Assessment of Ecosystem Health and Its Key Determinants in the Middle Reaches of the Yangtze River Urban Agglomeration, China

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha–Zhuzhou–Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

INTEGRATION OF BIM AND MOBILE AUGMENTED REALITY IN THE AECO DOMAIN

BIM (Building Information Modeling) is increasingly present in a wide range of applications (architecture, engineering, construction, land use planning, utility management, etc.). BIM allows better management of projects through precise planning, communication and collaboration between several stakeholders as well as facilitating the monitoring of project operations. The emergence of Augmented Reality (AR) technology allows the superposition of (2D, 3D) information directly on the physical world, so generating immersive, interactive and enriching experiences for the user. To take advantages of BIM and AR potential in the interaction and the intuitive management in AECO (Architecture, Engineering, Construction and Operation) projects, we propose a BIM-based AR workflow through an application called "EasyBIM". This latter allows access and interaction with a BIM model through functionalities for measurement, data consultation, collaboration, visualization and integration of information from sensors. The application is developed for mobile platforms (tablet, smartphone), and has as input an IFC file (Industry Foundation Classes). Promising test results show that the developed solution can be easily integrated into a BIM context for several use cases: marketing, collaboration, site monitoring, facility management, etc.

Comparison of Different Spatial Regression Methods for Predicting Organic Matter Content in Soil

Dynamic changes in soil organic matter content affects the sustainable supply of soil water and fertilizer and impacts the stability of soil ecological function. Understanding the spatial distribution characteristics of soil organic matter will help deepen our understanding of the differences in soil organic matter content, soil formation law; such understanding would be useful for rational land use planning. Taking terrain data, meteorological data, and remote sensing data as auxiliary variables and the ordinary Kriging (OK) method as a control, this study compares the spatial prediction accuracies and mapping effects of various models (MLR, RK, GWR, GWRK, MGWR, and MGWRK) on soil organic matter. Our results show that the spatial distribution trend of soil organic matter predicted by each model is similar, but the prediction of composite models can reflect more mapping details than that of unitary models. The OK method can provide better support for spatial prediction when the sampling points are dense; however, the local models are superior in dealing with spatial non-stationarity. Notably, the MGWR model is superior to the GWR model, but the MGWRK model is inferior to the GWRK model. As a new method, the prediction accuracy of MGWRK reached 47.72% for the OK and RK methods and 40.08% for the GWRK method. The GWRK method achieved a better prediction accuracy. The influence mechanism of soil organic matter is complex, but the MGWR model more clearly reveals the complex nonlinear relationship between soil organic matter content and factors influencing it. This research can provide reference methods and mapping technical support to improve the spatial prediction accuracy of soil organic matter.

Flood Assessment and Identification of Emergency Evacuation Routes in Seti River Basin, Nepal

Sudden floods frequently occur in the Himalayas under changing climates. Rapid glacial melt has resulted in the formation of glacial lakes and associated hazards. This research aimed to (1) identify flood-prone houses, (2) determine pedestrian emergency evacuation routes, and (3) analyze their relationships to socioeconomic status in the Seti River Basin. Detailed hazard maps were created using field survey results from unmanned aerial vehicle photogrammetry and the Hydrologic Engineering Center River Analysis System. Questionnaire, focus-group, and key-informant surveys helped identify the socioeconomic situation. Inundation maps revealed that most residents are exposed to future flooding hazards without proper evacuation routes. Highly impoverished and immigrant households were at the highest risk in terms of income inequality and migration rate (p < 0.001) and were located on the riverside. The locations of 455 laborers’ houses were significantly correlated with inundation hazards (p < 0.001). Governmental and associated agencies must develop adequate plans to relocate low-income households. Group discussions revealed the need for stronger adaptive capacity-building strategies for future risk management. Pokhara requires better systematic and scientific land-use planning strategies to address this issue efficiently. A similar approach that combines flood modeling, proper evacuation route access, and socioeconomic survey is suggested for this river basin.

Nature-Based Solutions in Poland against Climate Change

One of the currently promoted methods of counteracting climate change is nature-based climate solutions, which harness the power of nature to reduce greenhouse gas emissions. Sustainable management of ecosystems is a guarantee for sustained human well-being. This underestimated, but extremely efficient and cheap method of integrating nature resources into the urban fabric is an economic “injection” for communal authorities. These “green” benefits should be standard in land-use planning in the era of anthropocentrism. Solutions based on nature were the reason for investigating their perception by Polish municipalities. The survey covered the entire country (all 2477 municipalities) from 20 July to 31 August 2021 through an electronic survey, obtaining 2128 responses (85.9% return rate). In the final result, data were obtained that support the hypotheses posed in the study. The main objective of the research was to check the level of activity of municipalities in Poland in the field of proecological activities using nature-based solutions (NbS). The survey results confirmed little knowledge of nature-based solutions, at the same time giving it an educational dimension. Half of the respondents declared that they learned about NbS only from the survey. Polish decision makers and municipal authorities introduce some solutions based on nature without being aware of their European classification and adequate nomenclature. Environmental awareness in Poland remains largely the domain of urban municipalities, with higher current budget revenues per capita and in the central and western parts of the country. NbS are marginal in rural municipalities, which can be explained by the lack of ecological specialists, less car traffic and more single-family houses and thus modest public areas. The following surveys covering the entire territory of Poland are the first to be carried out on such a large scale.

A Decision-Making Tool for Urban Planners: A Framework to Model the Interdependency among Land Use, Accessibility, Density, and Surface Runoff in Urban Areas

The purpose of this study was to evaluate the four-dimensional relationship between land use, accessibility, density, and surface runoff in urban areas. In contemporary literature, a series of studies have been conducted that extensively discuss the natural components associated with the surface runoff in urban areas. However, the dynamic and complex dimensions of the urban form, such as land use, accessibility, and density, are yet to be fully understood. In this study, a 4D diagram was utilized to identify relationships between dimensions, in addition to decision tree analysis, to explore the structural flow between selected variables. Furthermore, a structural equation modeling (SEM) approach was employed with the purpose of investigating the direct, indirect, and moderating effects on the targeted dependent variable, surface runoff. The results of the analysis reported a strong correlation between land use, accessibility, density, and surface runoff, with an R-squared value of 0.802, which indicates an acceptable model accuracy by the international standard. A positive relationship between the four dimensions was indicated by the higher accessibility; the higher density in terms of a higher floor space index (FSI), ground space index (GSI), and open space; the building height of the adjacent buildings; the higher diversity of the land use; and the higher surface runoff. Accordingly, the findings of the study offer policy implications in the fields of land use planning, zoning regulations and overall urban development planning towards achieving climate resilient cities.