Abstract: crowd sourcing geographic data (CSGD) is a kind of open geospatial data provided to the public or related organizations through the internet. CSGD has the potential to be applied in the space-time allocation of emission inventories due to its characteristics of easy access, good timeliness and high accuracy. However, the existed emission inventory processing tools do not support the direct input of CSGD data and are difficult to meet the inventory formats required for the space allocation of emission inventories and the air quality models. Therefore, it is urgent to develop a new set of tools to expand the application of CSGD in the field of emission inventories. In the present study, we focused on the point of interest (POI) data in CSGD, and developed an emission inventory processing tool called ISAT based on the QGIS platform, C++ and Python. ISAT included the ISAT emission inventory spatial processing tool based on the Windows system and the ISAT.M tool under the Linux system. The results proved that the spatial distribution results based on the POI data in the ISAT were in good agreement with the actual emission characteristics of the emission source. The inline inventory outputted by the ISAT.M tool could be used as an input for the CMAQ air quality model and its DDM module. Moreover, the simulation results of inline inventory by ISAT.M showed high consistency with the results of Brute Force method of the SMOKE model in both the data and the spatial distribution. This study shows that the CSGD data applied to the emission inventory space allocation can reflect the spatial distribution characteristics of the emission source. At the same time, due to the information redundancy and the lack of data in the suburbs, attention should be paid to the data cleaning and data type selection during the application processes.