The present study illustrates an operational approach estimating individual and aggregate vineyards’ canopy volume estimation through three years Tree-Row-Volume (TRV) measurements and remotely sensed imagery acquired with unmanned aerial vehicle (UAV) Red-Green-Blue (RGB) digital camera, processed with MATLAB scripts, and validated through ArcGIS tools. The TRV methodology was applied by sampling a different number of rows and plants (per row) each year with the aim of evaluating reliability and accuracy of this technique compared with a remote approach. The empirical results indicate that the estimated tree-row-volumes derived from a UAV Canopy Height Model (CHM) are up to 50% different from those measured on the field using the routinary technique of TRV in 2019. The difference is even much higher in the two 2016 dates. These empirical findings outline the importance of data integration among techniques that mix proximal and remote sensing in routine vineyards’ agronomic practices, helping to reduce management costs and increase the environmental sustainability of traditional cultivation systems.

Integrating uavs and canopy height models in vineyard management: A time-space approach / Sassu, A.; Ghiani, L.; Salvati, L.; Mercenaro, L.; Deidda, A.; Gambella, F.. - In: REMOTE SENSING. - ISSN 2072-4292. - 14:1(2022). [10.3390/rs14010130]

Integrating uavs and canopy height models in vineyard management: A time-space approach

Salvati L.;
2022

Abstract

The present study illustrates an operational approach estimating individual and aggregate vineyards’ canopy volume estimation through three years Tree-Row-Volume (TRV) measurements and remotely sensed imagery acquired with unmanned aerial vehicle (UAV) Red-Green-Blue (RGB) digital camera, processed with MATLAB scripts, and validated through ArcGIS tools. The TRV methodology was applied by sampling a different number of rows and plants (per row) each year with the aim of evaluating reliability and accuracy of this technique compared with a remote approach. The empirical results indicate that the estimated tree-row-volumes derived from a UAV Canopy Height Model (CHM) are up to 50% different from those measured on the field using the routinary technique of TRV in 2019. The difference is even much higher in the two 2016 dates. These empirical findings outline the importance of data integration among techniques that mix proximal and remote sensing in routine vineyards’ agronomic practices, helping to reduce management costs and increase the environmental sustainability of traditional cultivation systems.
2022
CHM; Digital models; Grapevine canopy measurement; Precision viticulture; TRV; Unmanned aerial vehicle
01 Pubblicazione su rivista::01a Articolo in rivista
Integrating uavs and canopy height models in vineyard management: A time-space approach / Sassu, A.; Ghiani, L.; Salvati, L.; Mercenaro, L.; Deidda, A.; Gambella, F.. - In: REMOTE SENSING. - ISSN 2072-4292. - 14:1(2022). [10.3390/rs14010130]
File allegati a questo prodotto
File Dimensione Formato  
Salvati_Integrating-uavs_2022.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 4.09 MB
Formato Adobe PDF
4.09 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1675218
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 3
social impact