Estimating the parameters of the forest is the goal of the forest inventory. Continuing the example from previous lesson, you will use the inventory information gathered in the field to calculate the forest parameters, for the whole forest first, and then for the stands you digitized before.
The goal for this lesson: Calculate forest parameters at general and stand level.
The field teams visited the forest and with the help of the information you provided, gathered information about the forest at every sample plot.
Most often the information will be collected into paper forms in the field, then typed to a spreadsheet. The sample plots information has been condensed into a .csv
file that can be easily open in QGIS.
Continue with the QGIS project from the lesson about designing the inventory, you probably named it forest_inventory.qgs
.
First, add the sample plots measurements to your QGIS project:
systematic_inventory_results.csv
located in exercise_data\forestry\results\
.X
and Y
fields.ETRS89 / ETRS-TM35FIN
as the CRS.You can read the type of data that is contained in the sample plots measurements in the text file legend_2012_inventorydata.txt
located in the exercise_data\forestry\results\
folder.
The systematic_inventory_results
layer you just added is actually just a virtual representation of the text information in the .csv
file. Before you continue, convert the inventory results to a real shapefile:
systematic_inventory_results
layer.exercise_data\forestry\results\
folder.sample_plots_results.shp
.systematic_inventory_results
layer from your project.You can calculate the averages for this whole forest area from the inventory results for the some interesting parameters, like the volume and the number of stems per hectare. Since the systematic sample plots represent equal areas, you can directly calculate the averages of the volumes and number of stems per hectare from the sample_plots_results
layer.
You can calculate the average of a field in a vector layer using the Basic statistics tool:
sample_plots_results
as the Input Vector Layer.Vol
as Target field.The average volume in the forest is 135.2 m3/ha
.
You can calculate the average for the number of stems in the same way, 2745 stems/ha
.
You can make use of those same systematic sample plots to calculate estimates for the different forest stands you digitized previously. Some of the forest stands did not get any sample plot and for those you will not get information. You could have planned some extra sample plots when you planned the systematic inventory, so that the field teams would have measured a few extra sample plots for this purpose. Or you could send a field team later to get estimates of the missing forest stands to complete the stand inventory. Nevertheless, you will get information for a good number of stands just using the planned plots.
What you need is to get the averages of the sample plots that are falling within each of the forest stands. When you want to combine information based on their relative locations, you perform a spatial join:
forest_stands_2012
as the Target vector layer. The layer you want the results for.sample_plots_results
as the Join vector layer. The layer you want to calculate estimates from.forest_stands_2012_results.shp
and save it in the exercise_data\forestry\results\
folder.Open the Attribute table for forest_stands_2012_results
and review the results you got. Note that a number of forest stands have NULL
as the value for the calculations, those are the ones having no sample plots. Select them all review them in the map, they are some of the smaller stands:
Lets calculate now the same averages for the whole forest as you did before, only this time you will use the averages you got for the stands as the bases for the calculation. Remember that in the previous situation, each sample plot represented a theoretical stand of 80x80 m
. Now you have to consider the area of each of the stands individually instead. That way, again, the average values of the parameters that are in, for example, m3/ha for the volumes are converted to total volumes for the stands.
You need to first calculate the areas for the stands and then calculate total volumes and stem numbers for each of them:
area
.Decimal number (real)
.2
.$area / 10000
. This will calculate the area of the forest stands in ha.Now calculate a field with the total volumes and number of stems estimated for every stand:
s_vol
and s_stem
."area" * "MEANVol"
and "area" * "MEANStems"
for total volumes and total stems respectively.In the previous situation, the areas represented by every sample plot were the same, so it was enough to calculate the average of the sample plots. Now to calculate the estimates, you need to divide the sum of the stands volumes or number of stems by the sum of the areas of the stands containing information.
forest_stands_2012_results
layer, select all the stands containing information.forest_stands_2012_results
as the Input Vector Layer.area
as Target field.As you can see, the total sum of the stands’ areas is 66.04 ha
. Note that the area of the missing forest stands is only about 7 ha
.
In the same way, you can calculate that the total volume for these stands is 8908 m3/ha
and the total number of stems is 179594 stems
.
Using the information from the forest stands, instead of directly using that from the sample plots, gives the following average estimates:
184.9 m3/ha
and2719 stems/ha
.Save your QGIS project, forest_inventory.qgs
.
You managed to calculate forest estimates for the whole forest using the information from your systematic sample plots, first without considering the forest characteristics and also using the interpretation of the aerial image into forest stands. And you also got some valuable information about the particular stands, which could be used to plan the management of the forest in the coming years.
In the following lesson, you will first create a hillshade background from a LiDAR dataset which you will use to prepare a map presentation with the forest results you just calculated.