Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

Accurately assessing the multifaceted performance of urban commercial land is essential for steering consumption upgrading and refining urban spatial planning. However, existing scholarship continues to treat commercial land through a predominantly economic lens; non-economic indicators have rarely been compared with price-based metrics within a unified analytical framework. To bridge this gap, this study constructs a multidimensional benefit evaluation framework encompassing four indicators, namely, land values, shop rent, online reviews, and customer ratings, across 10,766 commercial land parcels in Chengdu, China, and applies XGBoost-SHAP methods to examine their predictive associations and spatial patterns. This study reveals the differences and commonalities among the four benefit indicators in terms of statistical characteristics, spatial distribution, and matching patterns, and further examines the ranking of their key predictors, as well as the nonlinear effects, threshold effects, and interaction effects with key factors. These findings corroborate the distinctiveness of the four benefit variables and the significance of comprehensively evaluating commercial land-use benefits. This study provides novel perspectives and empirical evidence for assessing commercial land-use benefits and their predictive mechanisms, and offers actionable guidance for formulating targeted consumption development, spatial layout, and business format optimization strategies, thereby contributing to the sustainable vitality of urban economic spaces.