Developing LiDAR-based Tools for Digital Forestry

Interdisciplinary Areas: Internet of Things and Cyber Physical Systems, Data/Information/Computation, Future Manufacturing, Power, Energy, and the Environment

Project Description

Forest ecosystems contribute $17 billion annually to the economy of Indiana through forest products, and $200 billion to the national economy. Forest industries support nearly one million jobs nationally. Accurate measurement of forest characteristics is essential for sustainable management of forests to meet both economic and ecological needs. Nevertheless, many forest measurement techniques in use today rely on manual sampling methods and tools developed decades ago. Recent technological advances offer new tools and techniques, such as LiDAR, with the potential to transform forestry industries through improved accuracy, automation, and efficiency of forest measurements. The desired outcome of this project is a user-friendly analytical tool that can ingest a wide-variety of LiDAR point cloud datasets and generate the information on forest structure, health, and quality that is essential to the success of forest industries in the 21st century. 

Start Date

Spring/Summer 2019

Postdoc Qualifications

We seek applicants to participate in a project that will develop automated processing workflows and analytical algorithms to derive essential forest structural information from point clouds generated using LiDAR systems deployed on terrestrial, aerial, and satellite platforms. The successful applicant will have expertise in some combination of the following areas: programming (R and Matlab preferred), software engineering, remote sensing, statistics, and/or point cloud processing.  


Dr. Ayman Habib (Primary Advisor)
Professor of Civil Engineering 
Purdue University

Dr. Brady Hardiman (Co-Advisor)
Assistant Professor of Forestry and Natural Resources, Environmental and Ecological Engineering
Purdue University 


1. Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

2. Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

3. Terrestrial Laser Scanning for Plot-Scale Forest Measurement

4. The role of canopy structural complexity in wood net primary production of a maturing northern deciduous forest

5. Quantifying vegetation and canopy structural complexity from terrestrial LiDAR data using the forestr r package