This study aims to assess the current status of green agricultural development and its influencing factors in Lincang City, a national innovation demonstration zone for sustainable development; it also seeks to enhance the potential and competitiveness of green agricultural development in underdeveloped border areas. To achieve this, an evaluation index system is constructed encompassing six dimensions. Using a coupled coordination and obstacle degree approach, this study explores the spatiotemporal differences in the level of green agricultural and sustainable development, as well as the power, coupled coordination degree, and factors that negatively impact green agricultural development in Lincang City from 2010 to 2019. The Liang-Kleeman information flow method is applied to uncover the key information flow factors that influence the coupled coordination degree in each county and district of Lincang City. The results reveal several insights: First, the comprehensive score of sustainable green agricultural development increased from 0.4405 to 0.5975 during the study period. Second, the coupling coordination degree of green agricultural development was relatively low, fluctuating between 0.1821 and 0.2816. Overall, the development has shifted from severe imbalance to mild imbalance. Third, the obstacle degree increased by 3.75%. From a systemic perspective, the “resource conservation” layer had the highest barrier level, with the maximum value being observed in Yun County at 25.5%. Further analysis of the indicators reveals that the use of outdated water-saving irrigation techniques has resulted in low irrigation efficiency and excessive water resource waste. This is the main cause of the high barrier levels in terms of water-saving irrigation intensity and effective irrigation area. Moreover, the excessive use of chemical pesticides to enhance vegetable production has contributed to high barrier levels for achieving yields of pollution-free vegetable production per unit area. Finally, the information flow values of the factors influencing the coordinated and harmonious development of green agriculture exhibit significant regional heterogeneity among counties and districts. The highest information flow value for the area of drought- and flood-resistant crop cultivation is in Zhengkang County at 1.86. Based on these results, local government departments and decision-makers should focus on promoting comprehensive improvements in the level of green agricultural development. It is crucial to tailor measures to the specific needs of each county to address the shortcomings in green agricultural development. Additionally, efforts should be made to strengthen the innovation-driven chain of green agricultural development, including production, processing and sales. Enhancing the green agricultural development system is essential for long-term progress.

Air/soil temperatures play important roles in land–atmosphere interactions. The three-dimensional (temporal, spatial, and vertical) variations of maximum, mean, and minimum ground soil temperature at 0 cm (GSTx, GSTm, and GSTn, respectively), surface air temperature at 2 m (SATx, SATm, and SATn, respectively), and soil–air temperature difference (SATDx, SATDm, and SATDn, respectively) and their potential linkages with large-scale indexes in Southwest China during 1980–2019 were analyzed. Variations of GST and SAT at the majority of stations (pixels) exhibited significant (p ≤ 0.05) warming, albeit at different rates; consequently, SATD exhibited different variation. Moreover, the period of GST, SAT, and SATD was similar in intra-annual and interannual oscillation but was different in interdecadal oscillation. The variation rate of GST, SAT, and SATD exhibited significant (p ≤ 0.05) correlation with elevation, but with different variation gradient. Notably, asymmetric variation of SATDx (downward trend) and of SATDn (upward trend) with elevation was found at elevations >3 km. Wavelet coherence showed that the Atlantic Multidecadal Oscillation is the dominant factor affecting GST and SAT, whereas the Pacific Decadal Oscillation and the North Atlantic Oscillation make the greatest contributions to SATD. It was found that GST, SAT, and SATD exhibit different variations under the effects of global warming, the driving mechanism of which requires further study.