F12: Microwave Remote Sensing of Vegetation and Terrestrial Snow (1)

Thursday, August 21  08:00-09:20,  Room #4

The use of microwave radiometers and radars to sense soil moisture, vegetation biomass and terrestrial snow characteristics are the subject matter of this session. Experimental activities concerning the observation of soil moisture, vegetation and snow from ground-based instruments, aircraft and satellites will be discussed. Passive and active sensing of terrestrial snow in open areas or forested regions are subjects of interest. Microwave models of emission and backscatter from soils covered by snow and/or vegetation using advanced radiative transfer models will be considered. Finally, retrieval of main parameters of soil, snow, and vegetation by using statistical inversion algorithms are of interest.

8:00  F12.1   USE OF PERIODIC STALKS TO MODEL L BAND RETURNS FROM CORN

R. H. Lang¹, S. S. Seker², M. Kurum³, P. E. O'Neill⁴, M. Cosh⁵

¹Dept of Electrical & Computer Engineering, George Washington Uniiversity, Washington, DC, United States
²Dept of Electrical-Electronic Engg, Bogazici University, Istanbul, Turkey
³Information Technology Institute, Tubitak-Bilgem, Kocaeli, Turkey
⁴Hydrological Sciences Branch, NASA Goddard Space Flight center, Greenbelt, Maryland, United States
⁵Hydrology and Remote Sensing Laboratory, US Dept of Agriculture, Beltsville, Maryland, United States

8:20  F12.2   ELECTROMAGNETIC SCATTERING FROM A CORN CANOPY

Y. Du¹, J. C. Shi², Z. -Y. Li³, E. -X. Chen³

¹Zhejiang University, Zhejiang, China
²Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China
³Research Institute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing, China

8:40  F12.3   ANGULAR ASPECTS OF MICROWAVE SINGLE SCATTERING ALBEDO FROM TAPERED VEGETATION CONSTITUENTS

M. Kurum¹, Q. Zhao², R. H. Lang³

¹Information Technologies Institute, TUBITAK-BILGEM, Kocaeli, Turkey
²OmniVision Technologies, Inc., Santa Clara, CA, USA
³Electrical and Computer Engineering, The George Washington University, Washington, DC, USA

9:00  F12.4   FOREST FEATURE ESTIMATION USING MULTI-MODAL REMOTE SENSING AND SENSOR EXTRAPOLATION TECHNIQUES

M. L. Benson, L. E. Pierce, K. Sarabandi

Electrical Engineering & Computer Science, University of Michigan, Ann Arbor, MI, United States