Detecting 3D Salinity Anomalies from Soil Sampling Points: A Case Study of the Yellow River Delta, China DOI Creative Commons

Zhoushun Han,

Xin Fu,

Jianing Yu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1488 - 1488

Published: Sept. 13, 2024

Rapidly capturing the spatial distribution of soil salinity plays important roles in saline soils’ management. Existing studies mostly focus on macroscopic soil-salinity changes, lacking effective methods to detect structure micro-regional areas anomalies. To overcome this problem, study proposes a 3D Soil-Salinity Anomaly Structure Extraction (3D-SSAS) methodology discover anomalies and step forward revealing irregular soil-anomaly from limited sampling points. We first interpolate points voxels using EBK. A novel concept, Local Index (LAI), is developed identify candidate with greatest amplitude change. By performing differential calculations LAI sequence determine threshold, anomaly candidates are selected. Finally, we adopt DBSCAN construct anomalous as structure. The experimental results Yellow River Delta data set show that 3D-SSAS can effectively salinity-anomaly areas, which highly correlated geographical mechanism salinity. This provides method for science, conducive further research complex variation process salinity’s distribution.

Language: Английский

Detecting 3D Salinity Anomalies from Soil Sampling Points: A Case Study of the Yellow River Delta, China DOI Creative Commons

Zhoushun Han,

Xin Fu,

Jianing Yu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(9), P. 1488 - 1488

Published: Sept. 13, 2024

Rapidly capturing the spatial distribution of soil salinity plays important roles in saline soils’ management. Existing studies mostly focus on macroscopic soil-salinity changes, lacking effective methods to detect structure micro-regional areas anomalies. To overcome this problem, study proposes a 3D Soil-Salinity Anomaly Structure Extraction (3D-SSAS) methodology discover anomalies and step forward revealing irregular soil-anomaly from limited sampling points. We first interpolate points voxels using EBK. A novel concept, Local Index (LAI), is developed identify candidate with greatest amplitude change. By performing differential calculations LAI sequence determine threshold, anomaly candidates are selected. Finally, we adopt DBSCAN construct anomalous as structure. The experimental results Yellow River Delta data set show that 3D-SSAS can effectively salinity-anomaly areas, which highly correlated geographical mechanism salinity. This provides method for science, conducive further research complex variation process salinity’s distribution.

Language: Английский

Citations

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