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Developing.crop specific area frame stratifications based on g.ospatial crop frequency and cultivation data layers

Journal of Integ.ative Ag.iculture 2017年第2期16卷 312-323页

作者： claire g. boryan Zheng.ei Yang.Patrick Willis Liping.Di 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

Area Sampling.Frames （ASFs） are the basis of many statistical prog.ams around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on g.ospatial crop planting.frequency and cultivation data is proposed. This paper investig.tes using.2008-2013 g.ospatial corn, soybean and wheat planting.frequency data layers to create three corresponding.sing.e 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 sing.e 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 Ag.icultural 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 Ag.ncy （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 g.eat potential to improve ASF accuracy, efficiency and crop estimates.

关键词： cropland data layer crop planting.frequency data layers automated stratification crop specific stratification multi-crop stratification

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