SIGNAL

Motivation

The joint project SIGNAL as part of the funding program BonaRes (Soil as a sustainable resource for the bioeconomy) investigates the effects of agroforestry systems on the biological functions of the soil, the rhizosphere, the above-ground material flows and the water use efficiency of the soil over a period of up to 9 years. The basis of the research approaches within the project is the central hypothesis that innovative land use systems consisting of a coupled cultivation of trees or shrubs with arable crops or grassland (agroforestry systems) can have positive ecological, economic and aesthetic effects in contrast to conventional crop production systems.

Agroforestry systems can achieve higher total area yields compared to the separate cultivation of crops as a monoculture. At the same time, as a result of interactions between tree and arable/grassland crops, yield differences occur within the arable/grassland strips, which can vary considerably depending on the system and location. The specific nature of the spatial variability is very important for the ecological and economic evaluation of the agroforestry system. The measurement of yields has so far often been based on spot surveys in transects or the use of a (plot) combine harvester. The variability of the crop parameters with distance to the trees can only be represented very imprecisely with these methods. A high spatial resolution and coverage can only be achieved at great expense.

Aims and approach

The research activities of the GNR department in the second phase of the SIGNAL project therefore aim to develop remote sensing methods that can map the small-scale variability of yield-relevant crop production parameters in high resolution and over a large area. For this purpose, high-resolution multispectral and hyperspectral data will be collected by means of drone-based remote sensing in the conventionally managed silvopastoral (Mariensee, Reiffenhausen) and silvoarable agroforestry trials (Wendhausen, Dornburg, Forst) of the SIGNAL project. In addition, point clouds will be created using images from a commercially available photo drone (Structure From Motion) in order to estimate biomass yields based on plant height. The aim is to determine which sensors are best suited for large-scale yield estimation and which spatial patterns can be found in the agroforestry systems investigated.

The aim of the work is both to test a simple method for the large-scale and high-resolution survey of crop yield parameters within agroforestry systems and to gain a better understanding of the ecological interactions between tree strips and agricultural crops.

Innovations and perspectives

In the second phase of the joint project, the GNR department of the University of Kassel/Witzenhausen will evaluate methods for recording the spatial variability of biomass and grain yields in agroforestry systems.

Another area of the project is the continuation of the long-term data collection in the silvopastoral agroforestry system of the Universities of Kassel and Göttingen in Reiffenhausen with regard to the biomass development of grassland and pasture stands and the determination of various quality parameters.