The observation of boundary layer clouds with high-resolution satellite data can provide comprehensive insights into spatiotemporal patterns of land-surface-driven modification of cloud occurrence, such as the diurnal variation of the occurrence of fog holes and cloud enhancements attributed to the impact of the urban heat island. High-resolution satellite-based cloud-masking approaches are often based on locally optimised thresholds that can be affected by the local surface reflectance, and they therefore introduce spatial biases in the detected cloud cover. In this study, geostationary satellite observations are used to develop and validate two high-resolution cloud-masking approaches for the region of Paris to show and improve applicability for analyses of urban effects on clouds. Firstly, the Local Empirical Cloud Detection Approach (LECDA) uses an optimised threshold to separate the distribution of visible reflectances into cloudy and clear sky for each individual pixel accounting for its locally specific brightness. Secondly, the Regional Empirical Cloud Detection Approach (RECDA) uses visible reflectance thresholds that are independent of surface reflection at the observed location. Validation against in-situ cloud fractions reveals that both approaches perform similarly, with a probability of detection (POD) of 0.77 and 0.69 for LECDA and RECDA, respectively. Results show that with the application of RECDA a decrease of cloud cover during typical fog or low-stratus conditions over the urban area of Paris for the month of November is likely a result of urban effects on cloud dissipation. While LECDA is representative for the widespread usage of locally optimised approaches, comparison against RECDA reveals that the cloud masks obtained from LECDA result in regional biases of Â±5 % that are most likely caused by the differences in surface reflectance in and around the urban areas of Paris. This makes the regional approach, RECDA, a more appropriate choice for the high-resolution satellite-based analysis of cloud cover modifications over different surface types and the interpretation of locally induced cloud processes. Further, this approach is potentially transferable to other regions and temporal scales for analysing long-term natural and anthropogenic impacts of land cover changes on clouds.