Image analysis aplications in precision agriculture

Aplicaciones de análisis de imágenes en agricultura de precisión

  • Wilson Fernando Moreno
  • Héctor Iván Tangarife
  • Andrés Escobar Díaz
Palabras clave: Aerial photography, agricultural applications, precision agriculture, UAV (en_US)
Palabras clave: Fotografía aérea, aplicaciones agrícolas, agricultura de precisión, UAV. (es_ES)

Resumen (en_US)

Unmanned Aircraft Vehicles (UAVs) are currently used for multiple applications in various fields: forestry, geology, the livestock sector and security. Among the most common applications, it is worth to stand out the image acquisition, irrigation, transport, surveillance and others. The study that one presents treats of the implementations that are realized by means of aerial images acquired with UAVs directed to the farming. Images acquired until recent years had been using satellites, however due to the high costs that are incurred and low accessibility to these technologies, UAVs, have become a tool for greater precision and scope for making decisions in agriculture. Information from databases of international magazines, groups and research centers is taken to determine the current state of implementations in Precision Agriculture (PA). This article describes tasks such as: soil preparation; limits and land areas, vegetation monitoring; classification of vegetation, growth, height, plant health; diseases management, pests and weeds, fertilization and inventory developed from analysis of aerial images acquired with UAVs.

Resumen (es_ES)

Los vehículos aéreos no tripulados (UAV) se usan actualmente para múltiples aplicaciones en múltiples campos: silvicultura, geología, sector ganadero y seguridad. Entre las aplicaciones más comunes cabe destacar la adquisición de imágenes, el riego, el transporte, la vigilancia, entre otros. Las imágenes adquiridas hasta los últimos años han estado utilizando satélites, sin embargo, debido a los altos costos que se incurren y el bajo acceso a estas tecnologías, los UAV se han convertido en una herramienta para mayor precisión y alcance para la toma de decisiones en la agricultura. La investigación que se presenta, trata de las implementaciones que se realizan mediante imágenes aéreas adquiridas con UAVs dirigidas a cultivos. La información de las bases de datos de revistas internacionales, grupos y centros de investigación se toma para determinar el estado actual de las implementaciones en Precision Agriculture (PA). Este artículo describe tareas tales como: preparación del suelo; límites y áreas de tierra, monitoreo de vegetación; clasificación de la vegetación, crecimiento, altura, estado fitosanitario; manejo de enfermedades, plagas y malezas, fertilización e inventarios desarrollados a partir del análisis de imágenes aéreas adquiridas con UAVs.

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Referencias

[1] F. López, “Uso de Vehículos Aéreos no tripulados ( UAV ) para la evaluación de la producción agraria” Ambient. Agric. precisión, pp. 40–52, 2013.

[2] S. Cox, “Information technology: The global key to precision agriculture and sustainability,” Comput. Electron. Agric., vol. 36, no. 2–3, pp. 93–111, 2002. https://doi.org/10.1016/S0168-1699(02)00095-9

[3] A. S. Danilov, U. D. Smirnov, and M. A. Pashkevich, “The system of the ecological monitoring of environment which is based on the usage of UAV,” Russ. J. Ecol., vol. 46, no. 1, pp. 14–19, 2015. https://doi.org/10.1134/S1067413615010038

[4] B. S. Faiçal, G. Pessin, G. P. R. Filho, A. C. P. L. F. Carvalho, G. Furquim, and J. Ueyama, “Fine-tuning of UAV control rules for spraying pesticides on crop fields,” IEEE, 2014.

[5] Y. Motor, “Yamaha unmanned helicopters,” Yamaha Australia Sky Division, p. 8, 2014.

[6] K. Uto, H. Seki, G. Saito, and Y. Kosugi, “Development of uav-mounted miniaturure hyperspectral sensor system for agricultural monitoring,” 2013 IEEE Int. Geosci. Remote Sens. Symp. - IGARSS, pp. 4415–4418, 2013. https://doi.org/10.1109/IGARSS.2013.6723814

[7] Y. Saleem, M. H. Rehmani, and S. Zeadally, “Integration of Cognitive Radio Technology with unmanned aerial vehicles: Issues, opportunities, and future research challenges,” J. Netw. Comput. Appl., vol. 50, pp. 15–31, 2015. https://doi.org/10.1016/j.jnca.2014.12.002

[8] A. Sato and H. Naknishi, “Observation and measurement in disaster areas using industrial use unmanned helicopters,” 2014 IEEE Int. Symp. Safety, Secur. Rescue Robot., pp. 1–5, 2014. https://doi.org/10.1109/SSRR.2014.7017671

[9] G. Bareth, “Use of drones in agriculture - prospects and limitations,” Plantekongres, p. 90, 2014.

[10] E. Salamí, C. Barrado, and E. Pastor, “UAV Flight Experiments Applied to the Remote Sensing of Vegetated Areas,” Remote Sens., vol. 6, no. 11, pp. 11051–11081, 2014. https://doi.org/10.3390/rs61111051

[11] D. Anthony, S. Elbaum, A. Lorenz, and C. Detweiler, “On Crop Height Estimation with UAVs,” IEEE, pp. 4805–4812, 2014. https://doi.org/10.1109/IROS.2014.6943245

[12] T. Arnold, M. De Biasio, A. Fritz, and R. Leitner, “UAV-based measurement of vegetation indices for environmental monitoring,” Proc. Int. Conf. Sens. Technol. ICST, pp. 704–707, 2013. https://doi.org/10.1109/ICSensT.2013.6727744

[13] F. Ay and B. Bili, “Insansız Hava Aracı ile Tarımsal ˙ Ilaçlama Application of Pesticide Using Unmanned Aerial Vehicle,” no. 2130187, pp. 0–3, 2015.

[14] E. A. George, G. Tiwari, R. N. Yadav, E. Peters, and S. Sadana, “UAV systems for Parameter Identification in Agriculture” IEEE, pp. 270–273, 2013. https://doi.org/10.1109/GHTC-SAS.2013.6629929

[15] B. P. L. Hollis, B. J. Hart, A. Austin, and R. Clover, “North Carolina to test UAV use in agricultural production,” vol. 42, no. 9, pp. 6–9, 2015.

[16] J. J. Berni, P. P. J. Zarco-tejada, L. Suarez, E. Fereres, S. Member, and L. Suárez, “Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle,” IEEE Trans. Geosci. Remote Sens., vol. 47, no 3, pp. 722–738, 2009. https://doi.org/10.1109/TGRS.2008.2010457

[17] D. Bannett, “What are key UAV issues for agriculture?,” South east farm press, p. 2, 1990.

[18] R. Bongiovanni and J. Lowenberg-Deboer, “Precision agriculture and sustainability,” Precis. Agric., vol. 5, no. 4, pp. 359–387, 2004. https://doi.org/10.1023/B:PRAG.0000040806.39604.aa

[19] F. R. Leiva, “La agricultura de precisión: Una producción más sostenible y competitiva con visión futurista,” VIII Congr. la Soc. Colomb. Fitomejoramiento y Prod. Cultiv, November, 2003.

[20] K. Thorp, “Encyclopedia of Remote Sensing: Precision agriculture article,” Precis. Agric., 2014. https://doi.org/10.1007/s11119-012-9274-5

[21] C. Zhang and J. M. Kovacs, “The application of small unmanned aerial systems for precision agriculture: A review,” Precis. Agric., vol. 13, no. 6, pp. 693–712, 2012.

[22] Yamaha, “Yamaha Helicopter Tipo II G / tipo II,” may 12th 2015. [Online]. Available: http://rmax.yamaha-motor.com.au/

[23] J. Gago, C. Douthe, R. E. Coopman, P. P. Gallego, M. Ribas-Carbo, J. Flexas, J. Escalona, and H. Medrano, “UAVs challenge to assess water stress for sustainable agriculture,” Agric. Water Manag., vol. 153, pp. 9–19, 2015. https://doi.org/10.1016/j.agwat.2015.01.020

[24] Aerodreams, “Chi-7 productos,” may 12th 2015 [Online]. Available: http://www.aerodreams-uav.com/

[25] A. Valencia, “Real Group Interactive,” may 12th 2015 [Online]. Available: http://www.realgroupinteractive.com

[26] GeoSpatial, “GeoSpatial soluciones espaciales para infrestructura,” may 12th 2015 [Online]. Available: http://www.geospatial.com.co/

[27] F. Escobar, “Advector s.a.s,” may 12th 2015 [Online]. Available: http://www.advector.co/

[28] J. Torres, F. López, and J. M. Peña, “An automatic object-based method for optimal thresholding in UAV images: Application for vegetation detection in herbaceous crops,” Comput. Electron. Agric., vol. 114, pp. 43–52, 2015. https://doi.org/10.1016/j.compag.2015.03.019

[29] J. Torres, J. M. Peña, A. I. de Castro, and F. López, “Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV,” Comput. Electron. Agric., vol. 103, pp. 104–113, 2014. https://doi.org/10.1016/j.compag.2014.02.009

[30] C. A. Rokhmana, “The Potential of UAV-based Remote Sensing for Supporting Precision Agriculture in Indonesia,” Procedia Environ. Sci., vol. 24, pp. 245–253, 2015. https://doi.org/10.1016/j.proenv.2015.03.032

[31] K. Shen, W. Li, Z. Pei, W. Fei, G. Sun, X. Zhang, X. Chen, and S. Ma, “Crop Area Estimation from UAV Transect and MSR Image Data Using Spatial Sampling Method,” Procedia Environ. Sci., vol. 26, no. 41301506, pp. 95–100, 2015. https://doi.org/10.1016/j.proenv.2015.05.007

[32] F. J. Mesas, M. D. Notario, J. E. Meroño de Larriva, M. Sánchez de la Orden, and A. García, “Validation of measurements of land plot area using UAV imagery,” Int. J. Appl. Earth Obs. Geoinf., vol. 33, pp. 270–279, 2014. https://doi.org/10.1016/j.jag.2014.06.009

[33] Y. Lin, M. Jiang, Y. Yao, L. Zhang, and J. Lin, “Use of UAV oblique imaging for the detection of individual trees in residential environments,” Urban For. Urban Green., vol. 14, no. 2, pp. 404–412, 2015. https://doi.org/10.1016/j.ufug.2015.03.003

[34] J. A. Gonçalves and R. Henriques, “UAV photogrammetry for topographic monitoring of coastal areas,” ISPRS J. Photogramm. Remote Sens., vol. 104, pp. 101–111, 2015. https://doi.org/10.1016/j.isprsjprs.2015.02.009

[35] J. Bendig, K. Yu, H. Aasen, A. Bolten, S. Bennertz, J. Broscheit, M. L. Gnyp, and G. Bareth, “Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley,” Int. J. Appl. Earth Obs. Geoinf., vol. 39, pp. 79–87, 2015. https://doi.org/10.1016/j.jag.2015.02.012

[36] P. J. Zarco, R. Diaz, V. Angileri, and P. Loudjani, “Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods,” Eur. J. Agron., vol. 55, pp. 89–99, 2014. https://doi.org/10.1016/j.eja.2014.01.004

[37] P. J. Zarco, M. L. Guillén, R. Hernández, A. Catalina, M. R. González, and P. Martín, “Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle (UAV),” Agric. For. Meteorol., vol. 171–172, pp. 281–294, 2013. https://doi.org/10.1016/j.agrformet.2012.12.013

[38] M. Uysal, A. S. Toprak, and N. Polat, “DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill,” Measurement, vol. 73, pp. 539–543, 2015. https://doi.org/10.1016/j.measurement.2015.06.010

[39] P. K. Freeman and R. S. Freeland, “Politics & technology: U.S. polices restricting unmanned aerial systems in agriculture,” Food Policy, vol. 49, pp. 302–311, 2014. https://doi.org/10.1016/j.foodpol.2014.09.008

[40] J. Straub, “Unmanned aerial systems: Consideration of the use of force for law enforcement applications,” Technol. Soc., vol. 39, pp. 100–109, 2014. https://doi.org/10.1016/j.techsoc.2013.12.004

[41] C. Pinilla, “Actualizaciones catastrales mediante teledetección,” in 1st International Congress on Unified and Multipurpose Cadastre, 2010, pp. 1–4.

[42] S. P. Bemis, S. Micklethwaite, D. Turner, M. R. James, S. Akciz, S. T. Thiele, and H. A. Bangash, “Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology,” J. Struct. Geol., vol. 69, pp. 163–178, 2014. https://doi.org/10.1016/j.jsg.2014.10.007

[43] S. Siebert and J. Teizer, “Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system,” Autom. Constr., vol. 41, pp. 1–14, 2014. https://doi.org/10.1016/j.autcon.2014.01.004

[44] K. D. Peter, S. d’Oleire-Oltmanns, J. B. Ries, I. Marzolff, and A. Ait Hssaine, “Soil erosion in gully catchments affected by land-levelling measures in the Souss Basin, Morocco, analysed by rainfall simulation and UAV remote sensing data,” Catena, vol. 113, pp. 24–40, 2014. https://doi.org/10.1016/j.catena.2013.09.004

[45] DANE, “Manual de uso de fotografía aérea y cartografía topográfica,” pp. 1–68, 2013.

[46] S. Yahyanejad and B. Rinner, “A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs,” ISPRS J. Photogramm. Remote Sens., vol. 104, pp. 189–202, 2015. https://doi.org/10.1016/j.isprsjprs.2014.07.015

[47] H. Xiang and L. Tian, “Method for automatic georeferencing aerial remote sensing (RS) images from an unmanned aerial vehicle (UAV) platform,” Biosyst. Eng., vol. 108, no. 2, pp. 104–113, 2011. https://doi.org/10.1016/j.biosystemseng.2010.11.003

[48] A. Matese, F. Capraro, J. Primicerio, G. Gualato, S. F. Di Gennaro, and G. Agati, “Precision agriculture ’13,” pp. 201–208, 2013.

[49] R. Ballesteros, J. F. Ortega, D. Hernández, M. A. Moreno, “Applications of georeferenced high-resolution images obtained with unmanned aerial vehicles. Part I: Description of image acquisition and processing,” Precis. Agric, vol. 15, pp. 579–592, 2014. https://doi.org/10.1007/s11119-014-9355-8

[50] C. Li, G. Zhang, T. Lei, and A. Gong, “Quick image-processing method of UAV without control points data in earthquake disaster area,” Trans. Nonferrous Met. Soc. China, vol. 21, pp. s523–s528, 2011. https://doi.org/10.1016/S1003-6326(12)61635-5

[51] M. L. Guillen, P. J. Zarco, J. J. Berni, P. R. J. North, and F. J. Villalobos, “Mapping radiation interception in row-structured orchards using 3D simulation and high-resolution airborne imagery acquired from a UAV,” Precis. Agric., vol. 13, no. 4, pp. 473–500, 2012. https://doi.org/10.1007/s11119-012-9263-8

[52] H. Xiang and L. Tian, “Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV),” Biosyst. Eng., vol. 108, no. 2, pp. 174–190, 2011. https://doi.org/10.1016/j.biosystemseng.2010.11.010

[53] B. S. Faiçal, F. G. Costa, G. Pessin, J. Ueyama, H. Freitas, A. Colombo, P. H. Fini, L. Villas, F. S. Osório, P. a. Vargas, and T. Braun, “The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides,” J. Syst. Archit., vol. 60, no. 4, pp. 393–404, 2014. https://doi.org/10.1016/j.sysarc.2014.01.004

[54] D. Gómez, A. I. De Castro, and F. López, “Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat,” Precis. Agric., vol. 15, no. 1, pp. 44–56, 2014. https://doi.org/10.1007/s11119-013-9335-4

[55] L. A. Perilla and A. M. Sanabria, “Condiciones que favorecen el desarrollo del mildeo polvoso (Aphaerotheca pannosa var rosae) en los cultivos de rosa de la sabana de Bogotá,” Tesis de grado para optar por el título de microbiólogo agrícola y veterinario, Universidad Javeriana, Facultad de ciencias, Bogotá, Colombia, 2007.

[56] R. Calderón, M. Montes, B. B. Landa, J. a. Navas-Cortés, and P. J. Zarco-Tejada, “Detection of downy mildew of opium poppy using high-resolution multi-spectral and thermal imagery acquired with an unmanned aerial vehicle,” Precis. Agric., vol. 15, no. 6, pp. 639–661, 2014. https://doi.org/10.1007/s11119-014-9360-y

[57] UPRM, “Sintomas visuales de deficiencias nutricionales (Diagnostico visual),” june 12th 2015. [Online]. Available: http://academic.uprm.edu/dsotomayor/agro4037/handouts/Sintomas_visuales.pdf

[58] R. Melchiori, A. Kemerer, and S. Albarenque, “Uso de un UAV para el diagnóstico del estado de nutrición nitrogenada en maíz,” EAA INTA Paraná, 2012.

[59] M. Zaman-Allah, O. Vergara, J. L. Araus, a Tarekegne, C. Magorokosho, P. J. Zarco-Tejada, a Hornero, a H. Albà, B. Das, P. Craufurd, M. Olsen, B. M. Prasanna, and J. Cairns, “Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize,” Plant Methods, vol. 11, no. 1, p. 35, 2015. https://doi.org/10.1186/s13007-015-0078-2

[60] F. A. Vega, F. C. Ramírez, M. P. Saiz, and F. O. Rosúa, “Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop,” Biosyst. Eng., vol. 132, pp. 19–27, 2015. https://doi.org/10.1016/j.biosystemseng.2015.01.008

[61] L. Comba, P. Gay, J. Primicerio, and D. Ricauda Aimonino, “Vineyard detection from unmanned aerial systems images,” Comput. Electron. Agric., vol. 114, pp. 78–87, 2015. https://doi.org/10.1016/j.compag.2015.03.011

[62] P. Chamoso, W. Reveane, V. Parra, and A. Gonzáles, “UAVs applied to the counting and monitoring of animals”, ambient intelligence-software and application, vol. 291. 2014. https://doi.org/10.1007/978-3-319-07596-9_8

[63] S. Herwitz, L. Johnson, S. Dunagan, R. Higgins, D. Sullivan, J. Zheng, B. Lobitz, J. Leung, B. Gallmeyer, M. Aoyagi, R. Slye, and J. Brass, “Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support,” Comput. Electron. Agric., vol. 44, no. 1, pp. 49–61, 2004. https://doi.org/10.1016/j.compag.2004.02.006

[64] V. Gonzalez, D. Goldhamer, P. J. Zarco, and E. Fereres, “Improving the precision of irrigation in a pistachio farm using an unmanned airborne thermal system,” Irrig. Sci., vol. 33, no. 1, pp. 43–52, 2015. https://doi.org/10.1007/s00271-014-0447-z

[65] A. Royuela, J. Manzano, and D. Intrigliolo, “Assessment drip irrigation sub-units using airborne thermal acquire with an Unmaned Aerial Vehicle (UAV),” in Springer link, no. Instituto Valenciano de Investigaciones Agrarias, J. V. Stafford, Ed. Wageningen Academic Publishers, 2013, pp. 705–711.

[66] J. Bellvert, P. J. Zarco, J. Girona, and E. Fereres, “Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle,” Precis. Agric., pp. 1–16, 2013.

[67] V. Gonzalez, P. Zarco, E. Nicolás, P. a. Nortes, J. J. Alarcón, D. S. Intrigliolo, and E. Fereres, “Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard,” Precis. Agric., vol. 14, pp. 660–678, 2013. https://doi.org/10.1007/s11119-013-9322-9

[68] P. J. Zarco, V. González, and J. A. J. Berni, “Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera,” Remote Sens. Environ., vol. 117, pp. 322–337, 2012. https://doi.org/10.1016/j.rse.2011.10.007

[69] J. Baluja, M. P. Diago, P. Balda, R. Zorer, F. Meggio, F. Morales, and J. Tardaguila, “Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV),” Irrig. Sci., vol. 30, no. 6, pp. 511–522, 2012. https://doi.org/10.1007/s00271-012-0382-9

[70] R. A. Zahawi, J. P. Dandois, K. D. Holl, D. Nadwodny, J. L. Reid, and E. C. Ellis, “Using lightweight unmanned aerial vehicles to monitor tropical forest recovery,” Biol. Conserv., vol. 186, pp. 287–295, 2015. https://doi.org/10.1016/j.biocon.2015.03.031

[71] Red de especialistas en agricultura, june 12th 2016, [Online] Available: http://agriculturers.com/category/tendencias/
Cómo citar
Moreno, W. F., Tangarife, H. I., & Escobar Díaz, A. (2017). Aplicaciones de análisis de imágenes en agricultura de precisión. Visión electrónica, 11(2), 200-210. https://doi.org/10.14483/22484728.14628
julio-diciembre de 2017
Publicado: 2017-12-31
Sección
Visión de Caso

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