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CFWE harnesses new technology for natural resource management

By March 20, 2024April 24th, 2024No Comments

Artificial intelligence (AI) and machine learning (ML) continue to emerge with the infinite potential to re-envision the operations of our society and multiple industries.

The College of Forestry, Wildlife and Environment (CFWE) faculty at Auburn University are harnessing the power of AI and ML to better address disparate environmental and natural resources issues and to deliver more effective solutions for communities, citizens and policy makers.

Recognizing AI and ML’s potential for industry problem-solving, CFWE expanded its faculty expertise in Geospatial and Environmental Informatics (GSEI), AI and ML and invested in modern technologies, positioning the college to leverage this wave of innovation for research and teaching.

Sanjiv Kumar (left), Latif Kalin (middle), and Li An (right) sitting at a table

Associate Professor Sanjiv Kumar, Clinton-McClure Professor Latif Kalin and Solon & Martha Dixon Endowed Professor Li An (left to right) discuss their individual uses of AI and ML technologies.


If there is one thing CFWE faculty utilizing AI and ML agree upon, it’s the absolute necessity of using these technologies and the impact they foresee on the future evolution of natural resources and related industries.

“In the past, scientists in data science, computer science and engineering, and mathematics and statistics were largely engaged in AI and ML, but now in nearly all scientific and application areas, people are enthusiastic about it,” said Li An, Solon & Martha Dixon Endowed Professor of ecosystem modeling. An currently uses AI to understand how people or animals make decisions or choices.

Clinton-McClure Professor Latif Kalin, a hydrologist, uses AI in many ways, including to predict salinity in the Mobile Bay delta and small coastal creeks or to predict flow and water quality in ungauged watersheds by combining AI with process-based models.

“AI and ML are not new; scientists have been using them, but their usage was limited,” said Kalin. “The key constraint was the available data and computational resources to process large data sets to train these models. Now, we have high-performance computing resources. Together, they opened the floodgate for AI and ML.”

Sanjiv Kumar said another trend feeding AI and ML growth is the availability of funding opportunities. Kumar, an associate professor of Earth system modeling and observation, also attributes the sheer amount of climate models and remote sensing data as a trend driving this growth. Lana Narine, an assistant professor of geospatial analytics, agrees.

“There are increasing volumes of multi-source data for supporting applications,” said Narine. “Approaches that are capable of handling large and complex datasets are necessary to extract meaningful information from these data.”

Narine develops methods, products and frameworks using Earth observation data with machine learning and deep learning techniques to support forest and natural resource sustainability.


With AI and ML here to stay, CFWE offers students multiple opportunities to train in these technologies.

An envisions AI and ML will attract and empower a new generation of young scholars or scientists to engage in natural resource and environmental management arenas.

Kalin agrees that widespread use and the diverse applications of the technologies are driving student interest. “Expertise of AI and ML will not be a luxury but a requirement in the future. Therefore, students need these skills,” said Kalin.

The CFWE’s Geospatial and Environmental Informatics (GSEI) program delivers a unique opportunity for students to learn AI and ML tools and techniques, which will broaden their future job opportunities.

“I envision that AI, ML and related technologies would offer exciting and unprecedented opportunities for CFWE students in research, education, daily life and outreach activities,” said An.

“They will observe a digital era of natural resources and environmental management. Big data, data science and high technologies can bring a remote world immediately in front of our students, letting them explore various policy scenarios and predict potential outcomes via AI- and ML-enabled models. In this way, our students can truly realize the dream of ‘acting locally and influencing globally’.”

In addition to the GSEI program, students can use AI and ML in Kumar’s Climate, Water and Society Lab and Narine’s Geospatial Analytics Lab. GSEI students can also apply for an USDA-EDS scholarship, which supports next-generation workforce development in data science, including AI and ML.

(Written by Amy Burtch)

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