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Figure 10 Correlation heatmap analysis (a, b) and principal component analysis (c, d) of various indicators within red and farmland soils; correlation between ferromagnetic mineral (FM), hematite (Hm), goethite (Gt), organic matter (OM), and soil color; and stratigraphic changes in magnetic minerals (e, f). The size of the circle corresponds to the average content within the layers, while the background color indicates the stratigraphic variations. Asterisks mark their significance: **, <0.01; or *, <0.05.
Figure 9 Scatter plot analysis of DRS parameters (a. Redness% vs. Hm; b. Hm vs. Gt; c. Gt vs. Hm/Gt; d. Hm vs. Hm/Gt)
Figure 8 Scatter plot analysis of magnetic parameters (a. χ_fd vs. χ_lf; b. χ_fd vs. χ_fd%; c. χ_lf vs. Gt; d. χ_lf vs. Hm)
Figure 7 Changes in Hm, Gt and Hm/Gt based on depth in farmland and red soils
Figure 6 Violin boxplots (a, b, c) and box plots (d, e, f) based on depth of Hm, Gt, and Hm/Gt in various farmland; and violin boxplots of Hm, Gt, and Hm/Gt in red soils (g, h, i)
Figure 5 Diffuse reflectance spectroscopy (DRS) curves (a), stacked pie chart (b) of reflectivity for each color band, and bar chart of reflectivity for each color band with a pie chart of average values for each section (c), second-order derivative curve of DRS (d, e) of farmland and red soils
Figure 4 χ-T curves and FORC diagrams of typical samples from red and farmland soils
Figure 3 Changes in χ_lf, χ_fdand χ_fd% based on the depth in farmland and red soils
Figure 2 Violin box plots (a, b, c) and box plots based on depths (d, e, f) of χ_lf, χ_fdand χ_fd% in various farmland; and violin box plots of χ_lf, χ_fdand χ_fd% in the red soils (g, h, i)
Figure 1 Study area (a), image of the area (b), sampling location (c, d), meteorological information (e), stratigraphy and magnetic susceptibility of red soil A (f), stratigraphy and magnetic susceptibility of red soil B (g) of Meizhou city
Figure 6 Significance ranking of factors (The size of the symbols represents the strength of the influence, while the colour gradient visually illustrates the impact of each factor on LST.)
Figure 5 Training and test set results
Figure 4 Pearson’s analysis results at different scales for 2005, 2010, 2015 and 2020 (*p < 0.05, ** p < 0.01)
Table 4 Area and proportion of temperature classifications
Figure 3 Mean standard deviation classification map of LST in Shenyang for 2005, 2010, 2015 and 2020
Figure 2 Spatial variation map of influencing factors in Shenyang for 2020 (Note: Owing to space limitations, only the spatial distribution of the influencing factors for 2020 is shown.)
Table 3 Factors influencing LST
Table 2 Landscape index and its significance
Table 1 Classification rules for different temperature zones
Figure 1 Location of Shenyang city, Liaoning province, Northeast China (Note: With the map approval number GS(2024)0650, the base map remains unmodified.)

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