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

手头的提案旨在卫星支持下生成地貌尺度的区域数据集，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。两个主要主题是(I)提供高分辨率气象数据集和(Ii)生成特定植被类型的数据集，即光利用效率和总初级生产力。因此，将采用一种综合办法，将来自150个试验田的现成的基于小区的气象和生态记录以及来自1500个研究区的其他植物学信息与光学遥感数据联系起来。这一方法的基础将是个别的现场数据集，这些数据集与时空配置的卫星产品信息在物理上或统计上有联系，并根据卫星得出的数据值分布在空间。将在该项目内使用/开发的卫星反演法将作为业务技术加以实施，以确保每周对参数进行有效和廉价的监测，并对参数进行准连续监测。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，以区域范围的数据集为基础，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.