Visual Research and Predictive Analysis of Land Resource Use Type Change

• Published in: Advances in Artificial Intelligence and Security Vol. 1587; pp. 473 - 483
• Main Authors: Zhao, YuDan, Zeng, Wu, Zhang, YingGe, Tan, RuoChen, Li, Jie, Chen, DaChang
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2022; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Data visualization; Land use type; National land change data
• ISBN: 3031067606; 9783031067600
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-031-06761-7_38

Land cover change is a hot topic in the interdisciplinary research of global change and land science. The existing spatial visualization methods based on remote sensing images have the advantages of wide detection range, strong timeliness and objective reflection of land surface changes. However, the data display mode is single and the interaction is weak, the reading threshold is high, and the visual analysis of land use statistics data is insufficient. This paper collects and collates land change data and social and economic data from 2009 to 2016 in China. Firstly, Echarts and other tools are used to achieve visual representation of data. Then the impact of social and economic development needs on land resource utilization is studied. Finally, a prediction model of land use data change is established. In conclusion, this paper presents an effective visual data analysis method according to the characteristics of land use data, which can assist land managers to understand and analyze data and provide scientific basis for their decision-making activities of land use.