AAG 2025 Symposium on Spatial AI & Data Science for Sustainability: Advances in multitemporal remote sensing for terrestrial ecosystems
Type: Paper - Hybrid/Streamed
Recording Plan: Yes
Theme:
Curated Track:
Sponsor Group(s):
Cyberinfrastructure Specialty Group, Geographic Information Science and Systems Specialty Group, Spatial Analysis and Modeling Specialty Group
Organizer(s):
Yilun Zhao University of Illinois Urbana-Champaign - Department of Geography and Geographic Information Science
Zijun Yang University of North Carolina - Wilmington
Chunyuan Diao
Chair(s):
Yilun Zhao, University of Illinois Urbana-Champaign - Department of Geography and Geographic Information Science
,
Call For Participation
If you are interested in presenting a paper in this session, please (1) register and submit your abstract through AAG, and (2) send your presenter identification number (PIN), paper title, and abstract, to Yilun Zhao (yilun3@illinois.edu) and Zijun Yang (yangz@uncw.edu). If you have any questions, please feel free to email us.
Description:
In the era of climate change and increased ecological pressures, it becomes increasingly important to understand the dynamics of terrestrial ecosystems and their responses to environmental changes. Multitemporal remote sensing offers a unique pathway for monitoring these ecosystems, capturing their temporal variations with unprecedented spatial detail and frequency. This session invites research that leverages multitemporal remote sensing to enhance our knowledge of terrestrial ecosystems. Specifically, this session calls for submissions that highlight novel theoretical frameworks, methodological advances, or applications of multitemporal remote sensing that contribute to our ability to observe, analyze, and model terrestrial ecosystems over time. We also encourage contributions that integrate multitemporal datasets with advanced analytical methods, such as machine learning and other data-driven approaches. Papers that demonstrate the synergy of multitemporal remote sensing with other data sources and technologies to provide deeper ecological insights are also welcome.
Potential topics include, but are not limited to:
- Climate and ecosystem monitoring
- Data generation with remote sensing and machine learning for ecosystem monitoring
- Modeling and quantification of ecosystem responses to climate change
- Near-real-time applications in ecosystem monitoring
- Cyberinfrastructure for multitemporal remote sensing
- Changes in land cover and use
- Assessment of ecosystem functioning and health
- Remote identification of vegetation phenology, biomass estimation, etc.
Presentations (if applicable) and Session Agenda:
Jing Miao, SUNY - Buffalo |
A large-scale mangrove species classification method using time-series data with phenological information and gaussian mixture model |
Gus Cooke |
Utilizing Machine Learning for Training and Custom Automatic Point Cloud Classification |
Xavier Haro-Carrión, Macalester College |
Landscape Attributes and Their Role in Shaping Tree Species Diversity in a Highly Fragmented Tropical Dry Forest Landscape in Coastal Ecuador: 2013 - 2023 |
Yilun Zhao, University of Illinois Urbana-Champaign - Department of Geography and Geographic Information Science |
Detecting Tamarisk beetle induced defoliation and vegetation regrowth in Colorado River Tributary with Landsat time series |
Zijun Yang, University of North Carolina - Wilmington |
Near real-time crop phenology characterization of the US Corn Belt |
Non-Presenting Participants
Role | Participant |
|
|
|
|
|
|
|
|
|
|
AAG 2025 Symposium on Spatial AI & Data Science for Sustainability: Advances in multitemporal remote sensing for terrestrial ecosystems
Description
Type: Paper - Hybrid/Streamed
Contact the Primary Organizer
Yilun Zhao University of Illinois Urbana-Champaign - Department of Geography and Geographic Information Science
yilun3@illinois.edu
Session sponsored by: