Ecosystem Services GeoAI Lab
We research on Geographic Information Science, Remote Sensing, Geovisualization, Ecosystem Service Assessments, and AI (Machine Learning and Deep Learning). The ultimate goals of this research group is to advance scientific understanding of where and how nature provides benefits to human societies, and to produce actionable knowledge and develop solutions to enhance sustainable land use planning and management across the continuum of urban and rural systems.
Latest Updates
Now Recruiting: Undergraduate Research Opportunities
We are currently looking for motivated undergraduate students to join our lab! We have two exciting paid opportunities available:
- AI Scholar Program: Open to all UF undergraduate students (any major). This paid research position allows you to work on cutting-edge geospatial AI and ecosystem services projects while gaining valuable research experience.
- IFAS/CALS Summer Internship: A paid summer internship ($15/hour, up to 240 hours) for CALS students to work on our USDA-funded cover crop mapping project. Applications due February 20, 2026.
We also offer undergraduate research credit hours for students who want to gain research experience while earning academic credit.
Two Papers Published in SIGSPATIAL '25
Congratulations to Jiayi Song, Hao-Yu Liao, Dr. Chang Zhao, and Wei Shao 🎉 on having two papers published in the 33rd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '25)! The papers showcase innovative applications of foundation models and multimodal AI in geospatial research 🌍🤖.
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FoundationSoil: Enhancing Soil Organic Carbon Mapping Using a Multi-Temporal Geospatial Foundation Model
Authors: Jiayi Song, Chang Zhao, Hao-Yu Liao, Wei Shao
Pages: 1067-1070
DOI: 10.1145/3748636.3764177 -
Mapping Cultural Ecosystem Services Using One-Shot In-Context Learning with Multimodal Large Language Models
Authors: Hao-Yu Liao, Chang Zhao, Jiayi Song, Wei Shao
Pages: 1071-1074
DOI: 10.1145/3748636.3764178
Book Chapter Publication on Ecosystem Degradation
Congratulations to Hao-Yu Liao and Dr. Chang Zhao 🎉 on their book chapter publication! Their chapter, "Ecosystem degradation" (Chapter 18), has been published in Data-Driven Earth Observation for Disaster Management: From Theory to Practical Applications (Earth Observation 2026) by Elsevier. The chapter synthesizes pathways through which Earth observation data are transformed into ecosystem service supply estimates and presents a case study on detecting urban trees using deep learning models 🌳📚.
AGU Fall Meeting 2025 Poster Presentations
Congratulations to our lab members 🎉 for presenting three poster presentations at the American Geophysical Union (AGU) Fall Meeting 2025! The presentations showcase our research in geospatial AI, ecosystem services, and remote sensing applications 🌍🤖.
- Hao-Yu Liao: Mapping Cultural Ecosystem Service Flows from Crowdsourced Imagery: A Zero-Shot Learning Approach with the Vision–Language Model CLIP (GC31H-0766)
- Jiayi Song: FoundationSoil: A GeoAI Framework for Mapping Soil Organic Carbon Stocks Using Foundation Models and Explainable Machine Learning (GC31H-0769)
- Mohanad Diab: Calibrated Multi-Model Ensemble with Dynamic Thresholding and Weighted Box Fusion for Robust Object Detection in Noisy Remote Sensing Datasets (GC31H-0770)
ACM SIGSPATIAL2025 Travel Award
Congratulations to Jiayi Song, Hao-Yu Liao 🎉 on receiving the highly competitive ACM SIGSPATIAL2025 Travel Award. Which had a total pool of 130+ applicants.
Journal Publication on Invasive Species Mapping
Congratulations to Jiayi Song, Hao-Yu Liao 🎉 on their latest journal publication in the International Journal of Applied Earth Observation and Geoinformation! Their paper, "Mapping invasive Opuntia stricta in Kenya's Drylands using explainable machine learning with time-series remote sensing and geographic context", demonstrates how explainable AI and geospatial data can support ecological monitoring and invasive species management 🌵🌍.
Two Papers Accepted to SIGSPATIAL '25
Congratulations to Jiayi Song, Hao-Yu Liao 🎉 for having two papers accepted to the 33rd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '25), which will be held in Minneapolis, MN, USA from November 3–6, 2025! The first paper, "FoundationSoil: Enhancing Soil Organic Carbon Mapping Using a Multi-Temporal Geospatial Foundation Model", introduces a foundation model for improving soil carbon mapping 🌱. The second paper, "Mapping Cultural Ecosystem Services Using One-Shot In-Context Learning with Multimodal Large Language Models", explores how multimodal AI can capture cultural ecosystem services 🤖🌍.
Conference Presentation in Ecuador
Congratulations to Joseph Benjamin and Hao-Yu Liao for presenting our research at the Resilience in Urban Environments toward SDG Sustainable Cities conference in Cuenca, Ecuador 🌍! Their poster, titled "Modelling the inequitable distribution of aesthetic green views across dimensions of supply, demand, accessibility, and flow", sheds light on how urban green aesthetics are unevenly distributed and why this matters for equitable and sustainable city design 🌱.
First Place in 3MC Competition
Congratulations to Joseph B. Benjamin for winning first place in the undergraduate Three Minute Capstone (3MC) in Sustainability and the Built Environment (SBE) at University of Florida!! 🎉🎉👏 Our research explores the spatial variability and interconnections of aesthetic green view (AGV) supply and flows in urban streetscapes, emphasizing their broader significance for urban greening initiatives 🌳.
Dunkle Geography Award
Congratulations to Olivia Zhang for being the winner of the 2025 John R. and Fawn T. Dunkle Geography Award !! 🎉🎉👏 The Dunkle award honors the long-time service and devotion of Professor John R. Dunkle to the Department of Geography at the University of Florida. Olivia is pursuing a Bachelor of Science in Geography along with a dual degree in Data Science.
AI University Scholars Award
Congratulations to Olivia Zhang on receiving the esteemed AI University Scholars Award for 2025-2026 at the University of Florida! 🎉🎉👏 This program was established to support outstanding undergraduate students venturing into the exciting world of academic research. As an AI University scholar in our lab, Olivia focuses on developing computer vision models to detect urban agriculture using both environmental and social sensing.
Postdoctoral Travel Award
Congratulations Dr. Hao-Yu Liao on winning the Travel Awards at our first-ever UF Postdoctoral Affairs Awards Ceremony! 🎉🎉🎉
AI Scholars Award 2024-2025
Congratulations to Joseph B. Benjamin on receiving the esteemed AI Scholars Award for 2024-2025 at the University of Florida! 🎉🎉👏 As an AI scholar in our lab, Joseph focuses on applying image segmentation models for cultural ecosystem services assessments in urban areas.
Dr. Chang Zhao
Assistant Professor of Ecosystem Services Artificial Intelligence (AI)
Dr. Zhao is an Assistant Professor of Ecosystem Services Artificial Intelligence (AI) at the University of Florida. She received her Ph.D. in Geography from the University of Iowa in 2018 and her B.E. in Geodesy and Geomatics Engineering from Wuhan University in 2012. Prior to joining the University of Florida, she worked as a research methodologist in spatial data science at NORC at the University of Chicago. Her research interests include Geographic Information Science, Remote Sensing, Geovisualization, Ecosystem Service Assessments, and AI (Machine Learning and Deep Learning).
Pioneering Geospatial Intelligence
The Ecosystem Services and Geospatial Artificial Intelligence (GeoAI) Lab at the University of Florida is at the forefront of integrating advanced AI technologies with geospatial analysis to understand and model ecosystem services.
Our research bridges the gap between artificial intelligence, remote sensing, and environmental science, creating innovative solutions for understanding complex ecological systems and their services to humanity. We employ a wide range of geospatial, statistical, and AI tools, as well as observational, modeling, and mixed approaches.
Our Research Focus
Geospatial AI
Combining machine learning, deep learning, GIS, remote sensing, and field observation to quantify spatiotemporal dynamics of ecosystem services across urban and agricultural landscapes.
Ecosystem Services
Incorporating socioeconomic data (census, surveys, social media, crowdsourced data) and qualitative methods into ecosystem service assessments to understand drivers and consequences on human health and well-being.
Remote Sensing
Utilizing GIS, remote sensing, and AI to support interdisciplinary applications in agriculture, public health and social sciences.
Spatial Modeling
Creating predictive models that integrate geospatial data with environmental variables to forecast ecosystem responses and support sustainable land use planning.
Big Data Analytics
Processing and analyzing large-scale geospatial datasets to extract meaningful insights about environmental patterns and ecosystem service flows.
Environmental Informatics
Developing computational tools and frameworks for integrating diverse environmental data sources and knowledge systems to enhance decision-making.
Meet the Researchers
Postdoctoral Associate
Hao-Yu Liao
Postdoctoral Associate
Hao-Yu Liao is a postdoctoral associate at the Agronomy department at UF/IFAS. Before joining the lab, he has a PhD degree in Environmental Engineering Sciences in the UF. He was an assistant researcher at National Taiwan University (NTU) from 2016 to 2019. Ecosystem Services, Carbon Storage and Sequestration, Recreational Activities, Machine Learning Algorithms, Optimization Methods, Data Analysis, and GeoAI are among his research interests.
Graduate Researchers
Song Jiayi
PhD Student
Jiayi is a PhD student in the School of Natural Resources and Environment. He received his master's from the University of Florida, where he studied computer engineering. For his PhD, he is working in interdisciplinary ecology, studying how Artificial Intelligence, especially Deep Learning, is used in ecosystem modelling.
Levi Hoskins
PhD Student
Levi is a PhD student in the School of Natural Resources and Environment and will be working on a PhD in interdisciplinary ecology. They received their bachelor's from Tulane University where they studied habitat fragmentation in the Chocó Rainforest of Ecuador. During their PhD, they will study how humans and migratory animals use urban greenspaces.
Mohanad Diab
PhD Student
Mohanad is a PhD student in the School of Natural Resources and Environment at the University of Florida, his main interests are related to artificial intelligence, remote sensing, and sustainability science. His research focuses on advancing learning theory and developing foundation models for geospatial and environmental applications.
Izhar Ahmad
PhD Student
Izhar Ahmad is a PhD student at the University of Florida. He holds a Bachelor's in Civil Engineering and a Master's in Water Resources and Environmental Engineering. His doctoral research centers on mapping cover crops and evaluating their ecosystem services, particularly their influence on water quality, quantity, and nutrient cycling.
Sotirios Kechagias
PhD Candidate
Sotirios is a first-year PhD candidate with a background in applied geology, earth observation, and AI-based soil mapping. His research focuses on monitoring temporal dynamic changes in soil properties driven by climate change and human interference.
Joseph B. Benjamin
Undergraduate Researcher
Joseph (Joey) Benjamin studies at the intersection of equitable spatial planning, AI technology, and environmentalism. Currently, he is a fourth-year Sustainability and the Built Environment + Geodesign undergraduate at the University of Florida.
Undergraduate Researchers
Olivia Zhang
Undergraduate Student
Olivia Zhang is an undergraduate student at the University of Florida studying Geography and Data Science and pursuing a certificate in Geographic AI. Having grown up in coastal cities, she is passionate about leveraging geospatial data to better understand human-environment interactions in a changing climate.
Luca Pishos
Undergraduate Researcher
Luca Pishos is an undergraduate researcher studying Computer Science and Mathematics in the College of Engineering. His experience includes software engineering, computer vision, computational modeling, and data analytics. In the lab, he focuses on geospatial informatics and remote sensing, using machine learning to analyze satellite imagery.
Angelina Wu
Undergraduate Researcher
Angelina Wu is an undergraduate researcher studying computer science and statistics. She is experienced in software engineering, from cloud and infrastructure to full-stack, and data analytics. She is interested in using computer science to create tools with equitable and scalable benefits. In this lab, she focuses on using machine learning to extract insights from satellite imagery.
Alumni
Zhou Tang
Former Postdoctoral Associate
Zhou (Joe) Tang was a postdoctoral associate at the Agronomy Department, University of Florida Institute of Food and Agricultural (UF/IFAS). He obtained his PhD degree in Crop and Soil Sciences from Washington State University.
Dinesh Chowdary
Alumni
Dinesh graduated with a Master of Science in Computer Science from the University of Florida.
Peer-Reviewed Journal Publications
Mapping invasive Opuntia stricta in Kenya's Drylands using explainable machine learning with time-series remote sensing and geographic context
International Journal of Applied Earth Observation and Geoinformation, 144, 104867
Read More →Detection and mapping of Amaranthus spinosus L. in bermudagrass pastures using drone imagery and deep learning for a site-specific weed management
Agronomy Journal, 116, 990–1002
Read More →Making Sense of Sensor Data: How Local Environmental Conditions Add Value to Social Science Research
Social Science Computer Review, 40(1), 179-194
Read More →Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology
Journal of Medical Internet Research, 23(8), e24408
Read More →Modeling retailer-based exemptions in flavored tobacco sales restrictions: National estimates on the impact of product availability
BMJ Open, 10(11), e040490
Read More →Wild bees and urban agriculture: assessing pollinator supply and demand across urban landscapes
Urban Ecosystems, 22(3), 455-470
Read More →Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr
ISPRS International Journal of Geo-Information, 8(1), 45
Read More →Space-time analysis of high technology entrepreneurship: A comparison of California and New England
Applied Geography, 95, 111–119
Read More →Assessing the sensitivity of urban ecosystem service maps to input spatial data resolution and method choice
Landscape and Urban Planning, 175, 11–22
Read More →Assessing the potential for raw meat to influence human colonization with Staphylococcus aureus
Scientific Reports, 7(1)
Read More →Comparisons of spatial and non-spatial models for predicting soil carbon content based on visible and near-infrared spectral technology
Geoderma, 285, 280–292
Read More →Exploring the Role of the Spatial Characteristics of Visible and Near-Infrared Reflectance in Predicting Soil Organic Carbon Density
ISPRS International Journal of Geo-Information, 6(10), 308
Read More →Dynamic Assessment of Current Management in an Intensively Managed Agroecosystem
Journal of Contemporary Water Research & Education, 158(1), 148–171
Read More →Quantifying and Mapping the Supply of and Demand for Carbon Storage and Sequestration Service from Urban Trees
PLOS ONE, 10(8), e0136392
Read More →Relative effects of geographically isolated wetlands on streamflow: a watershed-scale analysis
Ecohydrology, 9(1), 21–38
Read More →Peer-Reviewed Conference Proceedings
FoundationSoil: Enhancing Soil Organic Carbon Mapping Using a Multi-Temporal Geospatial Foundation Model
SIGSPATIAL '25: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, Pages 1067-1070. Published: 12 December 2025
Read More →Mapping Cultural Ecosystem Services Using One-Shot In-Context Learning with Multimodal Large Language Models
SIGSPATIAL '25: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, Pages 1071-1074. Published: 12 December 2025
Read More →Quantifying Heterogenous Ecosystem Services with Multi-label Soft Classification
In the 44th IEEE IGARSS International Geoscience and Remote Sensing Symposium, Greece
Book Chapters
Ecosystem degradation
Chapter 18 in Data-Driven Earth Observation for Disaster Management: From Theory to Practical Applications (Earth Observation 2026), Pages 303-325, Elsevier
Read More →Courses
AGR SWS 4932/6932
Ecosystem Services: Theory, Methods, and Practice
Course Number: AGR SWS 4932/6932
Description: Ecosystem Services: Theory, Methods, and Practice
AGR6932-CAM1
Geospatial AI for Sustainability Science
Course Number: AGR6932-CAM1 (24230)
Term: Fall 2025
Description: Geospatial AI for Sustainability Science
Join Our Team
PhD Opportunities
Graduate Research Position
Location: Gainesville, Florida, USA
Dr. Zhao's lab in the UF/IFAS Agronomy Department at the University of Florida is always looking for highly creative and motivated PhD candidates interested in Geospatial Artificial Intelligence, Remote Sensing, Ecosystem Services, and related interdisciplinary research areas.
Our research integrates geospatial analysis with artificial intelligence, machine learning, and deep learning to address critical questions in ecosystem services, crop mapping, environmental monitoring, and sustainable land management.
AI Scholar Program
Paid Research Position
Eligibility: UF undergraduate students (any major)
The AI Scholar Program is an exclusive opportunity for University of Florida undergraduates to conduct research in our lab. This is a paid position open to students from any major who are interested in geospatial AI, remote sensing, and ecosystem services research.
As an AI Scholar, you'll work alongside graduate students and faculty on cutting-edge research projects, gaining valuable experience in artificial intelligence, machine learning, and geospatial analysis. The program includes a $1,750 stipend paid over two semesters.
IFAS/CALS Summer Internship
Paid Summer Internship - Cover Crop Mapping Project
Eligibility: CALS undergraduate students
Deadline: February 20, 2026
Duration: July 1, 2026 - June 30, 2027 (up to 240 hours)
Compensation: $15 per hour
Join our USDA-funded cover crop mapping project for Florida. Work on satellite image data preprocessing, data annotation, data analysis, and visualization of agricultural monitoring data. This internship focuses on Earth observation-based cover crop mapping and monitoring, and agroecosystem services modeling.
Requirements:
- Undergraduate in a College of Agricultural and Life Sciences major
- Background in GIS, Remote Sensing, Python, and basic understanding of AI
- Available for summer
Undergraduate Research Credit Hours
Research Experience & Academic Credit
Prospective undergraduate students who want to work in our lab can gain research experience and academic credit through undergraduate research credit hours.
This opportunity allows you to:
- Work on real research projects in geospatial AI and ecosystem services
- Receive mentorship from faculty and graduate students
- Earn academic credit while building your research portfolio
- Explore potential career paths in research and academia
Open to all undergraduate students interested in our research areas, regardless of major.