Detecting tree water deficit by very low altitude remote sensing

doi:10.3832/ifor1690-009

In a context of climate change and expected increasing drought frequency, it is important to select tree species adapted to water deficit. Experimentation in tree nurseries makes it possible to control for various factors such as water supply. We analyzed the spectral responses for two genetic varieties of Douglas fir sapling exposed to different levels of water deficit. Our results show that the mean NDVI derived from remote sensing at very low altitudes clearly differentiated stress levels while genetic varieties were partially distinguished.

Keywords

Very Low Altitude Remote Sensing, Water Deficit, Variety, Douglas Fir

Authors’ address

(1)

IRSTEA National Research Institute of Science and Technology for Environment and Agriculture, Domaine des Barres, F-45290 Nogent-sur-Vernisson (France)

(2)

IRSTEA, National Research Institute of Science and Technology for Environment and Agriculture, 361 rue J.F. Breton, BP 5095, F-34196 Montpellier Cedex 5 (France)

Corresponding author

Hilaire Martin
hilaire.martin@irstea.fr

Citation

Martin H, Labbé S, Baldet P, Archaux F, Philippe G (2017). Detecting tree water deficit by very low altitude remote sensing. iForest 10: 215-219. - doi: 10.3832/ifor1690-009

Academic Editor

Giorgio Matteucci

Paper history

Received: Apr 27, 2015
Accepted: Nov 16, 2016

First online: Feb 11, 2017
Publication Date: Feb 28, 2017
Publication Time: 2.90 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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