The coordination relationship between urban resilience and high-quality development is of paramount importance for improving disaster-alleviated resilient governance and sustainable development in response to the globalized crisis. However, few studies have investigated the coupling between urban resilience and high-quality development. Therefore, based on the analysis of the coupling and coordination mechanism between urban resilience and high-quality development, this paper innovatively calculates the indicators of urban resilience and high-quality development of 41 cities in the Yangtze River Delta Area (YRDA) from 2005 to 2020. Moreover, we explore the spatiotemporal patterns, evolution characteristics of the coupling coordination degree (CCD) between urban resilience and high-quality development using the entropy method, coupling coordination model, kernel density estimation curve, and further analyze the influence factors with the spatial econometric models. The results revealed that urban resilience maintained a steady growth, while high-quality development displayed a trend of an initial increase and a subsequent decline. The coupling coordination degree continued to rise and the regional difference decreased conspicuously, manifesting a robust developing trend. From the perspective of spatial patterns, the coupling coordination degree, which was characterized by “being high in the east and low in the west, tended to be balanced in the north and south and was prominent in the middle of the distribution.” Furthermore, economic strength, industrial structure, transportation facilities, and government intervention exerted a dominant influence on the development of coupling coordination degree, resulting in the spatial spillover effects as well. This study can reveal the interactive relationship between urban resilience and high-quality development can as well as help Yangtze River Delta Area provide a benchmark for promoting economic and social development while focusing on prevention and control of risk.

Identifying ecological functional areas by clarifying the trade-off synergies of multiple ecosystem services to meet the practical needs of coordinating different ecosystem services in a specific region is highly important. Based on InVEST, RUSLE and other models, this study analyzed the tradeoff synergies of five typical ecosystem services in the Wanjiang Urban Belt from 1990 to 2020 using Pearson correlation analysis, and self-organizing map (SOM) carried out ecological functional zoning. The PLUS model was used to simulate the evolution of ecological functional zones in 2030. The results revealed that (1) from 1990 to 2020, water yield (WY), soil reservation (SR), and food production (FP) services in Wanjiang Urban Belt increased, whereas carbon storage (CS) and habitat quality (HQ) services decreased. The value of ecosystem services showed a pattern of “high in the south and low in the north”. (2) WY–SR, WY–HQ, HQ–CS, and HQ–SR were synergistic, and the synergistic relationship showed a weakening trend. There were trade-offs in WY–CS, WY–FP, and SR–FP, and the trade-off effects increased with time. (3) The study area was divided into an ecological transition area, an ecological conservation area, an urban development area, an ecological restoration area, an agroecological area, and a water conservation area, and the functions and structures of each cluster significantly differed. (4) Under the natural development scenario, the scales of the ecological transition, ecological conservation, and agroecological areas increased. Under the cropland protection scenario, the urban development and ecological conservation areas began to transform into agroecological areas. Under the urban development scenario, the transfer of areas from ecological conservation, ecological restoration, and agroecological areas to urban development areas increased. In conclusion, the ecosystem services of the Wanjiang Urban Belt are dominated by synergistic effects, but there is a potential risk of shifting to trade-off relationships. In the future, targeted regional ecosystem optimization measures according to the evolution status of each ecological functional zone are urgently needed to provide references for territorial space management and control in this region.

The rational utilization of cultivated land resources is central to ensuring both ecological and food security in the Yangtze River Economic Belt (YREB), holding strategic significance for regional sustainable development. Using panel data from 2010 to 2023 for 130 cities in the YREB, this study examines a spatial correlation network (SCN) for non-grain land use (NGLU) and its driving forces via a modified gravity model, social network analysis (SNA), and quadratic assignment procedure regression. The results show the following: (1) The risk of NGLU continues to increase, with the spatial pattern evolving from a “single-peak right deviation” pattern to a “multi-peak coexistence” pattern featuring three-level polarization and gradient transmission, primarily driven by economic potential disparities. (2) The SCN has increased in density, but its pathways are relatively singular. Node functions exhibit significant differentiation, with high-degree nodes forming “control poles”, high-intermediate nodes dominating cross-regional risk transmission, and low-proximity nodes experiencing “protective marginalization”. Node centrality distribution is highly connected with the regional development gradient. (3) The formation of the spatial network is jointly driven by multiple factors. Geographical proximity, economic potential differences, comparative benefit differences, non-agricultural employment differences, and factor mobility all positively contribute to the spillover effect. Conversely, implementing cultivated land protection policies and the regional imbalance in local industrial development path dependence significantly inhibit the non-grain trend. This study further reveals that a synergistic governance system characterized by “axial management, node classification, and edge support” should be recommended to prevent the gradient risk transmission induced by economic disparities, providing a scientific basis for achieving sustainable use of regional cultivated land resources and coordinated governance of food security.

In order to gain a comprehensive understanding of land system changes and regional sustainable development, it is crucial to explore the spatiotemporal distributions of multiple land use functions (LUFs). Therefore, herein, considering the Yangtze River Delta urban agglomeration (YRDUA) as the research object, we constructed an evaluation system based on the perspective of production–living–ecological (PLE) land functions. Furthermore, the coupling coordination model, kernel density curve, trend surface analysis, and spatial autocorrelation model were used to examine the spatial and temporal characteristics of LUFs and their coupling coordination and analyze the spatial clustering of the coupling coordination effect in the urban agglomeration from 2005 to 2020. The following results were obtained: The level of PLE functions and its coupling coordination degree in the YRDUA have been improved in the study period, and the distribution of high value areas of different functions is diverse. In terms of the spatial distribution of the coupling coordination degree, the high value areas of production function (PF)–living function (LF) is distributed in “clusters”, the PF–ecological function (EF) demonstrated a single-polarized development structure, and the LF-EF exhibited a multi-core structure. The coupling coordination of the LUFs demonstrated a “high in the east and low in the west” pattern in the east–west direction and an inverted “U” shape in the north–south direction. Moreover, both high-value and low-value areas exhibited a clustering phenomenon, with an evident spatial positive correlation. The results of this study can serve as a reference for the integrated socioeconomic development of the Yangtze River Delta region and the sustainable development of urban land use.

Industrial land allocation spatial morphology (ILASM) is crucial for economic development and the advancement of new-type industrialization. However, existing studies lack a comprehensive understanding of the evolutionary characteristics of the spatial morphology of industrial land allocation, let alone its driving factors and the spatial heterogeneity of their effects. Therefore, this paper classifies industrial land allocation spatial morphology into traditional industrial land allocation spatial morphology (TILASM) and high-tech industrial land allocation spatial morphology (HILASM), then evaluates and identifies their characteristics based on the precise geographic coordinates of each industrial land parcel between 2007 and 2024 in the Yangtze River Delta (YRD). Subsequently, the Random Forest Regression model and Multi-Scale Geographically Weighted Regression model are integrated to systematically investigate the driving factors and spatiotemporal patterns of ILASM, including both TILASM and HILASM. The results show that from 2007 to 2024, different types of ILASM exhibited distinct spatiotemporal evolutionary characteristics. Specifically, first, in terms of the evolution of spatial distribution direction, overall industrial land allocation exhibited a pronounced agglomeration pattern, extending from the western (slightly northern) part of the region to the eastern (slightly southern) part. Moreover, the evolutionary direction of traditional industrial land allocation was consistent with that of overall industrial land allocation. However, high-tech industrial land allocation exhibited an agglomeration trend extending from west (slightly south) to east (slightly north). Second, in terms of evolution of agglomeration pattern, the spatial distribution of TILASM evolved from three-core dispersed configuration to a multi-core linkage, before reverting to a multi-core dispersed state; by contrast, both ILASM and HILASM exhibited a spatial pattern that progressed from dispersion to contiguous agglomeration. Third, the spatial distribution characteristics of different types of ILASM were shaped by the combined influence of natural conditions, economic development, social environment, innovation environment and infrastructure. However, the dominant driving factors differed among them. Specifically, the number of foreign-invested enterprises exhibited a negative influence on ILASM, while having positive effects on both TILASM and HILASM. The effects of patent applications, population density and internet penetration rate on ILASM; foreign-invested level and slope proportion on TILASM; as well as road density, labor quality and foreign invested level on HILASM all exhibited U-shaped relationships. Moreover, the influences of opening-up level and per capital road area on ILASM and HILASM displayed relatively complex N-shaped relationships. Finally, the effects of these crucial drivers displayed significant spatial non-stationarity and certain gradient effects, manifesting in southern–northern, western–eastern and core–periphery spatial differentiation patterns. Overall, this study provides scientific evidence and practical references for optimizing the spatial allocation of industrial land.