Abstract
Urban expansion is often studied in large cities such as Beijing, Shanghai, and Guangzhou, while scant attention is paid to smaller cities such as Xining. However, Xining is the largest city on the Tibetan Plateau, and an important city in China's “Belt and Road Initiative”. As its economy and society develops, Xining will play an increasingly important role in connecting the central and western regions. In order to quantify the impacts of rapid urbanization, it is extremely important to collect data on the time and space variations of impervious surfaces. As such, we collected Landsat long-term sequence data about Xining City from 1987-2019 using the random forest method, and then optimized the feature parameters to obtain the dataset. Our results demonstrated that the overall accuracy of land use classification in Xining city is 83.4% and that the urban impervious surface accuracy is 89.5%. Additionally, the overall accuracy improved by 2.4% after optimizing the characteristic parameters, while the urban impervious surface accuracy is 92.8%. In 27 of the 33 years we studied, the classification accuracy of impervious surfaces exceeded 90%. After correcting for the temporal consistency check, the accuracy of impervious surfaces improved by 2% compared to the original sequence. We analyzed the change of impervious surfaces in Xining based on the results of the final dataset and found that the impervious surface area of Xining increased from 55 km 2 in 1987 to 334 km 2 in 2019. Xining is a typical semi-open river valley city which shares spatial and temporal characteristics with other urban centers. The spatial and temporal characteristics of the expansion of urban spaces in the main urban area of Xining are obvious and are primarily spread around the central area toward tree branch shaped road, which help other cities located in river valleys better understand how urbanization progresses.
Highlights
Cities are home to most humans and economic activity, making them the focus of much academic research [1]
China’s urbanization has been accelerating since the beginning of 1980s, with a large number of people relocating from rural areas to urban areas [4]–[8]
The green line refers to classification accuracy with additional parameters such as Normalized Difference Water Index (NDWI), Radio Vegetation Index (RVI), NDVI, Enhanced Vegetation Index (EVI), and Normalized Difference Building Index (NDBI), the red line refers to classification accuracy after selection using texture features, optimal windows, climatic factors, and feature parameters (Figure 6)
Summary
Cities are home to most humans and economic activity, making them the focus of much academic research [1]. Rapid economic growth and the gradual transformation of agricultural lands to urban cities has rapidly increased the population of China’s cities [9]. This pace of urbanization greatly impacts the environment and climate on different scales: the urban heat island effect makes Xining significantly warmer than surrounding rural areas [10], [11], local and regional precipitation levels change, water quality deteriorates [12]–[14], increases in urban impervious surfaces induce water runoff, and the loss of agricultural land negatively impacts food production [15]–[17].
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