Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation

Precision Agriculture

Volumn 13, Issue 6, 2012, Pages 611-627

  Samseemoung, Grianggai ^a   Soni, Peeyush ^b   Jayasuriya, Hemantha P W ^c   Salokhe, Vilas M ^d  

^a RAJAMANGALA UNIVERSITY OF TECHNOLOGY THANYABURI   (Thailand)

^b ASIAN INSTITUTE OF TECHNOLOGY   (Thailand)

^c SULTAN QABOOS UNIVERSITY   (Oman)

^d KAZIRANGA UNIVERSITY   (India)

Author keywords

Crane mounted image acquisition; Crop growth monitoring; Helicopter mounted image acquisition; NDVI; Weed detection

Indexed keywords

CHLOROPHYLL; DETECTION METHOD; DIGITAL IMAGE; GERMINATION; IMAGE ANALYSIS; MONITORING; NDVI; PLANTATION; REMOTE SENSING; SOYBEAN; WEED;

GLYCINE MAX;

EID: 84868629417     PISSN: 13852256     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11119-012-9271-8     Document Type: Article

References (15)

1. Chaisattapagon, C., & Zhang, N. (1995). Effective criteria for weed identification in wheat fields using machine vision. Transactions of the American Society of Agricultural and Biological Engineers, 38(3), 965-974.
2. Hunt, E. R., Cavigelli, M. A., Daughtry, C. S., McMurtrey, J. E., & Walthall, C. L. (2005). Evaluation of aerial photography from model aircraft for remote sensing crop biomass and nitrogen status, Precision Agriculture, 6(4), 359-378. doi: 10. 1007/s11119-005-2324-5.
3. James, J. S. T., Goodman, L., Franz, H., & Armanini, M. P. (1996). Characterization of a multi-component receptor for GDNF, Letters to nature, Nature 382, 80-83. doi: 10. 1038/382080a0.
4. Kim, K., & Chavas, J. P. (2003). Technological change and risk management: an application to the economics of corn production. Agricultural Economics, 29(2), 125-142.
5. Koundauri, P., Nauges, C., & Tzouvelekas, V. (2006). Technology adoption under production uncertainty: theory and application to irrigation technology. American Journal of Agricultural Economics, 88(3), 657-670.
6. Markwell, J., Osterman, J. C., & Mitchell, J. L. (1995). Calibration of the Minolta SPAD-502 leaf chlorophyll meter. Photosynthesis Research, 46, 467-472.
7. Meyer, K. (1998). A program to estimate covariance functions for longitudinal data by restricted maximum likelihood, Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, Armidale, 27, 465-466.
8. Samseemoung, G., Jayasuriya, H. P. W., & Soni, P. (2011). Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform, Journal of Applied Remote Sensing, 5, 053540; doi: 10. 1117/1. 3609843.
9. Stafford, J. V. (2000). Implementing precision agriculture in the 21st century. Journal of Agricultural Engineering Research, 76(3), 267-275.
10. Stafford, J. V., & Benloch, J. V. (1997). Machine assisted detection of weeds and weed patches, Precision Agriculture'97 Oxford, BIOS Scientific Publishers Limited, pp. 511-518.
11. Steven, M. D. (1993). Satellite remote sensing for agricultural management: opportunities and logistic constraints. ISPRS Journal of Photogrammetry and Remote Sensing, 48(4), 29-34.
12. Swain, K. C., & Jayasuriya, H. P. W. (2007). Land-use suitability evaluation criteria for precision agriculture adoption in a moderately yielding soybean cropping area in Thailand. Asia-Pacific Journal of Rural Development, 17(1), 113-125.
13. Tangwongkit, R., Salokhe, V. M., & Jayasuriya, H. P. W. (2006). Development of a real-time, variable rate herbicide applicator using machine vision for between-row weeding of sugarcane fields. The CIGR E-Journal, 8, 1-12.
14. Tian, L., Reid, J. F., & Hummel, J. (1999). Development of a precision sprayer for site-specific weed management. Transactions of the ASAE, 42(4), 893-900.
15. Tillet, N. D., Marchant, J. A., & Hague, T. (1996). Autonomous plant scale crop protection, Abstracts of the International Conference on Agricultural Engineering, AgEng Madrid 96, Paper No. 96A-124, pp. 255-256.