CFP : CV for Vegetation Structure - SF, CA - 07SEP2006

We were hoping for involvement from the Computer Vision community for this
conference session at the American Geophysical Union Fall Meeting (2006):
the application of CV techniques to the analysis of remote sensing imagery
of vegetation ecosystems.

We would like to call to your attention Session B07: Remote Characterization
of Vegetation Structure, to be held during the 2006 AGU Fall Meeting in San
Francisco.

A general description of the Fall Meeting is available at
http://www.agu.org/meetings/fm06

Abstracts can be submitted online
at http://www.agu.org/meetings/fm06/?content=program

The deadline for submitting the abstracts is 7 September 2006.

B07: Remote Characterization of Vegetation Structure

Co-conveners: Alistair Smith (University of Idaho), Lee Vierling (University
of Idaho) and Jonathan Greenberg (NASA Ames Research Center)

This session aims to highlight a broad cross-section of research centered on
the remote characterization of vegetation structure at scales ranging from
the individual plant to the landscape. Knowledge of vegetation structure,
such as the heights, crown width, canopy gaps, and shading, can be used to
evaluate biogeochemical pools and fluxes, vegetation functional group
classification, ecological successional dynamics, light/ and water
interception and their effects on radiative transfer and water budgets,
among other topics. The recent widespread application of light detection and
ranging (lidar) systems has re-emphasized the potential of remote sensing
datasets to characterize such structural information from the individual to
the landscape level.

However, numerous research studies exist that apply novel analysis
techniques to both lidar and passive remote sensing systems, which
collectively have the potential to quantify temporal changes in vegetation
structure and function over decadal time-scales. The session is for a half
day to facilitate interactions between biogeosceinces and hydrological
sciences related researchers. We are soliciting both oral and poster
presentations on all aspects of method development, monitoring, and modeling
applications of using such remotely sensed datasets to quantify vegetation
structure, with emphasis on the following topics:

- Development of automated methods to locate individual trees and shrubs
- Assessment of individual plant structural information from Lidar and
passive systems
- Remote sensing of stand level canopy structure and canopy gaps
- Measurement and prediction of stand to landscape level canopy variables
using Lidar and passive systems
- Using remote measures of vegetation structure to model light and water
interception effects on radiative transfer and water budgets
- Remote sensing to evaluate trends in woody encroachment, carbon
accumulation, and/or plant succession or establishment over decadal time
periods
- Modeling tree shade and shade effects on energy/ and water/snow
interactions