Application of categorical information in the spatial prediction of soil organic carbon in the red soil area of China

Figures & data

Figure 1  Location map of the study area and the soil sampling sites in southern China.

Table 1 Soil organic carbon content (g kg−1) statistics for various soil types, land uses and land use–soil types

Classification	Land use	Soil type			N	Mean	Min	Max	SD	CV
		Group	Subgroup^†	Families^‡
ST		Paddy soil	Hydromorphic, 1	PH-A	41	16.54	5.00	25.38	4.98	30.12
				PH-B	38	16.99	7.27	29.09	5.03	29.63
				PH-C	4	19.92	17.50	21.92	2.01	10.11
				PH-D	24	20.76	11.31	34.20	5.95	28.65
			Gleyed, 2	PG-B	4	19.32	16.34	22.08	2.39	12.35
				PG-D	6	24.23	21.00	34.03	4.98	20.54
		Red soil	Red soil, 3	RR-B	9	8.70	3.55	17.38	4.32	49.60
				RR-C	5	7.68	3.78	12.60	3.18	41.38
				RR-D	44	17.61	3.30	36.40	9.22	52.36
				RR-E	79	9.41	3.07	29.37	5.21	55.38
LU	Paddy field				118	18.31	5.00	34.20	5.53	30.21
	Upland field				76	8.99	3.07	21.32	4.24	47.20
	Forestland				46	15.81	3.11	36.40	9.96	62.97
	Vegetable field				7	16.28	9.48	24.21	5.38	33.04
	Orchard				7	10.66	5.15	21.09	5.86	54.96
LUST	Paddy field	Paddy soil	Hydromorphic	PH-A	41	16.54	5.00	25.38	4.98	30.12
				PH-B	38	16.99	7.27	29.09	5.03	29.63
				PH-C	4	19.92	17.5	21.92	2.01	10.11
				PH-D	24	20.76	11.31	34.20	5.95	28.65
			Gleyed	PG-B	4	19.32	16.34	22.08	2.39	12.35
				PG-D	6	24.23	21.00	34.03	4.98	20.54
	Upland field	Red soil	Red soil	RR-B	9	8.70	3.55	17.38	4.31	49.56
				RR-C	5	7.68	3.78	12.60	3.18	41.38
				RR-D	12	13.04	6.20	21.32	4.40	33.72
				RR-E	50	8.20	3.07	18.54	3.81	46.45
	Forestland	Red soil	Red soil	RR-C	30	19.43	3.30	36.40	10.19	52.44
				RR-D	16	9.04	3.11	21.04	4.65	51.51
	Vegetable field	Red soil	Red soil	RR-C	3	16.45	11.25	24.21	6.85	41.65
				RR-D	4	16.15	9.48	22.04	5.15	31.88
	Orchards	Red soil	Red soil	RR-D	7	10.66	5.15	21.09	5.86	54.96
Total					254	14.80	3.07	36.40	7.43	50.20
^†Reference to the WRB system: 1, Hydragric Anthrosols; 2, Gleyic-Hydragic Anthrosols; 3, Acrisols. ^‡Soil families are classified mainly according to parent materials. Refer to Fig. 2 for the names. Mean, mean soil organic carbon content; SD, standard deviation; CV, coefficient of variation (%); ST, Soil type; LU, Land use; LUST, Land use–soil type.

Figure 2  Soil (at the family level) and land use of the study area. The 10 families belong to two great groups including paddy soil (Anthrosols, WRB) and red soil (Acrisols, WRB), and three subgroups including Hydromorphic (Hydragric Anthrosols, WRB), Gleyed (Gleyic-Hydragic Anthrosols, WRB) and Red soil (Acrisols, WRB), which are abbreviated as PH, PG and RR. Soil families are classified mainly according to parent materials. A, B, C, D and E are labels for the following parent materials, alluvium, sandy conglomerate, quaternary red clay, shale and red sandstone, respectively.

Figure 3  Histograms of (a) soil organic carbon original data, (b) the residuals by removing the mean values of soil type, (c) land use and (d) land use–soil type.

Table 2 Best-fit semivariogram models and their parameters for the various prediction approaches

Approaches	Distribution	Model	C0	Sill	C/Sill	Range (m)	R ^2
OK	Normal	Exponential	0.365	0.879	0.585	6410	0.759
KST	Normal	Spherical	0.325	0.729	0.554	4730	0.847
KLU	Normal	Spherical	0.292	0.716	0.592	4800	0.620
KLUST	Normal	Spherical	0.303	0.711	0.574	4630	0.946
OK, ordinary kriging; KST, kriging combined with soil-type information; KLU, land use; KLUST, combined land use–soil type information.

Figure 4  Semivariograms of the studied interpolation approaches (a, b, c and d are for ordinary kriging [OK], kriging combined with soil-type information [KST], land use [KLU] and combined land use–soil type information [KLUST], respectively).

Figure 5  Relationship between the predicted and observed soil organic content from the interpolation methods (a, b, c, and d are for ordinary kriging [OK], kriging combined with soil-type information [KST], land use [KLU] and combined land use–soil type information [KLUST], respectively).

Figure 6  Comparison of the root mean square error (RMSE) associated with the application of different kriging interpolations in paddy and red soils.

Figure 7  Comparison of the root mean square error (RMSE) associated with the application of different kriging interpolations by land-use group.

Figure 8  Soil organic carbon (SOC) distribution maps generated from the four kriging approaches (a, b, c, and d are for ordinary kriging [OK], kriging combined with soil-type information [KST], land use [KLU] and combined land use–soil type information [KLUST], respectively).