This study was aimed at optimizing the weighted linear combination method (WLC) for agricultural land suitability evaluation (ALSE) through indicator selection, weight determination, and classification of overall suitability scores in Handan, China. Handan is a representative research area with distinct agricultural advantages and regional differences in land use, where the expansion of construction land has led to a rapid decrease of agricultural land in recent years. Natural factors (topography, climate, soil conditions, and vegetation cover) and socioeconomic factors (land use and spatial accessibility) were selected to establish a more comprehensive evaluation system. The index weight was calculated by the mutual information between index suitability and current land use. The consistency index was used to identify the boundary value dividing the overall suitability score into a suitable category and unsuitable category in each sub-region. The results demonstrated that the optimized WLC-ALSE model outperformed the comparison models using conventional methods in terms of the consistency between the evaluation results and current land use. Owing to the increasing limitations of topography, soil conditions, spatial accessibility, and land use, the proportions of suitable land in Zone 1, Zone 2, and Zone 3 were 77.4%, 67.5%, and 30.9%, respectively. The agricultural land unsuitable for agriculture (14.5%) was less than non-agricultural land suitable for agriculture (7.4%), indicating that agricultural land had low growth potential in Handan. Finally, specific recommendations were made to improve agricultural land suitability, alleviate land use conflicts, and further optimize the model. The results can provide effective guidance for WLC-ALSE and land use decision-making for sustainable agriculture.

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As resources are depleted, resource-based cities face unique challenges in the process of socio-economic development. We constructed a multidimensional socio-economic development level model by adopting Entropy Value Method, Analytical Hierarchy Process, time series weighting method, and Game Theory approach for the data of 10 indicators in 4 dimensions of 115 resource-based cities in China from 2004 to 2019 to explore the spatial and temporal divergence characteristics of multidimensional socio-economic development level and the driving mechanism of its pattern of evolution. The results show that: (1) the overall socio-economic development level of resource-based cities has improved from 2004 to 2019, but the overall level is low. Large differences exist in the spatial distribution of socio-economic development levels between cities with more significant regional spatial aggregation characteristics. (2) Secondary industry, tertiary industry, retail trade goods sales, urban construction land area, and total freight transport have a significant positive impact on socio-economic development; the correlation coefficient between the number of schools and the socio-economic development level index is negative. (3) Retail trade merchandise sales contribute the most to the Gini coefficient, where the percentage of secondary industry and urban construction land area have a higher cumulative contribution to growing cities (55.02%), the percentage of secondary industry has the lowest contribution to regenerating cities (10.94%), and the percentage of tertiary industry has an increasing contribution to declining cities year by year. Based on the above findings, some specific suggestions are provided to provide reference for resource-based city development planning.