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Linear spectral unmixing for crop and soil information extraction from a single worldview-2 image

Spatial information related to vegetation status and soil properties is needed in precision farming, especially early in the growing season. At these stages, vegetation has already emerged while soil is also visible in multispectral EO images. In this paper, linear spectral unmixing is applied to an...

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Main Authors: Bouroubi, Yacine, Tremblay, Nicolas, Vigneault, Philippe, Benoit, Mathieu
Format: Conference Proceeding
Language:English
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Tremblay, Nicolas
Vigneault, Philippe
Benoit, Mathieu
description Spatial information related to vegetation status and soil properties is needed in precision farming, especially early in the growing season. At these stages, vegetation has already emerged while soil is also visible in multispectral EO images. In this paper, linear spectral unmixing is applied to an 8 bands WorldView-2 image to extract information on both vegetation and soil acquired at in-season nitrogen sidedress stage in 2010 and 2011 for four corn fields located in the Montérégie region of Quebec, Canada. EO derived soil properties were strongly correlated to EC a . Correlation between dark soil abundance and EC a reached R=0.9 and correlation between bright soil abundance and EC a was about R=-0.7. Vegetation abundance for combined data of several fields was better correlated to measured biomass than NDVI and SAVI. The possibility to get valuable soil and plant information from a single multispectral image offers an interesting cost reduction opportunity for precision farming applications.
doi_str_mv 10.1109/IGARSS.2014.6947645
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subjects Agriculture
Correlation
crop status observation
Data mining
Linear spectral unmixing
precision farming
Soil measurements
Soil properties
Vegetation mapping
title Linear spectral unmixing for crop and soil information extraction from a single worldview-2 image
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