Applying RGB-Based Vegetation Indices Obtained from UAS Imagery for Monitoring the Rice Crop at the Field Scale: A Case Study in Portugal

Romeu Gerardo and Isabel P. de Lima ()
Additional contact information
Romeu Gerardo: Department of Civil Engineering, Faculty of Sciences and Technology, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal
Isabel P. de Lima: Department of Civil Engineering, Faculty of Sciences and Technology, University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal

Agriculture, 2023, vol. 13, issue 10, 1-18

Abstract: Nowadays, Unmanned Aerial Systems (UASs) provide an efficient and relatively affordable remote sensing technology for assessing vegetation attributes and status across agricultural areas through wide-area imagery collected with cameras installed on board. This reduces the cost and time of crop monitoring at the field scale in comparison to conventional field surveys. In general, by using remote sensing-based approaches, information on crop conditions is obtained through the calculation and mapping of multispectral vegetation indices. However, some farmers are unable to afford the cost of multispectral images, while the use of RGB images could be a viable approach for monitoring the rice crop quickly and cost-effectively. Nevertheless, the suitability of RGB indices for this specific purpose is not yet well established and needs further investigation. The aim of this work is to explore the use of UAS-based RGB vegetation indices to monitor the rice crop. The study was conducted in a paddy area located in the Lis Valley (Central Portugal). The results revealed that the RGB indices, Visible Atmospherically Resistant Index (VARI) and Triangular Greenness Index (TGI) can be useful tools for rice crop monitoring in the absence of multispectral images, particularly in the late vegetative phase.

Keywords: remote sensing; precision agriculture; paddy fields; UAV; multispectral; RGB indices (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/13/10/1916/pdf (application/pdf)
https://www.mdpi.com/2077-0472/13/10/1916/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:13:y:2023:i:10:p:1916-:d:1251073

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().