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Under complex external disturbances, rural suburbs are confronted with rapidly changing man-land conflict. In this context, the path of resilience development in coordination with the spatiotemporal changes of rural settlements should be taken. This study interpreted the complex system of rural settlements based on complicated social network in the case of Qin and Han New City, and developed a research framework of “spatial simulation–resilience evaluation–spatial planning”. The results include the evolution trends of settlement space from present to future and its spatial resilience in static and dynamic states. In the present study, 14 central villages and 6 types of rural development were finalized, and the study area possessed a long-term spatiotemporal resilience when 85 villages remained, thus forming an ideal spatial pattern of “rural relic zones + characteristic towns”. The findings can offer guidance for the resilience development in suburban villages as well as provide a basis for guiding the regional urban–rural coordination, village–town system planning and rural construction.

In the context of farmland afforestation and urbanization, it is necessary for the small watershed rural settlements in the hilly–gully Loess Plateau to coordinate spatiotemporal changes and take the path of resilience development. In the case of the Sanshui Watershed, this paper investigates the rural settlement systems based on complex networks, and develops a research framework of “spatial simulation–resilience evaluation–spatial planning”. The results include the evolution trends of settlement space from present to future, as well as its spatial resilience in static and dynamic states. In this study, a total of six central villages and six types of rural development are finalized, and the study area possesses a prolonged spatiotemporal resilience when 29 villages remain, thus forming an ideal spatial pattern of “rural corridor zones + characteristic towns”. The findings of this study can represent guidance for resilience development in small watershed villages and provide a basis for guiding the regional urban–rural integration, village layout, as well as resource allocation and construction.

In the future, big data will become an efficient and useful means for improving urban planning, and machine learning can take city as a simplified and efficient system. We take full advantage of the benefits of new technology, but also clarify that city is not a machine, also cannot fully mechanically control the urban development. This study presents a methodology for identifying low-carbon travel block, which can be used to identify the built environment conducive to residents’ low-carbon travel. We chose the four elements of traffic survey—travel mode, travel time, travel purpose and travel frequency—as the framework to evaluate travel carbon emissions. Using the index data collected from “WeChat,” a popular social-media platform in China and questionnaire surveys, we conducted hotspot analysis of the spatial distribution of travel carbon emissions in GIS. We obtained a comprehensive carbon emissions and its spatial distribution through the superposition of hotspot density surface of different indexes. The results show that E block within the research area has the lowest travel carbon emissions. These results suggest some planning implications from three aspects—land use mode, road network and public service facilities: In the old urban district of Pucheng, the ratio of residential building area and other types’ building area should be “4:1–3:1”; and we should develop the travel model of bicycle, and the interval of bicycle lanes should be 350–450 m; The ratio of walking road to total road area should be 15–20%, and the width of road should be restricted. Coverage of transit site buffered for the radius of 150 m is 40–50%, coverage of shopping services buffered for the radius of 50 m is 45–60%, and coverage of recreational facilities buffered for the radius of 100 m is 50–70%. The results confirm that “functional mixing” and “dense road network” are beneficial to residents’ low-carbon travel proposed by the predecessors. At the same time, we found that not the higher volume rate is, the more favorable for low-carbon travel. Small cities have limited number of population and scattered distribution of professional posts, which are not suitable for the traditional mode of improving the volume ratio and the bus system. It is not that the higher the bus station coverage is, the better for residents to travel as low-carbon, and the high popularity of public transportation in small cities will increase the carbon emission of residents. The study provides a new way to evaluate the carbon emission assessment of blocks and provides a basis for block planning with low-carbon concept.

The study of exploring the internal connection between rail transit and land use is of great significance for the coordinated development of urban space and rail transit construction, and it is also important for the intensive use of land affected by rail transit stations. The land use structure and population density surrounding the stations of Line 1.2.3 of Xi’an Rail Transit were clustered by SPSS for identifying the rail transit stations with high population density. Subsequently, We have established an indicator system of urban land use and rail transit operation capabilities based on multivariate data, and explored the coordinated relationship between rail transit and land use through data envelopment analysis (DEA) evaluation methods at high population density stations. Besides, the coupling degree of land use in rail transit stations with high population density was evaluated, and the key indicators affecting the coupling degree were further analyzed in Xi’an. In conclusion, this study finds that the relationship between rail transit capacity and land use of high population density rail transit stations is unbalanced. Hence, to promote the sustainable development of rail transit capacity and surrounding land, it is suggested that we should confine the development of land use intensity around the station, improve the service functions of small-scale living areas, and optimize the travel environment intended for short-distance travel. For residents, they are encouraged to choose the mode of rail transit for their long-distance travel. At the same time, the peak passenger flow at the stations should be evacuated accordingly.

To further study the effects of public service facilities on the land use intensity at regulatory planning level and enhance the scientific determination of land use intensity, this paper expounds the influence mechanism and factors of the public service facilities on land use intensity in regulatory planning, and conducts quantitative evaluation of the influence factors through theoretical analysis, mathematical analysis and analytic hierarchy process etc. The results show that the influence mechanism of public service facilities on the land use intensity goes throughout all three levels of regulatory planning. Different characteristics of public service facilities on each level determine their different influence factors and take effect on the land use intensity index of the corresponding level, thus affecting the determination of the block floor area ratio. Based on this, this paper proposes a method to determine the land use intensity in regulatory planning under the restriction of public service facilities and completes the test in practice, which may provide a reference for determining the land use intensity in regulatory planning.

The regulatory detailed planning is substantive legal planning stage of urban planning in China. The first problem is the need to check and inheritance the indicators of total planning land about construction in the process of compiling. According to city zoning rules establishment work reality, the basic thought of the system analysis, the traffic engineering and urban planning in the related theory and method on the basis of macroscopic traffic flow classification, using the road network capacity calculation method and traffic distribution forecasting method proposed with interregional channel planning level of service and the internal road network planning level of service as the control target, proposes the method by using the master planning road network control to inversely calculate the total amount for the construction of district land use. The calculation example is also given. Studies show that the presented control rules compiled for checking algorithm can play check function about the amount of land used for construction master planning achieve under the premise of the control overall situation trunk road network level of service, to avoid the amount of unnecessary in the subsequent units, neighbourhood planning adjustments.

To further study the effects of public service facilities on the land use intensity at regulatory planning level and enhance the scientific determination of land use intensity, this paper expounds the influence mechanism and factors of the public service facilities on land use intensity in regulatory planning, and conducts quantitative evaluation of the influence factors through theoretical analysis, mathematical analysis and analytic hierarchy process etc. The results show that the in- fluence mechanism of public service facilities on the land use intensity goes throughout all three levels of regulatory plan- ning. Different characteristics of public service facilities on each level determine their different influence factors and take effect on the land use intensity index of the corresponding level, thus affecting the determination of the block floor area ratio. Based on this, this paper proposes a method to determine the land use intensity in regulatory planning under the re- striction of public service facilities and completes the test in practice, which may provide a reference for determining the land use intensity in regulatory planning.