Integrated_stand_growth_model_system

It is a model which can predict the individual-tree growth with forest management considered, including diameter at breast height (DBH), tree height, under branches height (UBH), crown width, crown height, biomass and mortality.

ForestryIndividual-tree growth

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Contributor(s)

Initial contribute: 2018-08-11

Authorship

:  
Nanjing Normal University
:  
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry
:  
yangtd@ifrit.ac.cn
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Classification(s)

Method-focused categoriesProcess-perspectiveBiological process calculation

Detailed Description

Chinese {{currentDetailLanguage}} Chinese

Model Information

Plantation is an important part of forest in China. This model can predict the growth of individual trees in even-aged plantation.

It is a model which can predict the individual-tree growth with forest management considered, including diameter at breast height (DBH), tree height, under branches height (UBH), crown width, crown height, biomass and mortality.

Firstly, the model read shapefile data of forest. There are 2 types of shapefile data which you can select. Point data contained location and initial size of each tree in one plot. Polygon data are the distribution every stand, and have tree information including density, mean DBH and so on. And users can simulate the individual tree location by the information polygon data provided. DEM data of forest farm should also be input. User can choose different calculation models and fill in related parameters. The model can predict individual tree growth. The results of prediction will be output every interval period. When the number of trees changes because of cutting or death, the states of trees will be output, too.

Module Introduction

Input and Output

Reading DEM data and shapefiles of stand or plot, the model can get the information about locations and initial DBHs (and Height). The result of prediction can be saved in shapefiles and output. 

Growth prediction of trees DBH

Based on the locations of trees, initial DBHs and age, 16 different models can be used to predict the growth of DBH from initial age to end age. 

Growth prediction of trees height

There are 39 different models which can be selected to calculate the growth of tree height by using the DBH data. 

Growth prediction of trees UBH

There are 11 different models which can be selected to calculate the growth of tree under branches height. 

Growth prediction of trees crown height

The crown height model based on spatial structure parameters was used to calculate the crown height in each years. 

Growth prediction of trees crown width

There are 25 different models which can be selected to calculate the growth of tree crown width. 

Growth prediction of trees biomass

There are 7 classical models which can be selected to calculate the biomass of individual trees. 

Growth prediction of trees mortality

There are 10 different mortality models which can be selected to calculate the survival probability of individual trees. 

Marking cutting trees

According to the forest management target, this function can supply 5 cutting models to mark the cutting tree and realize the target. 

 

 

 

 

模型元数据

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Zaiyang Ma, Tingdong Yang (2018). Integrated_stand_growth_model_system, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/0b6c1ce7-b3c1-4bf7-82f9-aa95781f26b5
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Contributor(s)

Initial contribute : 2018-08-11

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Authorship

:  
Nanjing Normal University
:  
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry
:  
yangtd@ifrit.ac.cn
Is authorship not correct? Feed back

History

Last modifier
Zaiyang Ma
Last modify time
2023-02-03
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