Upscaling of spectroradiometer data for stress detection in orchards with remote sensing

Pieter Kempeneers; Steve De Backer; Stephanie Delalieux; Sindy Sterckx; Walter Debruyn; Pol Coppin; Paul Scheunders

doi:10.1117/12.565523

26 October 2004 Upscaling of spectroradiometer data for stress detection in orchards with remote sensing

Pieter Kempeneers, Steve De Backer, Stephanie Delalieux, Sindy Sterckx, Walter Debruyn, Pol Coppin, Paul Scheunders

Proceedings Volume 5568, Remote Sensing for Agriculture, Ecosystems, and Hydrology VI; (2004) https://doi.org/10.1117/12.565523
Event: Remote Sensing, 2004, Maspalomas, Canary Islands, Spain

Abstract

This paper studies the detection of vegetation stress in orchards via remote sensing. During previous research, it was shown that stress can be detected reliably on hyperspectral reflectances of the fresh leaves, using a generic wavelet based hyperspectral classification. In this work, we demonstrate the capability to detect stress from airborne/spaceborne hyperspectral sensors by upscaling the leaf reflectances to top of atmosphere (TOA) radiances. Several data sets are generated, measuring the foliar reflectance with a portable field spectroradiometer, covering different time periods, fruit variants and stress types. We concentrated on the Jonagold and Golden Delicious apple trees, induced with mildew and nitrogen deficiency. First, a directional homogeneous canopy reflectance model (ACRM) is applied on these data sets for simulating top of canopy (TOC) spectra. Then, the TOC level is further upscaled to TOA, using the atmospheric radiative transfer model MODTRAN4. To simulate hyperspectral imagery acquired with real airborne/spaceborne sensors, the spectrum is further filtered and subsampled to the available resolution. Using these simulated upscaled TOC and TOA spectra in classification, we will demonstrate that there is still a differentiation possible between stresses and non-stressed trees. Furthermore, results show it is possible to train a classifier with simulated TOA data, to make a classification of real hyperspectral imagery over the orchard.

Citation Download Citation

Pieter Kempeneers, Steve De Backer, Stephanie Delalieux, Sindy Sterckx, Walter Debruyn, Pol Coppin, and Paul Scheunders "Upscaling of spectroradiometer data for stress detection in orchards with remote sensing", Proc. SPIE 5568, Remote Sensing for Agriculture, Ecosystems, and Hydrology VI, (26 October 2004); https://doi.org/10.1117/12.565523

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