Developing crop specific area frame stratifications based on geospatial crop frequency and cultivation data layers

作     者：Claire G. Boryan Zhengwei Yang Patrick Willis Liping Di 

作者机构：Research and Development Division USDA National Agricultural Statistics Service VA 22030 USA Center for Spatial Information Science and Systems George Mason University VA 22030 USA 

出 版 物：《Journal of Integrative Agriculture》 (农业科学学报（英文版）)

年 卷 期：2017年第16卷第2期

页      面：312-323页

核心收录：

学科分类：0710[理学-生物学] 0832[工学-食品科学与工程（可授工学、农学学位）] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 0905[农学-畜牧学] 0906[农学-兽医学] 09[农学] 0901[农学-作物学] 0703[理学-化学] 0902[农学-园艺学] 0713[理学-生态学] 

基　　金：The authors would like to thank Ms. Lee Ebinger from the United States Department of Agriculture for creating the ifgures for this paper and Dr. Shirley Sampson from the United States Department of Agriculture for editorial review 

主　　题：cropland data layer crop planting frequency data layers automated stratification crop specific stratification multi-crop stratification 

摘      要：Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.