Abstract In the light of escalating climate challenges, agroforestry is receiving renewed attention for its potential to mitigate greenhouse gas emissions while enhancing the resilience of agricultural systems. The main difference between agroforestry and conventional agricultural systems is the presence and management of woody landscape features (WLF). The few datasets assessing WLF on agricultural land are limited in their spatial resolution and apply minimum mapping thresholds, potentially biasing derived estimates of WLF characteristics. Our study aimed to assess the current extent of WLF in Germany with high spatial resolution, including size variability and WLF type composition. We investigated WLF on agricultural land across seven federal states. In each of the seven states, 100 grid cells totalling 25 km 2 of agricultural land were selected, amounting to a total area of 175 km 2 . Within this area, WLF were manually identified, delineated and classified using digital orthophotos. The results were compared with state-of-the-art datasets, particularly the Digital Basic Landscape Model (ATKIS). We identified a total of 4.8 km 2 land hosting WLF, covering 2.7% of the investigated area. The extent of WLF estimated in our study was twice as large as the estimate derived from the ATKIS dataset. Overall, we identified a much larger number of WLF, which were on average much smaller in size compared to the WLF in the ATKIS dataset. Extrapolating our results to the national level, we estimate WLF coverage at 4,899 km 2 , corresponding to 57.2 Tg above-ground biomass or 28.6 Tg carbon. The biomass and carbon content were estimated based on literature-derived biomass densities. Our study indicates that accurately assessing WLF requires higher spatial resolutions than previously used. Datasets based on low-resolution images and those using minimal mapping units are not suited for capturing small WLF.