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classification based on satellite imagery to improve the precision of forest inventory area
estimates. Remote Sensing of Environment, 80, 1–9.
McRoberts, R. E., and Wendt, D. G.(2002). Implementing a land cover stratification on-the-fly. In
R.E. McRoberts, et al., (Eds.), Proceeding of the third annual forest inventory and analysis
symposium, Gen. Tech. Rep. NC-230. St. Paul, MN: U.S. Department of Agriculture, Forest
Service, North Central Research Station: 137–145.
Nusser, S. M., & House, C. C. (2009). Sampling, data collection, and estimation in agricultural
surveys. In D. Pfeffermann & C. R. Rao (Eds.), Handbook of statistics 29A, sample surveys:
Design, methods and applications (pp. 471–486). Amsterdam: Elsevier.
Perry, C., & Gentle, J. (2000). Optimal stratification of area frames. In Proceedings of the second
international conference on establishment surveys survey methods for businesses, farms, and
institutions, Buffalo, New York. June 17–21, 2000.
Perry, C. R. (2000). Improving the efficiency of the arkansas area frame using categorized satellite
imagery, NASS Technical Report, U.S. Department of Agriculture.
Pradhan, S. (2001). Crop area estimation using GIS, remote sensing and area frame sampling.
International Journal of Applied Earth Observation and GeoInformation, 3(1), 86–92.
QGIS. (2017). A free and open source geographic information system. http://qgis.org/en/site/. Last
accessed 24 April 2017.
Tsiligirides, T. (1998). Remote sensing as a tool for agricultural statistics: A case study of area
frame sampling methodology in Hellas. Computers and Electronics in Agriculture, 20, 45–77.
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USGS. (2017c). Landsat data missions: Landsat data access. https://landsat.usgs.gov/landsat-dataaccess. Last accessed 23 Apr 2017.
Vogel, F. A. (1995). The evolution and development of agricultural statistics at the United States
Department of Agriculture. Journal of Official Statistics, 11, 161–180.
Vogelman, J. E., Howard, S. M., Yang, L., Laron, C. R., Wylie, B. K., & Van Driel, N. (2001).
Completion of the 1990’s National Land Cover Data Set for the conterminous United States
from Landsat Thematic Mapper data and ancillary data sources. Photogrammetric Engineering
& Remote Sensing, 67, 650–662.
Workneh, F., Tylka, G., Yang, X., Faghihi, J., & Ferris, J. (1999). Regional assessment of soybean
brown stem rot, phytophthora sojae, and Heterodera glycines using area-frame sampling:
Prevalence and effects of tillage. Phytopathological, 89(3), 204–211.
298
C. G. Boryan and Z. Yang