Abstract: A farmland served as the carrier of grain production is an important material basis to the food security. The abandonment of farmland has become one of the most important problems in China's farmland utilization over the past 20 years, particularly on a series of social, economic, and environmental issues. Therefore, it is necessary to quickly capture the spatial and temporal information, including the accurate location, duration, and the scale of abandoned farmland, in order to evaluate the marginal trend, and further to maintain the sustainable use of farmland. According to the current status of information acquisition methods for the abandoned farmland, this study was first to summarize the advanced methods of acquiring abandoned farmland information, and then to make a comprehensive prospect for the directions of future research. The results show that: 1) Three types can be divided in the methods of information acquisition: sampling survey, literature meta-analysis, and remote sensing. 2) In a sampling survey, the information acquisition method of abandoned farmland was widely used in small-scale case studies, indicating a nearly consistent research paradigm, but the spatial representation ability was relatively weak. To a certain extent, the national household survey data increased the spatial attribute of data, but the secondary screening of original data reduced the sample size and the credibility. Moreover, most panel data has made it difficult to trace the abandoned farmland information in different historical stages. 3) In literature meta-analysis, the information statistics method of abandoned farmland applied the idea of big data analysis, and further integrated the previous research data. It can be used to not only represent the abandonment rate and spatial-temporal changes of different regions, but also compare the main driving factors of abandoned farmland in different regions. However, the research findings of this method were confined to only a few published articles, while, a comprehensive understanding of hot keywords was highly demanding in related fields. At present, only a relatively few applications were found in the acquisition of abandoned farmland information. 4) Remote sensing can be expected to the mainstream for the information acquisition of abandoned farmland, as the development of satellites and computer technologies in the future. A variety of detection methods for the abandoned farmland have been developed, according to the object features and information changes of land use. There was still a large optimization space in the remote sensing, due to the high spatial resolution and large-scale extraction requirements. With the emergence of cloud computing and machine learning, the remote sensing has the promising potential to explore large-scale and high-resolution detection of abandoned farmland. Therefore, future research can be further explored in data selection and processing, feature fusion, and method fusion. The findings can provide an appropriate reference for the detection and management of farmland use.