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Proceedings Paper

Leaf area index determination of wheat indicating heterogeneous soil conditions
Author(s): K. Huber; J. Eitzinger; P. Rischbeck; W. Schneider; F. Suppan; P. Weihs
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Paper Abstract

The objective of this study, which is part of the project "crop drought stress monitoring by remote sensing" (DROSMON), is to assess the potential of hyperspectral imagery to determine drought stress of crops due to heterogeneous soil composition by estimating the leaf area index (LAI). LAI, which characterizes the actual status of the crops and therefore the potential yield, may be seen as the most important parameter indicating medium term drought stress. As a result of former river meanders, the soils in the Marchfeld region are interrupted by bands of lighter soil. The higher content of sand in the bands leads to a lower water storage capacity and consequently to a decrease in plant growth. An airborne HyMap image was acquired in June 2005 during anthesis stage of wheat. Inversion of a radiative transfer model by means of a look-up-table (LUT) approach was performed to retrieve LAI and other canopy parameters from wheat canopy reflectance. Additionally, the LAI was estimated by establishing empirical relationships between LAI and spectral indices (MSAVI, TVI and MTVI2). Both ways of LAI estimation showed a reasonable correlation to final yield measurements obtained one month after the image data acquisition. However, there was a slightly better agreement of model inversion results. The results suggest the applicability of hyperspectral imagery to map potential drought risk of (wheat) fields.

Paper Details

Date Published: 17 October 2006
PDF: 9 pages
Proc. SPIE 6359, Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII, 63590M (17 October 2006); doi: 10.1117/12.689832
Show Author Affiliations
K. Huber, Univ. of Natural Resources and Applied Life Sciences (Austria)
J. Eitzinger, Univ. of Natural Resources and Applied Life Sciences (Austria)
P. Rischbeck, Univ. of Natural Resources and Applied Life Sciences (Austria)
W. Schneider, Univ. of Natural Resources and Applied Life Sciences (Austria)
F. Suppan, Univ. of Natural Resources and Applied Life Sciences (Austria)
P. Weihs, Univ. of Natural Resources and Applied Life Sciences (Austria)


Published in SPIE Proceedings Vol. 6359:
Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII
Manfred Owe; Guido D'Urso; Christopher M. U. Neale; Ben T. Gouweleeuw, Editor(s)

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