基于因素组合的耕地质量等级监测样点布控方法

科学确定耕地质量等级监测样点布控方法，形成中国耕地质量动态监测布控体系，是掌握耕地质量动态、支撑国家粮食安全的重要技术依据。该文基于标准样地设置，以滇黔高原山地区为例，提出以耕地质量等别为控制，熟制—土壤类型—海拔—土地利用系数—土地经济系数因素组合确定监测样点的方法，即因素组合法；其步骤为：根据因素组合类型初步确定监测点数量；依据面积比例修正各等别监测点数量；基于GIS确定和选取监测点空间位置和来源，形成监测样点；构建模型对监测点代表性进行检验。结果表明，滇黔高原山地区确定144个监测样点，其中7个来源于国家级标准样地，44个来源于省级标准样地，93个来源于耕地分等单元图斑；采用因素组合法形成滇黔高原山地区监测样点，能够实现国家尺度上二级区内对耕地质量变化的动态监测，监测样点满足统计学要求和面积代表性。基于因素组合的耕地质量监测样点布控方法，可以为建立覆盖全国的耕地质量监测体系提供借鉴，为中国耕地数量、质量并重的宏观管理提供技术支撑。

Layout method for monitoring sample point of arable land quality level based on combination of factors

Abstract: With the stability of arable land's quantity, monitoring land quality has become a high priority research for understanding the effects of the dynamic change of arable land on food security in China, as well as the layout method on monitoring arable land quality change. However, there are integrated factors such as climate, terrain, soil, access to irrigation, rural road, trade-off between input and output, which affect arable land quality change over time and space. We propose a new monitoring framework titled factors' combination, which includes such factors affecting arable land quality as natural conditions (e.g., climate, soil, geomorphology), the utilization of level (e.g., farmland infrastructure, land management, land use coefficient), income level (e.g., land use structure and mode, the input and output of arable land, land economic coefficient), and reference cropping system to form a monitoring reference arable land unit. We illustrate this new method using the Dianqian plateau mountain area as a case study. Spatial overlay analysis of main factors and geostatistics method using GIS were employed to test this method. Specific steps of factors' combination method are as follows: 1) we preliminarily determine the number of monitoring reference samples according to the type of factors' combination; 2) on the basis of the proportion of arable land area at each grade accounting for the total area, we then revise the number of monitoring samples and supplement monitoring samples for those gradations which have relatively few monitoring samples; 3) based on GIS analysis results, if the same factors' combination distributes in the different space positions of second zone and meets the requirements of monitoring sample, multiple figure spots of the factors' combination will be kept at the same time, and eventually figure spot of the grading unit will be determined; 4) given overlay the map spot of grading unit and the national standard sample and the provincial standard sample respectively, we take the national standard sample or provincial standard sample as the monitoring sample for those overlaying parts; then convert the remaining figure spots of grading into a point as the monitoring sample, and determine the final number of monitoring samples, spatial location and its source; 5) we build up model on representative index of area of monitoring sample and adopt the geo-statistical method to carry on the representative test for monitoring sample to optimize the monitoring sample. The results show that 144 monitoring reference sample units include 7 from the national standard sample, 44 from provincial standard sample and 93 from arable land grading unit, and they were selected as a whole for monitoring arable land quality in Dianqian plateau mountain area using our new method of factors' combination. The distribution of the selected monitoring reference land units not only provide samples to monitor the arable land quality change in the second zone of national scale, but also meet the requirements of statistical science and representative of area. Layout method for monitoring sample point of arable land quality level using factors' combination, can provide reference for building up the whole country's dynamic monitoring systems, and offer technical support to achieve comprehensive management of quantity and quality of arable land at national level in China.