Cultivated land has been one of the most important resources in agricultural production. Dynamically stable areas and the quality of cultivated land can greatly contribute to national food security and sustainable development. However, the cultivated land resources have been gradually fragmented and dispersed, with the rapid development of urbanization and industrialization. The cultivated land has been under serious threat in recent years. Therefore, this study aims to assess the suitability and necessity of cultivated land fragmentation for better cultivation zoning, in order to efficiently utilize the cultivated land resources and spatial layout. Accordingly, the background and progress were first combed to improve the research theory and logic fundamentals. The study area was selected as the typical mountainous county in the resource-oriented Dexing City in Jiangxi Province of China. 105 villages with cultivated land were taken as the evaluation unit. Secondly, a binding model was established for control and management. The "three zones and three lines" delineation was used as the reference. 20 indicators were also selected to construct an evaluation system for the suitability of cultivated land fragmentation, according to the three evaluation dimensions of production suitability, spatial agglomeration, and management control binding. The multi-factor integrated superposition was also evaluated for the appropriateness of cultivated land in the fragmentation management. Again, the three-dimensional Rubik's Cube spatial classification was used to construct the zoning guidelines. Production suitability, spatial agglomeration, and management control constraints were set as the X-, Y-, and Z-axis of the Rubik's Cube. The evaluation and grading results of each dimension were the nodes of the axes on the remediation and zoning. The results show that: 1) The better suitability of arable land resources production was 0.558, where 58 villages were more than the average value. The higher value was concentrated in the southwestern part of Dexing City; There was a uniform spatial agglomeration of arable land, with a citywide average of only 0.350. Less than half of the villages had a higher spatial agglomeration than the average, where the maximum of 0.577 was located in Jietian Village; The average value of the management control constraints was 0.075. There was a great variation in the villages, where the high values were concentrated mainly in the villages around towns and ecological red lines; The average value of the appropriateness in the management of cultivated land fragmentation was 0.711, and the appropriateness in the management of 53 villages was higher than the average, indicating the fine-fragmentation of cultivated land resources. 2) The comprehensive assessment showed that the 105 villages were divided into five zones, including the high-quality security, comprehensive improvement, facility optimization, intensive integration, and status quo maintenance zone, where the proportions of the cultivated land area were 38.36%, 12.01%, 19.11%, 17.84%, and 12.68%, respectively, according to the three-dimensional Rubik's Cube spatial classification. Differential remediation measures and strategies were also formulated to consider the different production suitability, spatial agglomeration, management and control constraints in each district. The finding can provide the theoretical basis and technical support to implement the diversified management and control measures in the different types of arable land resources, particularly in the cultivated land fragmentation remediation project.

Ecological barrier of national land space can be constructed to utilize the spatial-temporal evolution and influencing mechanism of landscape ecological risk in Xiuhe River Basin. It is of great significance to optimize the ecological risk management. This study aims to take the typical area with the mixed distribution in plain and mountainous areas in the time points of 2002, 2007, 2012, 2017 and 2022. Firstly, the grid database was constructed to cover the land use, human activities, climate and geographical location using GEE platform and ArcGIS 10.8 platform. Secondly, the landscape ecological risk of each evaluation unit was calculated using the landscape index. The spatial distribution of landscape ecological risk was then obtained by kriging interpolation. In addition, the spatial autocorrelation and topographic gradient classification models were used to reveal the spatial and temporal evolution of landscape ecological risk in horizontal and vertical space. Finally, the optimal parameter geographic detector was used to select the indicators from the human activities, climate conditions, natural environment and dimensions. A summary was made to clarify the influence and interaction mechanism of each factor on the landscape ecological risk. The results show that: 1) The spatial distribution of landscape ecological risks from 2002 to 2022 was characterized by "high concentration and low dispersion" from the perspective of temporal and spatial evolution, most of which were the low- and medium-low risk areas. The ecological risk level was basically high in the east and low in the west; The low- and medium-low risk areas increased by 491.89 km² over the past 20 years, while the high- and medium-high risk areas decreased by 926.17km². The ecological risk Basin was basically shifted from the high to low risk. The overall ecological risk shared the downward trend. 2) The landscape ecological risk was positively correlated in space, in terms of spatial and temporal distribution, with the significant spatial agglomeration and differentiation. The local agglomeration was mainly in the "H-H" and "L-L" pattern, with the gradually narrowing range of high-value agglomeration areas; The low ecological risk areas were distributed mainly in the middle and low terrain gradient on the vertical scale, while the high ecological risk areas were concentrated mostly in the range of low altitude and low slope gradient. The distribution index of high ecological risk increased with the decrease of altitude and the leveling of terrain, indicating the dominant distribution in space. 3) The landscape ecological risk was easily influenced by multi-dimensional factors. The explanatory power of natural environmental factors was generally stronger than that of human activities and climate conditions from the perspective of single factor. Each factor was relatively fluctuated in the different periods, but there was the strong influencing of topographic factors, human interference index, and annual average temperature; The interaction among factors showed a significant explanatory power enhancement at the level of factor detection, among which the interaction between natural environment and other factors was the strongest. The finding can also provide the useful reference for the management and control of ecological risks for the optimization of spatial layout.