Agricultural life cycle analysis (LCA) provides information about the environmental footprint of farming. Life cycle sustainability assessment (LCSA) includes social and economic indicators. As a contribution to LCSA, we developed an indicator measuring the impact of individual farms on visual landscape quality based on state-ofthe- art theory for landscape aesthetic assessment and conforming to general LCA principles. The indicator is a composite consisting of two independent sub-indicators, the aggregated diversity indicator (ADI) and the areaweighted preference value (AWPV). Both sub-indicators are based on the preference values of the Swiss population for the most frequent crop types and farmland features. The two sub-indicators were calculated when the land-use types with an available preference value represented 75% of a farms’ utilised agricultural area. Following this rule, we were able to evaluate 91% of Swiss farms. The ADI measures a farm’s contribution to land-use diversity and to seasonal diversity, while the AWPV measures a farm’s contribution to perceived naturalness. The two sub-indicators are combined to form the composite landscape indicator (CLI). The two sub-indicators were computed from Swiss farm structure data for 2015 without additional data collection. Two scenarios were defined to test the independence of the two sub-indicators from each other and the response of the CLI against landscape changes. The first scenario enriched the crop diversity of the farms to test the response of the ADI. The second scenario increased the number of standard trees on farms to test the AWPV. The results showed that the two sub-indicators complement one another by responding to different changes in landscape quality. In both cases, the CLI showed on average increasing values after enriching crop diversity or increasing the number of standard trees on selected farms. The solid conceptual grounding of the two sub-indicators in landscape aesthetic theory combined with LCA principles renders them reproducible and independent of the observer.