Aerial Monitoring of Rice Crop Variables using an UAV Robotic System
This paper presents the integration of an UAV for the autonomous monitoring of rice crops. The system integrates image processing and machine learning algorithms to analyze multispectral aerial imagery. Our approach calculates 8 vegetation indices from the images at each stage of rice growth: vegeta...
| Autores principales: | , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
INSTICC
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/105568 |
| _version_ | 1855531727867346944 |
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| author | Devia, Carlos Andres Rojas Bustos, Juan Pablo Petro, Eliel E. Mondragon, Iván Fernando Patino, D. Rebolledo, C. Colorado, Julian D. |
| author_browse | Colorado, Julian D. Devia, Carlos Andres Mondragon, Iván Fernando Patino, D. Petro, Eliel E. Rebolledo, C. Rojas Bustos, Juan Pablo |
| author_facet | Devia, Carlos Andres Rojas Bustos, Juan Pablo Petro, Eliel E. Mondragon, Iván Fernando Patino, D. Rebolledo, C. Colorado, Julian D. |
| author_sort | Devia, Carlos Andres |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This paper presents the integration of an UAV for the autonomous monitoring of rice crops. The system integrates image processing and machine learning algorithms to analyze multispectral aerial imagery. Our approach calculates 8 vegetation indices from the images at each stage of rice growth: vegetative, reproductive and ripening. Multivariable regressions and artificial neural networks have been implemented to model the relationship of these vegetation indices against two crop variables: biomass accumulation and leaf nitrogen concentration. Comprehensive experimental tests have been conducted to validate the setup. The results indicate that our system is capable of estimating biomass and nitrogen with an average correlation of 80% and 78% respectively. |
| format | Journal Article |
| id | CGSpace105568 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | INSTICC |
| publisherStr | INSTICC |
| record_format | dspace |
| spelling | CGSpace1055682025-11-05T17:46:39Z Aerial Monitoring of Rice Crop Variables using an UAV Robotic System Devia, Carlos Andres Rojas Bustos, Juan Pablo Petro, Eliel E. Mondragon, Iván Fernando Patino, D. Rebolledo, C. Colorado, Julian D. rice machine learning aprendizaje electrónico precision agriculture agricultura de precisión image processing tratamiento de imágenes multispectral imagery imágenes multiespectrales This paper presents the integration of an UAV for the autonomous monitoring of rice crops. The system integrates image processing and machine learning algorithms to analyze multispectral aerial imagery. Our approach calculates 8 vegetation indices from the images at each stage of rice growth: vegetative, reproductive and ripening. Multivariable regressions and artificial neural networks have been implemented to model the relationship of these vegetation indices against two crop variables: biomass accumulation and leaf nitrogen concentration. Comprehensive experimental tests have been conducted to validate the setup. The results indicate that our system is capable of estimating biomass and nitrogen with an average correlation of 80% and 78% respectively. 2019 2019-10-29T20:43:15Z 2019-10-29T20:43:15Z Journal Article https://hdl.handle.net/10568/105568 en Open Access application/pdf INSTICC Devia, Carlos Andres; Rojas Bustos, Juan P.; Petro, Eliel E.; Mondragon, Iván F.; Patino, D.; Rebolledo, C. & Colorado, Julian (2019). Aerial Monitoring of Rice Crop Variables using an UAV Robotic System. In: ICINCO 2019 - International Conference on Informatics in Control, Automation and Robotics. 29-31 Jul. Prague, Czech Republic, 1-7 p. |
| spellingShingle | rice machine learning aprendizaje electrónico precision agriculture agricultura de precisión image processing tratamiento de imágenes multispectral imagery imágenes multiespectrales Devia, Carlos Andres Rojas Bustos, Juan Pablo Petro, Eliel E. Mondragon, Iván Fernando Patino, D. Rebolledo, C. Colorado, Julian D. Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title | Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title_full | Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title_fullStr | Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title_full_unstemmed | Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title_short | Aerial Monitoring of Rice Crop Variables using an UAV Robotic System |
| title_sort | aerial monitoring of rice crop variables using an uav robotic system |
| topic | rice machine learning aprendizaje electrónico precision agriculture agricultura de precisión image processing tratamiento de imágenes multispectral imagery imágenes multiespectrales |
| url | https://hdl.handle.net/10568/105568 |
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