Water quality is highly dependent on the landscape characteristics. In this study, we investigated the relationships between water quality and landscape pattern (composition and configuration) in Huzhou City, China. The water quality variables, including pH, dissolved oxygen (DO), chemical oxygen demand (COD_Mn), Biochemical Oxygen Demand (BOD), NH₃-N, petroleum, dissolved total phosphorus (DTP), and total nitrogen (TN) in low water, normal water and flood periods were identified by investigating 34 sampling sites in Huzhou City during the period from 2001 to 2007. Landscape composition and landscape configuration metrics were calculated for different scales. It was found that scales and seasons both play important role when analyzing the relationships between landscape characteristics of different land use types. The results implied that some water quality parameters such as COD_Mn, petroleum are more polluted in flood period than the other two seasons at different scales, while DTP and TN are more polluted in low water period. Influences of different landscape metrics on water quality should operate at different spatial scales. The results shown in this paper will effectively provide scientific basis for the policy making in sustainable development of water environment.

Ecosystem health assessment is an important method for obtaining information on ecosystem conditions, and it plays a vital role in preserving and enhancing ecosystem health status. In addition, it provides useful information and knowledge for urban agglomeration development decision makers. However, ecological phenomena often vary considerably from one observation to the next, which makes it difficult to distinguish different status of the ecosystem health. In this study, hidden Markov model (HMM) was employed to simulate the internal-external correlations of ecosystem status through establishing the relationships between internal ecological health level and combination state of external observation. Based on the statistics and land use data in 2001, 2007 and 2013, the Vigor-Organization-Resilience (VOR) framework was employed to identify the ecosystem health in Shanghai-Hangzhou Bay Metropolitan (SHBM), in which the ecosystem health state was considered as a hidden state that could be estimated according to the conditions of vigor, organization and resilience. In addition, two parameter learning cases including mathematical statistics and extensible sequence method were employed to solve the iterative convergence problem of parameters in short-time series of ecosystem health simulation. Results show that HMM not only provides a comparable descriptive ability to that of the VOR model, but also can monitor ecosystem health at the optimal grid scale in SHBM. The combination of HMM and VOR greatly expands the spatiotemporal characteristics and provides a new research approach for the study of ecosystem health assessment of urban agglomerations.

Urban sustainability is a crucial part of the United Nations (UN) Sustainable Development Goals (SDGs) and one of the core objectives of China’s national strategy to promote new urbanization and achieve integration in the Yangtze River Delta (YRD). This paper mainly focused on the 11th SDG, which is a universal call to make cities and human settlements inclusive, safe, resilient and sustainable. The full permutation polygon synthetic indicator (FPPSI) method was applied to synthetically evaluate the sustainable level of 26 cities in the YRD urban agglomeration from 2007 to 2016. The results showed that: (1) the synthesis indicators were increasing year by year, which implied that the sustainable development of the YRD has shown obvious progress in recent years. However, each city faced its own challenges to achieving the sustainable development goals. The sustainability level for the majority of cities was restricted by obstacles such as the per capita green area, air quality and commercial housing sales area; (2) Among the 26 cities, small and medium-sized cities were subject to the traditional strong sustainability indicators while large and mega cities were more affected by weak sustainability indicators; (3) Spatial differences were found for the overall sustainable development level of the YRD. The diffusion and assembly effect among cities had not yet been formed; however, the strong spillover effect of developed cities might influence the ability of other cities to achieve sustainable development goals in many aspects of the environment, economy and society. The results suggest the need for a stronger focus on improving regional developing patterns and strengthening coordination in the process of achieving the sustainable development goal of urban agglomeration in the YRD. Furthermore, according to the conditions of different cities, integrated policies are required to address all aspects of sustainability and to avoid unintended consequences.

Taxis have always been an important part of the urban transportation system in metropolises since they can meet many demands and greatly improve travel efficiency. This article explores the distributions of hot spot destinations of taxi, land surface temperature data, and visible infrared imaging radiometer (VIIRS) nighttime light data in Beijing, Shanghai, and Wuhan. This article further selects point of interests (POIs) that are very close to taxi ridership patterns. This article finally uses a geographically weighted regression model to examine the relationship between population flow by taxi and urban vitality, which is represented by land surface temperature, nighttime light data, and influential POIs. The results suggest that urban structure has an impact on the distribution of drop-off points and nighttime light. The implementation of the relevant policies is revealed to have a certain influence on the alleviation of the urban thermal environment. Traffic stations and financial facilities contribute to an increase in travel, and their influences vary spatially. Similarly, the relationships between the drop-off points and LST and NTL vary spatially. This article aids in understanding population flow and urban vitality development. In addition, this article provides valuable results for policy-makers to promote urban vitality development.

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley’s K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning.