Thermal InfraRed (TIR) imaging sensors are already successfully used in several agriculture applications, for instance providing valuable information for assessing plant health, scheduling crop irrigation regimes, and, more in general, to support site-specific decision strategies based on monitoring crop stress and phenotyping. Once mounted on Unmanned Aerial Systems (UASs), they can be used for plant health monitoring purposes, collecting geospatial data at both high spatial and temporal resolutions. High resolution spatio-temporal monitoring requires the production of highly accurate data, which can only be ensured when the TIR sensors are well calibrated. This paper compares the performance of several techniques for the production of photogrammetric reconstructions, focusing in particular on the effect of GNSS measurements on the geometric self-camera calibration results, and on the consequent repercussions on the obtained 3D models.

Thermal camera geometric self-calibration supported by RTK measurements / Erica Isabella Parisi, Andrea Masiero, Grazia Tucci, Irene Cortesi, Francesco Mugnai. - ELETTRONICO. - (2022), pp. 249-254. (Intervento presentato al convegno IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) tenutosi a Perugia, Italia nel 3-5 novembre 2022) [10.1109/MetroAgriFor55389.2022.9964630].

Thermal camera geometric self-calibration supported by RTK measurements

Erica Isabella Parisi;Andrea Masiero;Grazia Tucci;Irene Cortesi;Francesco Mugnai
2022

Abstract

Thermal InfraRed (TIR) imaging sensors are already successfully used in several agriculture applications, for instance providing valuable information for assessing plant health, scheduling crop irrigation regimes, and, more in general, to support site-specific decision strategies based on monitoring crop stress and phenotyping. Once mounted on Unmanned Aerial Systems (UASs), they can be used for plant health monitoring purposes, collecting geospatial data at both high spatial and temporal resolutions. High resolution spatio-temporal monitoring requires the production of highly accurate data, which can only be ensured when the TIR sensors are well calibrated. This paper compares the performance of several techniques for the production of photogrammetric reconstructions, focusing in particular on the effect of GNSS measurements on the geometric self-camera calibration results, and on the consequent repercussions on the obtained 3D models.
2022
2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
Perugia, Italia
3-5 novembre 2022
Goal 9: Industry, Innovation, and Infrastructure
Erica Isabella Parisi, Andrea Masiero, Grazia Tucci, Irene Cortesi, Francesco Mugnai
File in questo prodotto:
File Dimensione Formato  
2022_TIR_RTK_IEEE.pdf

Accesso chiuso

Descrizione: Thermal camera geometric self-calibration supported by RTK measurements
Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 5.36 MB
Formato Adobe PDF
5.36 MB Adobe PDF   Richiedi una copia

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

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1293419
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 0
social impact