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Identification of Years with Extreme Vegetation State in Central Europe Based on Remote Sensing and Meteorological Data

机译：基于遥感和气象数据的中欧极端植被状态年确定

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Background and Purpose: Determination of an extreme year from the aspect of the vegetation activity using only meteorological data might be ambiguous and not adequate. Furthermore, in some ecosystems, e.g. forests, the response is not instantly visible, but the effects of the meteorological anomaly can be seen in the following year. The aim of the present paper is to select and characterize typical and anomalous years using satellite-based remote sensing data and meteorological observations during the recent years of 2000-2014 for Central Europe, based on the response of the vegetation. Materials and Methods: In the present study vegetation characteristics were described using remotely sensed official products of the MODerate resolution Imaging Spectroradiometer (MODIS), namely NDVI, EVI, FPAR, LAI, GPP, and NPP, with 8-day temporal and 500 meter spatial resolution for the period of 2000-2014. The corresponding mean temperature and precipitation data (on the same grid) were derived from the Open Database for Climate Change Related Impact Studies in Central Europe (FORESEE) daily meteorological dataset. Land cover specific anomalies of the meteorological and vegetation characteristics were created and averaged on a country-scale, where the distinction between the main land cover types was based on the synergetic use of MODIS land cover and Coordination of Information on the Environment (CORINE) Land Cover 2012 datasets. Results: It has been demonstrated that the anomaly detection based solely on basic meteorological variables is ambiguous since the strength of the anomaly depends on the selected integration time period. In contrast, the effect-based approach exploiting the available, state-of-the-art remote sensing based vegetation indices is a promising tool for the characterization of the anomalous behaviour of the different land cover types. The selection of extreme years was performed in an explicit way using percentile analysis on pixel level. Conclusions: Plant status in terms of both positive and negative anomalies shows strong land cover dependency in Central Europe. This is most likely due to the differences in heat and drought resistance of the vegetation, and species composition. The selection of country-specific extreme years can serve as a basis for forthcoming research.
机译：背景和目的：仅使用气象数据从植被活动的角度确定极端年份可能是模棱两可且不够充分。此外，在某些生态系统中，例如在森林中，反应不是立即可见的，但可以在第二年看到气象异常的影响。本文的目的是根据植被的响应情况，使用基于卫星的遥感数据和中欧最近几年（2000-2014年）的气象观测来选择和表征典型和异常年份。材料和方法：在本研究中，植被特征是使用MODerate分辨率成像光谱仪（MODIS）的遥感官方产品描述的，即NDVI，EVI，FPAR，LAI，GPP和NPP，具有8天的时空和500米的空间2000-2014年决议。相应的平均温度和降水数据（在同一网格上）来自中欧气候变化相关影响研究开放数据库（FORESEE）的每日气象数据集。在国家范围内创建并平均化了具有气象和植被特征的特定土地覆盖异常，其中主要土地覆盖类型之间的区别基于MODIS土地覆盖与环境信息协调（CORINE）土地的协同使用涵盖2012年的数据集。结果：已经证明，仅基于基本气象变量的异常检测是模棱两可的，因为异常的强度取决于所选的积分时间段。相比之下，利用基于可用的，最新的遥感植被指数的基于效果的方法是表征不同土地覆盖类型异常行为的有前途的工具。极端年份的选择是通过像素级别的百分位数分析以显式方式进行的。结论：就正反两方面而言，植物状况都表明中欧对土地覆盖的依赖性强。这很可能是由于植被的耐热和抗旱性以及物种组成的差异。选择特定国家的极端年份可以作为即将进行的研究的基础。

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