Evaluation of pixel- and object-based approaches for mapping wild oat (Avena sterilis) weed patches in wheat fields using QuickBird imagery for site-specific management

European Journal of Agronomy

Volumn 59, Issue , 2014, Pages 57-66

  Castillejo González, Isabel Luisa ^a   Peña Barragán, José Manuel ^b   Jurado Expósito, Montserrat ^b   Mesas Carrascosa, Francisco Javier ^a   López Granados, Francisca ^b  

^a UNIVERSITY OF CÓRDOBA   (Spain)

^b INSTITUTO DE AGRICULTURA SOSTENIBLE   (Spain)

Author keywords

Broad and field level weed mapping; Herbicide savings; Pixel and object based image analysis; Precision agriculture; Remote sensing; Weeds

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; IMAGE CLASSIFICATION; PIXEL; QUICKBIRD; SATELLITE IMAGERY; WEED; WHEAT;

EID: 84902191436     PISSN: 11610301     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eja.2014.05.009     Document Type: Article

References (29)

1. Baatz M., Schäpe A. Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation. Proceedings of the 12th Symposium for Applied Geographic Information Processing (Angewandte Geographische Informationsverarbeitung XII. AGIT 2000). July 5-7, 2000 2000.
2. Barroso J., Fernández-Quintanilla C., Maxwell B.D., Rew L. Simulating the effects of spatial weed pattern and resolution of mapping and spraying on economics of site-specific management. Weed Res. 2004, 44:460-468.
3. Barroso J., Fernández-Quintanilla C., Ruiz D., Hernaiz P., Rew L. Spatial stability of Avena sterilis ssp. ludoviciana under annual applications of low rates of imazamethabenz. Weed Res. 2004, 44:178-186.
4. Blanco-Moreno J.M., Chamorro L., Sans X. Spatial and temporal patterns of Lolium rigidum-Avena sterilis mixed populations in a cereal field. Weed Res. 2006, 46:207-218.
5. Blaschke T. Object based image analysis for remote sensing. ISPRS-J. Photogramm. Remote Sens. 2010, 65:2-16.
6. Castillejo-González I.L., López-Granados F., García-Ferrer A., Peña-Barragán J.M., Jurado-Expósito M., de la Orden M.S., González-Audicana M. Object- and pixel-based analysis for mapping crops and their agro-environmental associated measures using QuickBird imagery. Comput. Electron. Agric. 2009, 68:207-215.
7. De Castro A.I., Jurado-Expósito M., Gómez-Casero M.T., Gómez-Candón D., Caballero-Novella J.J., López-Granados F. Discrimination of cruciferous weeds in wheat using QuickBird satellite image. Proceedings of the 3rd International Symposium in Recent Advances in Quantitative Remote Sensing 2010, J.A. Sobrino (Ed.).
8. De Castro A.I., López-Granados F., Jurado-Expósito M. Broad-scale cruciferous weed patch classification in winter wheat using QuickBird imagery for in-season site-specific control. Precis. Agric. 2013, 14:392-413.
9. Fernández-Quintanilla C., Navarrete L., Torner C., Sánchez Del Arco M.J. Avena sterilis en cultivos de cereales. Biología de las Malas Hierbas de España, 4-17. Phytoma, Valencia, Spain 1997, X. Sans, C. Fernández-Quintanilla (Eds.).
10. Foody G.M. Status of land cover classification accuracy assessment. Remote Sens. Environ. 2002, 80:185-201.
11. FP7-NMP Framework Programme 7-NMP: Nanosciences, Nanotechnologies, Materials and New Production Technologies. RHEA Project (2010-2014): Robot Fleets for Highly Effective Agriculture and Forestry Management 2009, Available at: http://www.rhea-project.eu/.
12. Gómez-Casero M.T., Castillejo-González I.L.i, García-Ferrer A., Peña-Barragán J.M., Jurado-Expósito M., García-Torres L., López-Granados F. Spectral discrimination of wild oat and canary grass in wheat fields for less herbicide application. Agron. Sustain. Dev. 2010, 30:689-699.
13. Haralick R.M., Shapiro L.G. Image segmentation techniques. Comput. Gr. Image Process. 1985, 29:100-132.
14. Heijting S., Van Der Werf W., Stein A., Kropff M.J. Are weed patches stable in location? Application of an explicitly two-dimensional methodology. Weed Res. 2007, 47:381-395.
15. Jurado-Expósito M., López-Granados F., González-Andújar J.L., García-Torres L. Spatial and temporal analysis of Convolvulus arvensis L. populations over four growing seasons. Eur. J. Agron. 2004, 21:287-296.
16. Jurado-Expósito M., López-Granados F., González-Andújar J.L., García-Torres L. Characterizing population growth rate of Convolvulus arvensis L. in wheat-sunflower no-tillage systems. Crop Sci. 2005, 45:2106-2112.
17. Laliberte A.S., Fredrickson E.L., Rango A. Combining decision trees with hierarchical object-oriented image analysis for mapping arid rangelands. Photogramm. Eng. Remote Sens. 2007, 73:197-207.
18. Laliberte A.S., Herrick J.E., Rango A., Winters C. Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring. Photogramm. Eng. Remote Sens. 2010, 76:661-672.
19. López-Granados F., Peña-Barragán J.M., Jurado-Expósito M., García-Torres L. Using remote sensing for identification of late-season grassy weeds patches in wheat (Triticum durum) for precision agriculture. Weed Sci. 2006, 54:346-353.
20. López-Granados F. Weed detection for site-specific weed management: mapping and real-time approaches. Weed Res. 2011, 51:1-11.
21. Lu D., Weng Q. A survey of image classification methods and techniques for improving classification performance. Int. J. Remote Sens. 2007, 28:823-870.
22. Montserud R.A., Leamans R. Comparing global vegetation maps with the kappa statistic. Ecol. Model. 1992, 62:275-293.
23. Peña-Barragán J.M., Ngugi M.K., Plant R.E., Six J. Object-based crop identification using multiple vegetation indices, textural features and crop phenology. Remote Sens. Environ. 2011, 115:1301-1316.
24. Richards J.A. Remote Sensing Digital Image Analysis 1999, Springer-Verlag, Berlin.
25. Richards J.A., Jia X. Remote sensing digital image analysis: an introduction 2006, Springer, New York. 4th ed.
26. Saavedra M., Cuevas J., Mesa-García J., García-Torres L. Grassy weeds in winter cereals in southern Spain. Crop Prot. 1989, 8:181-187.
27. Song C., Woodcock C.E., Seto K.C., Lenney M.P., Macomber S.A. Classification and change detection using Landsat TM Data: when and how to correct atmospheric effects?. Remote Sens. Environ. 2001, 75:230-244.
28. Spanish Ministry Spanish Ministry of Agriculture, Food and Environment 2013, Available at: http://www.magrama.gob.es/es/agricultura/temas/producciones-agricolas/cultivos-herbaceos/cereales/.
29. Torres-Sánchez J., López-Granados F., De Castro A.I., Peña-Barragán J.M. Configuration and specifications of an unmanned aerial vehicle (UAV) for early site specific weed management. PLoS ONE 2013, 8:e58210.