privette, C. and J. Han, Y. 2016 Evaluating Reflected GPS Signal as a Potential Tool for Cotton Irrigation Scheduling. Advances in Remote Sensing, 5, 157-167. doi: 10.4236-ars.2016.53013.

Author: Xin Qiao1, Ahmad Khalilian1*, Jose O. Payero2, Joe Mari Maja2, Charles V. Privette1, Young J. Han1

Source: http://www.scirp.org/


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