In 2015, the “2030 Agenda for Sustainable Development” (2030 ASD), adopted by the United Nations, set 17 Sustainable Development Goals (SDGs). Scholars worldwide have conducted continuous research on the monitoring and evaluation of SDGs. Data deficiency and inadequate index monitoring abilities are considered vital restrictions in the regular monitoring and evaluation of SDGs. The application of Multisource Data to the monitoring and evaluation of SDGs can effectively address these deficiencies. Research progress on SDGs based on Multisource Data can be categorized into three types: the first type focuses on the basic theory and method system of SDG monitoring and evaluation based on Multisource Data; The second type conducts SDG monitoring and evaluation case studies based on Multisource Data; The third type focuses on strengthening the primary capacity building related to Multisource Data. The application of multisource data can strengthen the evaluation of natural ecosystems, identify critical areas, analyze the interaction between humans and nature, effectively compensate for the lack of data and other deficiencies, and improve the timeliness and spatial and temporal resolution of indicator data, which can significantly enrich the evaluation index system of the SDGs. This study proposes to strengthen the application of Multisource Data in the study of SDGs from four aspects: to expand the application of Multisource Data in the SDGs, promote interdisciplinary and comprehensive research, pilot the application of Multisource Data in the national innovation-driven demonstration zone for implementing the UN's 2030 ASD, and strengthen the primary capacity building of Multisource Data.