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In this paper, we focus on Guangdong province, which is a frontier area of Reform and Opening up, and analyze the variation of urban and rural temperature to detect the urbanization warming effect from 1951 to 2018, based on the daily temperature data of 85 weather stations. We classified the metrological stations into urban and rural stations according to the urbanization population size, population density and urban built-up area data. The combined methodology of mathematical statistics, trend analysis, urban/rural station comparison and spatial analysis was adopted to reveal the urbanization warming and its spatial–temporal heterogeneity. The results show that the warming process in Guangdong Province is very complex and has high temporal and spatial heterogeneity. From 1951 to 2018, the average temperature in the coldest month in Guangdong Province increased with the fastest (0.27 °C/10a) rate, and the annual average temperature increased slightly faster than the average temperature in the warmest month (0.15 °C/10a vs. 0.12 °C/10a). The comparative study on the temperature of urban and rural stations shows that the temperature increase rate of urban stations is faster than that of rural stations (0.30 °C/10a vs. 0.23 °C/10a), especially the average temperature in the coldest month, which is most significantly driven by urbanization, and the contribution rate of urbanization is about 24.09% in general. Affected by the background climate and the stages of urbanization, the warming effect of urbanization fluctuates obviously in different periods. Stronger urbanization effect can be witnessed during 1980–2000, when the urbanization developed into mid-level with highest rate. The spatial differentiation of urbanization warming effect is prominent. The temperature of urban stations in Eastern Guangdong increases most rapidly. The urbanization contribution rates to the coldest month average, annual average and the warmest month average temperature reach 33.86%, 25.70% and 17.64%, respectively, which are around 1.69, 1.50 and 1.19 times that of the Pearl River Delta. The average temperature of the warmest month in Western Guangdong shows a weak cooling effect. Multi-faceted, multi-level regulation of sustainable urbanization is the key to mitigating the warming caused by urbanization. [ABSTRACT FROM AUTHOR]

China has high biodiversity and is rapidly urbanizing. However, there is limited understanding of how urban expansion in the country is likely to affect its habitats and biodiversity. In this study, we examine urban expansion patterns and their likely impacts on biodiversity in China by 2030. Our analysis shows that most provinces are expected to experience urban expansion either near their protected areas or in biodiversity hotspots. In a few provinces such as Guangdong in the south, urban expansion is likely to impinge on both protected areas and biodiversity hotspots. We show that policies that could facilitate the integration of natural resource protection into urban planning exist on paper, but the prevailing incentives and institutional arrangements between the central and local governments prevent this kind of integration. Removing these obstacles will be necessary in order to safeguard the country's rich biodiversity in light of the scale of urbanization underway. [ABSTRACT FROM AUTHOR]

Shenzhen, located in South China has experienced rapid urbanization over the past three decades. This paper focuses on the urban sprawl integrating remote sensing and geographic information systems (GIS). The overlay of the urban area maps for two adjacent study years was used to generate the sprawl categories map. The three main sprawl categories of infilling sprawl, edge-expansion sprawl and outlying sprawl were calculated and analyzed in regard to their distribution and change throughout different counties during the study years. The result showed that the urban area in the study region had increased dramatically from 19.55 km in 1979 to 894.31 km in 2005. The urban area centroids over the six study years transferred from southwest to northeast from 1979 to 2005. Among the study counties, the patterns of sprawl categories were markedly distinctive over different study periods. From 1979 to 2005, Shenzhen's chief spread was outlying sprawl. Bao'an experienced the maximum sprawl within the three study counties. The findings show that studying urban sprawl can provide a method of monitoring urban area change, which, in turn, gives us a clearer perspective of urban sprawl patterns over a longer period of time. This would prove invaluable to those researchers such as land and urban planners. [ABSTRACT FROM AUTHOR]

Relative contributions of greenhouse gases (GHGs) concentration and land use/cover (LULC) change induced by urbanization on future temperature over the Guangdong-Hong Kong-Macao Greater Bay Area in China under different climate scenarios are investigated in this study. The Weather Research and Forecasting model is used to downscale the future mean and extreme temperature using the Representative Concentration Pathways (RCP) 4.5&8.5 simulations from the Community Earth System Model. Results show that GHGs concentration is the key dominate factor for future mean and extreme temperature over the Greater Bay Area in the next 10–30 years, LULC change (urbanization) has relative slight effect on the future regional temperature. On the urban local scale, the LULC change in urban area has an obvious warming effect on urban local temperature under future different GHGs concentration scenarios. The regional-averaged annual mean surface air temperature (SAT) of urban area will increase 0.51 °C (0.73 °C), 0.83 °C (1.17 °C) and 1.26 °C (1.74 °C) resulting from the combined contributions of urbanization and GHGs forcing for the year of 2030, 2040, and 2050 under RCP4.5(RCP8.5) scenario, respectively. The contributions of the GHGs forcing are 0.33 °C (0.53 °C), 0.66 °C (1.00 °C) and 1.12 °C (1.58 °C), the urbanization forcing are 0.18 °C (0.20 °C), 0.17 °C (0.17 °C) and 0.14 °C (0.16 °C). Same as regional-averaged annual mean SAT, for the extreme high- and low-temperature, the contribution of GHGs forcing is more important than that of the urbanization forcing. The extreme temperatures are more sensitively to GHGs concentration under RCP8.5 scenario than that under RCP4.5, especially for the extreme low-temperature. GHGs are the most important factor for dominating the future mean and extreme temperature of the Greater Bay Area. [ABSTRACT FROM AUTHOR]

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The green vegetation fraction (GVF) and surface albedo are important land surface parameters often used for validation of climate and land surface models that are influenced largely by environmental gradients and human activities. In this study, fine resolution GVF and albedo values derived from Landsat Thematic Mapper/Enhanced Thematic Mapper Plus images from 1990 to 2000 were used to examine the relationship of both GVF and albedo values to the spatial gradients of parameters related to dramatic urbanization in the Greater Guangzhou metropolitan area, Guangdong Province, in South China. Moderate resolution GVF and albedo datasets derived from the MODIS Collection 5 product were used to analyze the seasonal variation of GVF and albedo with rapid urban expansion from 2001 to 2007. The results show that the shortwave albedo had a clear declining trend from the urban center to natural land in 1990. However, no obvious trend in shortwave albedo change was observed along urban-rural gradients caused by the expansion of low-albedo urban buildings and more heterogeneous land cover patterns in 2000. A threshold of GVF (~0.21) was estimated for determining the change of albedo associated with vegetation fraction. Vegetation cover modified by urban expansion changed surface reflectance and influenced the surface energy balance. It is suggested that a large portion of energy absorbed in an urban area is likely to be converted to thermal energy that heating up is near the surface and emitted as longwave radiation. [ABSTRACT FROM AUTHOR]