LiDAR Analysis Services

data collection through light detection and ranging

Digital Modelling

LiDAR can be used to create extremely detailed terrain and vegetation models. 

This can be applied in planning, resource inventory erosion and biodiversity monitoring and environmental resource management. 

LiDAR assists the creation of GIS surfaces of trees and stand attributes and 3D walk through and visualisations.

LiDAR Software Applications

Interpine has developed a large toolbox giving us the ability to carry out a large number of LiDAR analysis workflows.  These build on our expertise in LAStools, Quick Terrain Modeler, FUSION, Pix4D, ERSI ArcMap Extensions and Arbonaut software tools.

UAV derived structure from motion photogrammetric point cloud analysis.

Predictive Modelling

Development of relationships between LiDAR metrics and tree and stand attributes such as volume and carbon, and building predictive models for stand characteristics.

Implementation of Regression Estimation and Regression Modelling and k-Nearest Neighbour (k-NN)approaches.

Out in Industry

Customer Feedback

Custmer Feedback

LiDAR Scanning Forests at Younger Age for Tree Selection Trials

Studying #trees early in their #forest rotation for selection is key to improving our #forests of the future. #3D #measurement for #stem form in young #trees using #SLAM #LiDAR generating a #virtual #3DForest duplicate. This is the same tree which has been #digitally...

Colourised LiDAR View of our Rotorua Head Office From Hovermap Backpack

#3D #pointcloud colourised view of our Rotorua Head Office as we put to work the #Hovermap #LiDAR from Emesent.  Our team were also out scanning a range of permanent sample plots, some of which were close to 50m tall #radiata pine. These were scanned in 3D from a walk...

Adding the Emesent Hovermap SLAM LiDAR Solution to our Services

We are proud to have recently purchased the Emesent #Hovermap #Hovermap #LiDAR simultaneous location and mapping #SLAM) solution to better serve our clients. This unit enhances our #forest #inventory, #drone #UAV and LiDAR services providing a glimpse that the future...

Operational Immersive Visualisation and Measurement of Dense Point Cloud Data in Forest Inventory

Interpine starts a new 2-year project working with Forest Wood Products Australia on operational immersive visualisation and measurement of dense point cloud data in forest inventory.   This new project extends on work started in 2016, and involves working alongside...

Our 15 Year Journey with LiDAR Presenting as Keynote Speaker at Arizona LiDAR Virtual Symposium

Our remotesensing team leader, Sarah Pitcher-Campbell is looking forward to presenting as the keynote speaker at the LIDAR Virtual Symposium hosted by the Arizona Geographic Information Council (AGIC) tomorrow, looking at how LiDAR is used throughout NZ.

Development of 3D LiDAR Tree Feature Extraction for Forest Inventory Assessment

Wondering what the future of Forest Inventory looks like from Interpine? An example of Interpine's automated extraction of 3D tree profiles and measurement.  Shaping today's forests with the technology of tomorrow.   Want to find out more, reach out to our team and...

Webinar – Explore the Use of HoverMap LiDAR for Forest Inventory

Emesent Hovermap's versatility, ease of use and data quality are set to be a game-changer for forestry management. On Thursday the 14 of May we are teaming up with Emesent, to bring you a webinar focused on the applications of Hovermap for forestry resource inventory...

New Forest Scanning Systems Tested

For the love of #trees, our teams love of #Environment #Forestry and #LiDAR combine with our recent work to step up virtual #forest #inventory with new scanning systems and analysis techniques. Our team continues to innovate in the assessment of...

3D LiDAR Terrain Model Carved from Laminated Wood

Visualising LiDAR 3D Terrain Models in Wood.  Thanks to some teamwork with Scion wood lab our team recently provided a client with a LiDAR-derived 3D terrain model carved from laminated wood. This unique way of visualising a landscape doubles the meaning of using...

Care to Avoid Loss of Subcanopy LiDAR Data through Noise Classficiation Algorthims

The capture and use of high density LiDAR data across forest plantations requires a good understanding of the final output. Sometimes this output is only a digital terrain model and or other times it is to quantify forest attributes, such as mean top height, DBH,...

Frequently Asked Questions

What is Plot Imputation and how do you generate Forest Yield Tables
Interpine uses YTGEN forest yield calculation combined with LiDAR data to produce forest attributes.  LiDAR metrics are computed across the area of interest (target imputation grid) and for all the reference plots.  These reference plots being a ground  measured plot where known assessments of volume and grade mix have been conducted, and a yield table is developed in software such as YTGEN.

Once the predictor metric relationships are established the reference plots are related (imputed) to represent a grid cell across the target imputation grid.  This introduces the concept of nearest neighbours (kNN).  In the simplest sense this could be thought of as 1 plot is used to represent each grid cell in the network, that being often referred to k=1 in the terminology of kNN.  However we can use more than 1 plot to represent a grid cell (k=2,3,4 etc) as a simple average or provide a respective weighting of each of these plots for each grid cell when k>1.

Then it’s just maths to simply select any “Area of Interest” (typically a stand, harvest area or might be an entire forest!) and the respective target imputation grid cells that fall in the area, to get a final yield table.

Why is LiDAR Data Quality Assurance is Important
Interpine undertakes a LiDAR quality assurance audit in every LiDAR inventory project.  The main objective is to ensure the data produced is accurate and meets acceptable standards.  A workflow process is applied to identify issues in the dataset, if these issues are not corrected on time it could create downstream problems.

To increase the success of any LiDAR project we must be sure any anomalies are not present in the dataset.  Producing a good quality control report increases the success of LiDAR inventory results.

If we didn't answer all of your questions, feel free to drop us a line anytime.