English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Surface soil moisture quantification models from reflectance data under field conditions

Haubrock, S., Chabrillat, S., Lemmnitz, C., Kaufmann, H. (2008): Surface soil moisture quantification models from reflectance data under field conditions. - International Journal of Remote Sensing, 29, 1, 3-29.
https://doi.org/10.1080/01431160701294695

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Haubrock, Sören1, Author           
Chabrillat, Sabine2, Author                 
Lemmnitz, C.3, Author
Kaufmann, Hermann2, Author           
1.3 Earth System Modelling, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, Author              
Affiliations:
1Deutsches GeoForschungsZentrum, ou_persistent13              
21.4 Remote Sensing, 1.0 Geodesy and Remote Sensing, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146028              
3External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 DDC: 550 - Earth sciences
 Abstract: A new approach to estimate surface soil moisture from reflectance data in the solar spectral range (350-2500 nm) is presented, called the Normalized Difference Soil Moisture Index (NSMI). The motivation for this new index is to make use of spectral features that fulfill the criteria of robustness against covariates, physical comprehensibility and easy applicability in the field and from remote sensing platforms. Spectral measurements were taken in the laboratory from 121 prepared as well as 467 natural soil samples consisting of different sands and clayey substrates originating from a lignite mine reclamation site. While the preparation procedure performed on samples from the first group removed the covariates' influence on the reflectance spectra, the natural samples in the second group maintained the influencing factors like impurity, crusts, and organic matter. In a systematic way all wavelengths were combined in different spectral feature approaches and optimum bands or band combinations were found for linear correlation with soil moisture. For the natural samples, the NSMI achieved best results in this study with R 2 of 0.61 by combining reflectance values at 1800 and 2119 nm. This value increased to 0.71 when samples with significant xylite proportions had been removed. Analyses on the effect of single covariates showed that neither surface crusts nor substrate heterogeneity changed the correlation between soil moisture and the NSMI significantly. The NSMI can therefore be seen as a new index for quick assessment of surface or near-surface soil moisture directly in the field using spectral instruments.

Details

show
hide
Language(s):
 Dates: 2008
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 10570
GFZPOF: 2.0 Geodynamik, Stoffkreisläufe und Ressourcen
GFZPOF: 3.0 Klimavariabilität und Lebensraum des Menschen
DOI: 10.1080/01431160701294695
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: International Journal of Remote Sensing
Source Genre: Journal, SCI, Scopus
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 29 (1) Sequence Number: - Start / End Page: 3 - 29 Identifier: CoNE: https://gfzpublic.gfz.de/cone/journals/resource/journals226