WE1.P3.3
PREDICTABILITY OF FOREST BIODIVERSITY VARIABLES ON VARYING SPECTRAL AND SPATIAL RESOLUTIONS
Ville Mäyrä, Aalto University, Finland; Joel Kostensalo, Natural Resources Insitute Finland, Finland; Florent Guiotte, Jorma Laaksonen, Aalto University, Finland
Session:
WE1.P3: Advances in Hyperspectral Remote Sensing Image Classification and Their Applications in Agriculture, Forestry, and Wetlands I Oral
Track:
Community-Contributed Sessions
Location:
Room P3
Presentation Time:
Wednesday, 6 August, 08:30 - 08:45
Presentation
Discussion
Resources
No resources available.
Session WE1.P3
WE1.P3.1: Hyperspectral Imaging Based Non-Destructive Peat Analysis for Peatland Protection and Sustainability
Yijun Yan, Joint Lab. of Power Remote Sensing Tech.,, China; Jinchang Ren, Guangdong Polytechnic Normal University, China; Barry Harrison, Oliver Lewis, The Scotch Whisky Research Institute, United Kingdom; Yi Ma, Yunnan Power Grid Co. Ltd, China; Yinhe Li, Yiwu Zhiyuan Research Center of Electronic Technology, China; Ping Ma, Shanghai Ocean University, China
WE1.P3.2: TREE SPECIES CLASSIFICATION WITH HYPERSPECTRAL IMAGES BASED ON CASCADING HIERARCHICAL CLASSIFICATION NETWORK
Yao Jin, Chen Wu, Wuhan University, China
WE1.P3.3: PREDICTABILITY OF FOREST BIODIVERSITY VARIABLES ON VARYING SPECTRAL AND SPATIAL RESOLUTIONS
Ville Mäyrä, Aalto University, Finland; Joel Kostensalo, Natural Resources Insitute Finland, Finland; Florent Guiotte, Jorma Laaksonen, Aalto University, Finland
WE1.P3.4: EMPIRICAL STUDIES OF THE AVIRIS HYPERSPECTRAL DATA SIGNATURES OF DIFFERENT EARTH TERRAINS
Emraul Islam Emon, Afia Mubassira Islam, Christopher Ball, Joel T. Johnson, The Ohio State University, United States; Vasit Sagan, Saint Louis University, United States
Resources
No resources available.