Journal of Arboriculture 31(5): September 2005 209 COMPARISON OF TWO SAMPLING METHODS FOR ESTIMATING URBAN TREE DENSITY By Ivan André Alvarez1 , Giuliana Del Nero Velasco2 Ana Maria Liner Pereira Lima3 , Henrique Sundfeld Barbin1 , and Hilton Thadeu Zarate do Couto4 , Abstract. Sampling can be used as a method for urban tree inventory estimation. There are several sampling methods available, and choices for urban tree inventory methods vary according to the place to be studied and the urban tree conditions. This study compared the results of simple and stratified random sampling methods with those of a total district tree census. The simple random sampling error was 17%, and the coefficient of variation was 47%. The stratified random sampling errors varied from 19% to 60%, and their coefficients of variation ranged from 32% to 70%, depending on the stratum. The Shannon diversity index (SDI) was low in the census (3.07), as in the simple random sampling (1.27). The total number of trees and the number of trees per kilometer of sidewalk calculated by the simple random sampling were similar to those obtained by the census. Because the sampling error obtained by stratified random sampling was higher than for that obtained by simple random sampling, the use of stratified random sampling was not advantageous when compared with simple random sampling. Furthermore, the stratified random sampling procedure was more complex. Key Words. Inventory; sampling; urban trees. Urban forest research has focused on tree surveys to assist planning by municipalities. Although a total tree survey is a difficult undertaking, there are statistical sampling methods that describe the whole from population samples. The use of sampling as a research tool can be applied by sampling city blocks and number of trees per lineal kilometer. By means of a sampling inventory, it is possible to draw some conclusions, such as the frequency of species, their diversity, and species’ adaptation to the site (Chacalo et al. 1994). Once the limits and characteristics of the population of street trees are known and the desired level of precision is established, the use of sampling techniques constitutes a procedure of significant efficiency for street tree evaluation. Using rectangular sample plots and number of trees per kilometer of forested sidewalk as main variables, simple random sampling procedures provided a significant efficiency for street tree evaluation, as previously demon- strated by Milano (1994). However, population heterogene- ity can introduce sampling errors when the simple random sampling method is used. Stratification can be used to increase survey precision when it is extrapolated for the total population once the characteristics of the strata are taken into account. The population can be divided in subpopulations, so that each one can be more homogeneous. This division in layers is called a stratum (Cochran 1977). Couto (1994) showed that stratified random sampling can be very useful for urban forest surveys. The strata can be selected based on the district, street tree density, or a group of blocks, depending on the criteria chosen for grouping the sampling units for stratum composition. To obtain a coherent survey, the strata should possess a homogeneity of measured values. Thus, a precise median value of any stratum estimate can be obtained using a small sample of that stratum. According to Cochran (1977), those estimates can be combined to produce an accurate estimate of the total population. Jaeson et al. (1992) used a method that combined different-sized blocks to identify the strata. The mean number of trees per randomly selected block was multi- plied by the number of trees per block to estimate the total number of trees. The choice of sampling type depends on a previous analysis or pre-sample of the area to be studied. According to Milano et al. (1992), it is necessary to quantify the forest and know its distribution in urban areas by defining its characteristics and quality. Determining the purpose of the inventory is important in choosing the most appropriate methodology because each methodology presents a different degree of precision (Grey and Deneke 1978). According to Couto (1994), determining the most appropriate sampling type depends on the distribution of the measurements in space and time. A common criterion for choosing sampling techniques is species present and their relative frequency. This study compares simple and stratified random sampling methods with a total tree survey of a district that has varying characteristics. MATERIALS AND METHODS The city of Piracicaba is located at 22°42′ 30.9′′ S latitude and 47°38′ 01′′ W longitude. The tree inventory was performed in Santa Cecília district (Figure 1), located in the East Zone of Piracicaba, São Paulo, Brazil. The residents of Santa Cecília are in the middle- and upper-middle-class income groups. ©2005 International Society of Arboriculture
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