Rapid Urban Land Expansion in Earthquake-Prone Areas of China

Abstract

A timely understanding of urban expansion in earthquake-prone areas is crucial for earthquake risk assessment and urban planning for earthquake mitigation. However, a comprehensive evaluation of urban expansion in earthquake-prone areas is lacking in China, especially in the context of rapid urbanization. Based on time series urban land data and seismic ground-motion parameter zonation maps, this study analyzed urban expansion in the most seismically hazardous areas (MSHAs) of China from 1992 to 2015 on the national, regional, and city scales. The results show that urban land area in the MSHAs expanded by 6767 km 2 from 1992 to 2015, with a gain of 350%. Specifically, the increase in urban land area of small cities in the MSHAs of western China during this period was the fastest, 6.24 times greater than that at the national level. In terms of spatial patterns, the urban land patches in the MSHAs in 2015 were more fragmented than those in 1992 on all scales. The percentage of change in the number of patches and the landscape shape index of the urban land patches of small cities in the MSHAs of western China were the highest across all cities. Therefore, we believe that special attention should be paid to the cities in the MSHAs that exhibit the most rapid increases in both urban land area and fragmentation, especially the small cities in western China. It is imperative to integrate earthquake mitigation into the urban planning of these cities. Keywords China Á Most seismically hazardous areas Á Seismic hazard exposure Á Urbanization Á Urban expansion Á Urban sustainability

Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

“…5d and 6d). Our results also reveal a more rapid growth trend of built-up land in the hazard areas for earthquakes in China (Table 2), which is in line with the findings of a recent study (Huang et al 2019). From the perspective of cropland, the cold spots of exposure to droughts emerged in the YERB and HURB (Figs.…”

“…Sun et al (2017) provided projections of future changes in population exposure to droughts for the Haihe River Basin, with a decrease of 30% and an increase of 75% in the 1.5°C and 2.0°C global warming scenarios, respectively. China is also facing great risks of earthquakes (He et al 2016;Huang et al 2019). Wu et al (2017) concluded that roughly 15% of China's asset values and 14% of GDP were in areas prone to earthquakes.…”

RETRACTED ARTICLE: Monitoring soil salinization in Manas River Basin, Northwestern China based on multi-spectral index group

“…Studies have shown that reflectance value of Landsat data has great potential for resource environment investigation and mapping. By Landsat remote sensing image, it is possible to estimate regional land use and cover (Gao et al, 2019;Q. Huang et al, 2019a;, water resource distribution (Du et al, 2019;Xiao & Ouyang, 2019;Yan & Guo, 2019), soil salinity pattern evolution (Essahlaoui et al, 2019), avalanche hazards (Singh et al, 2019), surface temperature (Dhar et al, 2019), crop yield (Filippi et al, 2019), soil nutrients (Darwish & Fadel, 2017), etc.…”

Study on the location factors of urban expansion in the drylands: A case study in the Hohhot-Baotou-Ordos-Yulin Urban Agglomeration, China

“…36 卷 自 然 资 源 学 报 法分析了印度孟买 1973-2010 年城市扩展的区位因素。Wu 等 [17] 通过 Logistic 回归方法探 索区位因素对京津冀城市群 1980-2010 年城市扩展的影响。可以看出，现有研究主要通 过 Logistic 回归方法定量分析旱区城市扩展过程的区位因素特征。然而由于 Logistic 回归 方法不能很好拟合非线性问题并且结果会受到多元共线性的影响，从而导致对旱区城市 扩展过程区位因素特征的认识不够准确。 随机森林是一种机器学习算法，它能够很好地拟合非线性关系，而且拟合结果不会 受到多元共线性的影响，同时可以评估特征因素的重要性 [18] 。当前，随机森林已被应用 于城市土地利用变化区位因素研究。如 Kamusoko 等 [19] 利用随机森林分析了影响津巴布韦 Harare 地区城市土地扩展的主要区位因素。Zhang 等 [20] 海拔约 1300 m。气候类型为温带大 陆性季风气候，多年平均气温约为 8 ℃，多年平均降水量约为 320 mm [21] 。 根据 2017 年的人口数据，参考 Huang 等 [22] 6635.86 亿元和 6600.76 亿元，年均增长率分别为 14.18%和 29.36% [23][24][25] 。该地区非农人口 从 1990 年的 239.87 万人增加到 2010 年的 462.13 万人，增长了 92.66% [26] 。城市土地面积从 1990 年的 151.29 km²增加到了 2017 年的 1230.86 km²，增长了 8.14 倍 [27] 。途经研究区的高 速公路主要有北京-拉萨高速公路、荣成-乌海高速公路和包头-茂名高速公路，国道 主要包括 109 和 110 国道，铁路主要有包头-兰州、包头-西安和北京-包头等铁路线， 还包括呼和浩特-包头高铁和呼和浩特-鄂尔多斯动车等。未来，区域将建设呼和浩特 -准格尔-鄂尔多斯、准格尔-朔州、蒙西-华中和神木-瓦塘等铁路，建设保德-榆 林、呼和浩特-朔州、赛罕塔拉-二连浩特等高速公路 [23]…”