Proceedings Article | 10 November 2021
KEYWORDS: Vegetation, Artificial intelligence, Remote sensing, Image classification, Landsat, Earth observing sensors, Image processing, Climatology, Classification systems, Stars
As a national-level economic zone, Guanzhong-Tianshui Economic Zone has played an important role in the economic development of Northwest China. During its development, urban expansion and ecological environment have also undergone tremendous changes. This paper uses the three Landsat remote sensing images in 2010, 2015, and 2018 as the data source, and uses the land use classification system and CART decision tree classification method to analyze the geographical expansion of six cities in Xi’an, Xianyang, Weinan, Tongchuan, Baoji, and Tianshui. Temporal and spatial changes and the characteristics of temporal and spatial changes of natural vegetation. The main conclusions are as follows: (1) Since 2009, the expansion of urban construction land in the Guanzhong-Tianshui Economic Zone has shown a slow growth (first fast and then slow). The high spatial expansion density is concentrated in Xi'an (including Xian yang) and Weinan. In addition, the connectivity between cities is not strong, and there is no trend of contiguous development. Urban expansion is mainly due to the conversion of cultivated land to construction land. (2) The mode of urban expansion is mainly marginal and infill, and each city has its own characteristics in the direction of expansion. Among them, Baoji City and Tianshui City mainly expanded from east to west, while Xi'an (including Xian yang), Wei nan City, and Tong chuan City expanded in all directions. (3) In the process of urban expansion, the overall greenness of vegetation showed a downward trend, and the areas with significant decline were all located in the periphery of the city, and the urban construction land in this area was significantly expanded. The research conclusions of this article will provide a strong scientific basis for urban construction and planning in this area.
