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Proceedings Paper

Direct gradient analysis as a new tool for interpretation of hyperspectral remote sensing data: application to HYMAP/DAISEX-99 data
Author(s): Maria Carmen Gonzalez-Sampedro; Robert John Zomer; Luis Alonso-Chorda; Jose F. Moreno; Susan L. Ustin
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Paper Abstract

Direct gradient analysis, and other canonical community ordination techniques, have been most commonly used by plant ecologists and others attempting to analyse complex multivariate datasets. These multivariate statistical techniques can be applied to a variety of spectral analyses. Particularly useful is the ability to test significance of environmental variables based upon Monte Carlo permutations, allowing for a step-wise model of variance to be built. This technique has been now applied to hyperspectral remotely sensed data, within the overall context of ESA DAISEX-99 experiment. An extensive field campaign in La-Mancha (Spain) was carried out, simultaneously with the overflight of two airborne imaging spectrometers (DAIS, HYMAP) and other sensors (POLDER, LEANDRE).We use in this work data from the 128-channels HYMAP imaging spectrometer jointly with the ground truth data. Direct gradient analysis of the imagery spectra indicated an overall statistical significance when a model based upon three variables was used. Leaf moisture, LAI, and total chlorophyll were the most highly correlated variables, and all demonstrated statistically significant p-values. Hyperspectral remote sensing data requires new techniques to analyse the increasingly complex data. Application of ordination techniques, although not commonly applied within the remote sensing data processing, show good perspectives for more in depth analysis of the whole DAISEX-99 dataset.

Paper Details

Date Published: 23 January 2001
PDF: 10 pages
Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); doi: 10.1117/12.413950
Show Author Affiliations
Maria Carmen Gonzalez-Sampedro, Univ. de Valencia (Spain)
Robert John Zomer, International Ctr. for Research in Agroforestry (Kenya)
Luis Alonso-Chorda, Univ. de Valencia (Spain)
Jose F. Moreno, Univ. de Valencia (Spain)
Susan L. Ustin, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 4171:
Remote Sensing for Agriculture, Ecosystems, and Hydrology II
Manfred Owe; Guido D'Urso; Eugenio Zilioli, Editor(s)

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