Effects of sampling approaches on quantifying urban forest structure
Bibliographic Data
| ID | 21469351 |
|---|---|
| Authors | Jing Jin (0000-0001-9032-521X, Tsinghua University), Jun Yang (0000-0001-6740-4358, Tsinghua University, corresponding author) |
| Year | 2020 |
| Volume | 195 |
| Pages | 103722 |
| Publication date | 2020-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Landscape and Urban Planning (JOURNAL) |
| Journal identifiers | ISSN: 0169-2046 • E-ISSN: 1872-6062 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.landurbplan.2019.103722 |
| OpenAlex | W2992195303 |
| Language | EN |
| References cited | 34 |
Beijing · Biology · China · Geography · Population · Sample size determination · Sampling design · Simple random sample · Species richness · Statistics · Stratified sampling · Systematic sampling · Urban forest · Computer Science · Environmental Science · Land Use and Ecosystem Services · Mathematics · Urban Agriculture and Sustainability · Urban Green Space and Health · Ecology · Forestry
Urban forests and pollution mitigation
The role of trees in urban stormwater management
Socioeconomics drive urban plant diversity
Global Change and the Ecology of Cities
Comparison of Convenience Sampling and Purposive Sampling
A Quantitative Review of Urban Ecosystem Service Assessments
Community Leaders and the Urban Forest
Urban tree cover change in Detroit and Atlanta, USA, 1951–2010
| Highly cited | No |
|---|