Development of an Integrated DBH Estimation Model Based on Stand and Climatic Conditions
- Authors
- Piao, Dongfan; Kim, Moonil; Choi, Go-Mee; Moon, Jooyeon; Yu, Hangnan; Lee, Woo-Kyun; Wang, Sonam Wangyel; Jeon, Seong Woo; Son, Yowhan; Son, Yeong-Mo; Cui, Guishan
- Issue Date
- 3월-2018
- Publisher
- MDPI
- Keywords
- climate factor; diameter at breast height (DBH); semi-variogram; residuals; national forest inventory
- Citation
- FORESTS, v.9, no.3
- Indexed
- SCIE
SCOPUS
- Journal Title
- FORESTS
- Volume
- 9
- Number
- 3
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/76803
- DOI
- 10.3390/f9030155
- ISSN
- 1999-4907
- Abstract
- Using Korean National Forest Inventory (NFI) data, our study developed a model to estimate stand mean diameter at breast height (DBH) reflecting the influence of site and climate factors on forest growth for the major tree species in South Korea. A DBH estimation model was developed using stand-level variables (stand age, site index and number of trees per hectare) as independent factors. The spatial autocorrelation of residuals of the model was identified using semi-variogram analysis for each tree species. Further, a residual model, in which residuals were estimated by climatic factors (mean temperature, sum temperature in the growing season and precipitation), was developed assuming that the spatial autocorrelation of residuals reflects the differences in regional climatic conditions. Linear regression analysis showed that residuals of all tree species were significantly correlated with temperature and precipitation. The DBH and residual models were integrated to estimate the current DBH under different climatic factors (temperature and precipitation) and stand-level variables. This model had high reliability (R-2 = 0.74-0.79), and no obvious dependencies or patterns in residuals were noted. Our results indicated that temperature increases caused by climate change would negatively affect the DBH estimate of coniferous trees, but not of oak species.
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Collections - College of Life Sciences and Biotechnology > Division of Environmental Science and Ecological Engineering > 1. Journal Articles
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