5. CHAPTER
ONE
INTRODUCTION TO IPTIM
Iptim (Integrated Planning for Timberland Management) is a timberland management planning tool that covers the
planning process from the valuation of a potential investment to the operational planning for the existing portfolio. It
provides a tool to optimise the sustainable utilization of wood resources.
Iptim contains modules for:
• Sample plot inventory and stand data management, including map data
• Stem volume, growth and yield modelling based on inventory data
• Growth projections and forestry operation modelling
• Financial analysis: optimisation of financial indicators (NPV, NAV, IRR), sensitivity analysis
• Reporting of the results of the above mentioned planning stages
Delivery:
• Iptim is delivered as a SaaS application; software as a service
• Iptim is a desktop application that can be easily downloaded from the internet by the user and can be used right
away.
1.1 Overview of this tutorial
The aim of this tutorial is to go through the various functionalities of Iptim and to familiarize you with the application
logic. The tutorial goes through Iptim in a step by step manner, starting from scratch. You should proceed through this
tutorial in the predetermined order and avoid skipping any steps.
Before you start going through this tutorial, make sure you have the file sampleplots.xls, which was provided together
with this tutorial. It is an excel file containing a simple dataset consisting of stands, sample plots and sample trees. We
will use this dataset throughout the tutorial.
You can progress through the tutorial by clicking next button in the top right corner and go back by clicking the
previous button. You can also go from a section to another using the Table of contents link.
1.2 Installation
Iptim is installed by double clicking the Iptim.air pacakage. Adobe Air 3 Runtime needs to be installed. We recom-
mend that the latest version of Adobe Air 3 Runtime is installed before installing Iptim.
Adobe Air 3 Runtime can be downloaded from here http://get.adobe.com/air/
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1.3 Signing in
Once Iptim is started, the Home view appears. Before you can start using Iptim you need to sign in. The the sign in
button is in the top right corner of the Home view.
When sign in button is clicked, the sign in dialog appears. By entering your username and password you can sign into
Iptim.
After signing in, you will be able to access all of the sessions in Iptim according to your own user permissions. You
can simply click in a session’s name to navigate between sessions.
1.4 Support
Iptim has an integrated feature for support. If an issue has been found, the user can simply click on the support button
that can always be found on the upper right corner.
This unique feature will serve as the main platform to comunicate with Iptim’s developers.
In order to use it, all you need is to fill out the fields as instructed bellow:
• Subject: Write a headline for the issue. The subject is ideally something short yet descriptive enough.
• E-mail: You should add your e-mail
• Description: You should describe, as detailed as possible, the issue you are experiencing or the suggestion you
have. When reporting an error, please include what you were attempting to do when the message appeared.
• Include screenshot: If this option is activated, Iptim will also attach a screenshot to the Issue report.
Press the “Create Issue” button in order to submit the issue.
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Alternatively, the support screen will also appear automatically if Iptim does not behave as expected for any reason.
If that ever happens to you, it is advisable to follow the same steps listed above, adding in the Description field all the
information you think could help the developers solve the problem as quickly as possible.
When you create an issue, you will receive an e-mail updating you about the measures being taken to attend to your
request.
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9. CHAPTER
TWO
PROJECT BASICS
In the Project section you can manage your projects and create new ones. A project is Iptim’s basic working unit and
typically encompasses a single manageable unit: a plantation or a natural forest holding. The geographic extent of a
single project can be from few hectares up to hundreds of thousands of hectares.
A project contains one or more sets of data. Typically, one data set represents the state of the project’s timberland at
one point in time. For example, a project can have multiple sample plot inventory data sets that represent the project’s
timberland in different points in time.
Each project requires an initial structure, which defines what type of data the project contains. These structures can
be defined in different ways: you can either copy a structure from an existing project or select a structure from data
structure templates. If you selected a structure from an existing project, you can also copy data for the new project
from the existing project.
Projects in Iptim are very flexible, making it a powerful tool to better encompass your company’s needs and realities.
2.1 Project browser
2.1.1 Creating a new project
To create a new project, click the new button on the application window and note that three options will appear. These
options mostly differ on how their packages will be structured.
• New Project: Will create a project from scratch. This option will give you the chance to define a new project
structure that fits your current data. If you decide to create a new project, you will also need to define the data
sets that will compose the new project. In order to do that, click on the new button on top of the data set field
and select either copy from template or copy existent data, much like described bellow.
• Copy template project: This option will allow you to select from very basic pre-defined structure templates
instead of creating one from scratch. The template can also be adapted according to your needs.
• Copy existing project: By selecting this option you will create an exact copy of an existing project.
After selecting the most appropriate option, a new project settings view appears. In this view you can set your project’s
name and description.
2.1.2 Loading the new project
Projects are loaded by selecting the desired project from the browser and then a data set that belongs to it. Next, you
need to either click load on the top right of the application, or double click the data set name. Note that a project is
not automatically loaded when creating a new one; the user must load it.
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Figure 2.1: The project Browser. You can create new projects or add data sets by clicking on the new button.
Each of these data sets is a piece of forest data that will have an individual structure. You can load as many data sets
as you want as long as they belong to the same project.
When a data set is loaded, its name appears on the top right of the application and a lock symbol appears before the
data set’s name in the browser. When you see the lock symbol, it means that project is locked and its contents cannot
be modified by any other user aside from the one who has locked it. You can easily find out who has locked the project
by landing the cursor on the lock symbol.
2.1.3 Saving and closing a project
To save the changes in the active project, click on the save button on the top right of the application. This will save all
changes you have made to your project. To close the active project, click on the close button on the top right of the
application.
2.2 Project structure
2.2.1 The Project structure editor
Project structure means simply the project’s data model, or data models, if a project contains more than one data sets
or packages. The project structure editor presents the project data structure as a hierarchical tree. One example is the
project data structure consisting of three data levels: Stand, Sample plot and Tree. Each of these three levels has a
number of properties (a.k.a. variables or attributes), such as Stand ID, Plot ID and Tree ID.
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Figure 2.2: You can also click on the more button to access more options.
Figure 2.3: Project structure view.
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2.2.2 Adding a new property
To add a new property, first select a level to which you want to add the new property and then click new button on the
top right. After clicking the new button, the property type selector appears.
Property types:
• Numeric variables: The most common type of variables. They quantify the data set and may be optimized.
Common numerical variables are area, age and tree volume.
• Text variables: Text variables are used to further define the data set. These are not directly used in the optimiza-
tion. Examples of text variables are farm and region names.
• Date variables: Variables that specify a point in time shaped as a date. They may be optimized. Inventory and
planting dates could be added as date variables.
• Category variables: Variables that have pre-determined values that organize the data by adding categories to it.
Examples of categorical variables are tree species, soil types, etc.
Do not add any properties yet! We’ll add new properties on the go when we import our sample plot data set.
2.2.3 Editing properties
It is possible to easily edit any of the Project Structure’s properties. To do so, select the property that needs to be
modified and click on edit. In this view you will be able to change property settings such as name and description.
When editing properties, it is also possible to define if filling that property is required or not. If so, one needs to set a
default value for that property which will be used if the field is left blank. While editing properties, one is also able to
add, remove or modify categories of categorical variables.
2.2.4 Modifying categorical variable options
As previously stated, categorical variables are used to categorize data into previously defined options. Once created,
these categories will appear as drop-down list that will further validate data. It is possible to add, remove or modify
these categories by editing the option list in the property editor menu.
2.3 Project - Importing data
2.3.1 Data import basics
Iptim’s data import tools allow you to upload your existing stand register or forest inventory data and use them in
Iptim. You can import data from various formats, such as Excel spreadsheets and various types of text files. You can
have data on different levels (such as stand, sample plot, or tree), and you can have as many properties (a.k.a. variables
or attributes) per level as you wish.
2.3.2 Importing data from Excel spreadsheets
To start data import, go to Project/Import data and select the appropriate format: either xls or xlsx. In the next step,
select the data files you want to import into Iptim. You can add and remove data files using the add + and remove -*
buttons in the top-right. You can import data from one or more files of each type each time.
Select the ‘sampleplots.xls’ that is included in this tutorial package by clicking the add + button in the top-right and
selecting the file using the system dialog. After that, proceed to the next step using the next button in the bottom-right.
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Figure 2.4: Importing from a spreadsheet.
In the next step you will need to link the data sheets as they are organized in Excel to the data levels defined in the
project structure. Simply select a data level on the left and an Excel data sheet on the right pannel and press the map
button on the center. This will signal to Iptim that the selected data sheet is the source of information that will be
imported into the data level.
Next, proceed to section assigning-key-values-and-levels
2.3.3 Importing data from text files
It is also possible to import data from common text files.
2.3.4 Assigning key columns and levels
In this stage you need to select the key columns (in the imported data sheets) that will be used to map the relationships
between the data objects on the different levels. In the sample dataset (sampleplots.xls), for example, we need to
connect trees to sample plots, and sample plots to stands.
Key columns are values that are used to map individual trees to sample plots, and sample plots to stands. In the
example dataset (sampleplots.xls), each tree can be identified by tree_id, plot_id, stand_id and estate. This means that,
in order to get a unique id for a tree, you need to know its estate, stand, sample plot and tree id. The tree_id alone is
not unique, as many trees can have ids “1”, “2”, “3” and so on.
In order to connect two data levels, select the key columns they have in common, and maintain a hierarchical order. For
example: to map trees to sample plots, select the key columns of the following tree-level properties: estate, stand_id
and plot_id, in this order. Match this selection in the sample-plot properties.
To map sample plots to stands, select the key columns of the following sample plot-level properties: estate and
stand_id. Match this selection in the stand-level properties and click next.
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Figure 2.5: Linking from spreadsheet to data levels.
Figure 2.6: Assigning key columns.
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2.3.5 Mapping data file properties to Iptim’s properties
In this stage you need to map the data file columns to Iptim’s properties. On the left side you see your data model, and
on the right your input file columns.
You need to connect the input data columns to Iptim properties. This is done by selecting a data file column on the
right side and a corresponding Iptim property on the left side and by pressing Map. Remember to make sure you are
selecting columns and properties on corresponding data levels! You can see how the column area (ha) is mapped to
Area property on Stand level.
Figure 2.7: Mapping data.
Notice that there are a few columns that do not yet have a corresponding Iptim property. The input data has columns
estate, stand_id and plot_id on tree level, and estate, stand_id and inventory_date on sample plot level which we don’t
need to care about.
On the stand level, there are three columns we would like to import, but don’t have Iptim properties for: estate,
soil_class and soil_preparation. First, we will create a new property for the estate column. This is done by selecting
the estate column on the right side and by clicking the New property. This opens a new view where you should select
“Text variable” as the type of the new (estate) property, which again takes you to new view . Here you should set the
new property name (“estate”) and description and click save. Now you should have the new property Estate on the left
hand side data structure. Select it and column estate on the right and click Map.
Next, do the same for columns soil_class and soil_preparation, but select Categorical variable instead of Text variable.
Name the new properties Soil type and Soil preparation, and map the corresponding columns to Iptim properties. When
creating the new categorical properties, do not add any options for them, we’ll do that in the next stage.
After mapping the input data columns to the Iptim properties, you can proceed to next stage with the Next button.
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Figure 2.8: Creating a new Categorical variable.
2.3.6 Mapping property values
In this stage you need to map categorical variable values to categorical property options and do conversions for nu-
merical values, if needed. In our sample data set, we have one numerical variable that needs a conversion, and that is
sample plot area from the “area” property for the “Sample plot” level. The sample plot area should be in same units as
the stand area, which in this project is hectares. The sample plot area in the input data is, however, in square meters.
To convert the areas into hectares, select the sample plot “plot_size” from the list of properties, and set the conversion
factor to 0.00001. This should update the preview values.
After converting the sample plot areas, you need to map the categorical values into Iptim’s categorical property options.
The columns with categorical values in the input data are “tree_species”, “soil_class” and “soil_preparation”.
First, select the “Species” and you’ll see that it has only one unique data value: “Pinus spp.”. Our data model in Iptim,
however, does not have any corresponding options (values) for this property. Open the Option editor and add a new
option with new button. Give the option name “pine”, value “1” and description “Pine spp.” and close the editor.
After closing the editor, you should now have “pine” in the Iptim values listing. Select “pine” from Iptim values and
“Pinus spp.” from Data values and click Map option. This should map the “Pinus spp.” values from input data into
“pine” option in the Iptim’s species property.
Next, create new options for the categorial values of “soil_class” and “soil_preparation” columns and map the cate-
gorical values to the new options. After doing this, you’re almost done with data import!
Click the Start import process button on the bottom right and save your project by clicking on the save button in the
top right corner.
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19. CHAPTER
THREE
DATA
3.1 Data basics
In the Project view you can manage your projects and create new projects. A project typically encompasses a single
manageable unit: a plantation or a natural forest holding. The geographic extent of a single project can be from few
hectares up to hundreds of thousands of hectares.
A project contains one or more sets of data. Typically one data set represents the state of the project’s timberland at
one point in time. For example, a project can have multiple sample plot inventory data sets that represent the project’s
timberland in different points in time. Project also has a number of configuration settings related to measurement and
monetary units.
3.2 Project - Data
3.2.1 Overview
Data sheet view gives you the tools to view and modify your existing data and to add new data. By clicking on Data,
you will be able to see the data sheet containing the sample data set you just imported. Each row represents a single
stand. You can sort the stands by any of the columns, just by clicking the column.
3.2.2 Navigating in data view
The data model in Iptim is hierarchical, which means that in our sample data, sample plots are children of stands, and
trees are children of sample plots. You can move from stand level to it’s sample plots, by clicking the Open button of
the Sample plot column for the stand of your choice. And from sample plot level you can move to the tree level by
again clicking Open for the sample plot of your choosing.
You can go back up to sample plot and to stand level by clicking Back in the bottom left.
3.2.3 Modifying data
Modifying data is done by clicking on a cell and typing the value you wish. How the data input works, depends on
the column (property) type. For numerical columns you can enter only numbers and for text columns only text. For
categorical columns you can select only options that have been defined for that particular categorical variable. If you
wish to modify these options, or anything else related to data properties, you can do that in Project structure view.
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Figure 3.1: You may also change the view by selecting another data set using this drop-down menu.
3.3 Project - Map
3.3.1 Overview
Iptim’s map view allows you to visualize your data spatially and is another interface for the same data sets previously
visualized in the data sheet view.
3.3.2 Map Navigation
Using the buttons on the upper right side of the map view it is possible to navigate and zoom the map freely.
Alternatively it is possible to select the pan tool button on the right hand side of the screen to navigate by clicking,
holding and dragging the cursor anywhere on the map. You can also use your mouse’s scroll wheel to zoom the view
in and out.
3.3.3 Viewing data
When a stand is selected by pressing the selection tool button to the right, it is possible to view and modify all data
relevant to that specific stand, much like it was presented in Project - Data.
3.3.4 Adding and removing Layers
You can also add layers to the map as a way to visualize spatially specific stand data. In order to do so, click on the
Layer button and a menu will appear. This menu allows you to add, remove and edit map layers to fit your needs.
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Figure 3.2: Map view.
Figure 3.3: Click on the + button to create layers.
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For instance, you can add a layer that will visually differentiate stands containing different tree species. In order to to
that click on the add button and select tree species as the property, as the operator select equal to, under the value field
select a tree species, finally select a color that will characterize the newly created layer. When you are done, all you
need to do is to type a name for the layer on the upper field and click on the apply button.
Figure 3.4: Layer Menu.
You will see that a new switch button appeared under the inventory data themes field and a new color was added
to the legend field on the right pannel, also, the stands containing the selected tree species are now displayed in the
selected color.
The inventory data themes pannel allows you can manage all map layers. Under it you can turn map layers on and off,
as well as edit and remove newly created layers.
3.4 Project - Summary
In data summary section you can examine your data using data summary and visualization tools. These tools can help
you to gain better understanding of your data and to find ocasional errors that might be in the data. The section has two
views: summary and relationships, and you can move between the two views using the summary and relationships
buttons in the top right.
3.4.1 Summary view
In the summary view you need to select data level from the dropdown list, a classifier (“group by”) variable and a
numerical variable (“numerical values by”). This should show you basic descriptive statistics for all classes of the
selected numerical variable.
It is possible to select multiple classifiers and numerical variables by pressing the “Ctrl” key if you are using Iptim in
Windows or the “cmd” key if you are using the Mac version.
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Figure 3.5: You can also edit layers you have created.
Figure 3.6: You can easily switch views by selecting Relationships as displayed.
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For instance, select on the “stand” data level and click on “Main tree species” and then on “Tree.diameter”. The
table and the box chart your screen will be updated immediately with all the relevant statistics that summarize your
selection.
3.4.2 Relationships view
In the relationships view you can examine the relationships between numerical variables. This can be useful for
identifying outliers in the data, that might be caused by measurement errors.
Using the dropdown lists on the left side you can select the data level and which attributes should be represented in
each axis.
You can also add filters that will highlight data points in the plot. In order to do that you simply need to click on the
add filter button and select the appropriate data level, property, operator and value. As soon as a filter is created the
plot will be updated automatically.
Figure 3.7: You may also land your cursor in any data point to see more information.
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25. CHAPTER
FOUR
MODELING
Modeling section contains tools for modeling forest growth and yield (Modeling growth & yield), adding timber price
tables and defining your silvicultural and harvest regimes (Modeling regimes).
Growth & yield models are used in the planning computations for projecting the future growth and development of
your forests. Good growth and yield models are extremely important when predicting the future wood flows and also
the incomes and expenses.
Timber price tables are valuable inputs in the optimizations that will be soon carried out.
Regimes define your silvicultural and harvest activities. Iptim offers you tools for defining your own harvest and
silviculture regimes with as much detail as needed.
4.1 Modeling growth & yield
4.1.1 Creating a new growth & yield model
You can start modeling your growth and yield by creating a new growth model using the new button in the top left
of the Model/Growth and Yield view. After clicking new, you will be asked for name and description for you growth
model. Input these and continue by clicking confirm.
Alternatively, if there are any previously created models, you can select it and click on edit to view or edit it.
4.1.2 Estimating model parameters
Next, select a categorical variable from the left hand side list, and then select a growth model by clicking the Select
growth and yield models button. Select, for instance, “Linear volume growth model” and click Select. You can then
click on Select data, select a project, a data level and classifies leaving only relevant data to be modeled. For instance,
you can select to stratify the data using Soil Type in order to select only stands located in rich soils.
After this, click the estimate button and a menu should appear. If you click on estimate again a straight line should
appear in the graph on the right. This is a very simple linear growth model estimated using the project data.
4.1.3 Setting model parameters manually
As this straight line is clearly not a very good growth model, we should come up with a better one. Select “Chapman-
Richards volume growth model” from the list of models and set its parameter (coefficient) values manually like this:
B0 = 382.98
B1 = 0.0865
B2 = 0.7019
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Figure 4.1: Growth & yield model.
This should give you a nicer looking growth model.
Next, select the “poor” soil type from data partition list, select the Chapman-Richards model for it and set the same
parameter values for it also. Now we have defined growth models for both poor and rich soil types, although in this
case, the models are exactly the same.
Now you save your growth model and proceed forward by clicking confirm. Remember to save you project with the
save button under you project name.
4.1.4 Calibrating model parameters
You can also choose to calibrate the model that has been setup manually. To do so, you need to click the estimate
button, select the “Utilize original parameters (calibrate)” option and insert a value ranging from 0 to 1. This value
will serve as the weight your original parameters will have on the calibration. If the value is closer to 0, your original
parameters will have little weight on the calibration and the parameter values can be drastically changed. On the other
hand, if you believe your parameters are reliable, values closer to 1 will assure that the calibration will only modify it
slightly.
4.2 Modeling regimes
4.2.1 Creating a new regime
The regime modeling works in a similar fashion to inventory, timber prices and growth modeling. You can define
different regimes for different data partitions (or classes), such as different tree species or soil types. You can start
defining your regime by clicking the new button in the regime view.
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Figure 4.2: Calibrating model parameters.
4.2.2 Adding an operation
Select first “poor” soil type from the data partition list (the list on the top left corner). Next, start your regime by
selecting “Planting” from the Operation type dropdown list. Set planting age as zero and add the planting to regime
by clicking the + button.
4.2.3 Operation costs
After adding the planting, you can define the costs of planting. Costs are divided into labor, material and other costs.
Labor costs consist of labor requirement (e.g. working days per area unit) and labor cost (cost per day per area unit).
Material costs consist of material requirement (number of units per area unit) and material cost (cost per unit per area
unit). Other costs are a fixed sum per area unit. Together these will constitute the cost per area unit.
Other operation types are coppicing (another type of regeneration), silviculture, thinning and clearcut. Silvicultural
operations cover all other operations than regenerations or harvests. Thinnings are harvests during the rotation and
clearcuts are done at the end of a rotation.
4.2.4 Silvicultural operations
Next, add a fertilization and a weed control for the same year as the planting. Both of them are silvicultural operations,
so select “Silviculture” from the dropdown list and change the operation name to “Fertilization”, set operation age to
0 and add the operation with +. Next do the same, but change operation name to “Weed control” and age to 0.5, so the
operation will be done 6 months after the planting.
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Figure 4.3: Modeling regimes.
4.2.5 Harvest operations
Next you will add two harvest operations: a thinning and a clearcut. First, select “Thinning” from the Operation type
dropdown list, set the thinning age to 10 and add the thinning to the regime using +. The costs of harvest operations
can be either per harvested area unit or per harvested wood volume unit. Leave the cost columns untouched.
Next, add a clearcut at age 20 to complete the regime. Set the timber prices and proportions.
Now we have the regime for the “poor” soil type. Even with a very simple regime such as this, it can take a while to
define a regime. If we would have a more complicated regime and more classifiers (meaning more data partitions), it
would mean a lot of work. To avoid this, we can clone this regime to all other data partitions by clicking the clone
button. This will copy the current regime to all other data partitions (classifier combinations), which can be again
modified separately for each data partition if needed.
4.2.6 Parameters
The parameter box located on the right allows you to define further details about the operations you have selected.
One example of this is, when dealing with planting, you can set what is the planted species and how many seedlings.
This feature adds much more depth to the planning possibilities.
4.3 Timber prices
Timber price tables are important features for the optimization and will directly affect the results yielded in later
planning phases.
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4.3.1 Creating a new timber price table
You can create a new timber price table using the new button in the top left of the Timber Prices view. You will need
to choose a project, a data level and classifiers that will define how your price table will be stratified. Next you need
to define names and descriptions for each timber assortments that will be contemplated in the table. Click on select to
proceed to naming and describing your price table.
4.3.2 Adding assortments
First select Species as the classifier and then set “pulpwood” and “log” as the possible timber assortments. This will
create a list that will set these assortments for each timber species in your data set. Remember that, as before, you can
hone your selection by changing the classifiers.
Figure 4.4: Price table.
4.3.3 Adding prices and proportions
Next, you will need to fill in the timber prices currently practiced in the market or forecasted timber prices for some
point in the future. These prices will need to be added for each line that will represent a combination of timber
assortment and classifiers selected when creating the price table. Next, you will need to define what is the proportion
of each timber assortment and the harvest cost incurred for each case. Note that, for obvious reasons, no individual
proportion or sum of proportions for a same species can exceed 100%.
4.3.4 Editing a timber price table
You can always visualize and edit a previously created price table by selecting it and clicking on the edit button located
on the upper right side.
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31. CHAPTER
FIVE
PLANNING
Planning tools allow you to plan your forest management actions, such as timing and type of harvests and silvicultural
operations and also to predict the future wood flows, incomes and expenses.
5.1 Plan
5.1.1 Creating a new plan
Much like in previous sections, to create a plan, go to Plan section and create a new plan with the new button. Give
your plan a name and a description.
5.1.2 Input and objective
Start defining the inputs for your new plan by adding a new row to plan settings using the + button. You will then
need to select your all the data you have been creating until this point. Choose your project as the plan’s project, your
growth model as the growth & yield set, your regime as the plan’s regime and lastly select the timber price table you
have defined.
Next you will need to set a starting date and a final date to your planing horizon. For that, use the dd/mm/yyyy format.
You will also be able to choose what objective should be pursued by the optimizer, what is a sensible interest rate and
for how long will the program be allowed to delay thinnings and clearcuts in order to achieve optimal results.
After defining the plan, save your plan with confirm button.
5.1.3 Creating and editing constraints
You can also add constraints to your plan by clicking on the constraints button on the upper right section of the screen.
After the appropriate screen appears you can create any number of new constraints by clicking on the + button and
remove unwanted ones by clicking on the - button.
There are basically two types of constraints that can be created, “variables compared to value” constraints and “variable
compared to variable” constraints. The former is suited for creating contraints that will be limited by a user-defined
value. For instance, constraints compared to value could be a maximum anual harvest level or a minimum accepted
cash flow level. On the other hand, variables compared to variables express relations between variables. These can be
used in situations that require an increase of the yearly planted area or cost maintenance from month to month.
After you are done building the constraints, be sure to click on the save button.
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Figure 5.3: Adding constraints.
5.1.4 Calculating plans
After your plans have been created and the inputs, objectives and contraints are as they should be, you should then
select a plan on the initial plan menu and click on the run button. You can always check if this plan has been calculated
or not by checking if the “Plan state” is set as Ready or Not ready
Note that Iptim shows you a list of warning as errors generated by the plan calculation. Warnings will show areas that
require attention but did not prevent the optimizer from running and generating a result. Error, however, are shown
when some of the defined parameters prevent the program from reaching an optimal solution.
5.2 Analysis
After you have created the plans you can now analyse and compare them to find the ones that are more suited to meet
your needs.
On the “Analysis” view you can compare select any plans that have already been calculated (have their “Plan status”
as Ready on the plan menu).
5.2.1 Comparing Plans
Simply select one or two plans by the purple an green boxes on the left side, select the first and last years you want
your analysis to be comprised and the time step (monthly, quarterly and annual).
Next you can start comparing plans by clicking on buttons on the left pannel represented which variables are to be
compared. You can select one or multiple buttons and the respective comparisons will be appear. You can interact
with the charts by clicking on the data bars to see more information on the data represented by it.
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Figure 5.4: Click on run to calculate your plans.
Figure 5.5: Plan analysis view.
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5.2.2 Operations list
The operations list will show an optimized list of the operations organized by stand. There you will find when would
be optimal for each operation to take place, along with other relevant information such as the volume generated and
the total operations’ cost.
5.2.3 Operations map
Using the slider located immediately under the map, it is possible to see geographically when will each type of
operation be carried out in each stand. Each operation will be color coded according to the legend to your right hand
side.
Figure 5.8: Operations map.
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37. CHAPTER
SIX
REPORTING
6.1 Creating new reports
In the reporting view you can generate various reports for analysing your plans. Reports can be exported to Excel or
as PDF documents.
To get started with reporting, go to Report section and create a new report with the new button. Next select your plan
as the report’s source plan.
Then you will need to add the first reporting variable by clicking the + button and selecting “Harvested timber volume”
from the Variable dropdown list. Give it a name and add “assortment” and “operation name” as classifiers. The “from”
and “to” dates are automatically set to the selected plan’s starting and ending dates, but you can modify the dates as
you want.
Next add more reporting variables: income by operation name, costs by operation name, costs by operation type and
area by soil class. After adding these,. and you can save the report by clicking confirm.
Figure 6.1: Creating new reports.
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6.2 Calculating reports
After your reports have been created as they should be, you should then select a report on the initial repor menu and
click on the run button. You can always check if this report has been calculated or not by checking if the “Report
state” is set as Ready or Not ready
After running the report, you can view the report by clicking View report.
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