Urban growth boundaries optimization under low-carbon development: Combining multi-objective programming and patch cellular automata models.

Urban Growth Boundaries (UGBs) are a tool to control urban sprawl. However, the way to optimize future urban land uses and fix their boundaries is not clear. This paper presents a new framework to delimit UGBs while accounting for ecological, economic, and carbon storage benefits. Aggregate land-use constraints are included in a multi-objective optimization algorithm to capture non-inferior solutions on the Pareto Surface (PS) under different objective scenarios. A patch-level cellular automata simulation model is then used to spatially allocate these land uses, followed by a new two-step adjustment method to delineate the UGBs. This modeling is applied to Wuhan, China. The results show that: (1) One district (Caidian) will have a strong economic growth under low-carbon development. (2) The maximization of carbon storage reduces losses in ecological benefits, suggesting that carbon storage be considered in urban growth planning. (3) The combined model framework and two-step boundary adjustment method can help urban planners define different UGB scenarios and make science-based policy decisions.

Impact of Driver's Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach.

The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fatality, with the alternative being a property damage only crash. In contrast to earlier research that has focused on young and old drivers, age is considered here on its lifetime continuum. A logit model is adopted and the gender and age of the at-fault drivers are part of the independent explanatory variables. The unit of analysis is the individual crash. Since age is a continuous variable, this analysis shows more precisely how age impacts accident severity and identifies when age has little effect. According to the results, the type of vehicle, timing of the crash, type of road and intersection, road condition, regional and locational factors, and socio-economic characteristic have a significant impact on crashes. Regarding the effect of age, when an accident occurs the probability of bodily injury or fatality is 0.703 for female drivers, and 0.718 for male drivers at 15 years of age. These probabilities decline very slightly to 0.696 and 0.711, respectively, around 33 years of age, then very slightly increase to 0.697 and 0.712, respectively, around 47.5 years of age. The results show that age affects crash severity following a polynomial curve. While the overall pattern is one of a downward trend with age, this trend is weak until the senior years. The policy implications of the results are discussed.

Does city-water layout matter? Comparing the cooling effects of water bodies across 34 Chinese megacities.

As most cities are located around or near waterbodies, it is essential to assess the thermal effect of these waterbodies. This research focuses on 34 Chinese megacities as case studies to examine the spatial relationship between city-water layout and the thermal effect of waterbodies. Landsat-8 remote-sensing images acquired around noontime in summer were used to retrieve land surface temperatures (LST) and classify land cover. The results show that there are three types of city-water layout. For most cities, waterbodies have a cooling effect, and their mean cooling distance (ΔLmax) ranges from 431 m to 1350 m, with the maximum temperature difference (ΔTmax) ranging from - 2.21 °C to 7.83 °C. The cooling effect of waterbodies is also influenced by their spatial distribution, size, location, and background climate regions. The larger the percentage or area of waterbodies in a city, the shorter ΔLmax and the bigger ΔTmax. Waterbodies have the longest ΔLmax and the smallest ΔTmax when they are dispersed within the city, whereas they have the shortest ΔLmax and the largest ΔTmax when they are flowing through the city. The results suggest that the thermal effects of waterbodies should be seriously considered by urban planners to improve the urban microclimate.

Simulation of Land-Use Spatiotemporal Changes under Ecological Quality Constraints: The Case of the Wuhan Urban Agglomeration Area, China, over 2020-2030.

Human activities coupled with land-use change pose a threat to the regional ecological environment. Therefore, it is essential to determine the future land-use structure and spatial layout for ecological protection and sustainable development. Land use simulations based on traditional scenarios do not fully consider ecological protection, leading to urban sprawl. Timely and dynamic monitoring of ecological status and change is vital to managing and protecting urban ecology and sustainable development. Remote sensing indices, including greenness, humidity, dryness, and heat, are calculated annually. This method compensates for data loss and difficulty in stitching remote sensing ecological indices over large-scale areas and long time-series. Herein, a framework is developed by integrating the four above-mentioned indices for a rapid, large-scale prediction of land use/cover that incorporates the protection of high ecological quality zone (HEQZ) land. The Google Earth Engine (GEE) platform is used to build a comprehensive HEQZ map of the Wuhan Urban Agglomeration Area (WUAA). Two scenarios are considered: Ecological protection (EP) based on HEQZ and natural growth (NG) without spatial ecological constraints. Land use/cover in the WUAA is predicted over 2020-2030, using the patch-generating land use simulation (PLUS) model. The results show that: (1) the HEQZ area covers 21,456 km2, accounting for 24% of the WUAA, and is mainly distributed in the Xianning, Huangshi, and Xiantao regions. Construction land has the highest growth rate (5.2%) under the NG scenario. The cropland area decreases by 3.2%, followed by woodlands (0.62%). (2) By delineating the HEQZ, woodlands, rivers, lakes, and wetlands are well protected; construction land displays a downward trend based on the EP scenario with the HEQZ, and the simulated construction land in 2030 is located outside the HEQZ. (3) Image processing based on GEE cloud computing can ameliorate the difficulties of remote sensing data (i.e., missing data, cloudiness, chromatic aberration, and time inconsistency). The results of this study can provide essential scientific guidance for territorial spatial planning under the premise of ecological security.

Greenspace configuration impact on the urban heat island in the Olympic Area of Beijing.

As urban green spaces have significant cooling effects on the urban heat island (UHI), a precise understanding of these effects is necessary to devise precise greenspace strategies for abating the UHI. This paper explores the impacts of different greenspace (trees, grass, and water) patterns on the UHI in Beijing's Olympic Area, using different grid cell sizes and spatial statistical models. Greenspace pattern metrics include percent cover, mean patch size (MPS), mean patch shape index (MSI), edge density (ED), and largest percent index (LPI). The results show that different greenspace metrics have varying effects on surface temperature. The spatial error model (SEM) turns out to be a good choice for estimating the relationship between Land Surface Temperature (LST) and the greenspace metrics. The regression coefficients of these metrics vary with grid cell size. Tree and grass edge densities have opposite effects, which suggest that trees should be planted in smaller clusters, whereas grass should be planted in larger and continuous patches in order to reach maximum LST cooling. The optimal grid cell size is in the [120-240 m] range. These findings can help urban planners mitigate the UHI in a city with limited green space availability.

Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach.

Understanding how complex urban factors affect the Urban Heat Island (UHI) is crucial for assessing the impacts of urban planning and environmental management on the thermal environment. This paper investigates the relationships between two-dimensional (2D) and three-dimensional (3D) factors and land surface temperatures (LST) within the Olympic Area of Beijing in different seasons, using the boosted regression tree (BRT) model. The BRT model captures the specific contributions of each urban factor to LST in each season and across a continuum of magnitudes for this factor. The results show that these relationships are complex and highly nonlinear. The four most common dominant factors are the Normalized Difference Built-up Index (NDBI), the Normalized Difference Vegetation Index (NDVI), a gravity index for parks (GPI), and average building height (BH). The most important factor in spring is NDBI, with a 45.5% contribution rate. In the other seasons, NDVI is the dominant factor, with contributions of 40% in summer, 21% in autumn, and 19% in winter. NDVI has an overall negative impact on LST in spring and summer, with a quadratic nonlinear decreasing curve, but a positive one in autumn and winter. The 2D land-use variables are most strongly related to LST in summer and spring, but 3D building-related variables have stronger impacts in colder weather. The Sky View Factor (SVF), a 3D measure of urban morphology, has also strong impacts in summer and winter. Both a building-based and a DSM-based SVFs are computed. The latter accounts for buildings, bridges, and trees. In contrast to a building-based SVF, the DSM-based SVF reduces LST when it varies between 0 and 0.75, reflecting the effects of high-density tree canopies that increase shades and evapotranspiration while blocking sky view. The marginal effect curves produced by the BRT are often characterized by thresholds. For instance, the maximal NDVI effect in summer takes place when NDVI = 0.7, suggesting that a very intense green coverage is not necessary to achieve maximal thermal results. Implications for urban planning and environmental management are outlined, including the increased use of evergreen trees that provide thermal benefits in both summer and winter.

Spatial regression models of park and land-use impacts on the urban heat island in central Beijing.

Understanding the relationship between urban land structure and land surface temperatures (LST) is important for mitigating the urban heat island (UHI). This paper explores this relationship within central Beijing, an area located within the 2nd Ring Road. The urban variables include the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Build-up Index (NDBI), the area of building footprints, the area of main roads, the area of water bodies and a gravity index for parks that account for both park size and distance. The data are captured over 8 grids of square cells (30 m, 60 m, 90 m, 120 m, 150 m, 180 m, 210 m, 240 m). The research involves: (1) estimating land surface temperatures using Landsat 8 satellite imagery, (2) building the database of urban variables, and (3) conducting regression analyses. The results show that (1) all the variables impact surface temperatures, (2) spatial regressions are necessary to capture neighboring effects, and (3) higher-order polynomial functions are more suitable for capturing the effects of NDVI and NDBI.

Costs of abandoned coal mine reclamation and associated recreation benefits in Ohio.

Two hundred years of coal mining in Ohio have degraded land and water resources, imposing social costs on its citizens. An interdisciplinary approach employing hydrology, geographic information systems, and a recreation visitation function model, is used to estimate the damages from upstream coal mining to lakes in Ohio. The estimated recreational damages to five of the coal-mining-impacted lakes, using dissolved sulfate as coal-mining-impact indicator, amount to $21 Million per year. Post-reclamation recreational benefits from reducing sulfate concentrations by 6.5% and 15% in the five impacted lakes were estimated to range from $1.89 to $4.92 Million per year, with a net present value ranging from $14.56 Million to $37.79 Million. A benefit costs analysis (BCA) of recreational benefits and coal mine reclamation costs provides some evidence for potential Pareto improvement by investing limited resources in reclamation projects.