We present a preliminary point inventory of the landslides associated with the M7.2 Nippes, Haiti, earthquake that occurred on August 14, 2021. The mapping was part of rapid response efforts to identify hazards for situational awareness and emergency response by humanitarian aid organizations. This inventory accompanies an Open-File Report detailing the hazards presented by the landslides triggered by the earthquake (Martinez et al., 2021). To map the landslides, we used mid- to high-resolution satellite imagery including Sentinel-2 (10-m resolution), WorldView (0.3-0.5-m resolution), Planet (2.7-4.0-m resolution), as well as a high-resolution (1.5 m) Digital Elevation Model (DEM) that was derived from lidar collected from 2014-2016 (HaitiData and The World Bank, 2021). We compared post-earthquake images to pre-earthquake images to assure the landslides were associated with the earthquake. Due to the varying quality of imagery used and our rapid mapping for the response, we estimate our accuracy of landslide head scarp points to be within tens of meters of their correct ___location at the top of the corresponding head scarp. For one of our more poorly orthorectified images, the root mean square error was calculated to be 45 m. This error is not representative of all images used, but it provides an upper limit on the positional accuracy of our mapping. Due to the large quantity of images utilized in our rapid mapping efforts, a formal and systematic assessment on the positional accuracy of the data has yet to be completed. We also referenced a grid of population data (Facebook Connectivity Lab and Center for International Earth Science Information Network, 2016) as well as OpenStreetMap data (OpenStreetMap, 2021) while mapping to determine the potential for human and infrastructure impacts. Specific hazards that were identified include landslide dams and roads that were undercut or covered by landslide debris. The inventory includes 4,893 landslides. This is a minimum, however, because high-resolution imagery remains unavailable in some areas. Additionally, there may be a few localized areas in our mapping area that did not have cloud free imagery.