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MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests

机译:基于MODIS的植被指数具有足够的敏感性,可以指示橡树和山毛榉森林中的站立水平季节内气候应力

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摘要

Context: Variation in photosynthetic activity of trees induced by climatic stress can be effectively evaluated using remote sensing data. Although adverse effects of climate on temperate forests have been subjected to increased scrutiny, the suitability of remote sensing imagery for identification of drought stress in such forests has not been explored fully. udAim: To evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests, and explore the differences in stress response of oaks and beech.udMethods: We identified 8 oak and 13 beech pure and mature stands, each covering between 4 and 13 MODIS pixels. For each pixel, we extracted a time series of MODIS NDVI from 2000 to 2010. We identified all sequences of continuous unseasonal NDVI decline to be used as the response variable indicative of environmental stress. Neural Networks-based regression modelling was then applied to identify the climatic variables that best explain observed NDVI declines.udResults: Tested variables explained 84–97% of the variation in NDVI, whilst air temperature-related climate extremes were found to be the most influential. Beech showed a linear response to the most influential climatic predictors, while oak responded in a unimodal pattern suggesting a better coping mechanism. udConclusions: MODIS NDVI has proved sufficiently sensitive as a stand-level indicator of climatic stress acting upon temperate broadleaf forests, leading to its potential use in predicting drought stress from meteorological observations and improving parameterisation of forest stress indices.
机译:背景:气候压力引起的树木光合作用变化可以通过遥感数据得到有效评估。尽管已经对气候对温带森林的不利影响进行了越来越严格的审查,但尚未充分探索遥感图像在这种森林中识别干旱压力的适用性。目的:评估基于MODIS的植被指数对温带森林炎热和干旱胁迫的敏感性,并探讨橡树和山毛榉的胁迫响应差异。覆盖4到13个MODIS像素。对于每个像素,我们提取了2000年至2010年的MODIS NDVI的时间序列。我们确定了连续的非季节性NDVI下降的所有序列都可以用作指示环境压力的响应变量。然后,基于神经网络的回归模型用于确定最能解释观测到的NDVI下降的气候变量。 ud结果:测试变量解释了NDVI变化的84–97%,而与气温相关的极端气候被认为是最大的有影响。 Beech对最有影响力的气候预测指标显示出线性响应,而Oak以单峰模式响应,提示了更好的应对机制。结论:MODIS NDVI已被证明足以作为对温带阔叶林起作用的气候压力的标准指标,从而使其有潜力用于通过气象观测预测干旱压力和改善森林压力指数的参数化。

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