Analysis of land use/cover change and landscape patterns based on remote sensing

Xiaoyu Bian; Jiaxin Wu; William .

doi:10.1117/12.3024567

21 February 2024 Analysis of land use/cover change and landscape patterns based on remote sensing

Xiaoyu Bian, Jiaxin Wu, William .

Proceedings Volume 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023); 129880Q (2024) https://doi.org/10.1117/12.3024567
Event: Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 2023, Xi’an, China

Abstract

Remote sensing technology enables the observation of terrestrial features on the Earth's surface at specific time intervals and over particular swaths, facilitating the analysis of land use/cover changes and landscape patterns in a study area over time, thereby enhancing planning and utilization. In this study, we calculated the area, dynamic degree, and land use transition matrix for different land use types in the Yunzhou District of Datong City, and discovered the following: the rate of change in the area of construction residential land and forest land in the Yunzhou District of Datong City is significant. The area of construction residential land has gradually increased, exhibiting a trend of continuous outward expansion, with all increases being a result of the conversion from cultivated land. The river surface of the Sanggan River is continually shrinking, with cultivated land year by year engulfing riparian wetlands. From the perspective of the landscape pattern index, the class area (CA) is highest for forest land, indicating that forest land has a higher degree of fragmentation. Special land uses (landscape, cultural and historical sites) are also more dispersed. The largest patch index (LPI) is highest for cultivated land, indicating that cultivated land is the dominant land use matrix type in the study area, with a high degree of dominance and concentrated distribution. In addition, the landscape shape index (LSI) is highest for forest land, making its shape and distribution the most complex.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Xiaoyu Bian, Jiaxin Wu, and William . "Analysis of land use/cover change and landscape patterns based on remote sensing", Proc. SPIE 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 129880Q (21 February 2024); https://doi.org/10.1117/12.3024567

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KEYWORDS

Remote sensing

Matrices

Mining

Reflection

Transportation

Artificial intelligence

Industry

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