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Can time series of multispectral satellite images be used to estimate stem water potential in vineyards?
Year:
2019
Authors :
Bahat, Idan
;
.
Ben-Gal, Alon
;
.
Cohen, Yafit
;
.
Gogumalla, P.
;
.
Helman, David
;
.
Volume :
Co-Authors:

Netzer, Y.; Lenski, I.; Michael, Y.

Facilitators :
From page:
445
To page:
451
(
Total pages:
7
)
Abstract:

Vegetation indices (VI) derived from a new generation of high-spatial resolution satellites, namely Planet and Sentinel-2, were tested as proxies for stem water potential (Ψ-stem) in commercial vineyards. Multivariable linear regression models were developed from the Planet and Sentinel-2 data and in-situ Ψ-stem measurements in 82 vineyards in Israel, providing Ψ-stem estimates every 1-2 weeks. With multivariable regression VIs in the VIS-NIR region (Planet) and moisture VIs in the NIR-SWIR region (Sentinel-2) were correlated with in-situ Ψ-stem measurements. In general, Sentinel-based models performed better (higher correlations and higher ability to capture temporal and spatial variability) than Planet-based models. The trade-off between spectral, spatial and temporal resolutions of these two satellites are further discussed. © Wageningen Academic Publishers 2019

Note:
Related Files :
Google earth engine
Planet-labs
remote sensing
Sentinel-2
Stem water potential
vineyard
Vitis / grapes
water
Show More
Related Content
More details
DOI :
10.3920/978-90-8686-888-9_55
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
44461
Last updated date:
02/03/2022 17:27
Creation date:
29/10/2019 15:38
Scientific Publication
Can time series of multispectral satellite images be used to estimate stem water potential in vineyards?

Netzer, Y.; Lenski, I.; Michael, Y.

Can time series of multispectral satellite images be used to estimate stem water potential in vineyards?

Vegetation indices (VI) derived from a new generation of high-spatial resolution satellites, namely Planet and Sentinel-2, were tested as proxies for stem water potential (Ψ-stem) in commercial vineyards. Multivariable linear regression models were developed from the Planet and Sentinel-2 data and in-situ Ψ-stem measurements in 82 vineyards in Israel, providing Ψ-stem estimates every 1-2 weeks. With multivariable regression VIs in the VIS-NIR region (Planet) and moisture VIs in the NIR-SWIR region (Sentinel-2) were correlated with in-situ Ψ-stem measurements. In general, Sentinel-based models performed better (higher correlations and higher ability to capture temporal and spatial variability) than Planet-based models. The trade-off between spectral, spatial and temporal resolutions of these two satellites are further discussed. © Wageningen Academic Publishers 2019

Scientific Publication
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