Satellite supported generation of area wide climate and vegetation datasets for an integrative analysis of ecosystem biodiversity relationships on grassland areas

目前的建议旨在卫星支持生成景观尺度的区域数据集，作为进一步综合分析草原地区生物多样性-生态系统功能关系的基础。两个主要课题是（i）提供高分辨率的气象数据集和（ii）生成选定的特定植被类型的数据集，即光能利用效率和总初级生产力。因此，将遵循一个综合的方法，链接现成的基于地块的气象和生态记录从多达150个实验地块和额外的植物学信息从1500个研究地块与光学遥感数据。这一方法的基础将是各个现场数据集，这些数据集在物理上或统计上与时空搭配的卫星产品信息相联系，并根据卫星获得的数据值在空间中分布。将在本项目中使用/开发的卫星检索将作为业务技术加以实施，以确保对参数进行有效和廉价的每周至准连续监测。这两个数据集将为几乎所有其他核心项目和次级项目的进一步分析提供宝贵的基础。此外，还打算与植物学核心项目（PI Fischer）密切合作，根据区域范围的数据集对生物多样性-生态系统功能关系进行综合分析，这也将成为未来生态生理学项目或模型应用的必然基础。

The proposal at hand aims at the satellite supported generation of area-wide datasets on the landscape scale as a basis of further integrative analysis of biodiversity-ecosystem functioning relationships on grassland areas. The two main subjects are (i) the provision of high resolution meteorological datasets and (ii) the generation of selected vegetation type specific datasets, namely the light use efficiency and the gross primary productivity. Therefore, an integrative approach will be followed that links readily available plot-based meteorological and ecological records from up to 150 experimental plots and additional botany information from 1500 study plots with optical remote sensing data. The basis of this approach will be the individual in-situ datasets which are physically or statistically linked with spatio-temporal collocated satellite product information and distributed in space based on the satellite-derived data values. The satellite retrievals that will be used/developed within this project will be implemented as operational techniques to ensure an efficient and inexpensive weekly to quasi-continuous monitoring of the parameters. Both datasets will form a valuable basis for virtually all other core and subprojects for further analysis. In addition, a close cooperation is intended with the botany core project (PI Fischer) to perform an integrative analysis of biodiversity-ecosystem functioning relationships based on the area-wide datasets which will also form an inevitable basis for future ecophysiological projects or model applications.