IEEE GRSS
First Slide
2026 IEEE International Geoscience and Remote Sensing Symposium
9 - 14 August 2026 • Washington, D.C.
TUP1.PG: Biomass and Carbon Cycle II
Tuesday, 11 August, 09:45 - 11:00
Location: Poster Area G
Session Type: Poster
Track: Land Applications
Poster Area G

TUP1.PG.1: A Daily-Scale 16 m NDVI Reconstruction Method Based on Tower-Derived Phenological Archetypes
Xiangyu Xiao, University of Electronic Science and Technology of China, China; Yadong Dong, Jing Zhao, Jing Li, Qinhuo Liu, Chinese Academy of Sciences, China
Poster Area G

TUP1.PG.2: HYPERSPECTRAL VEGETATION SPECIES MAPPING TO SUPPORT BUSHFIRE EMISSIONS INVENTORIES
Christopher Evangelides, James Lewis, Ricardo (Member of WSP), United Kingdom
Poster Area G

TUP1.PG.3: Aboveground Biomass Inversion Using DTM-Independent Crown Metrics from UAV Stereoscopic Imagery
Qiang Wang, Yu Wang, Xiaoling Yin, Zongling Jiang, Heilongjiang Institute of Technology, China
Poster Area G

TUP1.PG.4: INTEGRATING HYPERSPECTRAL IMAGING, LIDAR, AND 3D RADIATIVE TRANSFER MODELING TO PREDICT FOREST GPP
Zachary Butterfield, Kyla Dahlin, Meicheng Shen, Michigan State University, United States; Aaron Kamoske, US Department of Agriculture Forest Service, United States; Scott C Stark, Michigan State University, United States; Shawn Serbin, NASA Goddard Space Flight Center, United States; Chris Gough, Virginia Commonwealth University, United States; Hideki Kobayashi, Japan Agency for Marine-Earth Science and Technology, Japan
Poster Area G

TUP1.PG.5: ESTIMATION OF ABOVE GROUND BIOMASS IN AGROFORESTRY REGIONS USING INSTANCE SEGMENTATION
Chandan R, Ayush Kumar Gupta, Indian Institute of Technology Dharwad, India; Kallol Mallick, Azure Software Pvt. Ltd., India; Jayanta Mukhopadhyay, Indian Institute of Technology Kharagpur, India; Shashaank A. Mattur, Indian Institute of Technology Dharwad, India
Poster Area G

TUP1.PG.7: THE ROLE OF RADIOMETRIC FEATURES IN CROSS-SITE LEAF-WOOD SEGMENTATION OF LIDAR POINT CLOUDS
Roman Kaharlytskyi, Derek Robinson, Roberto Guglielmi, University of Waterloo, Canada
Poster Area G

TUP1.PG.8: A COMPARISON OF DEEP LEARNING OBJECT DETECTION ARCHITECTURES FOR CHM-BASED INDIVIDUAL TREE DETECTION IN DENSE CONIFEROUS FORESTS
Parsa Keshavarz Alamdari, California State University, Northridge, United States