Almond orchard management using multi-temporal UAV data: a proof of concept

Guimaraes, Nathalie; Padua, Luis; Sousa, Joaquim J.; Bento, Albino; Couto, Pedro

http://hdl.handle.net/10198/27009

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
ALMOND_ORCHARD.pdf		653.95 KB	Adobe PDF	Download

Send Feedback

Authors

Abstract(s)

In the last decade Unmanned Aerial Systems (UAS) have become a reference tool for agriculture applications. The integration of multispectral sensors that can capture near infrared (NIR) and red edge spectral reflectance allows the creation of vegetation indices, which are fundamental for crop monitoring process. In this study, we propose a methodology to analyze the vegetative state of almond crops using multi-temporal data acquired by a multispectral sensor accoupled to an Unmanned Aerial Vehicle (UAV). The methodology implemented allowed individual tree parameters extraction, such as number of trees, tree height, and tree crown area. This also allowed the acquisition of Normalized Difference Vegetation Index (NDVI) information for each tree. The multitemporal data showed significant variations in the vegetative state of almond crops.

Keywords

Almond crops monitoring UAV multitemporal data analysis Tree parameters extraction Vegetation indices Precision agriculture

URI

http://hdl.handle.net/10198/27009

Citation

Guimaraes, Nathalie; Padua, Luis; Sousa, Joaquim J.; Bento, Albino; Couto, Pedro (2022). Almond orchard management using multi-temporal UAV data: a proof of concept. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022. p. 4376-4379. ISBN 978-1-6654-2792-0