The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


Conveners will be contacted by the AGU25 Program Committee with any requests for mergers or edits to proposals. Conveners will be notified of the acceptance of their proposal in mid-June.


Abstract submissions will also open in mid-June and the deadline for abstract submissions is 30 July, 2025.


Please visit the AGU25 website for more information or please contact AGU with any questions.

Session Proposal: Advancing Remote Sensing for Ecosystem Health: Bridging Science, Technology, and Forest Management (AGU25)

B014
Advancing Remote Sensing for Ecosystem Health: Bridging Science, Technology, and Forest Management

Session ID#: 246687

Session Description:
Remote sensing enables the quantification of ecosystem properties, vegetation dynamics, and environmental disturbances, including disease outbreaks, drought stress, and climate-driven shifts. This session focuses on the application of optical, thermal, and microwave remote sensing, including multispectral and hyperspectral imaging, thermal infrared sensing, light detection and ranging (LiDAR), and synthetic aperture radar (SAR), in ecosystem monitoring. Contributions are invited on the integration of remote sensing with ecological modeling, climate data, and biodiversity assessments to improve the characterization of forest health, land surface processes, and biophysical parameters. The session will examine methodological developments and their application in large-scale environmental monitoring.
Index Terms:

0434 Data sets [BIOGEOSCIENCES]
0452 Instruments and techniques [BIOGEOSCIENCES]
Primary Convener:  Ms. Swati Singh, PhD, College of Forestry, Wildlife and Environment, Auburn, United States
Convener:  Swati Singh, College of Forestry, Wildlife and Environment, College of Forestry, Wildlife and Environment, Auburn, United States
Student/Early Career Convener:  Ms. Swati Singh, PhD, College of Forestry, Wildlife and Environment, Auburn, United States
 
A Deep Learning-based Method for High-precision Tree Species Classification and Stand Boundary Extraction (1912492)
Jianwen Huang1, Yong Pang2, Pumei Lang3 and Xuefeng Wang1, (1)Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijjing, China, (2)Chinese Academy of Forestry, Beijing, China, (3)Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China
 
Parameter Optimization of RGB-Based Structure-from-Motion Photogrammetry for Individual Tree Detection in a Loblolly Pine Forest (1939663)
Ms. Swati Singh, PhD, College of Forestry, Wildlife and Environment, Auburn, United States and Lana L. Narine
 
Deep Learning-Based Detection of Brown Spot Needle Blight in Pine Forests of the Southeastern US Using UAV-Based Imagery and LiDAR Data (1939971)
Ms. Swati Singh, PhD, College of Forestry, Wildlife and Environment, Auburn, United States and Lana L. Narine
 
Losing Green Lifelines: Three Decades of Riverine Forest Degradation in Sindh Revealed through Remote Sensing (1945884)
Raheela Naz, Punjab Forest Department, GIS LAB, Lahore, Pakistan, Muhammad Afrsiyab, 2., Assistant Inspector General Forests, Ministry of Climate Change and Environmental Coordination, Government of Pakistan., Islamabad, Pakistan, Sidrah Hafeez, R & D Hong Kong Science and Technology, Park,Previsico Asia Limited, Hong Kong, Hong Kong and Zaeem Shabir, National Defence University,, Researcher at Maritime Center of Excellence,, Islamabad, Pakistan
 
Building California-tailored disturbance monitoring system using long-term and continuous Landsat data (1948856)
Hirofumi Hashimoto1, Khuong H Tran2, Pratima K C3, Kyle Kristian Kabasares3, Zhe Zhu4, Scott Horner5, Wen Yip3, Ramakrishna R Nemani6, Ian G Brosnan7 and Taejin Park8, (1)California State University Monterey Bay, Seaside, CA, United States, (2)South Dakota State University, Geospatial Sciences Center of Excellence (GSCE), Department of Geography & Geospatial Sciences, Brookings, SD, United States, (3)Bay Area Environmental Research Institute, Moffett Field, United States, (4)University of Connecticut, Department of Natural Resources and the Environment, Storrs, United States, (5)NASA Ames Research Center, Moffett Field, United States, (6)NASA Ames Research Center, Moffett Field, CA, United States, (7)NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States, (8)NASA Ames Research Center/Bay Area Environmental Research Institute, Moffett Field, United States
 
Estimating Field Tree Volume and Biomass Change Using UAV Imagery and Structure from Motion Point Clouds (1965867)
Jiyeon Kim, Stephen F Austin State University, Nacogdoches, TX, United States, Sorin C Popescu, Texas A&M University, Department of Ecology and Conservation Biology, College Station, United States and The East Texas Pine Plantation Research Project (ETPPRP) team and the Stephen F. Austin State University (SFA) Geospatial Science team
 
Learning to Count Standing Dead Trees: CSRNet-Based Detection of Snags in Washington State (1966102)
Stephanie Willsey, Purdue University, West Lafayette, IN, United States and Songlin Fei, Purdue University, Forestry and Natural Resources, West Lafayette, United States
 
Species, Subspecies, and Stress: Spaceborne Hyperspectral Analysis of Forestry Monitoring Impacts (1977319)
Megan Gallagher1, Ryan Hammock2 and Jeremy Kravitz1, (1)Pixxel Space Technologies, El Segundo, United States, (2)Pixxel, Seattle, United States
 
Miti360: An Integrated Dataset Combining Remote Sensing, Ground Measurements and Weather Data for Improved Reforestation Monitoring (1987602)
Cedric Kiplimo1, Samuel Gachana1, Ciira wa Maina1, Arthur Sichangi2 and Dennis Gitundu2, (1)Dedan Kimathi University of Technology, Centre for Data Science and Artificial Intelligence, Nyeri, Kenya, (2)Dedan Kimathi University of Technology, Institute of Geomatics, GIS and Remote Sensing, Nyeri, Kenya
 
Mapping tree species diversity in a subtropical mountainous forest using Bi-temporal Sentinel-2 and airborne LIDAR data (1988682)
Shiming Li and Qing Liu, Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China
 
FasterR-CNN for Urban Tree Detection and Enumeration Using Optical R G B: Insights and Limitations from a City Scale Experimentation (1992809)
Michael S. Agbozo1, Luke J. Marzen1 and Matthew B. Kursah2, (1)Auburn University, Department of Geosciences, Auburn, AL, United States, (2)University of Education, Winneba, Department of Geography Education, Winneba, Ghana
See more of: Biogeosciences
<< Previous Session Proposal | Next Session Proposal >>