Estimating photosynthetically active radiation intercepted by almond and walnut trees using uav-captured aerial images and solar zenith angle

Francisco Rojo, Rajveer Dhillon, Shrinivasa K. Upadhyaya, Hunjun Liu, Jedediah Roach

Research output: Contribution to journalArticlepeer-review

Abstract

Photosynthetically Active Radiation (PAR) absorbed by the leaves is a key piece of information to study the crop response to environmental conditions that could be used to estimate crop production potential. Canopies in a commercial orchard present differences in their capability to intercept light mainly due to the spatial variability in canopy development. There is a need for developing tools that could capture spatial variability in PAR interception to predict potential yield. Unmanned Aerial Vehicles (UAV) present an interesting alternative to provide this information, as they cover a larger area than ground-based systems in a shorter period with high spatial resolution. The objective of this study was to determine the relationship between the shadow of a tree derived from a ground-based canopy light interception scan obtained using a lightbar mounted on a mobile platform and that acquired from UAV Red-Green-Blue (RGB) images. Information acquired by an UAV was classified to separate canopy from its shadow, grass and sunlit soil using maximum likelihood estimator. Boundaries of individual trees were identified based on their positions using watershed transform algorithm. The relationship between canopy PAR interception data, sun angle in the sky (zenith angle), and the information derived from aerial images was analyzed. Coefficient of determination (R2) values of 0.92 and 0.88 were found for the multiple linear regression between PAR, the shadow area and the cosine of zenith angle obtained for almond and walnut crops, respectively. Moreover, R2 values of 0.81 and 0.86 were found for the relationship between the shadow's area obtained underneath the canopy and the shadow's area obtained from the UAV images and the cosine of the zenith angle for almond and walnut crops, respectively. The results show that the PAR interception can be estimated using the zenith angle and the area of the shadow, which can be obtained from a RGB aerial image.

Original languageEnglish
Pages (from-to)751-761
Number of pages11
JournalApplied Engineering in Agriculture
Volume37
Issue number4
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Almond
  • Canopy segmentation
  • Image classification
  • PAR interception
  • Shadow area
  • UAV
  • Walnut

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