Geographical features may have a considerable effect on local climate. The Local Climate Zone (LCZ) system proposed by Stewart and Oke (2012) is nowadays seen as a standard referential to classify any zone according to a set of urban canopy parameters. While many methods already exist to map the LCZ, only few tools are openly and freely available. This manuscript presents the algorithm implemented in the GeoClimate software to identify the LCZ of any place in the world based on vector data. Seven types of information are needed as input: building footprint, road and rail networks, water, vegetation and impervious surfaces. First the territory is partitioned into Reference Spatial Units (RSU) using the road and rail network as well as the boundaries of large vegetation and water patches. Then 14 urban canopy parameters are calculated for each RSU. Their values are used to classify each unit to a given LCZ type according to a set of rules. GeoClimate can automatically prepare the inputs and calculate the LCZ for two datasets: OpenStreetMap (OSM - available worldwide) and the BD Topo v2.2 (BDT - a French dataset produced by the national mapping agency). The LCZ are calculated for 22 French communes using these two datasets in order to evaluate the effect of the dataset on the results. About 55 % of all areas has obtained the same LCZ type with large differences when differentiating this result by city (from 30 % to 82 %). The agreement is good for large patches of forest and water as well as for compact mid-rise and open low-rise LCZ types. It is lower for open mid-rise, open high-rise mainly due to height underestimation for OSM buildings located in open areas. By its simplicity of use, Geoclimate has a great potential for new collaboration in the LCZ field. The software (and its source code) used to produce the LCZ data is freely available at https://zenodo.org/record/6372337, the scripts and data used for the purpose of this manuscript can be freely accessed at https://zenodo.org/record/7687911 and are based on the R package available at https://zenodo.org/record/7646866.