A review: The role of remote sensing in precision agriculture

American Journal of Agricultural and Biological Science

Volumn 5, Issue 1, 2010, Pages 50-55

  Liaghat, S ^a   Balasundram, S K ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

Author keywords

Environment; Remotely sensed data; Spectral reflectance; Sustainable agriculture

Indexed keywords

EID: 75249096363     PISSN: 15574989     EISSN: 15574997     Source Type: Journal    
DOI: 10.3844/ajabssp.2010.50.55     Document Type: Review

References (34)

1. Auernhammer, H., 2001.Precision farming-the environmental challenge. Comput. Elect. Agric., 30: 41-33. DOI: 10.1016/S0168-1699(00)00153-8
2. Barnes, E.M. and M.G. Baker, 2000. Multispectral data for mapping soil texture: Possibilities and limitations. Applied Eng. Agric., 16: 731-741. http://asae.frymulti.com/abstract.asp?aid=5370&t=1
3. Barroso, L.A.M., J.G. Payan and E.R. Vivoni, 2008. Quantifying water stress on wheat using remote sensing in the Yaqui Valley, Sonora, Mexico. Agric. Water Mgmt., 95: 725-736. DOI: 10.1016/j.agwat.2008.01.016
4. Casady, W.W. and H. L. Palm, 2002. Precision agriculture: Remote sensing and ground truthing. MU Extension, University of Missouri-Columbia. http://extension.missouri.edu/explorepdf/envqual/eq0453.pdf
5. Dlamini, W.M., 2009. Characterization of the July 2007 Swaziland fire disaster using satellite remote sensing and GIS. Applied Geogr., 29: 299-307. DOI: 10.1016/j.apgeog.2008.10.007
6. Folhes, M.T., C.D. Renno and J.V. Soares, 2009. Remote sensing for irrigation water management in the semi-arid Northeast of Brazil. Agric. Water Mgmt., 96: 1398-1408. DOI: 10.1016/j.agwat.2009.04.021
7. Hinzman, L.D., M.E. Bauer and C.S.T. Daughtry, 1986. Effects of nitrogen fertilization on growth and reflectance characteristics of winter wheat. Remote Sens. Environ., 19: 47-61. DOI: 10.1016/0034-4257(86)90040-4
8. Jensen, J. R., 1996. Remote sensing of the environment: An Earth Resource Perspective. 3th Edn., Prentice Hall, USA, pp: 1-28.
9. Kropff, M.J., J. Wallinga and L.A.P. Lotz, 1997. Modelling for Precision Weed Management. In: Precision Agriculture: Spatial and Temporal Variability of Environmental Quality, Lake, J.V., G.R. Bock and J.A. Goode (Eds.). Chichester, Wiley, pp: 182-204.
10. Kurtz, D.B., J. Schellberg and M. Braun, 2009. Ground and satellite based assessment of rangeland management in sub-tropical Argentina. Applied Geogr. (In Press). DOI: 10.1016/j.apgeog.2009.01.006
11. Nowatzki, J., R. Andres and K. Kyllo, 2004. Agricultural remote sensing basics. http://www.ag.ndsu.edu/pubs/ageng/gis/ae1262.pdf
12. Lelong, C.C.D., P.C. Pinet and H. Poilve, 1998. Hyperspectral imaging and stress mapping in agriculture: A case study on wheat in Beauce (France). Remote Sens. Environ., 66: 179-191. DOI: 10.1016/S0034-4257(98)00049-2
13. Min, M., W.S. Lee, T.F. Burks, J.D. Jordan and A.W. Schumann, 2008. Design of a hyperspectral nitrogen sensing system for orange leaves. Comput. Elect. Agric., 63: 215-226. DOI: 10.1016/j.compag.2008.03.004
14. Moreau, S. and T.L. Toan, 2003. Biomass quantification of Andean wetland forages using ERS satellite SAR data for optimizing livestock management. Remote Sens. Environ., 84: 477-492. DOI: 10.1016/S0034-4257(02)00111-6
15. Oza, S.R., S. Panigrahy and J.S. Parihar, 2008. Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop. Int. J. Applied Earth Obst. Geoinform., 10: 296-304. DOI: 10.1016/j.jag.2007.12.002
16. Pal, M. and P.M. Mather, 2003. An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sens. Environ., 86: 554-565. DOI: 10.1016/S0034-4257(03)00132-9
17. Pan, G., G.J. Sun and F.M. Li, 2009. Using QuickBird imagery and a production efficiency model to improve. Environ. Model. Software, 24: 510-516. DOI: 10.1016/j.envsoft.2008.09.014
18. Perry, E.M. and J.R. Davenport, 2007. Spectral and spatial differences in response of vegetation indices to nitrogen treatments on apple. Comput. Elect. Agric., 59: 56-65. DOI: 10.1016/j.compag.2007.05.002
19. Riedell, W.E., S.L. Osborne and L.S. Hesler, 2004. Insect pest and disease detection using remote sensing techniques. Proceedings of 7th International Conference on Precision Agriculture. Minneapolis, MN USA. http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=166154
20. Samson, G., N. Tremblay, A.E. Dudelzak, S.M. Babichenko, L. Dextraze and J. Wollring, 2000. Nutrient stress of corn plants: Early detection and discrimination using a compact multiwavelength fluorescent lidar. Proceedings of EARSeL-SIG-Workshop LIDAR, June 16-17, Dresden/FRG, pp: 214-223. http://www.eproceedings.org/static/vol01_1/01_1_samson1.pdf
21. Schellberg, J., M.J. Hill, R. Gerhards, M. Rothmund and M. Braun, 2008. Precision agriculture on grassland: Applications, perspectives and constraints. Eur. J. Agron., 29: 59-71. DOI: 10.1016/j.eja.2008.05.005
22. Shikha, D.M.E., P. Waller, D. Hunsaker, T. Clarke and E. Barnes, 2007. Ground based remote sensing for assessing water and nitrogen status of broccoli. Agric. Water Mgmt., 92: 183-193. DOI: 10.1016/j.agwat.2007.05.020
23. Silva, T.A. and C.A. Beyl, 2005. Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency. Adv. Space Res., 35: 305-317. DOI: 10.1016/j.asr.2004.09.008
24. Singh, D., Sao, R. and Singh, K.P. 2007. A remote sensing assessment of pest infestation on sorghum. Adv. Space Res., 39: 155-163. DOI: 10.1016/j.asr.2006.02.025
25. Smart, D.R., M.L. Whiting and C. Stockert, 2007. Remote sensing of grape K deficiency symptoms using leaf level hyperspectral reflectance. Proceedings of Western Nutrient Management Conference, March 6-8, Salt Lake City, UT., pp: 19-24. http://cropandsoil.oregonstate.edu/sites/default/files/WERA103/2007_Proceedings/WNMC07.p19.Smart.pdf
26. Stroppiana, D., M. Boschetti, P.A. Brivio and S. Bocchi, 2008. Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry. Field Crop Res., 111: 119-129. DOI: 10.1016/j.fcr.2008.11.004
27. Tellaeche, A., X.P. BurgosArtizzu, G. Pajares, A. Ribeiro and C.F. Quintanilla, 2008. A new vision-based approach to differential spraying in precision agriculture. Comput. Elect. Agric., 60: 144-155. DOI: 10.1016/j.compag.2007.07.008
28. Tilling, A.K., G.J. O'Leary, J.G. Ferwerda, S.D. Jones, and G.J. Fitzgerald, 2007. Remote sensing of nitrogen and water stress in wheat. Field Crop Res., 104: 77-85. DOI: 10.1016/j.fcr.2007.03.023
29. Venkataratnam, L., 2001. Remote sensing and GIS in agricultural resources management. Proceedings of the 1st National Conference on Agro-Informatics, June3-4, Dharwad, India, pp: 20-29. http://www.insait.org/abstracts.pdf
30. Waheed, T., R.B. Bonnell, S.O. Prasher and E. Paulet, 2006. Measuring performance in precision agriculture: CART-A decision tree approach. Agric. Water Mgmt., 84: 173-185. DOI: 10.1016/j.agwat.2005.12.003
31. Yang, C.C., S.O. Prasher, P. Enright, C. Madramootoo and M. Burgess, 2003. Application of decision tree technology for image classification usingremote sensingdata. Agric. Syst., 76: 1101-1117. DOI: 10.1016/S0308-521X(02)00051-3
32. Yang, Y., H. Lin, Z. Guo and J. Jiang, 2007. A data mining approach for heavy rainfall forecasting based on satellite image sequence analysis. Comput. Geosci., 33: 20-30. DOI: 10.1016/j.cageo.2006.05.010
33. Zhang, N., M. Wang and N. Wang, 2002. Precision agriculture: A worldwide overview. Comput. Elect. Agric., 36: 113-132. DOI: 10.1016/S0168-1699(02)00096-0
34. Zhao, D., K.R. Reddy, V.G. Kakani and V.R. Reddy, 2005. Nitrogen deficiency effects on plant growth, leaf photosynthesis and hyperspectral reflectance properties of sorghum. Eur. J. Agron., 22: 391-403. DOI: 10.1016/j.eja.2004.06.005