期刊论文详细信息
iForest: Biogeosciences and Forestry
Detecting tree water deficit by very low altitude remote sensing
Martin, H.1 
关键词: Remote Sensing and Information System;    Very Low Altitude Remote Sensing;    Water Deficit;    Variety;    Douglas Fir;   
DOI  :  10.3832/ifor1690-009
学科分类:社会科学、人文和艺术(综合)
来源: Societa Italiana di Selvicoltura ed Ecologia Forestale (S I S E F)
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【 摘 要 】

Abstract: 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.

【 授权许可】

Unknown   

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