2005Arboriculture & Urban ForestryOpen access

Comparison Of Two Sampling Methods For Estimating Urban Tree Density

I. A. Alvarez, Giuliana Del Nero Velasco, Henrique Barbin, Ana Maria Liner Pereira Lima, Hilton Zarate do Couto

Open full text 17 citations

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.

Open-access reader

About this research paper

What this paper is about

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.

Why it matters

OpenAlex reports 17 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available 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 concepts: Stratified sampling, Simple random sample, Sampling (signal processing), Statistics, Systematic sampling, Sampling design, Cluster sampling, Poisson sampling

Related papers

Back to paper searchBrowse research topicsOriginal source
Comparison Of Two Sampling Methods For Estimating Urban Tree Density — Research Paper | ScholarLens