Improvements in and the assessment of land use efficiency are crucial pillars for achieving the Sustainable Development Goals (SDGs). This study reviews 208 representative papers, oral reports, and project reports to provide a systematic and comprehensive understanding of the current status and future trends of research on land use efficiency assessment. The findings reveal that (1) the number of papers on land use efficiency assessment is rapidly increasing, with research primarily focused on environmental science and ecology (n = 157, 75.48%). (2) Quantitative models are gaining popularity for land use efficiency assessment, with more than 46.63% of the studies adopting the data envelopment analysis (DEA) model. (3) The definition and analysis perspectives of land use efficiency are diverse, but research on relative land use efficiency and comprehensive analysis perspectives accounts for a significant proportion. (4) Constructing a large and complex model that incorporates geospatial effects, big data, and computer technology is a hot topic for future research methods. On the other hand, conducting land use efficiency research on a global scale is more conducive to achieving the SDGs. (5) The core to improving land use efficiency lies in the joint implementation of multi-pronged measures.

China’s transportation industry has made great achievements in the past 40 years of reform and opening up. At the same time, it has gradually accumulated a series of problems. These problems have led to closer and more complex social and economic connection within and between regions of different scales. The existing research only carries out the characteristic analysis of urban network spatial connection and pattern from a single perspective such as “flow space” theory, spatial interaction model and accessibility method, and fails to accurately describe the complex socio-economic relations between regions. Based on the big data of railway passenger flow, this study selected weighted average travel time, railway network density, and the economic connection model to express the urban network spatial connection and structure of China in 2016 from the perspectives of time, space, and interaction. In 2016, the accessibility, connectivity, and total urban external economic connection of the railway network showed a trend of declining from the east to the west. The top 50 cities ranked by interurban economic connection were all located in the central and eastern regions and showed “diamond shape” distribution characteristics. The four diamond-shaped pairs were Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, and Chengyu urban agglomerations. This shape was basically in line with the T-shaped space that has existed for a long time in China’s regional development. The accessibility, connectivity, and total external economic connection of national-level urban agglomerations were greater than those of regional-level urban agglomerations, and far greater than those of local-level urban agglomerations. The results showed that there was a mismatch between the layout of the railway network and the population. It will still be necessary to focus on strengthening the construction of transportation infrastructure in urban agglomerations and densely populated areas in the future. This study enriches the “flow space” theory, more fully describes urban network spatial connection and structure in China by considering the three perspectives of time, space, and interaction, and can provides reasonable suggestions for the development of national comprehensive three-dimensional transportation network planning, regional spatial structure optimization, and sustainable development.

Monitoring ecological environment with remote sensing technology is an effective means of environmental management and sustainable development. Based on Landsat image data and field survey data, this paper used the unweighted voting multi-classifier ensemble method to extract the ecosystem cover data of the water-land interaction area of Nansi Lake from 1987 to 2017, and analyzed the evolution characteristics of the ecosystem structure with the help of the transfer matrix and landscape pattern index. The results showed: (1) The accuracy of multi-classifier ensemble was higher than that of single classifier, with a maximum improvement of 4.17%. (2) In 2006, the change inflection point of ecosystem structure appeared in the study area, which showed that the trend of increase and decrease of ecosystem area changed, and the degree of landscape fragmentation was the lowest. The structure and type transfer of the ecosystem in the study area showed the characteristics of “ring” distribution, and the distribution and transfer of ecosystem at the junction of land and water and land were more complex. (3) Human activities under the intervention of China’s policies, climate change and ecosystem self-regulation were the main driving factors for the change of ecosystem structure in the study area. This study provided technical methods for the further exploration of the ecosystem, and provided constructive guidance for the protection and sustainable development of ecological environment.