The CLOSER-FORINVENT project represents a continuation of 3D-FORINVENT (IP-2016-06-7686, https://jaska.sumins.hr/3d-forinvent/) regarding further testing and development of suitable methodological approaches of different close-range remote sensing (CR-RS) technologies for the forest inventory applications. The main idea is to perform thorough testing of a different state of-the-art CR-RS technologies (unmanned aerial systems equipped with different sensors, static and mobile terrestrial laser scanning) for precision forest inventory in the main and the most important Croatian forest stand types (pedunculate oak, common beech) of different structural and terrain characteristics. The research will include testing of a different data acquisition protocols, different processing algorithms and methods, and various datasets collected from different sensors. The fusion of different sensors will also be investigated. All these, along with the collection of highly accurate ground reference data, will be performed to evaluate the accuracy and suitability of different CR-RS technologies in a various forest inventory task, such as: digital terrain model generation, individual tree detection and segmentation, determination of tree positions, tree species classification, and estimation of the main attributes at tree-, plot- and stand-level. In addition, the CLOSER-FORINVENT project will test the integration, i.e., data fusion of CR-RS data and available national remote sensing data aiming to upscale estimates to a larger forest area by wall-to-wall mapping. So far, there have been a lack of such detailed comparison studies dealing with performance and applicability of different high-end CR-RS technologies in forest inventory, especially in complex forest environment, such as mixed, deciduous, temperate forests of different structural characteristics. Therefore, it is of great importance for forestry science to perform research which will develop and recommend the most suitable methods for the possible application of CR-RS in operational forest inventory.