Interpine’s TreeTools VirtualPlot Forest Inventory tool has been developed for foresters to assess stocking in silvicultural operations during forest management. Using a drone, you can create virtual plots both onsite and offline in the forest, aiding in decision-making. This is an early beta test version release for Windows operating systems.

The purpose of the release is to give stakeholders an opportunity to test and provide feedback, while encouraging them to submit more data. The accuracy of the stocking assessment depends on factors like canopy recognition effectiveness and drone altitude precision.

Our goal is to keep the stocking error below 10% under normal conditions.

The following provides an overview for data capture and a guide to using the software.

This project has been developed with funding assistance from the Precision Silviculture Programme, A Sustainable Food and Fibre Futures (SFFF) partnership between MPI and the forest industry led by Forest Growers Research. This is freely available during the development funding to provide for industry feedback.

Drone Support

A list of currently supported drones and drone sensors is provided below. Where Interpine has completed custom calibration of a drone’s camera sensor field of view (FoV) in our test environment, the use of these drones provides the highest quality results. Where custom calibration has not been completed, Virtual Plot will still provide results based on the manufacturer’s FoV specifications. These results may not be optimal but may still be suitable for many applications.

If you have a specific drone or camera sensor you would like supported with a custom calibration, please reach out to the team.

What’s New

The latest software release notes and feature availability is shown below.

Version	Release Notes
2.05 (28/03/25)	1. Fix an error of AGL calculation using take-off photo on 2.03/2.04. NOTE: The outputs using take-off photo could be wrong in 2.03/2.04. Please update to at least this version for a correct take-off photo + DTM function. 2. Allow NZTM NZVD2016 DTMs. Select “Vertical Datum” after uploading DTM. The default value is “NZVD2016” for the convenience of NZ users. Currently it supports both NZVD2016 and Ellipsoidal vertical datums, and the horizontal coordinates could be NZTM2000 or WGS84. 3. Add “DTM Converter” function in “Tools” menu beside “Help” for converting NZTM NZVD2016 DTMs to WGS84 Ellipsoidal, which could be useful for DJI flight planning. 4. Update Post-Thinning AI Model with more training data. (Radiata pine Thinning Model v4)
2.04 (5/03/25)	1. Improved user interface for image processing workflow. 2. Inclusion of DTM and Take-Off image names if loaded for use, into the results.csv file. (28/03/2025) NOTE: The outputs using take-off photo could be wrong in this version. Please update to at least 2.05.
2.03 (28/02/25)	1. Add a function of using take-off photo + DTM to determine AGL for drone types not supporting recording of height above ellipsoid and only height above take off point, like DJI Phantom 4 Pro, DJI Mavic 2, etc. The take-off photo has to be taken at the take-off point with the drone on the ground. (28/03/2025) NOTE: The outputs using take-off photo could be wrong in this version. Please update to at least 2.05. 2. Update calibration parameters for DJI L2 LiDAR – RGB Sensor and DJI Mavic 3 Multispectral, which are also supported by the DTM function. 3. Update Post-Thinning AI Model with more training data. (Radiata pine Thinning Model v3) 4. Update Early Age Assessment AI Model with more training data. (Radiata pine Early Age Model v2)
2.02 (20/01/25)	Update calibration parameters for DJI L1 LiDAR – RGB Sensor.
2.01 (19/12/24)	1. Improve the interface to make it more user-friendly. Added video processing function and stream processing function. 2. Both video process and stream process need to choose drone type first. The video process is designed so that you can figure it out how to use it at a glance. Click “Save” button to save the current result and click “Exit” to terminate the process and a Summary.csv will be generated. 3. For real-time stream process, before clicking “GetIP” button your computer and your drone’s controller need to be in a same Local Area Network (LAN). The practical way of doing this is to turn on your phone’s hotspot and connect both your computer and your drone’s controller to the hotspot. It doesn’t need your phone has to catch signal in field. After connecting successfully, click “GetIP” button and the RTMP address will be printed on the right-side console window. Then type it to your drone controller and start streaming. The video stream will be pushed to your computer. Select the correct drone type and click “Video Stream Go” button. You should see the real-time inference result comes up. Fly your drone to look around. Click “Save” button to save the current result at any time and click “Exit” to terminate the process and a Summary.csv will be generated.
1.04 (6/12/24)	1. Updated the post-thinning model.  2. Added a function of using DTM to obtain flight height smartly and more precisely. Now the DTM method only supports DJI Mavic 3 Enterprise and DJI L1 RGB Sensor. The best DTM should be 1m tiles, and the coordinate system has to be WGS84 + Ellipsoidal Height.
1.03 (15/11/24)	Added a new column ‘PlotsToReach10PctPLE‘ in ‘Summary.csv’ to suggest how many plots are needed to reach 10% PLE.
1.02 (11/11/24)	Added a KMZ output, where all output results can be easily opened in Google Earth Pro.
1.01 (5/11/24)	Initial beta release for testing and development purposes.  Currently supported drones are the DJI Phantom 4 Pro, Mavic 2, Mavic 3 Enterprise.

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Capturing Data with Your Own Drone

The following guidelines will help you in capturing data using your drone for use with TreeTools VirtualPlot.

Please follow the suggested flight parameters below for data collection, and feel free to ask any questions if you have them.

Flight Parameter	Suggestion
Flight App	Any app will be sufficient as long as it supports terrain awareness / terrain follow. Maps Made Easy – Tag Pilot, for DJI Mavic 2, DJI Phantom series drones. Maps Made Easy – Map Pilot Pro, for the DJI Mavic 2, DJI Phantom series drones. DJI Pilot 2, for the DJI Matrice series, DJI Mavic 3 Enterprise drones. UgCS, for more complex flight planning.
Flight height above ground level	between 100-120 m. Preference to 120m as this provides a larger plot size. A larger plot size is more tolerant to getting precise results with tree stocking.
Flight speed	between 8 to 12 m/s. The key is reducing motion blur in the imagery to keep good tree detection quality. – if windy consider 8-10 m/s to reduce motion blur in moving trees). – if clear and little wind 10-12m/s should be fine).
Terrain Awareness	Terrain Awareness is also required so that the drone can maintain a constant height above ground during the flight. Using Tag Pilot terrain AGL lock mode. Using Map Pilot terrain follow mode. Using DJI Pilot 2 and need to create a GeoTIFF DTM file to load, follow this article. Using UgCS terrain follow mode. Using DJI Pilot 2 Real-time Terrain Follow
For Drones Only Reporting Height Above Take Off Point	For users of the DJI Phantom series, DJI Mavic 1 and 2, that only record height above take off point within each photo (not height above WGS84 ellipsoid), we recommend taking a photo on the ground at the takeoff point. This can then be uploaded during processing together with the DTM, to provide precise plot area measurements. See how this is used during processing. If your using Maps Made Easy Map Pilot, this software takes a ground image for you.
Terrain Conditions	In rolling to steep terrain, you will get optimized results by adding a DTM during processing. Find out more here.
Gimbal Pitch	90 Degrees (looking straight down). Images to far outside this range will not be processed.
Lighting conditions	Sunny or Cloudy – detection algorithm trained on a range of lighting conditions.
Overlap	Dependent only on the required plot intensity across the flight area. Suggest 50% or less. It is not required to have any image overlap in the flights to process with TreeTools VirtualPlot.

 

 

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Video Tutorial

Getting Started – the Basics of Virtual Plotting

A quick start video to get you up and running using the image processing workflow.

Using Digital Terrain Models to Enhance Results

You can now use a DTM to improve the results, especially in steep terrain. This works for all supported drones types.

Get Started

Download, Open and Activate License

Request to download the software using our contact form.  After downloading the software, simply double-click to use. The software does not require any installation and can be run directly from the application file downloaded.

The following GUI will appear. You will notice a 2-month license will initially be provided for testing and evaluation.

If your license expires, contact our team and get a renewal code which can be entered in the Help > License Renewal menu.

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Set Initial Parameters

 Initial parameters allow you to define the analysis project.

Parameter	Description / Use
Project / Entity	A reference for your own use. This is output in the final data and can be used to link the data back to a client name, project, forest-compartment-stand for example. e.g. MATA-101-3
DataRef / JobRef	A reference for your own use. This is output in the final data and can be used to link the data back to a specific job, contractor, operator for example. Useful to make this the Job Number from GeoMaster is using the inventory import function. e.g. J10234
Assumed AGL (m)	Assumed flight height above the ground (AGL) in meters. This should be set to the altitude used for the terrain following AGL used during flight operations. Can be approximate if also planning to analyze using a DTM (digital terrain model) as the DTM will be used to further refine the analysis when made available. e.g. 120. “Assumed AGL” also influences the virtual plot size as using DTM or DTM+Take-Off functions. Bigger Assumed AGL for larger virtual plot.
Model Select	This is the AI model which will be used to detect the trees. e.g. Post-Thinning
Tree Height est (m)	The average tree height roughly estimated for the target area in meters.  This is used to approximate the distance from the drone to the treetops based on the assumed AGL. Therefore, the plot area is calculated at the treetops rather than ground level, as the detection algorithm considers the treetops are the inclusion/exclusion criteria for stocking counts. Typically, just an estimate +/- 5m would be fine. e.g. 10

Selecting the AI Tree Detection Model

When deciding to select the appropriate AI model it is worth considering the data in which it has been trained on. Part of the development of tree tools is the extension of models available for end users. If you have data you can contribute to train the models for specific species and operation types, just reach out to us.

Model Name	Model Description
Post-thinning	Species: Radiata pine. Ages: 5-10 years. This model has mostly been trained for use for post waste thinning silviculture operations, but can also be used successfully for pre-thinning assessment in these age ranges. It may not perform well in preassessment when the forest has reached full canopy closure.
Early Age Assessment	Species: Radiata pine. Age 4 years. This model has been developed for early age assessment for pre-pruning and thinning silviculture scheduling.

Select a Data Input Type (Image, Video, Video Streaming)

Select one of 3 types of workflows for different input data sources.

Images Processing Workflow

Image processing is often the easiest and best method to get good results. This will take a folder/s of images and analyze them, creating a virtual plot for each of the JPEG files located in the folder. TIP: consider cleaning up the folder prior to analysis, removing any images which are not relevant to your area of interest.

Selecting the images process button on the interface will expose a few extra parameters.

Parameter	Description / Use
Image Folder	Select the folder of images to be processed. All subfolders of images in the folder will also be processed if present.
DTM (Optional)	Select a DTM to refine the AGL (m) and get higher precision results. Currently supporting both NZVD2016 and Ellipsoidal vertical datums, and the horizontal coordinates could be NZTM2000 or WGS84. This is recommended to improve the precision of the results in steeper forest areas.
Clear DTM	Clear or remove the use of DTM during processing.
Vertical Datum	Select the vertical datum of the DTM uploaded. Currently supporting both NZVD2016 and Ellipsoidal vertical datums.
Take-Off Image	This image is used to calibrate to the provided DTM file, enabling precise plot area measurement. This is recommended when using a drone which only supports recording of height above take off point in the EXIF metadata within each image. Virtual Plot will prompt for this when this type of drone data is provided, and you have provided a DTM during analysis. Expecting an image file taken while drone is on the ground.
Clear Take-Off Image	Clear or remove the use of a take-off image during processing.
GO	Start processing
PAUSE / CONTINUE	To pause and continue processing of selected folder of images.
STOP	Stop current processing. Will not complete the summary output files.

Download Images and Select Folder/s of Images to be Processed

Once you have downloaded the images using an SD card from your drone. Click “Select a Folder of Images” button, then select the folder containing the target data.

 

 

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Image Processing to Virtual Forest Inventory Plots

Using the Go button you can start the processing. The images in the folder, including those in the subfolders, will be processed one by one and shown on the screen. The stocking is represented as “TreesPerHectare”, together with a TreeCount. You will see each image pop up with the detection and stocking estimates as it is processed.

You can stop the processing at any stage using the Stop button. Once you processing is complete, check out the results

Improve Plot Area Precision Using a DTM

Providing a DTM to your processing workflow will improve your results by more precisely measuring the plot area. Terrain follow flights are often smoothed out flightpaths due to either use of a lower resolution terrain model or to avoid sharp drops or inclines in the drone flight. Therefore even with a planned flight at 100m AGL (above ground level) you are likely to see variation in actual height above ground depending on the terrain of +/-10m or so. So, a way to compensate for this and get more precision from TreeTools VirtualPlot is to provide a 1m DTM which will be used to refine the flight height of the drone above ground for each image.

Follow our guide to create a suitable DTM to use in TreeTools VirtualPlot. It needs to be NZVD2016 or Ellipsoidal elevation heights.

Use of Take-Off Image for DTM AGL Correction

For drone types that do not support recording of height above ellipsoid and only height above take off point, like DJI Phantom 4, DJI Phantom 4 Pro, or DJI Mavic 2. Virtual Plot will prompt you to upload a take-off location photo. This should have been taken at the home point while the drone is on the ground. This allows for precise plot area calculations based on the provided DTM.

Video Processing Workflow

You can fly the drone, just collecting a video file and use this for extracting virtual plots. This is not as precise as using images but is a useful way to get quick results over specific areas.

Select the Video Process button on the interface will expose a few extra parameters.

Parameter	Description / Use
Select a Video File	Select a video file for analysis
Drone Select	Select the type of drone you have. This ensure the correct camera sensor settings are selected. Unlike the image processing, this type of information is not available to TreeTools via the video streaming so must be set manually by selecting the drone type. Contact us if your drone type is not available.
Go	Start the video analysis. The results will be shown in the pop-up window.
Save	Save a plot result as output. You can select when a plot will be extracted and analyzed from the current view.
Exit	Stop current processing of video.
Video Navigation Timeline Select	Use the timeline to select specific parts of the video, by skipping forward or backward to select section of video for analysis.

Streaming Video Live Analysis Workflow

Streaming the analysis live from the drone while in flight, provides a way for real-time results. A result will be shown approximately every 3 seconds during flight (when AGL and gimbal settings suitable). It is recommended this only be done when there if more than 1 person onsite. It is important the drone pilot is not distracted from their task of operating the drone safely. This works in a similar way to video processing where results will not be as precise as image processing option, and the output will not include the GPS location of each plot as this is not available as part of the live stream video feed from the drone.

Selecting the Stream Process button on the interface will expose a few extra parameters.

Parameter	Description / Use
Drone Select	Select the type of drone you have. This ensure the correct camera sensor settings are selected. Unlike the image processing, this type of information is not available to TreeTools via the video streaming so must be set manually by selecting the drone type. Contact us if your drone type is not available.
Get IP	Selecting this provides the RTMP address of the device for input into the drone application. This will be displayed in the log window to the right. Goto your drone application, and select Video Streaming output. You can select RTMP Server and type in / copy the URL provided and select Start Streaming on the drone app.
Video Stream Go	Start the video streaming analysis.

The drone tablet / controller and your analysis computer need to be on the same WiFi network for this to work. The practical way of doing this is to turn on your phone’s hotspot and connect both your computer and your drone’s controller to the hotspot. This does not require mobile reception / internet reception in the field, just the WiFi hotspot connecting the two devices.

Results and Outputs

After the processing is complete, the following outputs and reporting is provided.

Output	Description
Results.csv	Virtual plot listed for each image processed or selected for output. Includes attributes for each plot including tree count, stocking, and a range of input and analysis parameters. A full list of data types is available below.
Summary.csv	Contains the averages and statistical analysis for the folders/s processed. Includes statistics such as PLE (95% CI over the mean as a %), and an estimate of plots required to achieve 10% PLE. A full list of data types is available below.
Output.kmz	The KMZ file can be opened in Google Earth Pro to view the images in their spatial location.
<image>_result.jpg	In the source folder a output of each virtual plot is provided with the suffix “_result”.

The output images for every submitted image can be double-checked manually to correct the stocking information. For example, if you find a missing tree in the yellow plot circle, then add a “TreeFreq” to the “TreesPerHectare” number for a correction to the stocking. On the other hand, if you find an area that is mistakenly marked as a tree but isn’t one, then subtract a “TreeFreq” from the “TreesPerHectare” number. 

File Format: Results.CSV

Field Name	Description
TreeToolsVersion	Software version release.
Entity	Parameter Input: custom field input by user.
JobRef	Parameter Input: custom field input by user.
PhotoPath	Directory path of the input image.
DateTime	Date and time of the image taken.
Latitude	Latitude location of the plot center (degrees).
Longtitude	Longitude location of the plot center (degrees).
AiModel	AI model applied. Includes a version of model. This version number is considered independent from the VirtualPlot software as it relates to the iteration of the Ai model training.
TreePerHectare	Tree count * TreeFreq representing tree per hectare. Trees per hectare is not the same as stems per hectare. Under NZ standard mensuration conventions, a tree with two stems below breast height will contribute twice as many stems as trees to the plot level per hectare estimate.
TreeCount	Tree count within the bounded plot area. A tree is considered to count towards the stocking if the tree crown is at least 50% within with the plot boundary. This is calculated by the center point of the detection square as represented on the virtual plot image.
SampleArea	Bounded plot size (hectares).
Radius	Radius of the bounded plot (meters).
TreeFreq	The number of trees per hectare represented by this tree. The frequency is calculated as 1/(plot area) and all trees have the same frequency.
FoV	Camera field of view applied for the sensor type.
FoVSource	FoV source.
Resolution	Pixel image resolution of the input image processed.
Pitch	Camera gimbal angle (degrees).
HAE	Height above ellipsoid (meters).
AGL	Altitude above ground level (meters).
AGLSource	AGL source (and therefore confidence). – Manual, just using the user provided default parameter value of assumed AGL, by default plot size and FoV will remain constant. – DTM, refers to use of the digital terrain model input file. Currently, 2.05 supports both NZVD2016 and Ellipsoidal vertical datums, and the horizontal coordinates could be NZTM2000 or WGS84. – DTM+Takeoff, refers to use of the digital terrain model input, whereby calculated height above ground based on the difference from a take-off image at the home point ground location.
TreeHeight	Parameter input: approx crop tree height (meters).
Orientation	Drone heading (degrees).
DTM	Filename of the DTM used.
VerticalDatum	Vertical Datum of the DTM
TakeOffImage	Filename of the Take-off Image used.
DroneModel	Drone model detected from the EXIF data.
CameraModel	Camera model detected from the EXIF data.

File Format: Summary.CSV

Field Name	Description
TreeToolsVersion	Software version release.
Entity	Parameter Input: custom field input by user.
JobRef	Parameter Input: custom field input by user.
TotalImagesProcessed	Total images / virtual plots used to create the summary.
FoVSource	FoV source.
AverageTreeCount	Average tree count within the bounded plot area for each image processed. A tree is considered to count towards the stocking if the tree crown is at least 50% within with the plot boundary. This is calculated by the center point of the detection square as represented on the virtual plot image.
AverageTreesPerHectare	Average of the Tree count * TreeFreq representing tree per hectare for each image processed. Trees per hectare is not the same as stems per hectare. Under NZ standard mensuration conventions, a tree with two stems below breast height will contribute twice as many stems as trees to the plot level per hectare estimate.
TPH_SD	Trees per hectare standard deviation
TPH_CI95	Trees per hectare 95% confidence interval.
TPH_PLE	Trees per hectare probable limit of error %. This being the 95% confidence interval divided by average trees per hectare represented as a %.
PlotsToReach10PctPLE	Estimated additional images / virtual plots required to reach a PLE of 10%. Will show zero where PLE is already below 10%.

Importing Results to ArcGIS Pro

Importing Results to ArcGIS Pro. Use the “XY Table to Point” layer option to import the results.csv file for display in ArcGIS.

Importing Results to GeoMaster

Import into GeoMaster using the Inventory Import function from the Tools menu. Select the relevant Job Number field to link the inventory results to during the import.

More Information on How It Works

Here is some additional information for those guru’s keen to understand more. Click to expand the more detailed content.

Further Support

Thanks for using TreeTools VirtualPlot.   Follow us for more detail on our product page.

We wrote these articles to equip you with everything you need to get the job done on your own, but we understand that sometimes this isn’t sufficient.

If you’re stuck, the Interpine support team may be able to help. You can contact them by submitting a contact request.