Page 188 - Special Topic Session (STS) - Volume 1

STS 423 Avery S. et al.

Figure 3: (left) CDL Cultivated Layer based Primary Sampling Unit with percent
cultivation; (right) the same area sampling frame with CDL derived strata, where strata
11 represents greater than 75% cultivated, strata 12 represents 51-75% cultivated,
strata 20 represents 15-50% cultivated, and 40 represents less than 15% cultivated.
resents less than 15% cultivated.

Though the new fully-automated stratification method has improved
stratification efficiency, objectivity, and accuracy in the intensively cropped
areas, it achieves lower accuracies in low or non-agricultural areas.
Consequently, a hybrid approach that integrates the automated stratification
results with manual editing/review methods was implemented operationally.
Since 2014, ten state-level area frames were built using the new integrated
operational process. Boryan and Yang (2017) describe the area frame
improvements, which include improved accuracy (30% improvement) and a
reduction in labor costs, as well as other measurement criteria. As an example,
the traditional Oklahoma area frame was constructed in 4,552 employee
hours, while the hybrid frame required 1,980 employee hours.

June Area Survey Imputation
The JAS is the largest NASS annual survey in which approximately 9,000
square mile sample segments are visited by enumerators at the beginning of
June to collect crop type and acreage information. Estimates of crop acreage
and livestock inventories are based on these survey data (USDA/NASS,
Understanding Statistics 2018). Although the JAS sampling frame provides
complete coverage of all agriculture activity occurring on land pertaining to
the target population, operator non-response and inaccessibility leads to the
need to impute missing information. JAS imputation was traditionally based
on historical records, which are not always available for the selected samples.
The CDL data provide a reliable alternative data source for imputation.
Now NASS statisticians import the digital JAS segment boundary files directly
into CropScape for analysis and use CDL data to 1) identify field-level planting
history and crop rotation cycles, 2) confirm the area of irregularly shaped
fields, and 3) review and resolve conflicts in reported data on segment-specific

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