Construction of an ecological security pattern based on ecosystem sensitivity and the importance of ecological services: A case study of the Guanzhong Plain urban agglomeration, China

Urban residents are gradually being exposed to increasing urban high temperatures and extreme heatwave events under rapid urbanization and global warming. Although there is an increase in air and surface temperatures observed, spatiotemporal changes in urban human thermal comfort and their drivers are rarely considered when assessing the urban thermal environment, especially at a national scale in China. Based on weather stations, we combined daily meteorological data, including air temperature, solar radiation, wind speed, and humidity, to comprehensively assess the annual dynamics of urban thermal comfort and their relationship with rapid urbanization and climate change in 183 Chinese cities from 1990 to 2016. Our results show that urban air temperature and solar radiation have increased, and urban humidity and wind speed have decreased at the national scale. Following these changes, urban residents' thermal comfort is deteriorating, with physiological equivalent temperature and uncomfortable days increasing in 68% and 59% of cities, respectively, during summer in China, predominantly located in temperate monsoon and continental climatic zones. The worsening of urban thermal comfort was largely explained by climate change, and rapid urbanization contributed 10.9% in our study. Climate change (e.g., global warming, precipitation, and wind speed decrease) and rapid urbanization had positive effects (P < 0.05) on the deteriorative urban thermal environment. Our findings could enrich the knowledge on spatiotemporal changes in the urban thermal environment under climate change and rapid urbanization. 

Rapid urbanization and climate change significantly contribute to worsening urban human thermal comfort: A national 183-city, 26-year study in China

The impact of the rapid expansion of urban land on the urban thermal environment and carbon chain has attracted widespread attention. This paper uses artificial neural network-cellular automata (ANN-CA) and long short-term memory model of the improved whale optimization algorithm (IWOA-LSTM) models to predict the changes of LULC and LST, and explores the correlation between LST and carbon emissions in Wuhan.The results show that urban land will occupy >70.05% of the central urban area, while green land and water areas will continue to decrease to varying degrees in 2030 and 2040. The area of the high temperature area (LST > 30 °C) is expanding in the urban land, while the green land and the low temperature area of the water body are gradually shrinking. The area of high temperature is expanding, and the area with LST > 30 °C accounts for 67.84% in summer, and the area with LST at 10 °C ∼ 15 °C accounts for 96.32% in winter. The fitting results of correlation regression show that there is a significant correlation between carbon emissions and LST. The R2 of linear fitting between LST and carbon emissions in summer and winter of 2000 are 0.6227 and 0.6143, respectively. The R2 of linear fitting in summer and winter is higher, both of which are >0.85 in 2010 and 2020. This research may provide new clues for future urban development and thermal environment governance and carbon emission mitigation. 

Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China

The impacts of landscape patterns spatio-temporal changes on land surface temperature from a multi-scale perspective: A case study of the Yangtze River Delta.

In our current global warming climate, the growth of record-breaking heat waves (HWs) is expected to increase in its frequency and intensity. Consequently, the considerably growing and agglomerated world’s urban population becomes more exposed to serious heat-related health risks. In this context, the study of Surface Urban Heat Island (SUHI) intensity during HWs is of substantial importance due to the potential vulnerability urbanized areas might have to HWs in comparison to their surrounding rural areas. This article discusses Land Surface Temperatures (LST) reached during the extreme HW over Western North America during the boreal summer of 2021 using Thermal InfraRed (TIR) imagery acquired from TIR Sensor (TIRS) (30 m spatial resolution) onboard Landsat-8 platform and Moderate Resolution Imaging Spectroradiometer (MODIS) (1 km spatial resolution) onboard Terra/Aqua platforms. We provide an early assessment of maximum LSTs reached over the affected areas, as well as impacts in terms of SUHI over the main cities and towns. MODIS series of LST from 2000 to 2021 over urbanized areas presented the highest recorded LST values in late June 2021, with maximum values around 50 °C for some cities. High spatial resolution LSTs (Landsat-8) were used to map SUHI intensity as well as to assess the impact of SUHI on thermal comfort conditions at intraurban space by means of a thermal environmental quality indicator, the Urban Field Thermal Variance Index (UFTVI). The same high resolution LSTs were used to verify the existence of clusters and employ a Local Indicator of Spatial Association (LISA) to quantify its degree of strength. We identified the spatial distribution of heat patterns within the intraurban space as well as described its behavior across the thermal landscape by fitting a polynomial regression model. We also qualitatively analyze the relationship between both UFTVI and LST clusters with different land cover types. Findings indicate that average daytime SUHI intensity for the studied cities was typically within 1 to 5 °C, with some exceptional values surpassing 7 °C and 9 °C. During night, the SUHI intensity was reduced to variations within 1–3 °C, with a maximum value of +4 °C. The extreme LSTs recorded indicate no significant influence of HW on SUHI intensity. SUHI intensity maps of the intraurban space evidence hotspots of much higher values located at densely built-up areas, while urban green spaces and dense vegetation show lower values. In the same manner, UTFVI has shown “no” SUHI for densely vegetated regions, water bodies, and low-dense built-up areas with intertwined dense vegetation, while the “strongest” SUHI was observed for non-vegetated dense built-up areas with low albedo material such as concrete and pavement. LST was evidenced as a good marker for assessing the influence of HWs on SUHI and recognizing potential thermal environmental consequences of SUHI intensity. This finding highlights that remote-sensing based LST is particularly suitable as an indicator in the analysis of SUHI intensity patterns during HWs at different spatial resolutions. LST used as an indicator for analyzing and detecting extreme temperature events and its consequences seems to be a promising means for rapid and accurate monitoring and mapping.

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The Extreme Heat Wave over Western North America in 2021: An Assessment by Means of Land Surface Temperature

Effect of urban growth pattern on land surface temperature in China: A multi-scale landscape analysis of 338 cities

With rapid urbanization destroying the ecological environment, scholars have focused on ways to coordinate harmonious development using urban spatial layouts and landscape ecological security. To explore landscape ecological security (the landscape elements, spatial positions and connections that are of key significance to the health and safety of ecological processes) from the perspective of urban form evolution pattern will help to open a new perspective of urban management research, and become the basic work of urban space policy and the implementation of the beautiful China strategy. Based on urban growth and land use data from 356 cities in China, this study applied a geographically weighted regression (GWR) model to quantify the impact of China’s urban growth pattern on landscape ecological security at the spatial level. The research results show that: (1) To some extent, the infilling growth pattern has a certain effect on the enhancement of regional landscape ecological security; (2) In the three control variables (DEM, Population density and GDP), the following conclusions are drawn: regional landscape planning should reasonably allocate landscape resources according to the local topographic features to obtain a higher landscape ecological security; The increase of population density leads to the fragmentation and diversity of the landscape in some regions, which makes the landscape ecological security weak; more economically developed areas have stronger landscape ecological security. This paper highlights the importance of urban growth patterns to landscape ecological security. In addition, considering the different urban evolution trajectories in developed and developing countries, this study proposes targeted development recommendations, providing a reference for urban managers to formulate reasonable development policies and to realize sustainable development with the goal of landscape safety management and control.

Yingxue Rao

Papers

Effect of urban growth pattern on land surface temperature in China: A multi-scale landscape analysis of 338 cities

Effect of Compactness of Urban Growth on Regional Landscape Ecological Security