In addition to providing food, fibre and biomass, agriculture can deliver a variety of ecosystem services, like biodiversity conservation and carbon sequestration. Often, however, the use of agricultural landscapes is prioritized to the provision of food and feed, resulting in negative environmental impacts (e.g. soil erosion). These negative environmental impacts decrease provision of ecosystem services by rural landscapes.
To address this imbalance in the provision of food and feed on the one hand and other ecosystem services at the other hand, targeted policy instruments are required to ensure that these other ecosystem services are also provided. Contract-based approaches such as publicly funded agri-environmental-climate measures (AECM) in the context of Rural Development Programs (RDPs) and the Common Agricultural Policy (CAP) or privately negotiated and funded Payments for Ecosystem Services (PES) can be important components of a diverse policy mix to support the provision of ecosystem services.
This MSc thesis aims to assess how satellite earth observation data can be used to support the monitoring of effects of AECM on the environment. Since 2016 a new approach has been implemented in The Netherlands, whereby measures are coordinated by farmers collectives. One of the main objectives of AECM in the Netherlands is to increase areas of favourable habitat for farmland birds. Farmers receive subsidies to manage grasslands and croplands so that a mosaic of suitable areas at different stages of the life cycle is generated. Because of the novel farmers collectives approach, an increased spatial coordination of measures is expected. However, the effects of this new approach on the quality and connectivity of the habitats for farmland birds have not yet been monitored. Collection of data on birds habitats through field visits would be a long and costly process. Earth observation data might provide a very useful alternative.
- Develop a method based on spatial data to monitor the effects of measures on farmland management and habitat conditions. The method will contribute to evaluate the effects of AECM on habitats quality and connectivity for farmland birds.
- Stenzel, S., Fassnacht, F.E., Mack, B. and Schmidtlein, S., 2017. Identification of high nature value grassland with remote sensing and minimal field data. Ecological Indicators, 74: 28-38.
- Griffiths, P., Nendel, C., Pickert, J. and Hostert, P., 2020. Towards national-scale characterization of grassland use intensity from integrated Sentinel-2 and Landsat time series. Remote Sensing of Environment, 238: 111124.
- Bekkerma, M., Eleveld, M., 2018. Mapping Grassland Management Intensity Using Sentinel-2 Satellite Data. Journal for Geographic Information Science, 6, 194 - 213
- Howison, R.A., Piersma, T., Kentie, R., Hooijmeijer, J.C.E.W. and Olff, H., 2018. Quantifying landscape-level land-use intensity patterns through radar-based remote sensing. Journal of Applied Ecology, 55(3): 1276-1287.
Theme(s): Sensing & measuring; Integrated Land Monitoring