4.7 Article

Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery

Journal

REMOTE SENSING
Volume 5, Issue 12, Pages 6647-6666

Publisher

MDPI
DOI: 10.3390/rs5126647

Keywords

stem water potential; multispectral imagery; robust estimation; vegetation indices; pear orchards

Funding

  1. Agency for Innovation by Science and Technology in Flanders (IWT-Vlaanderen)
  2. Soil Service of Belgium (BDB)
  3. Proefcentrum Fruitteelt (PC Fruit)

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Remote sensing can provide good alternatives for traditional in situ water status measurements in orchard crops, such as stem water potential (Psi(stem)). However, the heterogeneity of these cropping systems causes significant differences with regards to remote sensing products within one orchard and between orchards. In this study, robust spectral indicators of Psi(stem) were sought after, independent of sensor viewing geometry, orchard architecture and management. To this end, Psi(stem) was monitored throughout three consecutive growing seasons in (deficit) irrigated and rainfed pear orchards and related to spectral observations of leaves, canopies and WorldView-2 imagery. On a leaf and canopy level, high correlations were observed between the shortwave infrared reflectance and in situ measured Psi(stem). Additionally, for canopy measurements, visible and near-infrared wavelengths (R-530/R-600, R-530/R-700 and R-720/R-800) showed significant correlations. Therefore, the Red-edge Normalized Difference Vegetation Index (ReNDVI) was applied on fully sunlit satellite imagery and found strongly related with Psi(stem) (R-2 = 0.47; RMSE = 0.36 MPa), undoubtedly showing the potential of WorldView-2 to monitor water stress in pear orchards. The relationship between ReNDVI and Psi(stem) was independent of management, irrigation setup, phenology and environmental conditions. In addition, results showed that this relation was also independent of off-nadir viewing angle and almost independent of viewing geometry, as the correlation decreased after the inclusion of fully shaded scenes. With further research focusing on issues related to viewing geometry and shadows, high spatial water status monitoring with space borne remote sensing is achievable.

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