Despite the ecological importance of natural habitats, they are facing threats of loss and degradation. The Habitats Directive requires EU countries to accurately map and monitor the condition of Annex I habitats. Ireland must report, map and monitor the conservation status of its Annex 1 habitats based on ecological field data every six years. This field-based mapping and assessment methodology, while desirable, is time-consuming and expensive. Thus, more efficient mapping approaches should be considered to supplement these traditional field-based methods. The use of remote sensing techniques to map, monitor and evaluate Irish habitats enables repeatable and cost-effective surveys. The advent of Unmanned Aerial Vehicles (UAVs) delivers new developments in the field of remote sensing by providing multi-sensor images with centimeter-level resolution. UAVs also offer flexible data acquisition suited for monitoring and change detection applications due to their independence from weather and cloud cover. The “Habitat Mapping, Assessment and Monitoring using High-Resolution Imagery” Project or iHabiMap is a part of Ireland’s initiative to produce detailed assessment of its habitats using ultra-high resolution images acquired from UAVs. Analytical approaches will be developed to map, assess, and monitor three habitats - upland, grasslands, and coastal zones, by utilizing UAV data and machine learning algorithms. This poster presentation will give an overview of the project. Multispectral data will be acquired and tested for each habitat. The methodology will provide a reproducible automated technique to enable frequent habitat mapping in Ireland. Field surveys will be conducted alongside the acquisition of UAV data at each study site. Overall, this study aims to develop and test a methodology that integrates remote sensing data and machine learning technologies to map and monitor these three Annex I habitats.