FY-3D/MERSI-II全球火点监测产品主要包括全球范围内的火点位置、亚像元火点面积和火点强度等信息，可用于实时监测全球范围的森林草原火灾、秸秆焚烧等生物质燃烧状况。火点判识算法主要根据中红外通道对高温热源的敏感特性，即含有火点的中红外通道像元辐亮度和亮温较远红外通道的辐亮度和亮温偏高，同时较周边非火点的中红外像元偏高，建立合适的阈值可探测含有火点的像元。亚像元火点面积估算主要使用中红外单通道估算，根据亚像元火点面积估算结果对火点强度进行分级，不同的级别表示不同程度的火点辐射强度。基于全球火点自动判识结果，每日生成0.01°分辨率的卫星遥感日全球火点产品，每月生产0.25°×0.25°格点的全球月火点密度图。在利用FY-3D/MERSI-II火点产品开展的全球火点监测应用中，对多起全球重大野火事件进行了监测，为防灾减灾、全球气候变化研究、生态环境保护等方面提供卫星遥感信息支持。

Fengyun/Medium Resolution Spectral Imager-II (FY-3D/MERSI-II) global fire products can be used in real-time monitoring of forest and grassland fires, straw burning, and other biomass burning worldwide. This paper discusses FY-3D/MERSI-II global fire products, including the methods, product contents, and applications.Fire spot discerning considers several conditions, such as cloud contamination, cloud edge, and thin cloud influences. Subpixel size evaluation uses a single channel with fire temperature set to 750 K. Fire intensity level is established on the basis of Fire Radiative Power (FRP) and is calculated using sub-pixel size and fire temperature. Daily global fire products with 0.01° spatial resolution are generated, and global monthly fire spot density maps with 0.25°×0.25° grid points are produced monthly on the basis of the results of automatic global fire spot discerning.We selected the results in several typical areas, including Northeast China, Russian Far East, South America, and South-central Africa, from May to June 2018, and compared them using interactive fire spot discerning as the truth to verify the accuracy of automatic fire spot discerning in Fengyun/Medium Resolution Spectral Imager-II (FY-3D/MERSI-II) global fire monitoring. The statistical analysis results show that the accuracy of the automatic fire monitoring algorithm reaches more than 95. The daily FY-3D/MERSI-II global fire products include fire location, subpixel size (in hectare, temperature, fire intensity level, and FRP. Two application examples are introduced, where the first example is for monitoring the huge wildfire that occurred in California, US in 2018, and the second example is for analyzing the temporal and spatial changing features of wildfire around the Arctic Pole circle in the summer of 2018.The FY-3 global fire spot discerning algorithm considers various weather and underlying conditions, making it suitable for fire monitoring in different regions of the world. The results show that the proposed algorithm has good accuracy. The rich detection information and global observation ability of FY-3 meteorological satellite reach the international advanced level of forest and grassland fire monitoring. FY-3 global fire product can be used for disaster prevention and mitigation, climate change, and ecological environment protection worldwide. In future studies, we will develop methods, such as burned area assessment and estimation of biomass carbon emissions, smoke impact prediction, and forest and grassland fire risk warning. FY-3 meteorological satellite will play a huge role in global wildfire monitoring and early warning and prediction services.