It has come to our attention that in preparing the final version of this paper, we inadvertently misspelled the first name of an author Ziming Zhou as ''Zimin Zhou''. In addition, we have made two errors in describing the reagents in the STAR Methods. First, under the subheading of ''Synthesis of barcoded beads'' in the Method Details section, the supplier of the magnetic beads coated with carboxyl groups should be Suzhou Knowledge & Benefit Sphere Tech. Co., Ltd. (diameter 20-25 mm, http://www.kbspheretech. com/), instead of Zhiyi. Second, under the subheading of ''Cell collection and lysis'' in the Method Details section, the concentration of Tris-HCL for the cold lysis buffer should be 0.1 M, instead of 1 M. These errors have been corrected online, and we apologize for any confusions we may have caused.

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.

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In this study, Moderate Resolution Imaging Spectroradiometer land cover, land surface temperature (LST), and enhanced vegetation index (EVI) data were used to investigate the trends of surface urban heat island intensity (SUHII, urban LST minus rural LST) and their relations with vegetation in 397 global big cities during 2001–2017. Major findings include the following: (1) Annual daytime and nighttime SUHII increased significantly (p < 0.05, Mann‐Kendall trend test) in 42.1% and 30.5% cities, respectively. (2) The daytime SUHII in the growing season was significantly and positively correlated with rural EVI in 58.9% cities. This is because high rural EVI can increase the EVI difference between urban and rural areas. (3) Rural greening contributed 22.5% of the increased daytime SUHII in the growing season at the global scale. This study highlights that the effect of greening in rural areas was a significant and widespread driver for the increased daytime SUHII.

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