Microclimate (e.g., temperature and humidity) in urban green space (UGS) patches changes nonlinearly from the edge to the interior, displaying a microclimatic edge effect (MEE). Reducing the MEE width is an effective and practical strategy for UGS planning and management to enhance climatic benefits (e.g., cooling). However, cost-effective approaches are not available to quantify the MEE width, let alone explore its driving factors. This study proposes a novel and cost-effective method to quantify the MEE width, based on the relationship between climatic variables (e.g., temperature and humidity) and the percentage of remaining UGS after successive edge removals. The method was tested in the subtropical city of Changsha, China, considering air temperature (AT) and humidity. Its effectiveness was also tested using widely available land surface temperature (LST) datasets while considering different spatial resolutions of the UGS map (i.e., 1–10 m) and different analytical units (i.e., 1 km2 grid and township census tract). Finally, the generalizability of this method was validated with data on six other representative Chinese cities. The results show that: (1) The estimated MEE widths for temperature and humidity in Changsha are about 8 m and 6 m, respectively. (2) The approach obtains consistent MEE widths irrespective of temperature types and analytical units. (3) A high spatial resolution UGS map (i.e., 1 m) is recommended for higher accuracy. (4) This approach effectively identifies MEE width in six other representative Chinese cities (Beijing, Chengdu, Shanghai, Shenyang, Wuhan, Xi’an), demonstrating its generalizability. This novel approach provides an easy and fast method to identify the MEE width at the landscape scale, which can help (1) better understand the relationship between UGS fragmentation and the urban microclimate, and (2) better plan and manage UGS to improve the urban microclimate.