冬小麦种植面积空间抽样效率影响因子分析

Analysis of influence factors about space sampling efficiency of winter wheat planting area

基于遥感与抽样的农作物种植面积测量方法结合了遥感和抽样理论的优势,已经成为农作物种植面积测量中有着广泛应用前景的测量方法。以格网为单元,进行分层空间抽样,分析在二值图像的情况下,抽样格网大小、分层层数对抽样精度、抽样精度方差、抽样比的影响;将二值图像分类结果定义为作物区,随机混入不同丰度10%,20%,……,100%的冬小麦,在不同冬小麦丰度(即不同的分类误差)的前提下,分析抽样格网大小、分层层数、分类误差对抽样精度、抽样比的影响,确定最优分层定义为6层,在分类误差小于40%(即冬小麦丰度大于60%)的前提下,可以有效地进行空间抽样推算区域冬小麦种植面积,为农作物种植面积测量空间抽样方案的优化提供理论基础。

Based on the sample space of farming area measurement method combining the advantages of remote sensing and sampling theory, spatial sample method has been widely applied for crop planting area. In the paper, a stratfied sampling method based on grid was introduced for such purposes. Firstly, with the 0-1 image, the effects of the factors of grid size, strata layer number on sampling accuracy, sampling variance and sampling ratio were analyzed. Secondly, binary image classification defming as result for crop area, random mix error was adopted for different kinds of abundance （10%, 20% 100%） of winter wheat. The effects of the factors of grid size, strata layer number and classification error on sampling accuracy, sample ratio were analyzed. Finally, the layer number defined as six was brought up, and under classification error lower 40% was good for crop area estimation with spatial sample method. In a word, the research has developed a good method for optimizing spatial sampling.