Abstract
The global field protection (GFP) was developed to protect and optimize pest management resources integrating satellite images for precise field demarcation with physical models of controlled release devices of pesticides to protect large fields. The GFP was implemented using a graphical user interface to aid the end-user to select location and define an arbitrary perimeter for protection. The system provides coordinates of drop points for the controlled release devices which can be delivered using drone technology, e.g. unmanned air vehicles. In this work, we present the first proof of concept of this technology. A vast number of pest management applications can benefit from this work, including prevention against vector-borne diseases as well as protection of large agriculture fields.
References
Alonso, P. L., Brown, G., Arevalo-Herrera, M., Binka, F., Chitnis, C., Collins, F., et al. (2011). A research agenda to underpin malaria eradication. PLoS Medicine, 8(1), e1000406.
Bratney, A., Whelan, B., Ancev, T., & Bouma, J. (2005). Future directions of precision agriculture. Precision Agriculture, 6(1), 7–23.
Chenghai, Y., Everitt, J. H., Du, B., Luo, Q., & Chanussot, J. (2013). Using high-resolution airborne and satellite imagery to assess crop growth and yield variability for precision agriculture. Proceedings of the IEEE, 101(3), 582–592.
Elman, N. M. (2013). Sustained release delivery devices, US patent 20140230313 A1.
Fuller, E. N., Schettler, P. D., & Giddings, J. C. (1966). New method for prediction of binary gas—phase diffusion coefficients. Industrial and Engineering Chemistry, 58(5), 18–27.
Herring, D. (2001). Precision farming: Feature articles. http://earthobservatory.nasa.gov/Features/PrecisionFarming/. Accessed, January 1, 2016.
Jenkins, H. (2008). Chemical thermodynamics at a glance., Clausius-Clapeyron equation Oxford: Blackwell Publishing Ltd.
Perkins, A., Scott, T. W., Le Menach, A., & Smith, D. L. (2013). Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission. PLoS Computational Biology, 9(12), e1003327.
Persson, P. O. (2004). Mesh generation for implicit geometries. Ph.D. thesis, Department of Mathematics, MIT.
Persson, P. O., & Strang, G. (2014). A simple mesh generator in MATLAB. SIAM Review, 46(2), 329–334.
Primicerio, J., Di Gennaro, S. F., Fiorillo, E., Genesio, L., Lugato, E., Matese, A., et al. (2012). A flexible unmanned aerial vehicle for precision agriculture. Precision Agriculture, 13(4), 517–523.
Schleier, J. J, 3rd, & Peterson, R. K. (2014). The mosquito ultra-low volume dispersion model for estimating environmental concentrations of insecticides used for adult mosquito management. Journal of the American Mosquito Control Association, 30(3), 223–227.
Smith, D. L., Perkins, A. T., Reiner, R. C, Jr, Barker, C. M., Niu, T., et al. (2014). Recasting the theory of mosquito-borne pathogen transmission dynamics and control. Transactions of the Royal Society of Tropical Medicine and Hygiene, 108(4), 185–197.
Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture, 13(6), 693–712.
Acknowledgments
This research work was partially supported by the following organizations: the US Army Research Office (contract: W911NF-07-D-0004) and the Department of Defense Deployed Warfighter Protection Program (contract: W911QY-12-1-0005) via the Institute for Soldier Nanotechnologies (ISN) at MIT.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have not conflict of interest.
Rights and permissions
About this article
Cite this article
Bright, L.Z., Handley, M., Chien, I. et al. Analytical models integrated with satellite images for optimized pest management. Precision Agric 17, 628–636 (2016). https://doi.org/10.1007/s11119-016-9434-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11119-016-9434-0