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VEGETATION STRESS INDICATORS DERIVED FROM MULTISPECTRAL AND MULTITEMPORAL DATA

机译：从多光谱和多时相数据推导的植被应力指标

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Remote sensing is already an operational tool widely used in vegetation studies for ecological monitoring, change detection of natural ecosystems and in agriculture for crop state assessment and yield prediction. A strong stress is being put on the accuracy of the retrieved information. This requires reliable indicators of plant growth and physiological status. The development of efficient means for data analysis is still one of the most essential issues. The importance of this issue is directly related to the ever-increasing amount of data provided by numerous sensors. The use of multi-spectral and multitemporal remotely sensed data and the implementation of advanced data processing technologies results in the possibility of getting different information needed for decision-making in solving problems related to vegetation preservation and agricultural land use. The application of satellite data requires knowledge of land covers spectral behaviour under different environmental conditions considering regional and local peculiarities. In this context detailed ground-based and airborne spectrometric studies complement the array of geo-spatial data products. These studies are the most appropriate way of aiding the interpretation and providing a reference source for validation of remotely sensed data. This paper is devoted to plant stress detection using VIS and NIR multispectral data. Empirical modelling of various agricultural crops under different soil and ecological conditions has been performed in order to describe the relationships between plant spectral and biophysical features and to derive sustainable spectral indicators of plant state.
机译：遥感已经是一种操作工具，已广泛用于植被研究，生态监测，自然生态系统的变化检测以及农业中的作物状态评估和产量预测。对检索到的信息的准确性施加了很大的压力。这就需要可靠的植物生长和生理状况指标。开发有效的数据分析手段仍然是最重要的问题之一。此问题的重要性直接与众多传感器提供的数据量不断增加有关。多光谱和多时相遥感数据的使用以及先进数据处理技术的实施，导致有可能获得决策所需的不同信息，以解决与植被保存和农业土地利用有关的问题。卫星数据的应用需要了解在考虑区域和本地特性的不同环境条件下的土地覆盖光谱行为。在这种情况下，详细的地面和机载光谱学研究补充了一系列地理空间数据产品。这些研究是帮助解释并为验证遥感数据提供参考来源的最合适方法。本文致力于利用VIS和NIR多光谱数据进行植物胁迫检测。为了描述植物光谱与生物物理特征之间的关系并得出植物状态的可持续光谱指标，对不同土壤和生态条件下各种农作物进行了经验建模。

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