Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest

Growth model provides an efficient way in preparing resource forecasts especially on decision making options and silvicultural alternatives. Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, diameter increment models...

Full description

Saved in:
Bibliographic Details
Main Authors: Nurashikin Saaludin, Suriyati Harun, Yasmin Yahya, Wan Suriyani Che Wan Ahmad, (UniKL MIIT)
Format:
Published: ACM 2014
Subjects:
Online Access:http://dl.acm.org/citation.cfm?id=2557992
http://localhost/xmlui/handle/123456789/6307
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Kuala Lumpur
id my.unikl.ir-6307
record_format eprints
spelling my.unikl.ir-63072014-04-24T03:33:01Z Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest Nurashikin Saaludin Suriyati Harun Yasmin Yahya Wan Suriyani Che Wan Ahmad (UniKL MIIT) Diameter increment multiple linear regression model validation Growth model provides an efficient way in preparing resource forecasts especially on decision making options and silvicultural alternatives. Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, diameter increment models were developed for individual tree of dipterocarpaceae and non-dipterocarpaceae tree species in semi-evergreen forest in Seam Reap, Cambodia. Regression analysis is the preferred technique used in growth and yield modeling in forestry. The stepwise ordinary least square (OLS) regression technique has been used to fit model parameters. The predictor variables in both models represent tree size attribute, which are diameter at breast height (DBH) and basal area (BA) and also the tree position attribute, which is sum of basal area (m2) in trees with DBHs are larger than subject tree’s DBH (BAL). Each model was then validated and found to be good predictor by the small values of the four lacks of fit statistics. As a result, both of the models give better fit especially with regards to bias and relative bias. 2014-04-24T03:33:01Z 2014-04-24T03:33:01Z 2014-01 978-1-4503-2644-5 http://dl.acm.org/citation.cfm?id=2557992 http://localhost/xmlui/handle/123456789/6307 Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication; ACM
institution Universiti Kuala Lumpur
building UniKL Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kuala Lumpur
content_source UniKL Institutional Repository
url_provider http://ir.unikl.edu.my/
topic Diameter increment
multiple linear regression
model validation
spellingShingle Diameter increment
multiple linear regression
model validation
Nurashikin Saaludin
Suriyati Harun
Yasmin Yahya
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
description Growth model provides an efficient way in preparing resource forecasts especially on decision making options and silvicultural alternatives. Diameter increment is one of the common and important tree characteristics used in forest management decision making. In this paper, diameter increment models were developed for individual tree of dipterocarpaceae and non-dipterocarpaceae tree species in semi-evergreen forest in Seam Reap, Cambodia. Regression analysis is the preferred technique used in growth and yield modeling in forestry. The stepwise ordinary least square (OLS) regression technique has been used to fit model parameters. The predictor variables in both models represent tree size attribute, which are diameter at breast height (DBH) and basal area (BA) and also the tree position attribute, which is sum of basal area (m2) in trees with DBHs are larger than subject tree’s DBH (BAL). Each model was then validated and found to be good predictor by the small values of the four lacks of fit statistics. As a result, both of the models give better fit especially with regards to bias and relative bias.
format
author Nurashikin Saaludin
Suriyati Harun
Yasmin Yahya
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
author_facet Nurashikin Saaludin
Suriyati Harun
Yasmin Yahya
Wan Suriyani Che Wan Ahmad
(UniKL MIIT)
author_sort Nurashikin Saaludin
title Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
title_short Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
title_full Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
title_fullStr Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
title_full_unstemmed Modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
title_sort modeling individual tree diameter increment for dipterocarpaceae and non-dipterocarpaceae in tropical rainforest
publisher ACM
publishDate 2014
url http://dl.acm.org/citation.cfm?id=2557992
http://localhost/xmlui/handle/123456789/6307
_version_ 1644484808436350976