基于空间聚类分层抽样的黄骅市县域耕地质量等别监测样点布设

doi:10.18402/resci.2019.02.05

摘要/Abstract

摘要：

耕地质量监测是当前国家及时掌握耕地质量和产能变化的重要工作手段。合理布设耕地质量监测样点可以大幅提高耕地质量监测的效率。以河北省黄骅市县域耕地为研究对象,以耕地的质量属性和空间位置属性为耕地质量等别监测区的划定依据,采用空间聚类法生成20种备选监测区方案,通过综合比较方差、抽样误差、抽样效率和抽样弹性系数,选出初始监测区方案,并在此基础上局部优化,最终生成耕地质量等别监测区方案,最后以耕地质量等别监测区为分层依据,运用分层抽样法布设了耕地质量等别监测样点。研究表明：①在抽样误差为1%的要求下,分区数为65的备选耕地质量等别监测区方案的综合样本容量为77,抽样效率相对较高,被选定为初始监测区方案;②随着耕地质量等别监测区数目从5增加到100,相同监测区内耕地单元之间在空间位置和耕地质量等别上的差异程度由快速减少到趋于平稳;③在布设相同数量的监测样点时,本文提出的基于空间聚类分层抽样的样点布设方法在表土质地、剖面构型、盐渍化、有机质含量、排水条件、灌溉条件和国家耕地质量自然等指数等因素方面的抽样误差分别为0.37、1.02、1.39、0.91、0.31、1.53和1.27,均明显低于传统的等别分层抽样、简单随机抽样、网格分层抽样,具有较高的抽样效率。研究成果可为耕地质量等别监测样点布设相关工作和研究提供有效指导。

关键词: 耕地质量等别, 监测样点布设, 抽样误差, 抽样效率, 空间聚类分层抽样, 黄骅市

Abstract:

Cultivated land quality monitoring is an important strategy to grasp the changes in cultivated land quality and productivity for the country. Arranging cultivated land quality monitoring samples in a reasonable way can greatly improve the efficiency of cultivated land quality monitoring. This study took the typical area of the coastal plain, Huanghua City as an example, generated 20 alternative monitoring area scenarios with the method of spatial clustering. The initial monitoring area plan was selected by comprehensive comparison of variance, sampling error, sampling efficiency, and sampling elastic coefficient, and by partial optimization, the project of the cultivated land quality monitoring area was finally generated. Finally, based on the stratified sampling area, the stratified sampling method was used to lay out the monitoring records of cultivated land quality.The results showed that under the requirement of 1% sampling error, the alternative cultivated land quality monitoring area with a partition number of 65 did exhibit a comprehensive sample capacity of 77 and a relatively high sampling efficiency, which was selected as the initial monitoring area. The difference in spatial position and cultivated land quality between cultivated land units in the same monitoring area decreased rapidly first, and finally remained stable, with the number of cultivated land quality monitoring areas increases from 5 to 100. By laying the same number of monitoring samples, the sampling error in terms of topsoil texture, section configuration, salinization, organic matter content, drainage conditions, irrigation conditions, and national natural index were 0.37, 1.02, 1.39, 0.91, 0.31, 1.53, and 1.27 respectively. Based on spatial clustering stratified sampling proposed in this paper, the observations were lower than traditional stratified sampling, simple random sampling, grid stratified sampling, and had higher sampling efficiency. The results are intended to provide effective guidance for the deployment of relevant work and research on the quality monitoring samples of cultivated land.

Key words: cultivated land quality, monitoring sample layout, sampling error, sampling efficiency, spatial clustering stratified sampling, Huanghua City

杨江燕, 殷守强, 张利, 门明新, 陈影. 基于空间聚类分层抽样的黄骅市县域耕地质量等别监测样点布设[J]. 资源科学, 2019, 41(2): 257-267.

Jiangyan YANG, Shouqiang YIN, Li ZHANG, Mingxin MEN, Ying CHEN. The layout of county area cultivated land quality monitoring samples in Huanghua City based on spatial clustering stratified sampling[J]. Resources Science, 2019, 41(2): 257-267.

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分区数/个	0.1%	0.2%	0.3%	0.4%	0.5%	1.0%	1.5%	2.0%	2.5%	3.0%	3.5%	4.0%	4.5%	5.0%	6.0%	7.0%	8.0%	9.0%	10.0%
5	14 001	11 422	9 312	7 554	6 271	2 596	1 314	777	511	361	267	206	164	133	94	70	55	43	36
10	12 086	9 634	8 051	6 643	5 441	2 195	1 102	651	425	299	222	170	135	110	75	56	44	34	28
15	11 890	9 649	8 142	6 779	5 590	2 282	1 151	680	447	313	230	180	142	116	78	60	47	38	29
20	9 116	5 764	3 881	2 813	2 118	699	332	192	127	88	69	53	49	38	31	25	23	22	21
25	8 960	5 717	3 679	2 491	1 777	530	245	141	93	68	51	41	36	31	29	26	26	25	25
30	5 775	2 981	1 677	1 041	703	194	89	54	42	34	32	30	30	30	30	30	30	30	30
35	5 602	2 964	1 686	1 058	718	199	97	61	47	38	37	35	35	35	35	35	35	35	35
40	4 272	2 065	1 138	702	475	140	73	52	44	42	40	40	40	40	40	40	40	40	40
45	3 670	1 783	972	600	408	124	56	55	49	46	45	45	45	45	45	45	45	45	45
50	2 798	1 319	719	446	305	105	65	55	51	51	50	50	50	50	50	50	50	50	50
55	2 599	1 215	665	416	287	100	66	59	56	55	55	55	55	55	55	55	55	55	55
60	2 354	1 022	543	337	236	90	68	61	60	60	60	60	60	60	60	60	60	60	60
65	1 465	609	327	213	155	77	67	65	65	65	65	65	65	65	65	65	65	65	65
70	2 180	833	425	261	188	83	72	70	70	70	70	70	70	70	70	70	70	70	70
75	1 517	599	323	211	155	83	75	75	75	75	75	75	75	75	75	75	75	75	75
80	1 728	710	383	250	182	91	82	80	80	80	80	80	80	80	80	80	80	80	80
85	1 413	562	309	208	157	92	85	85	85	85	85	85	85	85	85	85	85	85	85
90	1 026	425	246	173	137	94	91	90	90	90	90	90	90	90	90	90	90	90	90
95	1 601	729	412	275	206	112	97	95	95	95	95	95	95	95	95	95	95	95	95
100	1 265	509	289	201	158	107	100	100	100	100	100	100	100	100	100	100	100	100	100

抽样方法	表土质地/%	剖面构型/%	盐渍化/%	有机质含量/%	排水条件/%	灌溉条件/%	耕地质量国家自然等指数/%
空间聚类分层抽样	0.37	1.02	1.39	0.91	0.31	1.53	1.27
等别分层抽样	0.97	2.41	4.28	4.54	1.28	2.04	1.06
简单随机抽样	1.45	3.00	4.23	4.16	1.17	6.01	1.89
网格分层抽样	1.23	2.73	4.69	3.06	0.49	7.69	2.16

耕地等别	耕地面积/km²	空间聚类分层抽样样点布设数量/个	等别分层抽样样点布设数量/个	简单随机抽样样点布设数量/个	网格分层抽样样点布设数量/个
10	593.45	55	42	63	50
11	69.94	10	13	12	10
7	21.71	5	5	1	1
8	8.14	1	3	0	4
9	176.41	10	8	5	16
总计	869.64	81	81	81	81