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

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,...

Virtual Reality Forest Inventory – Tree Quality Assessment – May 2019 Update

Full Forest Inventory Tree Assessment using Virtual Reality (VR).   Data is collected using LiDAR and then field assessment is done within Virtual Reality.     Another iteration in the development of field assessment using VR using a point cloud collected from above...

LiDAR Project Started Acquiring and Processing 1.35 million ha in Victoria Australia

Our team is excited this month to be starting the acquisition and processing of 1.35 million hectares of #LiDAR across #Victoria #Australia. This data-set will support updates to mapping old growth #forests and #rainforest throughout #Victoria for Department of...

Demostration of Virtual Reality Forest Inventory at ForestTech 2018

Interpine team recently presented and demonstrated at ForestTech 2018 the use of virtual reality for in forest inventory.   While the system can use terrestrial LiDAR the focus was on using utra dense point clouds from airborne sensors flying above the tree canopy....

Meet the Team at ForestTech 2018

Interpine will again be along at ForestTech 2018, being held in Rotorua and Melbourne this November.   Come along and hear about our latest advances in Virtual Reality, LiDAR and Drone applications across the forest industry.

Virtual reality experiments in Rotorua could replace forestry field work

The forestry industry has been experimenting with virtual reality in Rotorua this week to develop new ways of measuring tree growth.  The University of Tasmania and Interpine are carrying out the research, which is partially funded by Forest and Wood Products...

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.