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United States Department of Agriculture

Agricultural Research Service

Title: Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

Authors
item Swain, Kishore - NOVA SCOTIA AGRIC,COLLEGE
item THOMSON, STEVEN
item Jayasuriya, Hemantha -

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 15, 2009
Publication Date: March 1, 2010
Citation: Swain, K.C., Thomson, S.J., Jayasuriya, H. 2010. Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop. Transactions of the ASABE. 53(1):21-27.

Interpretive Summary: Timely application of nutrients is important for optimal yield of rice. Under-application of nutrients can limit growth, but over- (or too frequent) application can be costly and has the potential of increasing pollution to ground and surface waters. Remote sensing from aircraft or satellites has the potential to determine areas of a field that require extra nitrogen (N), but conventional methods are usually quite costly, cannot be scheduled frequently, and are not readily accessible to the farmer. Use of a remotely controlled helicopter with remote sensing cameras is proposed to obtain images of nutrient-stressed field areas for rice management. In Asia, many fields are small, so this platform is ideal for obtaining imagery on a frequent basis. Frequent scheduling can be quite critical during periods of pending crop stress due to nitrogen or water deficiency, for example. A low cost radio-controlled helicopter with remote sensing cameras could be owned by a single manager of a large farm, a farmer cooperative, or a local consulting service and has a low physical storage requirement. The system can be easily transported, and is amenable to rapid processing of imagery for determination of where in a field to apply nutrients. A study was conducted to estimate yield and total biomass of a rice crop using a helicopter-based remote sensing system. Fifteen rice field plots with five N-treatments having three replications each were arranged in a randomized complete block design for estimating yield and biomass as a function of applied N. Images were obtained by the remote sensing platform mounted in the helicopter, operating at the height of 20-m over experimental plots. The rice yield and total biomass for five N-treatments were found to be significantly different at the 0.05 and 0.1 levels of significance, respectively. NDVI (Normalized Difference Vegetation Index) values at booting stage were highly correlated with yield and total biomass with regression coefficients of 0.95 and 0.96, respectively. The study demonstrated the suitability of using images obtained from remotely controlled helicopter for prediction of yield and total biomass in rice cropping. The system could be used to evaluate areas that require additional nutrients at critical growth stages to improve final yield in rice cropping.

Technical Abstract: A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33, 66, 99 and 132 kg ha-1) having three replications each were arranged in a randomized complete block design for estimating yield and biomass as a function of applied N. Images were obtained by image acquisition sensors mounted on the LARS platform operating at the height of 20-m over experimental plots. The rice yield and total biomass for five N-treatments were found to be significantly different at the 0.05 and 0.1 levels of significance, respectively. NDVI (Normalized Difference Vegetation Index) values at booting stage were highly correlated with yield and total biomass with regression coefficients of 0.95 and 0.96, respectively. The study demonstrated the suitability of using LARS images for prediction of yield and total biomass in rice cropping. The system could be used to evaluate areas that require additional nutrients at critical growth stages to improve final yield in rice cropping.

Last Modified: 8/27/2014
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