Soil Moisture Estimation From Soil Spectral Characteristics in a Precision Farming Environment
Kaleita, Amy Leigh
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/86052
Description
Title
Soil Moisture Estimation From Soil Spectral Characteristics in a Precision Farming Environment
Author(s)
Kaleita, Amy Leigh
Issue Date
2003
Doctoral Committee Chair(s)
Michael C. Hirschi
Department of Study
Agricultural Engineering
Discipline
Agricultural Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Remote Sensing
Language
eng
Abstract
Spectral reflectance data were analyzed in conjunction with surface moisture data to determine the nature of the relationship between the two. For one of the fields, the strongest relationship between reflectance and surface moisture was between 550 and 620 nm. For the other, the strongest relationship was around 945 nm. Finally, a combination of spectral data and limited moisture data was used to create moisture maps. Use of a cokriging technique generated more detailed soil moisture maps than the limited data alone. This method shows potential for development as part of a data fusion technique to generate moisture maps from a minimum of samples.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.