THE AREA FRAME: A SAMPLING BASE FOR ESTABLISHMENT SURVEYS Jeffrey Bush, Carol House, National Agricultural Statistics Service Jeffrey Bush, NASS, Room 301, 3251 Old Lee Highway, Fairfax, Virginia 22030 KEY WORDS: Area frame, stratification, primary objectives. Area frame samples are used alone and in sampling unit combination with list samples (multiple frame). NASS contacts approximately 50,()()() farm establishments each Area frame methodology has fonned one of the year through their area frame sampling procedures. cornerstones of probability sampling for several decades. While area frames are frequently used in urban setti ngs This section updates the work of Cotter and Nealon as it for household surveys and population censuses, those describes the procedures used by NASS to construct area with a rural focus have proved valuable for targeting frames and sample from them. It discusses data farm establishments to provide basic statistics on collection procedures, estimators, and costs associated agriculture and ecological resources. Colter and Nealon with these different activities. Finally it discusses outline the advantages and disadvantages of area frame methods to objectively assess the "aging" of an area methodology. They state that area frames are highly frame. versatile sampling frames providing statistically sound estimates based on complete coverage of land area. Area Frame Construction and Sampling Although costly to build they are generally slow to become outdated. However, area frame sampling is NASS constructs area frames separately by state and generally less efficient than list sampling for targeting maintains one for every state except Alaska. Generally, any individual item and is inadequate for estimating rare two new frames are constructed each year to replace out­ populations. dated ones. The most recent frame construction was for Oklahoma. It became operational in lune 1993. This This paper describes four different area frame frame will be used as the "example" throughout this methodologies currently in use as a base for sampling in paper. rural areas. These are: a) the area frame used by the United States Department of Agriculture's (USDA) Frame construction produces a complete listing of National Agricultural Statistics Service; b) the area parcels of land, averaging six to eight square miles in frame used by Statistics Canada for agricultural size, throughout a state. These parcels selVe as the statistics; c) the hexagonal area frame used by the U.S. primary sampl ing uni cs (PSUs) in a two stage design, and Environmental Protection Agency; and d) the area frame each contain a varying number of population units or used by the USDA's Soil Conservation SelVice for the segments. The sampling process selects PSUs, and only National Inventory Survey. The paper's greatest those selected PSUs are broken down into segments. emphasis is on the NASS area frame. For this frame, the This two stage process saves considerable time and authors provide additional detail on area frame money over that required to break the entire land area construction, sampling, data collection and estimation. into segments. The paper provides a profile of costs associated with these activities, as well as procedures to assess quality Construction of and sampling from an area frame deterioration in an "aging" frame. involves five basic steps: 1) detennining specifications for the frame; 2) stratifying the land area and delineating NASS AREA FRAME PSUs within each stratum, 3) allocating stratum level optimal sample sizes; 4) creating sub-strata and selecting The National Agricultural Statistics Service (NASS) is PSUs; and 5) selecting segments within PSUs. Each step the major data collector for the U.S. Department of is discussed in detail below. Agriculture. As such it has responsibility to provide timely and accurate estimates of crop acreages, livestock Frame Specifications inventories, farm expenditures, farm labor and sim ilar agri cultural items. NASS also provides statistical and The specifications for building an area frame consist of data collection services to other Federal and State strata definitions and target sizes for both PSUs and agencies. They have used an area sampli ng frame segments within each stratum. Statisticians define these extensively for over 30 years in the pursuit of these by examining previous survey data, and assessing 335 urbanization and other trends in the state's agriculture. Stratj fi cAtjon and Delineation of PSUs Table I lists the frame specifications for the Oklahoma framc. Once strata defi nitions are set, the stratification process divides the land area of the state into PSUs and assigns Stra ta are based on general land usage. A typical NASS each to the appropriate land use strata. Each PSU must area frame employs one or more strata for land in confonn to the definition and target size outlined for its intensive agricultural (SO percent or more cuhivated), particular stratum. PSU boundaries become a permanent extensive agricultural (IS to SO percent cultivated), and part of the area frame and must be identifiable for the life range land (less than IS percent cultivated). Less of the frame. Thus the stratifier uses only the most frequently an area frame contai ns "crop specific" strata. pennanent boundaries available when drawing offPSUs. Thi s occurs when a high percentage of the land in a state Acceptable boundaries include pennanent roads, rivers, is dedicated to the production of a specific type of crop, and rai lroads. The final product of the stratification such as citrus in Florida. In addition, each area fram e process is a "frame" file which contains a record for uses an agri-urban and commercial stratu m (more than every PSU in a state. Specifically, each record includes 100 homes per square mile) plus a non-agricultural the PSU number, stratum assignment, county, and size. stratum including such entities as military bases, This frame file is maintained over the life of a frame as airports, and wildlife reserves. Finall y, large bodies of the sampl ing base. water are separated into a water stratum. Prior to 1990 the process of stratification used paper Boundary points for agricultural strata are generally maps, aerial photography, satellite imagery, and a restri cted to a set of standardized breaks: 15 , 25, SO and considerable quantity of skilled labor. The end product 75 percent cultivated. To delennine the exact breaks for was a frame delineated on paper U.S . Geological Survey a given state, the percent cultivated for each segment I: 100,000 scale maps. In 1990, NASS implemented its sampled under the old frame is calculated from survey Computer Aided Stratification and Sampling System data. The resulting distribution is examined using the (CASS). CASS automates the stratification steps on a cumulative square root of frequency rule proposed by graphical workstation using digital satellite imagery and Dalenius and Hodges. The standardized breaks may be li ne graph (road and waterway) data from the U.S. collapsed or expanded based on the structure of the Geological Survey . distribution. The di gital satellite imagery employed by the CASS Two criteria are the most imponant for detennining system is currentl y obtained from the thematic mapper target sizes for PSUs and segments within strata: (TM) sensor on the LANDSAT-S satellite. The TM has availability of good natural boundaries and the expected a spatial resolution of 30 meters and is made up of 7 num ber of farm establishments. Generally, a lack of spectral bands. TM bands 1-5 and 7 reside in the good boundaries will prompt the use of larger target reflective region of the spectrum while band 6 is located sizes, wh il e a large expected nu mber of fann in the thermal infrared region. NASS experience with the establishments will prompt sma ller target sizes. image ry shows that bands 2 , 3, and 4 highlight cultivated areas of land most accurately. Table 1: Ok1ahoma Frame Specifications Primary Sampling Unil Size Segment Stratum Definition Size Minimum Desired Maximum (sq. miles) (sq. miles) (sq. miles) (sq. miles) 11 >75% CULTIVATED 1.00 6.0 · 8.0 12.0 1.00 12 51-75% CULTIVATED 1.00 6.0·8.0 12.0 1.00 20 15-50% CULTIVATED 1.00 6.0·8.0 12.0 1.00 31 AGRl-VRBAN:>loo HOMFJSQMI 0.25 1.0 · 2.0 3.0 0.25 32 COMMERCIAL:> 100 HOMFlSQMI 0.10 0.5· 1.0 1.0 0.10 40 < 15% CULTIVATED 3.00 18.0·24.0 36.0 3.00 50 NON-AGRICULTURAL 1.00 none 50.0 ppsi 62 WATER 1.00 none none not sampled I ...eg mcn s are SC'CClcu Wl m prouaJIJI,y proportlOna to sIre; I.e. r .>u S arc IrC31cu as scgmen s. 336 While TM data is very useful in providing infonnation 15,000 PSUs and then one segment per selected PSU. with respect to land usage, its large scale (30 meier The sampling process is described in more detail below. resolution) renders it practically useless for identifying good PSU boundaries. Therefore the CASS system also Following stratification a multivariate optimal allocation uses di gital files of U.S. Geological Survey 1:100,000 analysis is performed to allocate the flfst stage sample of scale maps, in which feature class codes are assigned to PSUs between land use strata. This is a multivariate all roads, water, railroads, power lines, and pipelines. procedure because the area frame must target a variety of The CASS system incorporates the road and waterway agricultural items. The analysis requires the following data from these fil es and overlays it on the TM imagery. inpUls: a) population counts of segments per stratum; b) estimated tOials of important commodities from previous Personnel use a mouse and a "drawing" program to year's survey; c) standard deviations from previous delineate boundaries of the PSUs and label them with survey derived by locating old segments in the new their appropriate stratum number and sequence.