Land Surface Temperature (LST), which determines the radiation and energy exchange at the surface, is one of the key parameters in the physical processes of the ground surface. It has been widely used in numerical forecasting, agricultural situation estimation, disaster monitoring, ecological environment assessment, and many other aspects. With the development of remote sensing technology, the study of LST based on remote sensing has received extensive attention from scholars at home and abroad.In this paper, based on the core database of Web of Science, we used VOSviewer and CiteSpace software to conduct a bibliometric study on 5336 papers on remote sensing-derived LST from 1985 to 2023. We analyzed the number of papers, research institutions, countries, authors, issuing journals, and keywords and looked forward to the future trend by combining with the hot spots of current research.Results show that (1) the field of remote sensing-derived LST has experienced rapid growth, especially after 2012, showing exponential expansion. China and the United States have made particularly outstanding contributions to this field, with 2169 and 1422 papers respectively. Chinese scholars have played a pivotal role in the field of remote sensing-derived LST, and the Chinese Academy of Sciences has achieved remarkable results. The organizations have shown a close cooperation between institutions, presenting an internationalized research pattern that promotes the sharing of scientific research resources and dissemination of knowledge worldwide. (2) Over time, the research center in the field of remote sensing-derived LST still focuses on the basic disciplines and gradually shifts to the applied disciplines. In terms of journals, Remote Sensing has become the main journal in the field of remote sensing-derived LST with its all-open-source feature, and Remote Sensing of Environment leads in popularity with a high citation count of 38884, underscoring its academic influence. (3) By clustering the keywords, four mainstream clusters are identified. LST data from sources like AVHRR, MODIS, and Landsat are extensively utilized, marking a shift in research focus from traditional topics like vegetation index and soil to emerging domains such as machine learning and local climate zones. This evolution is characterized by ongoing innovation and development in technological methods and research content. In the past decade, in addition to the traditional research directions of inversion, validation, and normalization of remotely sensed surface temperature, reconstruction, downscaling, and spatiotemporal fusion have become emerging research hotspots in the field.

remote sensing;land surface temperature;bibliometrics;research hotspots;Development trends;fields of application;satellite data