## 2 Materials and Methods
### Data
#### 2.2.3 Satellite Time Series  
For every labeled parcel, the spectral signal was aggregated by taking the mean value over the field. These field boundaries are made publicly available by the government and updated annually, ensuring up-to-date field boundaries. They are also referred to as the Land Parcel Information System (LPIS). The object-based approach reduces noise and heterogeneity within a field and is useful in a decision-making context, as decisions are generally made at the parcel level [25]. To further reduce noise, we applied a 10 m inward buffer at each parcel, a technique that removes the spectrally mixed pixels at the edges of the parcels, thereby reducing the edge effects [10]. Input time series were downloaded for the period of August-April, chosen based on the crop calendars for catch crops and the other prominent winter crops in Flanders. This, therefore, delineates our study period. \begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{1}{c}{**Common Name**} & \multicolumn{1}{c}{**Scientific Name**} & \multicolumn{1}{c}{**Classification Group**} \\ \hline Bristle oat & _Avena strigosa_ & Grass group \\ Festulolium & _Lolium \(\times\) Festuca_ spp. & Grass group \\ Grasses & e.g., & \\ Grass herbs & _Lolium multiforum_ & \\ Grass sods & _Lolium multiforum_ var. _westernolcium_ & Grass group \\ Undersowing grass & & \\ Oat (spring) & _Avena sativa_ & Grass group \\ Oat (winter) & _Avena sativa_ & Grass group \\ Rye & _Scale cereale_ & Grass group \\ Sudan grass & _Sorghum \(\times\) drummondii_ & Grass group \\ English ryegrass and white clover & _Trifolium repens + Lolium perenne_ & Grass group \\ \hline Arugula & _Eruca vesicaria_ subsp. _Sativa_ & Leafy group \\ Buckwheat & _Fagopyrum esculentum_ & Leafy group \\ Cow cabbage & _Brassica oleracea convur._ & Leafy group \\ Leaf mustard & _Brassica juncea_ & Leafy group \\ Phacelia & _Phacelia tanacetifolia_ & Leafy group \\ White mustard & _Sinupis albu_ & Leafy group \\ Borage & _Borage officinalis_ & Leafy group 1 \\ Nyger & _Guizeta abissinica_ & Leafy group 1 \\ Oil radish & _Raphanus sativus_ supsp. _Oleiferus_ & Leafy group 1 \\ Oilseed turnip & _Brassica rapu_ subsp. _oleifera_ & Leafy group 1 \\ Tagetes & _Tagetes_ spp. & Leafy group 1 \\ \hline Mixtures of non-legume cover species & & Mixtures \\ \hline \hline \end{tabular} \({}^{1}\) Interpretation based on plant morphology.  
\end{table} 
Table 1: Overview of all allowed catch crop species with their common name, scientific name [36], and group. Time series data were calculated for every field using the Sentinel-2 optical satellite constellation, part of the Copernicus program. The mission consists of a two-satellite constellation in a sun-synchronous orbit with a 180\({}^{\circ}\) phase difference [40]. The first satellite was launched in 2015, and the second in 2017. Every 5 days, the same area is visited under equal viewing conditions, but due to overlap in swaths of different orbits, there is a revisit time of about 2-3 days over Belgium. Sentinel-2 uses optical remote sensing in the range of 400 nm to 2500 nm, which includes the Visible (VIS), Near Infrared (NIR), and Short-Wave Infrared (SWIR) regions. The multispectral sensor, MultiSpectral Instrument (MSI), measures 13 spectral bands at different spatial resolutions: four bands at 10 m, six bands at 20 m, and three bands at 60 m. To obtain data from this mission, two different services were used, CropSAR (version 1.0) and openEO (version 0.22.0). CropSAR is a service that monitors crop growth in Belgium, and it is provided by VITO, the Flemish Institute for Technological Research [41]. The CropSAR service provides daily time series by applying a deep learning network trained on cloud-free images of both Sentinel-1 and Sentinel-2 to interpolate between the gaps of optical acquisitions, thereby combining optical and radar data [42].