Increased coverage of impervious surfaces is an important measure of urban sprawl, and understanding spatiotemporal dynamics of impervious surfaces is vital for regional and local development. Combining vegetation-impervious-surfaces oil model and linear spectral unmixing model, this paper used the Landsat TM and OLI remote sensing data from 2009 to 2019 to study the temporal and spatial variation characteristics of the impervious surfaces of Zhengzhou, and discussed the main driving factors leading to urban expansion. We found that impervious surface growth in the main urban area of Zhengzhou City was obvious, and the area of impervious surfaces increased from 337.52 km2 in 2009 to 464.93 km2 in 2019, with an average expansion speed of 12.69 km2 /year. The impervious surfaces pattern of the research area changed significantly, and the expansion of impervious surface showed a flaky development in all directions. From 2009 to 2014, Zhengzhou’s expansion was mainly concentrated in Hi-Tech Industrial Development Zone, Zhongyuan District, as well as Economic and Technological Development Zone. Most of the expansion between 2014 and 2019 was concentrated in Zhengdong New District and Huiji District. Physical geography, urban population, GDP and national policies were the main drivers affecting the expansion of impervious surfaces.
Zhengzhou City suffered the strongest rainstorm in history in July 2021, floods and other secondary disasters have greatly endangered the property and safety of local residents in Henan Province, China. In this paper, the flood risk of Henan Province was analyzed from the three perspectives of hazard, exposure and vulnerability, and seven factors of rainfall, elevation, slope, distribution density of river network, population, GDP and arable land occupation ratio were selected to create a flood disaster risk evaluation index system. Remotely sensed data and GIS were used to analyze and map the influencing factors, and then the comprehensive risk results of flood disasters in Henan Province were obtained based on analytic hierarchy process (AHP) method. Results show that the higher-risk area and high-risk area mainly locate in cities of Xinyang, Luohe, Zhumadian, Zhoukou and Xuchang, as well as the north of Zhengzhou, accounting for 43% of the total area of Henan Province. High risk area is mainly caused by high hazard of the flat terrain and abundant rainfall. The lower-risk area is mainly distributed in Sanmenxia, Jiyuan and Anyang, and the western part of Luoyang, that locate in high-elevation areas, and the vulnerability index of GDP is low in these areas. The rest of the areas are medium-risk areas. This research provides the background information for disaster prevention and mitigation management in Henan Province.
The ecological environment of the Yellow River Basin continues to deteriorate due to the rapid population growth and urban expansion. Understanding the land use change is helpful to analyze the land use trends under the interference of human activities and changes in the natural environment. In this manuscript, the TM and OLI images in 2008 and 2017 were mainly used to analyze the spatiotemporal dynamic of the land use in Henan Section of Yellow River Basin. The driving factors of land use changes were also quantified. Results show that the land use area of construction land and woodland gradually increased, and the arable land decreased significantly during the past ten years. The transfer of land use types was mainly reflected in the conversion of arable land to construction land. The total land use dynamic degree has reached 4.80% in the past decade. Based on the results, it can be concluded that the terrain and the socio-economic activities are the key factors affecting land use change in the study area. The research results can provide data support for ecological environmental protection and high-quality development of the Henan section of the Yellow River Basin, and help local governments take corresponding measures to achieve coordinated and sustainable socioeconomic and environmental development.
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