Skip to Main Content

AI learns to simulate how trees grow and shape in response to their environments

DNA inspires the application of deep learning to long-standing computer graphics problem

A research team from Purdue University’s Department of Computer Science and Institute for Digital Forestry, with collaborator Sören Pirk at Kiel University in Germany, has discovered that artificial intelligence can simulate tree growth and shape.

The DNA molecule encodes both tree shape and environmental response in one tiny, subcellular package. In work inspired by DNA, Bedrich Benes, professor of computer science, and his associates developed novel AI models that compress the information required for encoding tree form into a megabyte-sized neural model.

After training, the AI models encode the local development of trees that can be used to generate complex tree models of several gigabytes of detailed geometry as an output.  

In two papers published in ACM Transactions on Graphics of the Association for Computing Machinery and IEEE Transactions on Visualizations and Computer Graphics, Benes and his co-authors describe how they created their tree-simulation AI models. “The AI models learn from large data sets to mimic the intrinsic discovered behavior,” Benes said.

Non-AI-based digital tree models are quite complicated, involving simulation algorithms that consider many mutually affecting nonlinear factors. Such models are needed in endeavors such as architecture and urban planning, as well as in the gaming and entertainment industries, to make designs more realistically appealing to their potential clients and audiences.

Growth simulations Novel Artificial intelligence-based methods generate tree models that adapt to changing environmental conditions. (Images courtesy of Bedrich Benes)

After working with AI models for nearly 10 years, Benes expected them to be able to significantly improve the existing methods for digital tree twins. The size of the models was surprising, however. “It's complex behavior, but it has been compressed to rather a small amount of data,” he said.

Co-authors of the ACM Transactions on Graphics paper were Jae Joong Lee and Bosheng Li, Purdue graduate students in computer science. Co-authors of the IEEE Transactions on Visualization and Computer Graphics paper were Li and Xiaochen Zhou, also a Purdue graduate student in computer science; Songlin Fei, the Dean’s Chair in Remote Sensing and director of the Institute for Digital Forestry; and Sören Pirk of Kiel University, Germany.

The researchers used deep learning, a branch of machine learning within AI, to generate growth models for maple, oak, pine, walnut and other tree species, both with and without leaves. Deep learning involves developing software that trains AI models to perform specified tasks through linked neural networks that attempt to mimic certain functionalities of the human brain.

AI tree modeling Researchers at Purdue University and Kiel University in Germany used artificial intelligence to generate these tree-growth simulations. See their papers in ACM Transactions on Graphics and in IEEE Transactions on Visualization and Computer Graphics for details. (Videos courtesy of Bedrich Benes)

“Although AI has become seemingly pervasive, thus far it has mostly proved highly successful in modeling 3D geometries unrelated to nature,” Benes said. These include endeavors related to computer-aided design and improving algorithms for digital manufacturing.

“Getting a 3D geometry vegetation model has been an open problem in computer graphics for decades,” stated Benes and his co-authors in their ACM Transactions paper. Although some approaches to simulating biological behaviors are improving, they noted, “simple methods that would quickly provide many 3D models of real trees are not readily available.”

Experts with biological expertise have traditionally developed tree-growth simulations. They understand how trees interact with environmental conditions. Understanding these complicated interactions depends upon characteristics bestowed upon the tree by its DNA. These include branching angles, which are much larger for pines than for oaks, for example. The environment, meanwhile, dictates other characteristics that can result in the same type of tree grown under two different conditions displaying completely different shapes.

“Decoupling the tree’s intrinsic properties and its environmental response is extremely complicated,” Benes said. “We looked at thousands of trees, and we thought, ‘Hey, let AI learn it.’ And maybe we can then learn the essence of tree form with AI.”

Scientists typically build models based on hypotheses and observations of nature. As models created by humans, they have reasoning behind them. The researchers’ models generalize behavior from several thousand trees’ worth of input data that became encoded within the AI. Then the researchers validate that the models behave the way the input data behave.

Bedrich Benes Bedrich Benes, professor of computer science

The AI tree models’ weakness is that they lack training data that describes real-world 3D tree geometry. “In our methods, we needed to generate the data. So our AI models are not simulating nature. They are simulating tree developmental algorithms,” Benes said. He aspires to reconstruct 3D geometry data from real trees inside a computer.

“You take your cellphone, take a picture of a tree, and you get a 3D geometry inside the computer. It could be rotated. Zoom in. Zoom out,” he said. “This is next. And it’s perfectly aligned with the mission of digital forestry.”

The Department of Computer Science is part of the Purdue Computes initiative.

Featured Stories

Dog outdoors drinking water
Keeping your pets safe during the dog days of summer

As temperatures and humidity rise across the U.S., Candace Croney, director of the Center for...

Read More
Eastern hellbender salamanders feeding on bloodworms in their raceway at the Purdue Hellbender the Hellbender lab.
Metazoa Beer to Benefit Help the Hellbender Lab

Metazoa Brewing Company and the Indiana Lakes Management Society have teamed up to collaborate on...

Read More
Sonling Fei in front of digital trees
Digital forestry can help mitigate and prevent wildfires

The National Interagency Fire Center reports that, as of this writing, 19,444 fires have burned...

Read More
tomas hook next to boat
What you can do this summer to reduce the spread of aquatic invasive species

In 2020, an alligator was captured in a lagoon of Chicago’s Humbolt Park. The reptile out...

Read More
Researcher uses pipette on parsley plant
Researchers examine nanotechnological methods for improving agriculture

Nanoscale particles could potentially help address agricultural and environmental sustainability...

Read More
Fairgoers ride a tractor, sponsored by the Indiana Soybean Alliance, and browse food tents during the 2023 Indiana State Fair. (Purdue Agricultural Communications photo)
Purdue Extension to present engaging art and nature demonstrations at Indiana State Fair

The Indiana State Fair kicks off Aug. 2 and highlights the theme “The Art & Nature of...

Read More
To Top