The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characte...The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong–Hong Kong–Macao Greater Bay Area(GBA) is inadequate. Combined with data(e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity(SUHII) in the GBA. The SUHII was calculated based on the urban–rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum(minimum) SUHII was found in summer(winter);similarly, the largest(smallest) diurnal difference in SUHII was during summer(winter). Generally, the Mann–Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban–rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI.展开更多
In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate ...In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.展开更多
基金National Natural Science Foundation of China,No.42071123,No.42201104。
文摘The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong–Hong Kong–Macao Greater Bay Area(GBA) is inadequate. Combined with data(e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity(SUHII) in the GBA. The SUHII was calculated based on the urban–rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum(minimum) SUHII was found in summer(winter);similarly, the largest(smallest) diurnal difference in SUHII was during summer(winter). Generally, the Mann–Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban–rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI.
基金National Natural Science Foundation of China,No.41130748 No.41171070+2 种基金 China Postdoctoral Science Foundation,No.200902132 No.20080440511 The Humanities and Social Sciences Project of Ministry of Education,PRC,No.10YJCZH031
文摘In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.
