High-resolution imaging of a vineyard in south of France using ground penetrating radar and electromagnetic induction

André, Frédéric; Saussez, Stéphanie; Duraient, R. Van; Leeuwen, Cornelius van; Moghadas, Davood; Delvaux, Bruno; Vereecken, Harry; Lambot, Sébastien

doi:10.1109/icgpr.2010.5550145

Cited by 1 publication

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When it concerns specifically the study of vineyards, the PA refers to precision viticulture (PV). Two main technologies applied to PV can be identified: (a) variable-rate-technologies (VRT) which use agricultural machines controlled by data from sensors and Global Positioning Systems (GPS) and, (b) monitoring technologies which focus on the observation of biological or structural parameters such as the leaf area index (LAI) [1,2], the canopy and vigour (that is, leaf area and pruning weight), the chlorophyll content or/and the anthocyanin concentration [3], the sugar content [4] or the soil properties [5]. Satellites [1,2], airborne [6] or un-manned aerial vehicles (drones) are also solutions for multi-parcels and large areas monitoring while sensors based on ground, such as low frequency Ground-Penetrating Radar (GPR) [7], LiDAR [8] or optical cameras [9], are good candidates for monitoring the LAI, the vigour or the ground electrical conductivity.…”

Section: Introductionmentioning

confidence: 99%

Remote estimation of intra-parcel grape quantity from three-dimensional imagery technique using ground-based microwave FMCW radar

Henry¹,

Aubert²,

Véronèse³

et al. 2017

IEEE Instrum. Meas. Mag.

View full text Add to dashboard Cite

For better benefits and yields, a good estimation of grapes quantity in vineyard is necessary. In this paper, three-dimensional (3D) imagery technique using conventional 24GHz Frequency-Modulated Continuous-Wave (FMCW) Radar is applied for detecting and remotely estimating the intra-parcel quantity of grapes. An estimation is possible even in presence of natural or artificial clutters such as leaves, wood or irrigation hoses. The microwave sensing is performed from the radar beam scanning of a vineyard and an estimator is defined to derive the quantity of grapes in grapevines from radar echoes distribution in the interrogated 3D scene. An algorithm based on contour detection is applied to the 3D radar image and a new parameter, called the spread factor, is defined for classifying the echo levels of grapes. The quantity of grapes is finally deduced from an appropriate estimator. This remote sensing approach brings a new and flexible solution for precision viticulture by estimating the grape quantity even for grapes hidden by leaves.

show abstract