Open AccessComparison Of Two Sampling Methods For Estimating Urban Tree Density
Author(s) -
I. A. Alvarez,
Giuliana Del Nero Velasco,
Henrique Sundfeld Barbin,
Ana María,
Liner Pereira Lima
Publication year - 2005
Publication title -
arboriculture and urban forestry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.222
H-Index - 47
eISSN - 2155-0778
pISSN - 1935-5297
DOI - 10.48044/jauf.2005.027
Subject(s) - stratified sampling , simple random sample , sampling (signal processing) , statistics , systematic sampling , sampling design , cluster sampling , poisson sampling , mathematics , slice sampling , importance sampling , computer science , monte carlo method , population , demography , filter (signal processing) , sociology , computer vision
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.