Folk分类的海底沉积物类型赋值制图方法研究

doi:10.11978/2025085

Abstract

Abstract:

Seabed sediment type maps play a crucial role in marine environmental analysis, marine engineering construction, and the exploration of marine mineral resources. This paper proposes a novel mapping method for seabed sediment type assignment based on the Folk classification. Using spatial interpolation analysis of surface sediment data from the southwestern waters of Hainan Island, a Folk classification system was developed. After data classification, a grid was overlaid to integrate with the Folk classification system. Subsequently, grid erosion was performed to generate the seabed sediment type map. In a comparative analysis of interpolation methods, including Sibson, IDW (inverse distance weighting), Kriging, and Spline, the Sibson method was used as the foundation for mapping in this study. This method features a simple operational process, high mapping efficiency, and is unaffected by subjective factors, resulting in relatively accurate mapping and strong practicability. It can be applied to the mapping of seabed sediment types at different scales or with different sampling station spacings, demonstrating broad potential for practical application.

Key words: sediment type map, spatial interpolation, Sibson, reclassification, raster math, Grid Nibble

CLC Number:

P717

LIN Mingzhi, QIN Maogang, CHEN Yang, CHEN Bo, WANG Xuemu, LIU Yanrui, SONG Jiawei, SUN Longfei. Research on the assignment mapping method of seabed sediment types based on Folk classification[J].Journal of Tropical Oceanography, 2026, 45(1): 178-187.

Figures/Tables 11

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References 33

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插值方法	主要原理	特点
Sibson (自然邻域法)	取样站位构成邻近原始Voronoi多边形, 插值点周围创建新Voronoi多边形, 基于新的多边形与原始多边形之间的重叠比例作权重进行插值	a)仅利用插值点周围的取样站位数据; 插值均在局部取样站位数据区间内; 插值表面平滑 b)图件界线合理、圆滑
IDW (反距离权重法)	以反距离函数为权重, 使用一组站位数据的线性权重组合来确定插值	a)主要依赖于反距离的幂值, 幂值越高表面越不平滑, 反之表面更加平滑, 最佳幂值不易确定 b)图件界线相对合理, 但容易产生“孤岛”
Kriging (克里金法)	普通克里金是一个线性估计系统, 适用于任何满足各向同性假设的固有平稳随机场	a)根据地统计分析, 创建变异函数和协方差函数, 估算数据的空间自相关, 最后进行插值 b)插值取决于变量的自相关性强弱, 强相关性插值结果平滑, 弱相关性插值结果有可能呈现“锯齿状” c)绘制沉积物类型图需要兼顾砾含量、砂含量、砂/泥比值、粉砂/黏土比值、含砾界线划分等空间相关性, 难以找到合适的插值参数
Spline (样条函数法)	利用最小化表面总曲率的数学函数来插值	a)插值表面平滑、平缓变化 b)插值范围易超出合理范围, 难以找到合适的插值参数

含砾碎屑沉积物分类						不含砾碎屑沉积物分类
砾组分含量/%	砂/泥比值	砾组分含量赋值	砂/泥比值赋值	沉积物类型赋值	沉积物类型	砂组分含量/%	粉砂/黏土比值	砂组分含量赋值	粉砂/黏土比值赋值	沉积物类型赋值	沉积物类型
1	2	3	4	3+4	5	6	7	8	9	8+9	10
≥80		10		10	砾	≥90		60		60	砂
30~80	≥9	20	1	21	砂质砾	50~90	≥2	70	5	75	粉砂质砂
30~80	1~9	20	2	22	泥质砂质砾	50~90	0.5~2	70	6	76	泥质砂
30~80	<1	20	3	23	泥质砾	50~90	<0.5	70	7	77	黏土质砂
5~30	≥9	30	1	31	砾质砂	10~50	≥2	80	5	85	砂质粉砂
5~30	1~9	30	2	32	砾质泥质砂	10~50	0.5~2	80	6	86	砂质泥
5~30	<1	30	3	33	砾质泥	10~50	<0.5	80	7	87	砂质黏土
0.01~5	≥9	40	1	41	含砾砂	<10	≥2	90	5	95	粉砂
0.01~5	1~9	40	2	42	含砾泥质砂	<10	0.5~2	90	6	96	泥
0.01~5	<1	40	3	43	含砾泥	<10	<0.5	90	7	97	黏土
<0.01	≥9	50	1	51	砂
<0.01	1~9	50	2	52	泥质砂
<0.01	1/9~1	50	3	53	砂质泥
<0.01	<1/9	50	4	54	泥

空间插值方法	砾含量/%	砂含量/%	砂/泥比值	粉砂/黏土比值
自然邻域法	1.03~50.13	10.18~98.11	0.15~97.58	0.02~3.48
反距离权重法	0~50.95	9.64~98.31	0.12~98.27	0~3.51
克里金法	0~26.88	23.57~87.04	0.84~43.91	1.09~2.80
样条函数法	−21.64~51.37	−12.47~155.23	−35.47~139.47	−0.94~3.52
取样站位	0~51.00	9.60~98.36	0.11~45.28	1.45~3.51

空间插值方法	图斑面积占比/%			图斑数量/块				沉积物类型数量/个					未蚕食预测新增沉积物类型
	未蚕食		蚕食后	未蚕食			蚕食后	未蚕食				蚕食后
	站位控制	预测	站位控制	站位控制	预测	合计	站位控制	站位控制	预测	预测新增	合计	站位控制
自然邻域法	85.05	14.95	100	40	86	126	38	13	12	1	14	13	泥质砂
反距离权重法	87.89	12.11	100	47	52	99	46	13	10	1	14	13	泥质砂

图件	4a	4b	4c	4d	4e	4f	4g	4h	4i	4j	4k	4l
4a	1
4b	0.81	1
4c	0.67	0.63	1
4d	0.61	0.71	0.84	1
4e	0.48	0.42	0.28	0.28	1
4f	0.44	0.51	0.3	0.33	0.83	1
4g	0.29	0.26	0.25	0.23	0.64	0.56	1
4h	0.27	0.29	0.22	0.26	0.58	0.62	0.87	1
4i	0.52	0.47	0.39	0.37	0.62	0.56	0.45	0.42	1
4j	0.44	0.49	0.35	0.38	0.49	0.55	0.35	0.38	0.66	1
4k	0.42	0.4	0.38	0.37	0.53	0.5	0.52	0.47	0.72	0.53	1
4l	0.45	0.49	0.42	0.45	0.53	0.58	0.48	0.48	0.65	0.64	0.83	1

Research on the assignment mapping method of seabed sediment types based on Folk classification

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制图方法	插值变量	含砾与不含砾分类	图面效果	实际采样点对比	蚕食	制图效率
推荐方法—— 自然邻域赋值法	组分及比值 (无须对组分进行闭合约束)	以取样站位等分	孤岛少、分区较圆滑、图面美观	一致	蚕食或部分蚕食	高
反距离权重赋值法	组分及比值 (无须对组分进行闭合约束)	以取样站位等分	孤岛较多	一致	蚕食或部分蚕食	高
闭合组分法	组分 (一般需要对组分进行闭合约束)	以含砾0.01%划分, 弱化不含砾分类	孤岛多、尤其是不含砾分类易呈孤岛	一致	无	高
勾绘法	主观勾绘	以取样站位平均划分或其他方法确定	因人而异	一致	无	低