An isoline-based translation technique of spectral vegetation index using EO-1 Hyperion data

Yoshioka, H; Miura, T; Huete, AR

An isoline-based translation technique of spectral vegetation index using EO-1 Hyperion data

Yoshioka, H Miura, T Huete, AR

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Geoscience and Remote Sensing, 2003, 41 (6 PART I), pp. 1363 - 1372
Issue Date:: 2003-06-01

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Field	Value	Language
dc.contributor.author	Yoshioka, H	en_US
dc.contributor.author	Miura, T	en_US
dc.contributor.author	Huete, AR https://orcid.org/0000-0003-2809-2376	en_US
dc.date.issued	2003-06-01	en_US
dc.identifier.citation	IEEE Transactions on Geoscience and Remote Sensing, 2003, 41 (6 PART I), pp. 1363 - 1372	en_US
dc.identifier.issn	0196-2892	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8512
dc.description.abstract	The availability of similar satellite data products from multiple sensors has focused much attention on the issue of continuity across satellite data products from past, current, and future sensors. Hyperspectral datasets acquired over a variety of land cover types are extremely useful in attempting to resolve spectral differences in the global datasets from different sensors. The datasets from the Earth Observing 1 (EO-1) Hyperion sensor are very suitable for this purpose, as is airborne hyperspectral data. In this paper, we examine the possibility of translating vegetation index (VI) data between two sensors by using imagery from the Hyperion sensor and utilizing the vegetation isoline concept. The objectives of this paper are to introduce and test a VI translation technique, focused on the spectral differences associated with sensor spectral bandpass filters. The translation of global VI datasets from one sensor to another requires a methodology applicable over various land cover types and throughout the wide ranges in VI values. To meet these requirements, a technique is proposed that utilizes adjustable translation coefficients, based on an estimation of the leaf area index value relative to a numerical canopy model. The theoretical basis of the proposed translation algorithm is explained in terms of the vegetation isoline concept. Its performance was tested through a numerical experiment with a Hyperion image, focusing on the normalized difference vegetation index (NDVI) as a representative vegetation index. The results indicate the potential of the isoline-based translation technique for stable translation throughout wide ranges of NDVI values.	en_US
dc.relation.ispartof	IEEE Transactions on Geoscience and Remote Sensing	en_US
dc.relation.isbasedon	10.1109/TGRS.2003.813212	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	An isoline-based translation technique of spectral vegetation index using EO-1 Hyperion data	en_US
dc.type	Journal Article
utslib.citation.volume	6 PART I	en_US
utslib.citation.volume	41	en_US
utslib.for	0404 Geophysics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0909 Geomatic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access
pubs.issue	6 PART I	en_US
pubs.publication-status	Published	en_US
pubs.volume	41	en_US

Abstract:

The availability of similar satellite data products from multiple sensors has focused much attention on the issue of continuity across satellite data products from past, current, and future sensors. Hyperspectral datasets acquired over a variety of land cover types are extremely useful in attempting to resolve spectral differences in the global datasets from different sensors. The datasets from the Earth Observing 1 (EO-1) Hyperion sensor are very suitable for this purpose, as is airborne hyperspectral data. In this paper, we examine the possibility of translating vegetation index (VI) data between two sensors by using imagery from the Hyperion sensor and utilizing the vegetation isoline concept. The objectives of this paper are to introduce and test a VI translation technique, focused on the spectral differences associated with sensor spectral bandpass filters. The translation of global VI datasets from one sensor to another requires a methodology applicable over various land cover types and throughout the wide ranges in VI values. To meet these requirements, a technique is proposed that utilizes adjustable translation coefficients, based on an estimation of the leaf area index value relative to a numerical canopy model. The theoretical basis of the proposed translation algorithm is explained in terms of the vegetation isoline concept. Its performance was tested through a numerical experiment with a Hyperion image, focusing on the normalized difference vegetation index (NDVI) as a representative vegetation index. The results indicate the potential of the isoline-based translation technique for stable translation throughout wide ranges of NDVI values.

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http://hdl.handle.net/10453/8512