首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于半方差函数与等别的耕地质量监测样点优化布设方法
引用本文:祝锦霞,徐保根,章琳云.基于半方差函数与等别的耕地质量监测样点优化布设方法[J].农业工程学报,2015,31(19):254-261.
作者姓名:祝锦霞  徐保根  章琳云
作者单位:浙江财经大学经济与社会发展研究院,杭州 310018,浙江财经大学经济与社会发展研究院,杭州 310018,浙江财经大学经济与社会发展研究院,杭州 310018
基金项目:国家自然科学基金项目(41501190);浙江省自然科学基金项目(LQ14D010003);浙江省国土资源厅专项公益资金:浙江省耕地质量等级监测评价工作阶段性研究成果;卫星海洋环境动力学国家重点实验室开放课题(SOED1404)
摘    要:耕地的数量和质量在维护国家安全、社会稳定方面具有举足轻重的作用。该文以浙江省耕地质量监测试点松阳县为例,探讨县级尺度的耕地质量监测样点的布设方法。选择自然等指数的均方差和绝对偏差计算在允许误差范围内监测样点的样本容量;采用地统计学半方差函数分析耕地质量的变异情况,利用自然等指数的变异特征与规律实现监测样点的预布设;重点分析耕地质量等别、分等因素、耕地质量潜在变化区域的空间分布,结合等别组合的空间分布特征对预布设的监测样点进行优化,得到40个监测样点。研究成果提高了监测样点的精度、代表性、科学性,方法易操作推广,具有很好的应用价值,能为耕地质量监测的管理工作提供参考。

关 键 词:土地利用  监测  方法  优化  地统计  半方差函数  等别组合  耕地
收稿时间:2015/5/14 0:00:00
修稿时间:2015/9/15 0:00:00

Optimization layout method of monitoring sample points of cultivated land quality based on semi-variance analysis and grade combination
Zhu Jinxi,Xu Baogen and Zhang Linyun.Optimization layout method of monitoring sample points of cultivated land quality based on semi-variance analysis and grade combination[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(19):254-261.
Authors:Zhu Jinxi  Xu Baogen and Zhang Linyun
Institution:Institute of Economic and Social Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China,Institute of Economic and Social Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China and Institute of Economic and Social Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China
Abstract:Abstract: The quantity and quality of cultivated land plays an important role in the national food security and the long-term stability of the community. The purpose of this study was to explore a method of location sampling with optical number for monitoring the quality of cultivated land at county level. Songyang County, Zhejiang Province was selected as our study area to investigate the proposed method. We adopted a combination of theoretical modeling and empirical analysis together in this study. The absolute deviation and the variance of national natural index of cultivated land were used to calculate the theoretical sample size of the monitoring points of cultivated land within the permitted statistical error range. We preliminarily determined the number of monitoring reference samples according to the technical specification for soil environmental monitoring. There were 47 monitoring sample points simulated in Songyang County. Then, we applied the variogram model of geostatistics to set up the monitoring sample points, which provided a way for controlling monitoring costs and improving monitoring accuracy based on variability analysis. The input parameter of semi-variable function was national natural index. All the process was explored in the software GS+. The semivariance of agricultural land natural index was analyzed at separation distance. The variation of the radius of cultivated land in Songyang was 3.1 km, which was the exactly radius of the grid in the proposed method. There were 89 monitoring points of land quality grading arranged by the use of variogram results. Next, sample points were corrected and optimized by the use of grading combination and spatial attributes. The core idea of the procedure was how to correct the monitoring sample points to reflect the land quality level successfully. In order to improve the representativeness of monitoring points and the integrity of arable land quality monitoring information, we analyzed the distribution characteristics of grading factors and the potential change areas of cultivated land quality. In this study, there were 14 grade combinations of national agricultural land natural level, national land use level and national agricultural land economical level. After spatial overlay analysis of quality grading factors, potential change areas and grade of cultivated land using the geostatistics method of the GIS (geographic information system), the number of reasonable layout of the monitoring points was reduced to 40. Finally, we compared the grade monitoring point arrangement and the distribution map of grading results of land quality respectively between the proposed and the traditional method. The overall accuracy of national natural grade, national usage grade and national economic grade was improved by 12.75%, 5.3% and 10.55%, respectively. Kappa coefficient was also improved by 0.19, 0.10 and 0.17, respectively. Additionally, the area ratio of grading factors was almost the same as the number ratio of monitoring points of cultivated land. We also analyzed the distribution of monitoring points within potential change areas of cultivated land quality. The area ratio of potential change areas was almost the same as the number ratio of monitoring points in potential change areas. Results indicated that the proposed method was effective for locating sampling for monitoring the quality of cultivated land and significantly improved the accuracy of the cultivated land grading. All the monitoring points were successful in representing the integrity of cultivated land quality. The explored new method is feasible, scientific and standard, which can be widely used in the management of monitoring the quality of cultivated land at county level. Further research is needed in other scales, such as city, province and country. The proposed method should be further tested in other regions containing more complex conditions in geology and geomorphology.
Keywords:land use  monitoring  methods  optimization  geo-statistical analysis  semi-variance analysis  grade-combination  cultivated land
本文献已被 万方数据 等数据库收录!
点击此处可从《农业工程学报》浏览原始摘要信息
点击此处可从《农业工程学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号