Clarifying the consistency and uncertainty of different wildfire data products is the prerequisite and foundation for analyzing and applying the products. FireCCI51 and MOSEV are two internationally widely used wildfire data products， and the pan-Arctic permafrost region is a global concentration of wildfires and an important carbon pool. Analyzing the consistency of wildfire data products in the pan-Arctic permafrost region could be important for enhancement of data accuracy of wildfire products in the future and reduction of carbon flux estimates in this region. This study use spatial analysis to identify the consistency of the FireCCI51 and MOSEV data products in the pan-Arctic permafrost region from the aspects of burned area and spatial location of the burned zones. And then analyzes the geographic characteristics of the consistent zones and inconsistent zones.The results show that： ① The burned area of FireCCI51 product is larger than that of MOSEV from 2001 to 2019， and the percentage difference of burning area of the two products fluctuates irregularly in the range of 7% to 60% The spatial distribution consistency of the burned areas identified by the two products ranges from 27.68 % to 47.14 %. Consistent zones are mainly found in areas where burned areas are concentrated， such as Central Canada， Central and East Siberia in Russia and its southern extension， the Daxinganling region. Inconsistent areas are distributed in the southern Russia and Western Siberia in addition to these areas； ③ Elevation， climate types and vegetation types all have a certain impact on the distribution of the consistent areas. In lower altitude regions and constant wet and cold temperate climate regions， the area of consistent zones of the two products accounted for more， while in relatively higher altitude regions and subboreal monsoon climate regions， the area of inconsistent zones of the two products accounted for more. And both consistent and inconsistent zones are greater in woody savannah and savannah areas. Therefore， future applications of both data products need to be carefully evaluated， especially for regions with a high distribution of inconsistent regions， such as southern Russia， Western Siberia， and subboreal monsoon climate regions.